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PolicyLink Prevention Institute Convergence Partnership

H e a l t h y , E q u i t a b l e T r a n s p o r t a t i o n P o l i c y R E C O M M E N D A T I O N S A N D R E S E A R C H

Design by Chen Design Associates

Leslie Yang for PolicyLink

PolicyLink PolicyLink is a national research and action institute advancing economic and social equity by Lifting Up What Works.®

Prevention Institute Putting prevention and equitable health outcomes at the center of community well-being.

This report was commissioned by the Convergence Partnership which includes the following institutions: The California Endowment Kaiser Permanente The Kresge Foundation Nemours Robert Wood Johnson Foundation W.K. Kellogg Foundation Centers for Disease Control and Prevention as technical advisors

Hea lthy, Equitable Transpor tation Policy Recommendations a nd Resea rch

E D I T E D BY

SHir EEn M a lEk a fza li Senior A ssociate, PolicyLin k

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5 Foreword Congressman James Oberstar, Chairman of the House Transportation and Infrastructure Committee

6 Preface Angela Glover Blackwell, Founder and CEO, PolicyLink

9 The Transportation Prescription: A Summary of Findings and a Framework for Action Judith Bell, M.P.A., President, PolicyLink Larry Cohen, M.S.W., Founder and Executive Director, Prevention Institute

21 Chapter 1. Health Effects of Transportation Policy Judith Bell, M.P.A., President, PolicyLink Larry Cohen, M.S.W., Founder and Executive Director, Prevention Institute

27 Chapter 2. Transportation Authorization 101: A Backgrounder Susan Polan, Ph.D., Associate Executive Director, American Public Health Association Tracy Kolian, M.P.H., Senior Health Policy Analyst, American Public Health Association Shireen Malekafzali, M.P.H., Senior Associate, PolicyLink

35 Transportation Choices

37 Chapter 3. Public Transportation and Health Todd Litman, M.E.S., Founder and Executive Director, Victoria Transport Policy Institute

63 Chapter 4. Walking, Bicycling, and Health Susan Handy, Ph.D., Professor of Environmental Science and Policy, Director of the Sustainable Transportation Center, University of California, Davis

79 Chapter 5. Roadways and Health: Making the Case for Collaboration Catherine L. Ross, Ph.D., Director, Center for Quality Growth and Regional Development, Harry West Chair, Georgia Tech

Contents

97 Key Issues

99 Chapter 6. Breaking Down Silos: Transportation, Economic Development, and Health Todd Swanstrom, Ph.D., E. Desmond Lee Professor of Community Collaboration and Public Policy Administration, University of Missouri, St. Louis

113 Chapter 7. Sustainable Food Systems: Perspectives on Transportation Policy Kami Pothukuchi, Ph.D., Associate Professor of Urban Planning, Wayne State University Richard Wallace, Senior Project Manager, Center for Automotive Research

131 Chapter 8. Traffic Injury Prevention: A 21st-Century Approach Larry Cohen, M.S.W., Founder and Executive Director, Prevention Institute Leslie Mikkelsen, R.D., M.P.H., Managing Director, Prevention Institute Janani Srikantharajah, B.A., Program Coordinator, Prevention Institute

146 Author Biographies

150 Acknowledgments

151 Notes

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Discussions of public health and wellness often are limited to the health and medical fields. It is my hope that soon, the transportation sector will be part of the discussion and play a role in providing solutions to improving the nation’s overall health, well-being, and quality of life.

One of my goals as Chairman of the Committee on Transportation and Infrastructure is to create a new model for surface transportation, one that invests in alternative modes and promotes active, healthy lifestyles. Public health and transportation policy choices are inextricably linked. The transportation sector is responsible for one-third of the greenhouse gas emissions in the United States. Our infrastructure and land use choices often dictate our daily travel, and whether or not we have access to clean, healthy transportation options. And in any given year, approximately 40,000 Americans are killed on our roadways. The policy decisions we make regarding transportation have repercussions on public health throughout our society.

For too long now, our transportation decision making has failed to address the impacts that our infrastructure network has on public health and equity. The asphalt poured and lane miles constructed enhanced our mobility and strengthened our economic growth; but too often, this auto-centric mindset took hold and crowded out opportunities to invest in a truly sustainable intermodal transportation system, in particular a system that meets the needs of underserved communities.

The failure to link transportation and land use decision making, and to consider the public health effects of these choices, has led to a tilted playing field that has made driving the easiest—and often the only—option available in many parts of the country. Our transportation policies and investments must do more to provide access for all through various modes. Transit, walking, and bicycling all have a significant role to play in lowering our dependence on foreign oil, reducing our greenhouse gas emissions and air pollutants,

and helping Americans incorporate exercise and fresh air into their daily travel routines. We must also continue our pursuit to reduce the number—and rate—of traffic fatalities and injuries that occur each year.

Our most recent surface transportation legislation, enacted in 2005, took important steps toward building a healthier infrastructure by investing billions of dollars in safety, public transit, walking, and bicycling. This legislation is helping to construct safer infrastructure, enable workforce development, build new transit lines, repair existing systems, and establish non- motorized transportation networks. We also enacted the Safe Routes to School program, which allows states to invest in safety improvements and education campaigns to get kids walking and biking to school again. This program has shown great early success and has the ability to change the habits of an entire generation.

Environmental sustainability, access, and our collective well-being must combine with mobility and safety as the cornerstones of our transportation investments. The following report represents an important contribution to our emerging understanding of the connections between transportation and public health and is an invaluable resource for policymakers and all those interested in building healthy communities. With a greater recognition of the strong linkage between public health and transportation, I believe we can build a network that supports our mobility and creates access and economic strength while promoting equity, sustaining our good health and quality of life.

Congressman James Oberstar

Chairman of the House Transportation and Infrastructure Committee

Foreword Congressman James Oberstar

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Transportation policy has enormous potential to catalyze the development of healthy communities of opportunity. The upcoming authorization of the federal surface transportation bill represents the single biggest federal opportunity to influence how our communities, cities, and regions are shaped.

Transportation impacts health directly; it affects air quality, injury risk, physical activity levels, and access to necessities such as grocery stores. Transportation is also one of the largest drivers of land use patterns; it thus determines whether communities have sidewalks and areas to play and be physically active as well as whether communities are connected to or isolated from economic and social opportunities.

Research shows that low-income communities and communities of color often do not have access to the benefits our transportation system can provide, yet they bear the burdens of that system. For example, many low-income neighborhoods have little or no efficient, reliable public transportation to get them to jobs and essential goods and services. But these communities are often situated near bus depots, highways, and truck routes, where pollution levels are high—and not coincidentally, asthma rates are high as well. In addition, many of these same communities live without safe, complete sidewalks or bike paths, making walking and biking difficult and often dangerous. As a result, these neighborhoods

have low levels of physical activity and high rates of chronic diseases. Creating a more equitable transportation system must lie at the core of any analysis of transportation or health, and it must guide all reform.

The Convergence Partnership, the collaborative of funders that commissioned this project, embraces the imperative that health and equity be central to transportation policy debates. Further, the Convergence Partnership recognizes how transportation policy is connected to the Partnership’s broader efforts to support environmental and policy changes that will create healthy people and healthy places. The Partnership’s steering committee includes: The California Endowment, Kaiser Permanente, the Kresge Foundation, Nemours, the Robert Wood Johnson Foundation, and the W. K. Kellogg Foundation. The Centers for Disease Control and Prevention serves as technical advisor.

In this project, leading academic researchers and advocates working at the intersection of transportation policy, equity, and public health identify opportunities for creating transportation systems that promote health and equity. This report synthesizes their insights and offers concrete recommendations for change.

Reform is long overdue. Climate change, shameful health disparities, growing rates of chronic diseases—transportation policy has contributed to these problems, and now it must

Preface Angela Glover Blackwell

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address them. Increasing rates of poverty and a severe economic downturn add to the urgency for reform.

This report intentionally uses the term authorization and not the more common word, reauthorization, in reference to the surface transportation bill. We want to make clear that new thinking and innovative approaches are necessary to meet the needs of a changing and diverse America.

Many advocates are already working hard to push for fundamental reform. This report was written for community leaders, policymakers, funders, practitioners, and advocates interested in an overarching strategy to promote active living and to build healthy communities of opportunity. PolicyLink, Prevention Institute, and the Convergence Partnership believe that building healthy communities requires a collaboration of stakeholders from diverse fields and sectors. Together, we can identify and support shared solutions.

The project recognizes that effective strategies to improve health, particularly in vulnerable communities, often fall outside the conventional domain of health policy, yet deserve equal attention. Federal transportation policy is a critical opportunity at our fingertips. Leveraging the strength of collaboration and networking can yield powerful results. Let’s seize the moment.

Angela Glover Blackwell

Founder and CEO PolicyLink

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The Transportation Prescription: A Summar y of Findings and a Framework for Action JUDITH BELL , M.P. A . President, PolicyLink

L A R RY COHEN, M.S.W. Founder a nd Executive Director, Prevention Institute

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In St. Louis, MO, major cuts in bus service this spring left workers, students, disabled people, and elderly residents stranded and feeling bereft. Stuart and Dianne Falk, who are both in wheelchairs, told CNN they no longer would be able to get to the gym or the downtown theater company where they volunteer. “To be saddled, to be imprisoned, that is what it is going to feeling like,” Stuart Falk said.1

In West Oakland, CA, families have no escape from the diesel exhaust belching from trucks at the nearby port: The air inside some homes is five times more toxic than in other parts of the city. “I’m constantly doing this dance about cleaning diesel soot from my blinds and window sills,” 57-year-old Margaret Gordon told the San Francisco Chronicle.2

In Seattle, WA, Maggieh Rathbun, a 55-year- old diabetic who has no car, takes an hour-long bus ride to buy fresh fruits and vegetables. She cannot haul more than a few small bags at a time so she shops frequently—if she feels well enough. “It depends on what kind of day I’m having with my diabetes to decide whether I’m going to make do with a bowl of cereal or try to go get something better,” she told the Seattle Post-Intelligencer.3

Our transportation system has an enormous impact on our way of life, on the air we breathe, and on the vitality of our communities. Transportation choices influence personal decisions about where to live, shop, attend school, work, and enjoy leisure. They affect stress levels, family budgets, and the time we spend with our children. Although most people don’t think of it as a determinant of health, our transportation system has far-reaching implications for our risk of disease and injury. Transportation policies and accompanying land use patterns contribute to the glaring health disparities between the affluent and the poor and between white people and people of color.

This report demonstrates that transportation policy is, in effect, health policy—and

environmental policy, food policy, employment policy, and metropolitan development policy, each of which bears on health independently and in concert with the others. Longstanding transportation and land use policies are at odds with serious health, environmental, and economic needs of the country, and they have harmed low-income communities and communities of color especially. Forward- thinking transportation policies must promote healthy, green, safe, accessible, and affordable ways of getting where we need to go. They also must go hand in hand with equitable, sustainable land use planning and community economic development.

Streets and roads are the largest chunks of property owned by most cities and states. We have choices to make about how to use, and share, that real estate. Who decides? Who benefits? Who pays? Transportation policy at all levels of government can be a vehicle to promote public health, sustainability, equitable opportunity, and the economic strength of neighborhoods, cities, and regions. But that will happen only if advocates, experts, and organizers steeped in all these issues bring their knowledge and passion to critical transportation decisions. The upcoming authorization of the most important transportation legislation in the United States, the federal surface transportation bill, makes this a pivotal moment to bring a broad vision for health and equity to transportation policy.

T r a n s p o r t a t i o n i n a m e r i c a : a n e w V i s i o n

Underlying this report is a vision of transportation as more than a means to move people and goods, but also as a way to build healthy, opportunity-rich communities. Health is often viewed from an individual perspective. Yet, each resident in a region is both an individual and part of a larger community. Therefore, our vision for healthy, equitable communities is one that extends beyond

The Transportation Prescription

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individual outcomes and creates conditions that allow all to reach their full potential. It does not force us to balance one individual against another. It provides the opportunity for everyone to participate in their community, be healthy, and prosper.

Transportation systems are essential to the competitiveness of the nation and the viability of regions. Building America’s Future, a bipartisan coalition of elected officials, views increased transportation investment as a key to the economic growth and job creation needed to strengthen cities and rural communities.4 The American Recovery and Reinvestment Act (ARRA), the nearly $1 trillion stimulus package passed by Congress and signed by President Obama in early 2009, emphasizes transportation investments to revive the ailing economy and rebuild regions.5 The act galvanized advocates to push government agencies to spend the money in ways that promote health, protect the environment, and benefit everyone. Now momentum is building to bring a focus on health and equity to the next version of the federal surface transportation bill.6

Over the past half-century, federal transportation policy has changed the American landscape, physically, socially, and culturally. Beginning with the Federal-Aid Highway Act of 1956 authorizing the Interstate Highway System, the leading transportation priority by far has been what planners call mobility and which became synonymous with the movement of more and more cars and goods farther and faster. Mobility advanced the nation’s growth and prosperity, and it formed our sense of identity as well as our image abroad. The car was more than a machine to get us around; it stood as a symbol of American freedom, ingenuity, and manufacturing prowess.

While some have few or no transportation choices due to limited transportation infrastructure and resources in their communities, many Americans do have the

opportunity to make choices about how to travel and where to go. For these people, the car provides the means to flee the city, buy a quarter-acre patch of suburbia, and drive to their hearts’ content without giving much thought to the disinvested neighborhoods left behind, or the farmland lost to development, or the fossil fuels and other natural resources their lifestyles consumed. Community environments, however, affect the choices individuals make, and public policy molds those environments. As the nation confronts severe economic, environmental, and health challenges as well as the widening gulf between rich and poor, it is becoming clear that we must make different choices as individuals and as a society.

A new framework for transportation policy and planning is emerging. Rather than focus almost exclusively on mobility (and its corollaries, speed and distance), this framework also emphasizes transportation accessibility. In other words, instead of designing transportation systems primarily to move cars and goods, the new approach calls for systems designed to serve people—all people—efficiently, affordably, and safely. This approach prioritizes investments in: (1) public transportation, walking, and bicycling—transportation modes that can promote health, opportunity, environmental quality, and indeed mobility for people who do not have access to cars; and (2) communities with the greatest need for affordable, safe, reliable transportation linkages linkages to jobs, and essential goods and services—chiefly, low- income communities and communities of color.

The goal is to improve transportation for everyone while delivering other important payoffs, including better respiratory and cardiovascular health; improved physical fitness; less emotional stress; cleaner air; quieter streets; fewer traffic injuries and deaths; and greater access to jobs, nutritious foods, pharmacies, clinics, and other essentials for healthy, productive living.

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The Transportation Prescription

This new vision is at the core of a burgeoning movement to shape transportation policy to support work in a number of critical areas, such as climate change, sustainable agriculture, the prevention of chronic diseases, workforce development, and neighborhood revitalization. Advocates and experts in public health, environmental justice, labor, community economic development, food policy, and other fields and disciplines have important roles to play in transportation debates. A broad range of interests working in partnership, can craft innovative, environmentally sound solutions that benefit everyone, rather than plans that reflect the motor vehicle orientation of road engineers and builders. Government transportation agencies and developers—the architects of our transportation systems for decades—must be held accountable for how their investments affect the economic prospects of regions, the health of communities, and the well-being of residents.

This shift in thinking about what transportation policy must achieve and who should drive it stems from a long list of factors. Among them: near-crippling congestion in many metropolitan areas; renewed interest in city living and a hunger for shorter commutes; demographic changes (including the increasing number of people over 65 and immigrants, two groups less likely to drive or own cars); the rise in obesity; the enduring poverty in inner-city and rural communities; the growing understanding of the connections among health, the built environment, and transportation plans; and the increasing frustration among residents and advocates about the limited accountability and inequitable transportation decision-making processes at the state and regional levels which over represent suburban and white male interests.

But the push to reform transportation (along with its cousin, land use planning) has gained urgency in the face of three massive challenges that are upending the status quo of every field and that go to the heart of our love affair with the car: (1) Climate change, with its threat of global ecological upheaval. (2) U.S. dependence

on foreign oil, which carries grave risks for our economy and security. (3) A healthcare system crumbling under the demands of skyrocketing rates of diabetes and other chronic diseases associated with sedentary lifestyles, and astronomical costs. Transporting goods, services, and people accounts for about one-third of greenhouse gas emissions and two-thirds of petroleum consumption in the United States.7 As the National Surface Transportation Policy and Revenue Study Commission noted in its landmark report, Transportation for Tomorrow, the environmental gains we achieve through incremental fixes such as higher fuel-efficiency standards, though important, will be trumped by increases in driving and traffic if we continue on our current policy course.

The good news is that change can happen, and inspiring examples abound. In the rural San Joaquin Valley in California, where public transportation has been virtually nonexistent, a new system of publicly managed vanpools is connecting farm worker families to jobs, schools, and medical services.8

In Chicago’s West Garfield Park, an alliance of residents, activists, and faith-based organizations not only successfully fought the closure of the rail line that linked the neighborhood to downtown; they also transformed a transit stop into an anchor of development of shops, community services, and moderately priced housing.9

In port cities around the country, many groups are working to reduce pollution from ships, locomotives, and trucks, some of the worst emitters of soot and greenhouse gases. In the Los Angeles region—one of a number of regions where the movement of goods represents a significant part of transportation investment and economic activity, and where ports and freeways abut low-income neighborhoods—the Coalition for Clean and Safe Ports has formed an effective alliance of residents, truck drivers, public health experts, environmentalists, environmental justice

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activists, unions, immigrant groups, and public officials to push for clean air solutions.10

The authorization of the next federal surface transportation bill presents an immense opportunity to broaden such engagement and to forge an equitable policy response to the unprecedented challenges facing the country. The bill authorizes federal funding for highways, highway safety, public transportation, and bicycling and pedestrian infrastructure for approximately six years.11 It transfers hundreds of billions of dollars from the federal government to states and localities. It also triggers hundreds of billions more in matching state and local spending. The bill marks the largest transportation expenditure in the United States.

But the legislation does more than provide money. It also communicates national policy priorities. Will we build roads on the farthest edges of regions or fix aging roads and bridges in cities and inner-ring suburbs? Will we invest in healthy, green transportation—bicycle lanes, safe sidewalks for walking, clean buses, ridesharing, light rails? Will we ensure that all voices are equitably represented in transportation decision-making processes? And will we include incentives and requirements for affordable housing near public transportation to ensure broad access to the job opportunities and services that transit oriented development stimulates? Or will we spend most of the money as we have for decades: on new and bigger highways with little public accountability? The bill establishes funding categories and requirements and in some cases gives communities and metropolitan regions flexibility to shape strategies to local needs. The new law is a chance to design communities for health, sustainability, and opportunity—and to give all Americans physically active, clean, affordable, convenient, reliable, and safe options to get where they need to go.

W h a t D o e s H e a lt h y, E q u i t a b l e T r a n s p o r t a t i o n P o l i c y l o o k l i k e?

Our current transportation system has many direct health consequences: pollution-related asthma, steep declines in physical activity, and the associated rise in obesity and chronic illnesses are just a few examples. Transportation affects health indirectly by connecting people— or by failing to provide connections—to jobs, medical care, healthy food outlets, and other necessities. For more details on the connections between transportation and health see Chapter 2, Health Effects of Transportation Policy.

The National Surface Transportation Policy and Revenue Study Commission—created by Congress in 2005 to examine the condition and future needs of our network of highways, ports, freight and passenger railroads, and public transportation systems—reached a sobering conclusion: “The nation’s surface transportation network regrettably exacts a terrible toll in lost lives and damaged health.”12 Nowhere is the toll higher than among low-income people and people of color.

Research shows that when properly designed, transportation systems can provide exercise opportunities, improve safety, lower emotional stress, link poor people to opportunity, connect isolated older adults and people with disabilities to crucial services and social supports, and stimulate economic development. Healthy, equitable transportation policy draws on that research to create transportation systems that benefit everyone.

Specifically, healthy, equitable transportation policy:

• Supports the development of accessible, efficient, affordable, and safe alternatives to car travel, and especially to driving solo. These alternatives enable everyone to walk more, travel by bicycle, and use public

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transportation more—in other words, to get around in ways that improve health, expand access to opportunity, and reduce toxic pollutants and greenhouse gas emissions.

• Works hand in hand with sustainable land use planning. Together, they encourage and support high-density, mixed-use, mixed- income metropolitan development and affordable housing with good access to transportation options. Together, they focus, particularly, on underserved and economically isolated communities.

• Recognizes that income is important to health, and that good transportation has an impact on family income. Healthy, equitable transportation policy support systems that connect all people, especially low-income and underserved communities, to employment and other opportunities. It also encourages hiring low-income residents of color for well- paying jobs in transportation construction, maintenance, and service.

• Understands the importance of ensuring equal representation. All community members, regardless of race, gender or geographical location should be equitably represented and involved in making decisions which impact their communities, their infrastructure and their options for travel.

• Recognizes that access to healthy foods is integral to good health and that transportation systems are integral to food production and distribution. Healthy, equitable transportation policy explicitly addresses food access issues, including transportation to grocery stores and food transport practices.

This summary draws on the six thematic chapters in this book authored by academics and advocates working at the intersection of transportation, health, and equity. Each chapter describes innovative transportation and land use policies, strategies, and programs built on

a foundation of equity and sustainability. Three chapters in this collection address transportation options:

• Todd Litman, M.E.S., founder and executive director of the Victoria Transport Policy Institute in British Columbia, identifies numerous economic, social, and environmental benefits that can result from public transportation improvements. Among them: reduced traffic crashes, improved physical fitness and health, energy conservation, reduced pollution emissions, increased community livability, increased affordability, consumer savings, economic development, and expanded opportunity. Litman contends that improving public transportation is one of the most cost- effective ways to improve public health, and better health is one of the most significant potential benefits of public transportation improvements. He identifies policy and planning reforms to create a more diverse and efficient transportation system. He recommends developing a strategic vision of high-quality public transportation services, with supportive land use policies to provide basic mobility to people who are socially isolated, economically disadvantaged, or physically disabled, as well as to attract “discretionary” travelers, or people who would otherwise drive for a particular trip.

• Susan Handy, Ph.D., director of the Sustainable Development Center at the University of California at Davis, argues that increasing walking and bicycling while assuring safety, particularly for low-income families, children, and older adults, is an important goal for federal transportation policy. Walking and bicycling, or “active travel,” are low-cost, physically active, and environmentally clean alternatives to driving, yet they represent fewer than 10 percent of all trips in the United States. In addition to expanding specialized programs for active travel, the federal government should assist, enable, encourage, and, in some instances,

The Transportation Prescription

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require state, regional, and local governments to address pedestrian and bicycling needs.

• Catherine L. Ross, Ph.D., the Harry West Chair and director of the Center for Quality Growth and Regional Development at Georgia Institute of Technology, argues that roadways are more than transport routes; they are also our primary spaces for civic, social, and commercial enterprise. Roadways—highways in particular—receive the largest share of federal transportation dollars by far. Federal policy has historically emphasized highways designed to move large numbers of cars and freight vehicles at high speeds. Ross argues for greater investments in roadways that integrate physical activity, enrich social interaction, increase safety, and provide transportation linkages in underserved communities. She urges policymakers and others to consider expanded assessments of the effects of roadways on health, through the use of methodologies similar to health impact assessment (HIA).13

The remaining papers offer transportation policy perspectives in key areas that have a significant impact on public health and equity:

• Todd Swanstrom, Ph.D., the E. Desmond Lee Professor of Community Collaboration and Public Policy Administration at the University of Missouri, St. Louis, makes the case that federal transportation policy can and should address economic development, particularly in communities left behind by decades of transportation planning that favored car travel and encouraged sprawl. Targeted transportation investment can promote economic opportunity and reduce health disparities by (1) improving transportation linkages between housing and employment hubs and between residential neighborhoods and clinics, pharmacies, and grocery stores; and (2) encouraging affordable, high-density, mixed-use transit

oriented development14; and (3) creating workforce strategies to ensure that jobs in the large, growing transportation sector are open to all, including minority and women workers and contractors. Swanstrom also asserts that while the goals of equity and environmental sustainability are not mutually exclusive, policymakers and advocates must address the short-term needs of low-income families who live in places where driving is essential.

• Kami Pothukuchi, Ph.D., associate professor of urban planning at Wayne State University, and Richard Wallace, M.S., senior project manager at the Center for Automotive Research, argue that federal transportation policy should seek to increase access to healthy foods. Today’s transportation networks make large quantities of foods from around the nation and the globe readily available for many Americans, but industrialized agriculture and the concentrated structure of food retail have negative health and environmental consequences for low-income communities, especially people of color, inner-city and rural residents, and immigrant farm workers. For example, urban and rural communities often have fewer and smaller supermarkets than suburban communities (if they have any at all) as well as more limited selections of healthy foods. As a result, residents eat fewer fruits and vegetables and have higher rates of diet-related illnesses. In addition, long- distance food hauling has a disproportionate impact on the air quality and noise levels in poor and minority communities along freight routes. Although food access falls outside the traditional realm of transportation policy, improved public transportation, transit oriented development, and cleaner methods to move freight can increase access to healthy foods in underserved communities, reduce air and noise pollution, and foster local, sustainable agri-food systems.

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• Larry Cohen, M.S.W., Leslie Mikkelsen, R.D., M.P.H, and Janani Srikantharajah, B.A., of Prevention Institute argue that traffic crashes are preventable and that federal transportation policy must make safety for all travelers a priority. Traffic crashes rank as the leading cause of death for people ages one to 34 and contribute to unnecessary human, social, and economic costs. Resources should be directed to communities with the least infrastructure to support safe walking, bicycling, and public transportation use and continue to support effective vehicle safety and occupant protection strategies. Traffic safety is an important strategy not only to reduce injuries and death but also to encourage physical activity, improve air quality, and increase transportation accessibility.

T h e fe d e r a l T r a n s p o r t a t i o n l e g a c y a n d C h a l l e n g e s a h e a d

Transportation in America is a federal system, not a centralized, national system. Federal policy plays a critical role, not by dictating practices but by enabling and encouraging innovation by states, regional transportation organizations, transit operators, and other agencies. This happens in several ways.

First, the federal government sends billions of dollars for transportation to states and localities. For example, the American Recovery and Reinvestment Act provides nearly $50 billion to build and repair roads, bridges, railways, and ports. The current surface transportation bill, SAFETEA-LU (Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users), set to expire in September 2009, guaranteed $244.1 billion over six years. These dollars, in turn, leverage direct infrastructure investments by state governments, local governments, and private investors.

Second, the policies and requirements embedded in federal transportation programs influence state and local land use decisions and transportation priorities. Many observers contend that transportation stands as one of the biggest policy successes in United States history. The Federal-Aid Highway Act of 1956 and its progeny promoted mobility, which contributed mightily to American growth and prosperity. However, many advocates take a more nuanced view of the federal legacy. They point to the health, equity, and environmental consequences of an ethic that held the faster, the farther, the better, as well as the consequences of policies focused almost wholly on car and truck travel, with little accountability to goals beyond mobility.

Either way, the current transport system is no longer sustainable or fixable by incremental changes such as pilot projects, encouragements, and small incentives. As the National Surface Transportation Policy and Revenue Study Commission, created by SAFETEA-LU, wrote in its final report to Congress: “The strong and dynamic American surface transportation system is becoming a thing of the past.”

At 300 million people, the nation’s population has doubled since the creation of the Interstate Highway System. We will number 420 million by 2050. “Congestion was once just a nuisance. Today gridlock is a way of life,” the commission’s report said. Growing transportation demand threatens to dwarf regulatory and legislative efforts to mitigate its health and environmental consequences. Increases in total vehicular mileage have all but wiped out the gains achieved through hard-won regulations on fuel efficiency and emissions control. Expansion of freeways cannot get us out of these problems; it will only make them worse. The more we have expanded highways, the more traffic we have created. The United States needs multi-modal systems with public

The Transportation Prescription

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transportation that efficiently serves a large segment of the population, using existing streets and highways.

The Intermodal Transportation Efficiency Act (ISTEA), the 1991 version of the federal surface transportation bill, was supposed to lead us there. The act incorporated significant policy change. Since then, the stated goal of federal transportation policy has been to expand access and improve efficiency through an interconnected multi-modal system that supports highways, public transportation, walking, and biking. This goal has yet to be achieved. Funding mechanisms and formulas have continued to favor highway construction and car travel. For example, the allocation formula for the Surface Transportation Program (STP), the largest program within the federal bill, rewards states that consume more gas, have more miles of highway, and have residents who drive a lot.15 Alternatives to driving remain underinvested. Approximately 80 percent of the surface transportation bill is allocated for distribution through the Federal Highway Administration for mostly highway programs, while less than 20 percent goes to the Federal Transit Agency for public transportation. Other modes of travel constitute a minute amount of spending in comparison to highways and public transportation.

Case in point: walking is the only travel mode that has not had significant declines in casualties in 40 years. Yet only a tiny share of transportation funding goes to infrastructure initiatives that would make walking and biking safer. Walking and bicycling accounted for 8.6 percent of all trips in 2001 but 12 percent of traffic deaths.16

Another case in point: operating costs for public transportation systems present a huge challenge for many communities. Yet federal transportation investment is focused on capital projects. For example, cities with 200,000 people or more may not use grants from the

U.S. Department of Transportation’s main public transportation programs for transit operating costs.17 In the face of budget shortfalls, local and regional transportation agencies throughout the country have cut service, hiked fares, and deferred maintenance—arguably at a time when people need affordable, reliable links to jobs more than ever.

While federal policy plays a significant role in shaping transportation systems, states and metropolitan regions are also critical agents of change. The new surface transportation bill offers an opportunity to increase support, encouragement, and pressure for integrating land use and transportation planning to promote balanced regional growth, equitable economic opportunity, and healthy communities for all.

a fo u n d a t i o n f o r 2 1 s t - C e n t u r y T r a n s p o r t a t i o n P o l i c y

Healthy, equitable transportation policy is grounded in four principles. These may also serve as benchmarks to assess the impacts of transportation plans on public health, equity, and environmental quality:

1. Develop transportation policies and plans that support health, equity, and environmental quality. Federal, state, and local transportation policies should be aligned with the top health and environmental goals of federal departments and agencies. For example, transportation policies should be aligned with the Department of Health and Human Services’ strategic goals to promote health equity and foster the economic and social well-being of individuals, families, and communities. Transportation policies should also support the CDC’s commitment to eliminate health disparities and to promote its “healthy people in healthy places” goals.

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2. Prioritize transportation investments in distressed regions, low-income neighborhoods, and communities of color. Federal, state, and local transportation agencies should emphasize projects that will revitalize the economy of struggling communities, lower health disparities, and will connect vulnerable populations to jobs, business opportunities, healthy food outlets, medical services, and other necessities. Government agencies must ensure that these projects are financially sustainable by providing adequate funding for maintenance and operations. The jobs associated with transportation construction, maintenance, and service should be available to low- income people and communities of color.

3. Emphasize accessibility, instead of simply mobility, in transportation policies and programs at all levels of government as well as across sectors and policy silos. Transportation systems should give communities wider access to all the things that are necessary for a good life, not to move people faster and farther. The definition of access must also include affordability. If transportation is physically accessible, yet unaffordable, it is not truly accessible.

4. Ensure transparency, accountability, and meaningful participation by residents, advocates with diverse interests, and experts from different fields. State and regional transportation officials and private developers must engage new partners in decision making and provide the data, training, and resources to allow full, informed participation by the people affected most by decisions and investments. Voices and expertise from local communities, public health, environmental justice, community development, and other arenas can help ensure that transportation plans respond to local needs and deliver health, environmental, and economic benefits broadly.

P o l i c y a n d P r o g r a m P r i o r i t i e s t o i m p r o v e H e a lt h a n d E q u i t y

Government at all levels must consider the health and equity impacts of transportation investments at the beginning of decision-making processes. Public and private transportation investments must be designed to promote health rather than to erode it. The following recommendations can help policymakers and planners achieve these ends:

1. Prioritize investments in public transportation, including regional systems that connect housing and jobs as well as local services that improve access to healthy foods, medical care, and other basic services. Investments should include capital costs as well as costs for maintenance and operations. Because older diesel buses have high emission rates and since bus depots and other facilities are often concentrated in low-income and minority neighborhoods, policies must be in place to ensure that expanded public transportation does not lead to increased exposure to pollutants in these same communities.

2. Prioritize investments in bicycle and pedestrian infrastructure to make walking and biking safer and more convenient. Strategies include complete streets designed with all users in mind, not just drivers; traffic-calming measures; and safe routes to transit and Safe Routes to Schools programs, which create infrastructure and programming to support safe walking and bicycling to bus stops, rail stations, and schools. Targeted infrastructure investments should also support walking and bicycling in rural communities by, for example, improving road shoulders and building trails to town centers.

The Transportation Prescription

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3. Encourage equitable transit oriented development by creating incentives for integrated land use and transportation planning. Transit oriented development must emphasize affordability and accessibility. It also must incorporate affordable housing and commercial properties that provide jobs, services, and essential goods near people’s homes. Because people of all income levels desire walkable neighborhoods and shorter commutes, displacement of longtime neighborhood residents can be an unintended consequence of transit oriented development. Policymakers must ensure that the local residents guide planning and development and that equity is a goal from day one.

4. Create incentives and accountability measures to ensure that transportation plans account for their impacts on health, safety, and equity. New projects must be held accountable for better results. Government investment should support the creation of tools that more sensitively and accurately measure walking and bicycling practices and improved outcomes. Health impact assessment is an emerging methodology to evaluate the effects of policies, programs, and plans on the health of a population and should be considered an important tool. People should also have the right to sue under Title VI of the Civil Rights Act of 1964 if they suffer disparate impacts from federal transportation investments, and the U.S. Department of Transportation should have the power to withhold dollars if investments are not made equitably.18

5. Give state, regional, and local government agencies and organizations more flexibility to move dollars among funding categories and to target spending to meet local needs. Greater flexibility would give communities more leeway to fund walking, bicycling, and public transportation programs. It would

also enable communities to invest in fixing, maintaining, and operating local bus and rail systems. Flexibility should be strongly tied to new standards for accountability, transparency, and inclusion which ensure all people impacted by transportation decisions are equitably represented in the decision- making process.

6. Prioritize transportation investments in communities with high unemployment and poverty rates to stimulate economic growth and provide access to jobs. The American Recovery and Reinvestment Act (ARRA) has language to direct resources to struggling and disinvested communities. The new version of the surface transportation bill should include similar language and expand on this commitment by creating strong accountability and enforcement measures tied to achieving equitable economic benefits.

7. Make sure that jobs and contracts created by federal transportation investments reach low-income people and communities of color. A Sense of Congress amendment to SAFETEAU-LU, passed in 2005, encourages local hiring provisions for highway construction projects. Some projects aim for 30 percent of workforce hours to be filled by employees who live in the community. Local hiring should be made a requirement, not just encouraged. It should also be expanded beyond highway projects to include public and mass transit development. Capital investments should also fund workforce development programs to train local residents for jobs in the transportation sector.19

8. Support the development of cleaner bus and truck fleets and invest in freight rail infrastructure to reduce greenhouse gas emissions, improve local air quality, promote health, and foster energy independence.

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9. Advance safety for all travelers, with particular emphasis on those at the highest risk of car injuries and death. Investments should continue advancing known vehicle safety and occupant-protection strategies as well as roadway and community design modifications to protect the safety of pedestrians, bicyclists, drivers, and passengers.

10. Support policies and programs that increase access to healthy foods. Promote public-private van and bus systems to shuttle customers to grocery stores. Expand weekend bus service to connect low-income neighborhoods to supermarkets and other food outlets. Invest in safe and affordable transportation for farm and food production workers. Promote sustainable modes of transporting foods from farms to stores as well as policies to increase the viability of local and regional farming.

11. Give low-income rural communities greater access to public transportation funds from the surface transportation bill providing the opportunity to access employment and education opportunities. Low-density and long travel distances make developing and operating conventional bus and rail systems financially challenging. Federal public transportation dollars should support economically efficient innovations, such as vanpools and voucher programs.

C o n c l u s i o n

The authorization of the next federal surface transportation bill can be a starting point for creating many changes Americans say they want: better health, cleaner air, more time with our families, opportunities to connect with our neighbors. The new legislation can also mark an important step toward building a society in which everyone can participate and prosper, and no community is left behind.

Change will not come easily. The car culture has deep roots in America. The interest groups supporting highway investment are powerful and well-funded. But advocates and grass-roots activists around the country have demonstrated that change can happen. They have successfully fought for cleaner buses and for public transportation in communities that never had it. They have transformed train stations into centers of vibrant community development in disinvested neighborhoods. They have pressured local officials and supermarket operators to provide free bus rides so families can shop for food.

Now is the time to tap into that kind of energy and lift successes like these to the level of federal policy. Leaders, experts, and advocates from many spheres—public health, environmental justice, food policy, agriculture, labor, equity, community economic development, business, and government—must join in partnership to push for broad reform. Collectively, we can gain power and build political support for creating transportation systems that address the big challenges we face and that nourish healthy communities throughout our nation.

The Transportation Prescription

Hea lth Effects of ch. 1 Transportation Policy JUDITH BELL , M.P. A . President, PolicyLink

L A R RY COHEN, M.S.W. Founder a nd Executive Director, Prevention Institute

ABSTRACT >> There is a deep and evolving knowledge base about the links between transportation and health. Research shows that when properly designed, transportation systems can provide exercise opportunities, improve safety, lower emotional stress, link poor people to opportunity, connect isolated older adults and people with disabilities to crucial services and social supports, and stimulate economic development. Conventional auto mobility-focused planning by local, regional, and state transportation agencies generally overlooks or undervalues the impacts of transportation investments on health and equity.

This chapter provides an overview of the impacts of transportation on health. Subsequent chapters on transportation options and key issues provide further detail.

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i n t r o d u c t i o n

Our current transportation system has many direct health consequences: pollution-related asthma, steep declines in physical activity, and the associated rise in obesity and chronic illnesses are just a few examples. Transportation affects health indirectly by connecting people— or by failing to provide connections—to jobs, medical care, healthy food outlets, and other necessities. The National Surface Transportation Policy and Revenue Study Commission—created by Congress in 2005 to examine the condition and future needs of our network of highways, ports, freight and passenger railroads, and public transportation systems—reached a sobering conclusion: “The nation’s surface transportation network regrettably exacts a terrible toll in lost lives and damaged health.”1 Nowhere is the toll higher than among low- income people and people of color.

D i r e c t H e a lt h E f f e c t s

Pollution

Pollutants from cars, buses, and trucks are associated with impaired lung development and function in infants2 and children,3 and with lung cancer,4 heart disease, respiratory illness,5 and premature death.6 Long-term exposure to pollution from traffic may be as significant a threat for premature death as traffic crashes and obesity.7 In California alone, pollution is a factor in an estimated 8,800 premature deaths a year.8

The main culprits are fine particulate matter, including diesel exhaust particles; ground-level ozone, a toxic component of smog formed when tailpipe emissions from cars and trucks react with sunlight and oxygen; and nitrogen oxide (NOx), which contributes to the formation of ozone and smog. The health risks are exacerbated by transportation patterns that often embed heavy traffic and diesel-spewing facilities in poor and predominantly minority neighborhoods. The American Lung Association has found that 61.3 percent of African American children, 67.7 percent of Asian American children, and 69.2 percent of Latino children live in areas that exceed air-quality standards for ozone, compared with 50.8 percent of white children.9 Ground-level ozone, a gas, can chemically burn the lining of the respiratory tract.

Air pollution is also “one of the most underappreciated” triggers of asthma attacks, according to the Centers for Disease Control and Prevention (CDC).10 More than 20 million Americans—roughly seven percent of adults and nearly nine percent of all children—have asthma. In poor and minority communities, the rates are considerably higher. For example, in Harlem and Washington Heights in northern Manhattan, home to mostly low-income African American and Latino residents, one in four children suffers from the disease.11 Research shows that air pollution can trigger the wheezing, coughing, and gasping for breath

Health Effects of Transportation Policy

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that signal an attack in people with asthma. But a study in 10 Southern California cities raises the troubling possibility that pollution can also lead to the onset of the disease. The study found that the closer children live to a freeway, the more likely they are to develop asthma.12

Environmental justice activists have called attention for years to the connections among pollution, illness, and transportation policy— and the burden on communities of color. For instance, in the mid-1990s, West Harlem Environmental Action (WE ACT) used mapping, air monitoring, and resident surveys to show that the neighborhood’s asthma rates were linked to its dubious status as the diesel capital of New York City. When WE ACT began work on the issue, Harlem housed six of the city’s eight bus depots and 650 Port Authority buses. The group played an important role in getting the city to convert buses to clean fuel.13

Pollution from freight transport is another big concern around the country. To meet America’s insatiable demand for goods, ports and highways are continually expanding to accommodate more ships, locomotives, and trucks. Ports frequently border low-income and minority neighborhoods, and highways often run through them. The upshot: some of the worst emitters of fine particles, soot, and greenhouse gases (GHGs) are a growing presence in already vulnerable communities.

Climate Change

GHGs are not pollutants in the classical sense. They cause the atmospheric changes and resulting climate disruptions that are projected to alter the natural and built environments on which society relies.14 The health risks come largely from those environmental alterations. In a major shift in federal policy, the Environmental Protection Agency in April 2009 adopted the position that greenhouse gases pose a danger to human health and welfare. A few weeks later, the Climate Change and Health Protection and Promotion Act, H.R. 2323, was introduced

in the House of Representatives.15 The bill would direct the Department of Health and Human Services to develop a national strategic action plan to prepare for and respond to the health effects of climate change.

Researchers are just beginning to assess the specific health dangers in the United States; most of the published data to date come from abroad. A recent report predicts that kidney stones, linked to dehydration, may increase by as much as 30 percent in the driest regions of the United States.16 So far, however, there are more questions than answers. How will less rainfall affect the potential for waterborne diseases? Food supplies? Food prices? How will extreme weather conditions such as heat waves or hurricanes affect mental health? Physical activity? Population displacement?

Scientists believe that climate change could exacerbate a number of current health problems, including heat-related deaths, diarrheal diseases, allergies, and asthma.17 Those already at highest risk—the poor, minorities, children, and older adults—will be even more vulnerable. Policy neglect would compound the problems. Hurricane Katrina revealed, to a horrified public, the disastrous results that can occur when nature (the sort of extreme storm that experts expect to occur more frequently as the earth’s temperature changes) combines with government disregard (in this case, the poorly maintained levees that failed to protect New Orleans from catastrophic flooding) as well as resource inequities (the lack of transportation, which made evacuation impossible for thousands of people).

The urgent need to reduce GHGs has catapulted transportation policy into the limelight. The United States has only about five percent of the world’s population but contributes nearly 25 percent of GHGs, mainly because of fossil fuel consumption, motor vehicle emissions, and industrial agricultural practices (which themselves are promoted by our transportation system).

ch. 1

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Improving vehicle technology, while important, is not enough. Americans need to drive less. That will happen only if walking, bicycling, and public transportation become feasible, efficient alternatives to driving in many more communities, and if land use patterns are changed so people no longer have to jump in the car for every trip.

Physical Activity

Sixty percent of adults in the United States do not meet recommended levels of physical activity, and 25 percent are completely sedentary.18 African Americans and Latinos are less likely than whites to get enough daily physical activity.19 The links between physical activity and health are well established. Sedentary lifestyles are estimated to contribute to as many as 255,000 deaths each year.20 Many children and teens are already at risk for heart disease and type 2 diabetes, once considered “adult” ailments. Today’s youth may turn out to be the first generation in modern history to live shorter lives than their parents.21

Physical inactivity is an important factor in the rising rates of obesity and chronic disease—and transportation practices strongly influence physical activity habits. The more time a person spends in a car, the more likely he or she is to be overweight. Conversely, higher rates of walking and bicycling are associated with lower rates of obesity. A 2004 study found that every additional hour spent in a car is associated with a six percent increase in the likelihood of obesity, and every additional kilometer walked is associated with a 4.8 percent reduction.22

There are many ways to be physically active, but quite a few require time, skill, and money. Walking and bicycling not only for recreation but also for transportation are the most practical ways to improve fitness. They are often the only viable option for low-income residents who live in neighborhoods without parks, who cannot

afford gym memberships, and who do not have the luxury of leisure time.

People who use public transportation tend to walk to and from bus stops and train stations, increasing their likelihood of meeting physical activity recommendations.23 Residents of compact neighborhoods walk, bike, and use public transportation more than residents of spread-out communities, and they have lower rates of obesity.

Mental Health

Rush-hour gridlock, long waits for the bus, and arduous commutes are stressful. They take time away from family, friends, and the activities that provide emotional sustenance: hobbies, religion, sports, clubs, civic engagement, and volunteer commitments. Every 10 minutes spent commuting is associated with a 10 percent drop in the time spent traveling for social purposes.24

Many people find commuting by high-quality public transportation to be less stressful than commuting by car. As we discuss below, the financial costs associated with long commutes

Health Effects of Transportation Policy

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exacerbate the stress, particularly in low-income households.

Safety

Traffic crashes are a leading cause of death and injury for Americans in the prime of life.25 In 2000, motor vehicle crashes cost $230.6 billion in medical costs, property damages, lost worker productivity, travel delays, and other expenses.26 That figure equals about half of all spending on public education from kindergarten through 12th grade.

Native Americans die in traffic crashes at more than 1.5 times the rate of other racial groups.27 African Americans drive less than whites but die at higher rates in car crashes. Walking, too, is also more dangerous in communities of color. CDC data in the mid-1990s revealed that the pedestrian death rate for Latino males in the Atlanta metropolitan area was six times greater than for whites.28 African Americans make up 12 percent of the U.S. population but account for 20 percent of pedestrian deaths.29

Inequitable transportation policies and resources contribute to these disparities. Low- income people and people of color have fewer resources to buy products that improve safety, such as late-model cars and new child safety seats. In underinvested neighborhoods, poorly designed streets, neglected road maintenance, inadequate lighting, limited sidewalks, and minimal traffic enforcement place residents at higher risk of injury.

Safety is also a huge concern for older adults—the fastest-growing segment of the population—and for rural residents. Driving skills decline with age, and frailty makes older adults especially vulnerable in a collision.30 They are more likely to be killed or injured in a crash of a given severity than any other age group.31 Older adults also walk slower and are more susceptible to pedestrian injuries.

Although less than a quarter of all driving in the United States takes place in rural settings,32 more than half of all motor vehicle crashes occur there.33

The more we drive, the more likely we are to get hurt or die in a crash; there is a strong positive relationship between per capita vehicle miles traveled and traffic casualty rates.34 Communities with high annual mileage tend to have higher traffic death rates than communities where people drive less. Passengers on buses, light rail, and commuter rail have about one- tenth the traffic death rate as people in cars.

Investments in public transportation and walking and bicycling infrastructure can reduce injuries and deaths. Contrary to popular belief that more walkers and cyclists lead to more casualties, greater numbers of walkers and bicyclists actually decrease the risks.35

i n d i r e c t H e a lt h E f f e c t s

Transportation is a lifeline. We depend on it to get to work, school, the doctor’s office, the bank, the supermarket, the gym, or a friend’s house. People without reliable, efficient, affordable ways to get around are cut off from jobs, social connections, and essential services. Access to transportation, to economic and social opportunity, and to resources for healthy living are inextricably linked. Gaps in all three areas feed on one another in complex ways. Policy reforms that put health equity objectives at the center of transportation planning and funding decisions can reduce these inequities.

Transportation, Income, and Health

As housing and jobs have moved farther apart, the distance has created employment barriers for anyone without unlimited ability to drive. Nineteen percent of African Americans and 13.7 percent of Latinos lack access to automobiles,

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compared with 4.6 percent of whites. Poverty complicates the problem: 33 percent of poor African Americans and 25 percent of poor Latinos lack automobile access, compared with 12.1 percent of poor whites.36 Cars owned by low-income people tend to be older, less reliable, and less fuel-efficient. This makes commuting to work unpredictable and more expensive, at best.

Income is an important determinant of health.37 The association between poverty and poor health is well documented. Jobs with good wages, including those in the transportation sector, are essential to sustaining health.

Transportation impacts not only family earnings but also expenses. The cost of getting around takes a significant bite out of household budgets. The general standard holds that a family should spend no more than 20 percent of income on transportation, or the costs will eat into other necessities, such as nutritious foods and medical care.38 The average family in the United States spends about 18 percent of after-tax income on transportation, but this varies significantly by income and geography. For example, low-wage households (earning $20,000 to $35,000) living far from employment centers spend 37 percent of their incomes on transportation.39 In neighborhoods well served by public transportation, families spend an average of nine percent.40

Older Adults and People with Disabilities

More than one in five Americans ages 65 and older do not drive because of poor health or eyesight, limited physical or mental abilities, concerns about safety, or because they have no car. More than half of nondrivers, or 3.6 million Americans, stay home on any given day—and more than half of that group, or 1.9 million, have disabilities.41 Isolation is especially acute in rural communities, sprawling suburbs, and black and Latino communities. Compared with

older drivers, older nondrivers take 15 percent fewer trips to the doctor; 59 percent fewer trips to shops and restaurants; and 65 percent fewer trips for family, social, and religious activities.42

When affordable, high-quality public transportation and safe, walkable streets are available, older adults take advantage of them. More than half of older adults make walking a regular activity. More than half of older nondrivers in dense communities use public transportation at least occasionally, compared with one in 20 in spread-out communities.43

The Americans with Disabilities Act (ADA) of 1990 significantly expanded transportation options for people with disabilities. ADA required public bus and rail operators to provide accommodations, such as lifts and ramps, to enable people in wheelchairs to ride. But street design in most communities makes traveling to and from bus stops challenging—and often unsafe—for people with disabilities. Paratransit systems, which use vans or shared taxis to transport people door-to-door, are helpful, but many systems are stretched thin and require appointments well in advance.

C o n c l u s i o n

Transportation and health: until recently, policymakers, government officials, advocates, and indeed, most Americans thought of these as distinct realms. But research shows that how we get around and how we transport goods and services have a profound impact on individual, community, and public health. Further, inequities in transportation resources contribute to the pronounced health disparities in the United States and to the growing income gap between the affluent and the poor. An overarching transportation policy that does not seriously consider public health, environmental quality, and equitable access will inevitably damage all three. Health and equity must be at the center of transportation planning and investments.

Health Effects of Transportation Policy

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Transportation Authorization 101: ch. 2 A Backgrounder SUSA N POL A N, Ph.D. Associate Executive Director, A merica n Public Hea lth Association

TR ACY KOLI A N, M.P.H. Senior Hea lth Policy A na lyst, A merica n Public Hea lth Association

SHIR EEN M A LEK A FZA LI, M.P.H. Senior Associate, PolicyLink

ABSTRACT >> For most people, federal policy seems removed from day-to-day life in their communities. But the federal surface transportation bill is a critical determinant of how our communities are formed, how they grow, and what types of transportation choices—if any— are available to us. Highways, rail systems, sidewalks, biking and walking paths, transit oriented development—all of these, and more—are shaped in large part by the federal transportation authorization. And federal transportation dollars are a major source of funding for states and metropolitan areas as they build new infrastructure and maintain existing transportation systems.

This publication discusses the connections between transportation and health; the analysis and the recommendations focus on the upcoming authorization of the federal surface transportation bill as a key opportunity for promoting health and equity. This section orients readers to the bill by briefly describing what the legislation includes, how it is authorized, and by whom—naming key committees and policymakers. This chapter also explains how federal funding is allocated to states and metropolitan regions to pay for public transportation systems, highways, bridges, sidewalks, bike paths, and other transportation projects in our communities.

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O v e r v i e w

Approximately every five years, Congress passes a new surface transportation bill and authorizes the U.S. Department of Transportation (DOT) to implement it. This bill sets federal transportation policy and designates transportation funding to states directly through formulas or through competitive grant programs for which states can apply. The programs and projects in the bill are funded through the Highway Trust Fund, which draws on a nationwide 18-cent per gallon tax on gas. The current law, passed in 2005, is called the Safe, Accountable, Flexible, Efficient, Transportation Equity: A Legacy for Users, or SAFETEA-LU. It represents a $244.1 billion federal investment in transportation infrastructure. SAFETEA-LU is set to expire September 30, 2009, and Congress must authorize a new bill. A new bill may also be postponed through extension of SAFETEA-LU until lawmakers are prepared to pass a new bill.

This report intentionally uses the term authorization and not reauthorization when referring to the process of developing a new surface transportation bill. “Authorization” symbolizes the significant reform necessary in the existing bill to meet current and future needs of a changing and diverse U.S. population. Reform is long overdue. With imperatives such as climate change, growing rates of chronic diseases and health disparities, increasing poverty rates, and an economic downturn, transportation policy must connect with national priorities, consider its impacts on these critical issues, and help to significantly change them. A reauthorization of the current bill will not address these challenges. A new federal transportation policy is needed to align its goals and actions to national priorities, address critical issues facing Americans, and ensure accountability and equity.

SAFETEA-LU includes a whopping 108 programs, each with distinct funding allocations and eligible activities for which funding may be used. For example, the eligible activities for one

program, the Safe Routes to School Program, includes activities related to the planning, design, and construction of infrastructure projects that improve the ability of students to walk and bike to school; states can use a portion of the funds for noninfrastructure-related activities to encourage walking and bicycling to school. The overall goal of the program is to enable and encourage walking and bicycling to school in a safe and appealing manner.1

An authorization establishes programs and sets ground rules under which the programs operate including the amount of funding available, how the funds are distributed, the length of time the funds can be used, and a list of eligible activities. Subsequent authorizations can change programs, eliminate programs, and create programs.

In the past several months, Congress and the DOT have been preparing to introduce a new federal surface transportation bill. Advocates have been gearing up to make sure this immense investment reflects the needs of all Americans. Right now is a crucial time to engage in transportation policy and to work to ensure that the policies and funding levels set for the next several years are aligned with important goals and ideals—health, safety, sustainability, economic opportunity, and equity.

The new bill could have enormous impacts on the funding available for various modes of travel as well as specific projects, thus influencing the decisions transportation planners and engineers make at the local level. For example, a region could expand a roadway instead of creating a subway system because there is more federal funding readily available for the highway project and the project evaluation and approval process for major transit investments is substantially more burdensome than the highway process. The federal pot of money for highway projects is far bigger than the pot available for public transportation. Currently, approximately 80 percent of federal transportation dollars go to the Federal Highway Administration (FHWA) as part of highway programs, while merely

Transportation Authorization 101

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one-fifth, or 20 percent, goes to the Federal Transit Agency (FTA) to be used for public transportation infrastructure. Only a very small portion of overall transportation funds are used for walking and biking infrastructure or other programs and most are administered through FHWA and FTA.

The first federal surface transportation bill, the Federal Aid Highway Act (popularly known as the National Interstate Defense Highways Act), was passed in 1956 as a means to fund a massive interstate highway system from coast to coast. Since the inception of the federal surface transportation bill, it has focused on highways as the key mode of travel. The 1991 surface transportation bill, the Intermodal Surface Transportation Efficiency Act (ISTEA), critically shifted the focus of federal transportation policy. In addition to funding traditional highway and transit programs, ISTEA included money for projects aimed at improving air quality, reducing congestion, and providing pedestrian and biking infrastructure. It launched the beginning of a more environmentally sensitive and multi-modal approach to transportation planning.2 While these laws made great strides at the time, we are far from implementing a truly multi-modal system where public transportation, walking, and biking are on equal footing with highways.

The next surface transportation bill must set about the urgent task of repairing and maintaining our transportation assets, building new transportation connections, and making our current system work more efficiently and safely to create complete and healthy communities that address the transportation needs of all communities. Modern and affordable public transportation, safe places to walk and bicycle, smarter highways that use technology to better manage congestion, land use policies that reduce travel demand by locating more affordable housing near jobs and services, and long-distance rail networks all have the potential to help us reduce our dependency on foreign oil, slow climate change, improve social equity, enhance public health, and fashion a vibrant new economy.

T h e a u t h o r i z a t i o n P r o c e s s

The U.S. Senate and the U.S. House each develops a transportation bill and then reconciles their differences before presenting a final bill to the president. In the House, the Transportation and Infrastructure Committee (T&I Committee), chaired by Rep. James Oberstar (D-MN), has primary jurisdiction over the bill. At time of printing, Chairman Oberstar has been working hard to write and pass a new bill with limited to no extensions to the current bill, SAFETEA-LU. Since SAFETEA-LU expires on September 30, 2009, some form of extension is likely to take place though it still remains unclear whether it will be a short extension or a longer 18-month extension as suggested by the administration.

The House T&I Committee has two counterparts in the Senate, where the jurisdiction is slightly more diffused. The Senate Environment and Public Works Committee (EPW Committee), chaired by Sen. Barbara Boxer (D-CA), has primary jurisdiction over the highway portion of the transportation bill, while the Senate Banking, Housing and Urban Affairs Committee (Banking Committee), chaired by Sen. Christopher Dodd (D-CT), has primary jurisdiction over public transportation portions. Both T&I, EPW and Banking have subcommittees focused on surface transportation that must develop and pass the first draft of the bill out of the subcommittees: the Highway and Transit Subcommittee of T&I, chaired by Rep. Peter DeFazio (D-OR); EPW’s Transportation and Infrastructure Subcommittee, chaired by Sen. Max Baucus (D-MT), and the Banking Committee’s Housing, Transportation and Community Development Subcommittee, chaired by Sen. Robert Menendez (D-NJ). Because of its financing mechanisms, the bill must also go through the House Ways and Means Committee, chaired by Rep. Charles Rangel (D-NY), and the Senate Finance Committee, chaired by Sen. Baucus. Other committees are also involved on the Senate side to a lesser degree. The following diagram traces the path of the transportation bill

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Transportation Authorization 101

Diagram 1. Surface Transportation Bill Authorization Process through Congress

Source: Chart from Federal Highway Administration, http://www.fhwa.dot.gov/reports/financingfederalaid/ authact.htm.

Subcommittee Bill

Committee Bill

Senate Bill

HOUSE OF REPRESENTATIVES

Public Hearings

Subcommittee Bill

Committee Bill

House Bill

SENATE

Public Hearings

Any Differences?

No

President

Veto

Override Veto?

No

Start Over SURFACE TRANSPORTATION ACT

Yes

Approval

Conference Committee

Conference Bill

Floor Action

Yes

Diagram 1: Surface Transportation Bill Authorization Process through Congress

2-1

Source: Chart from Federal Highway Administration, http://www.fhwa.dot.gov/reports/financingfederalaid/authact.htm.

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through Congress.

At each level of deliberation—whether subcommittee, committee, or floor—there is an opportunity to educate policymakers and their staff about the connections among transportation, equity, and health and to propose recommendations that will benefit the American public. While all representatives are important when the bill hits the floor of the Senate and House, key committee members are particularly influential in how the bill develops. Each subcommittee and committee has numerous representatives who can weigh in. Members of Congress are elected to serve us, the American people, and they often look to their various constituencies for advice. Advocates on Capitol Hill are making their interests known, and those outside of the nation’s capital are building coalitions, calling their elected representatives, and setting up appointments to voice their needs. The time to act is now.

fe d e r a l O v e r s i g h t a n d a d m i n i s t r a t i o n

The U.S. Department of Transportation and its implementing agencies—including the Federal Transit Agency, the Federal Highway Administration, and the National Traffic Highway Safety Administration—administer the funds authorized by the surface transportation bill.

The Highway Trust Fund (HTF) is the primary funding source for transportation. Like other federal trust funds the HTF is a financing mechanism to account for taxes collected by the federal government which are earmarked for a specific purpose or program. Initially, the HTF funded highways only. Later, Congress established that a portion of the funds should be used for public transportation creating the Mass Transit Account as part of HTF in 1983. Currently the Mass Transit Account receives 2.86 cents out of the 18 cent per gallon gasoline tax.3 Recently the HTF has not collected

enough revenue from the gas tax to cover the expenditures it supports. Congress has supplied funds from the general treasury to stop the gap, but this is not a sustainable solution. Congress and advocates are exploring new revenue streams to close the immense funding shortfalls. These include indexing the gas tax to inflation, imposing user fees such as toll or congestion pricing, or levying a sales tax on oil. Financing is an important debate, given the regressive nature of some forms of taxation and fees and the public’s resistance to raising taxes.

At the national level, there are three broad categories of federal transportation funding— highways, public transportation, and highway and motor vehicle safety. Each of these categories represents funding from numerous programs. Walking and biking infrastructure is not listed as a category because it is only a sliver of overall federal transportation spending, primarily through the Transportation Enhancements Program.

Most of the money from the surface transportation bill is distributed to states in two ways—through formula grant programs and through competitive grant programs. Formula- funded programs are by far the largest portion of this funding. The Surface Transportation Program (STP) —the largest program authorized in the surface transportation bill, which many call the highway program—allocates funds directly to state Departments of Transportation using the following formula:

• 25 percent based on total lane miles of federal-aid highways

• 40 percent based on vehicle miles traveled on lanes of federal-aid highways

• 35 percent based on estimated state contributions to the Highway Account 4

This program therefore rewards states and regions that drive more, build more highways, and use more gas—a combination that does little

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to promote health and environmental quality.

Another significant formula-funded program is the Urbanized Area Formula Grants Program (also called the Large Urban Cities Program), which allocates funds used for public transportation. Urbanized areas of 200,000 or more receive this money directly instead of having the funds go through state departments of transportation. The funds are distributed based on the following formulas:

For areas of 50,000 to 199,999 in population, the formula is based on population and population density. For areas with populations of 200,000 and more, the formula is based on a combination of: (1) the distance in miles that a revenue vehicle (a vehicle that is charging a fare) is operated while it is available for passenger service (also called bus revenue vehicle miles), (2) bus passenger miles, (3) revenue vehicle miles that run along exclusive or controlled rights-of-way or rails (also called fixed guideway revenue vehicle miles), (4) the number of miles of exclusive or controlled right-of-ways or rails for transit (also called fixed guideway route miles), and (5) population and population density.5

The Urbanized Area Formula Grants Program provides funds for public transportation, both rail and bus service. Transit dollars are explicitly prohibited from being used for operations in jurisdictions of 200,000 people and above. Therefore, most federal transit dollars can only be used on capital expenditures and not on operations. Many transit operators have huge gaps in their budgets and are raising fares and decreasing services—often at the same time—to stay afloat; many transit-dependent populations are suffering from this combination. Cutting routes that many residents depend on can create a situation where people cannot get to work or access goods and services. Raising fares particularly hurts low-income people who comprise the majority of the transit-dependent population. Many find themselves struggling even more to budget their transportation costs.

Another important formula program, the Highway Safety Improvement Program, is allocated via formula. The program was specifically created to improve highway safety. Funds are distributed to states based on the following three factors, all of which are weighed equally: (1) lane miles of Federal-aid highways, (2) vehicle miles traveled on Federal aid-highways, and (3) the number of fatalities on the Federal-aid system.6 Thus, the program awards more money to states which drive more, have more highways and more fatalities.

Some programs allow, encourage, or require a portion of the formula funds to be used for specific programmatic goals. For example, the Transportation Enhancements Program (TEP) is allocated using a portion of STP funds. TEP requires the use of a small percent of STP dollars for 12 eligible activities of which walking and biking infrastructure is a significant portion.

Competitive grants are also available for which states and locales can compete. These programs include money for specific program goals. For example, the Job Access and Reverse Commute Program (JARC) provides funding for projects that specifically help connect low-income workers to job centers.7 Another key example of competitive grant programs is the New Starts Program. This is the federal government’s primary financial resource for supporting locally planned, implemented, and operated major transit capital investments. It funds new and extensions to commuter rail, light rail, heavy rail, bus rapid transit, streetcars, and ferries, among others.8 Local entities must match the dollars provided by the Program. While the federal portion of the match can be up to about 80 percent, in reality locales have paid about 50 percent for projects funded by New Starts due to the high demand for this program and the competitive nature of funding. This adds a high financial burden on locales to support the creation of new transit projects.

Transportation Authorization 101

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S t a t e a n d l o c a l O v e r s i g h t

Federal dollars typically require a match by states or local agencies. The exact requirement of matching funds for competitive grants and formula grants varies by program.

Generally, transportation projects have been funded accordingly:

• Highways: 25 percent federal, mostly for capital investments; 50 percent states, for capital and maintenance; remaining 25 percent local governments9

• Transit: 25 percent federal, for largely capital investment; the remaining funds are split, 70–80 percent funded directly from transit users and local governments for operational costs; the remaining 20–30 percent is provided by state governments.10

At the local level, metropolitan planning organizations (MPOs) share $300 million a year in federal transportation funds. MPOs make policy at the regional level and work with state transportation agencies and regional officials to develop regional transportation plans. MPOs’ composition varies significantly from region to region, with representatives from local government, transportation authorities, and other stakeholders. About 385 MPOs operate in the United States. MPOs are required for urbanized areas with populations of more than 50,000 residents. The U.S. Secretary of Transportation can also designate transportation management areas (TMAs) for metropolitan areas with populations greater than 200,000.

While the needs of rural communities have been somewhat overlooked in transportation planning and decision making, rural planning organizations (RPOs) —consisting of networks of local planners, officials, and other stakeholders—do exist in smaller communities.

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RPOs are not federally mandated. State DOTs control planning and project selection outside of MPO areas. Therefore, rural areas have very little say in how transportation investments are made in their communities. Previous transportation bills provided some flexibility for transferring funds and suballocating dollars to cities and regions, but they lacked federal direction on what kind of national objectives should be promoted through these investments. Local and regional empowerment has been stunted in most states, given the lack of authority at the regional or local level in the project selection process or the direct funding allocation decision making. The impending bill should seek to provide direction on national objectives and create opportunities for appropriate ways to empower regional and local decision making that is equitable and provides a voice for all residents.

a T i m e f o r r e f o r m

There is no doubt that the U.S. transportation system critically needs reforming. Many of the most pressing issues and challenges our nation faces today—obesity, air quality, climate change, congestion, energy independence, lack of access, and sprawl—are linked to transportation.

Public health and equity advocates have vital roles to play among the many partners who will shape this new system. In fact, all of our transportation policies, programs, and decisions should be steeped in the understanding that safety, health, equity, and well-being of the general public is a national priority, that public health and equity must always be considered when creating transportation policy. National transportation objectives are being considered in the next surface transportation bill. Objectives would guide transportation investments to correspond with national goals of environmental quality, safety, equity and public health. National objectives also improve accountability of transportation investments by setting performance measures which help eliminate disparate funding between modes and ensure the country’s transportation system helps America move towards a healthy and sustainable future.

The coming authorization of the federal surface transportation bill affords the crucial opportunity to help shape and, more importantly, reform our transportation system. And this time around: public health and equity considerations must not be confined to a small number of specialty program areas; they should be an overriding theme throughout all transportation programming.

Transportation Authorization 101

ch. 2

How we get around—in cars or on foot, by bus, bicycle, light rail, or commuter train—affects public health, environmental quality, economic vitality, and social equity. The following section examines specific surface modes of transportation that have significant potential to improve health, reduce emissions, and increase access to jobs and other opportunities, particularly in underserved communities. These travel options also hold enormous opportunity for reform through the upcoming authorization of the federal surface transportation bill.

The chapters in this section cover:

>> Public transportation

>> Walking and bicycling

>> roadways

While modes of travel are important to highlight in debates over the bill and in the national priorities it will ultimately reflect, federal transportation policies and funding should not fall into mode silos. Rather, policies and funding should be driven by performance measures that hold states and locales accountable for creating transportation systems that promote health, environmental quality, and opportunity for all.

Modes of travel should not compete with one another. Instead, each mode should be placed on equal footing to allow American cities and towns to incorporate and connect various modes of travel in order to meet the needs of diverse and changing populations.

TrAnSPOrTATIOn OPTIOnS

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Public Transportation and Hea lth ch. 3 TODD LITM A N, M.E.S. Founder a nd Executive Director Victoria Tra nspor t Policy Institute Victoria, British Columbia

ABSTRACT >> Improving public transportation service, encouraging its use, and integrating it into community development plans can make Americans healthier by reducing per capita automobile travel and associated risks, increasing walking and cycling activity, and improving mobility for disadvantaged people. Conventional transportation policies and planning practices tend to favor the automobile. Various reforms can help create more efficient and equitable transportation systems that, among other benefits, help improve public health. This paper investigates these issues, examines the role public transportation plays in an efficient and equitable transport system, and presents specific recommendations for transportation and land use policies to help achieve public health objectives.

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Public Transportation and Health

CONTENTS

Introduction .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 39

Public Transportation's Roles.. .. .. .. .. .. .. .. .. .. 39

Public Transportation Health Impacts . .. .. .. .. .. 47

Traffic Crashes .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 47

Pollution Emissions .. .. .. .. .. .. .. .. .. .. .. .. .. 49

Physical Activity and Fitness . .. .. .. .. .. .. .. .. 49

Community Cohesion . .. .. .. .. .. .. .. .. .. .. .. 51

Mental Health Impacts .. .. .. .. .. .. .. .. .. .. .. 52

Basic Mobility.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 53

Policy Opportunities and Barriers . .. .. .. .. .. .. .. 53

Recommendations .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 55

Convergence Opportunities .. .. .. .. .. .. .. .. .. .. 59

Conclusion.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 60

LIST OF ILLUSTRATIONS

Figures

1. Transit Commute Mode Split in Selected Cities .. .. .. .. .. .. .. .. .. .. .. .. .. .. 40

2. Cycle of Automobile Dependency and Sprawl .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 43

3. International Vehicle Travel Trends . .. .. .. .. .. 44

4. Annual Change in Transit and Vehicle Travel . .. .. .. .. .. .. .. .. .. .. .. .. .. 45

5. Transport Fatalities .. .. .. .. .. .. .. .. .. .. .. .. .. 46

6. Annual Traffic Death Rates .. .. .. .. .. .. .. .. .. 47

7. U.S. Traffic Deaths .. .. .. .. .. .. .. .. .. .. .. .. .. 48

8. Daily Walking Trips and Transit Travel .. .. .. .. 50

9. Mode Split vs. National Obesity Rates . .. .. .. 52

Tables

1. Transit Level-of-Service Indicators.. .. .. .. .. .. 41

2. Personal Travel Mode Split of Various Countries .. .. .. .. .. .. .. .. .. .. .. .. 51

3. Scope of Conventional Planning Analysis .. .. 54

4. Healthy Transportation Policy Implementation . .. .. .. .. .. .. .. .. .. .. .. .. .. .. 58

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i n t r o d u c t i o n

Public transportation (also called public transit and mass transit) refers to various services using shared vehicles to provide mobility to the public, including buses, trains, and shared taxis. High- quality and affordable public transportation can help achieve various public health and equity goals by reducing traffic fatality rates, reducing air pollution emissions, increasing physical fitness, and improving nondrivers’ access to elemental goods and services—fresh, healthy food and healthcare—and reducing financial burdens on low-income households. In addition, public transportation can bolster a community’s quality of life by easing traffic congestion, energy costs, and pollution. Consequently, policies and investments that improve public transportation can be considered win-win strategies, providing diverse benefits and attracting broad support from a variety of interest groups.

However, current policies and planning practices fail to support public transportation to the degree justified by these benefits. Current evaluation practices overlook many benefits of public transportation, including many health benefits, and transportation financing systems provide inadequate funding. Without policy and planning reforms, public transportation will fail to provide its full potential benefits.

This paper examines the role public transportation plays in an efficient transportation system, the health benefits that can accrue from such a system, and models for creating a more equitable community by reforming transport policies and planning practices.

P u b l i c T r a n s p o r t a t i o n ’s r o l e s

Public transportation plays multiple roles in an efficient and equitable transportation system. It provides basic mobility for people who cannot use or access an automobile; it provides

efficient transportation on major urban corridors; and it serves as a catalyst for more compact, walkable communities, called transit oriented development.

Public transportation consists of:

• Heavy rail—relatively large, higher-speed trains, operating on separate rights-of-way, with infrequent stops, providing service between communities.

• Light-rail transit—moderate-size, medium- speed trains, operating mainly on separate rights-of-way, with variable distances between stations, providing service within an urban area.

• Bus rapid transit—bus systems with premium features, including grade separation, quick boarding, and frequent service.

• Express commuter bus—direct bus service from residential to employment areas.

• Conventional urban bus transit— medium- and full-size buses on fixed route, scheduled service.

• Mini bus—smaller buses or large vans used for public transportation.

• Demand response paratransit—small buses or vans that provide direct (door-to- door) service, often intended primarily for people with disabilities.

Each type of public transportation has its niche. Bus rapid transit and light-rail transit are the most appropriate on major urban corridors connecting large activity centers. Express commuter service is most appropriate on longer-distance commuter corridors with large employment centers (such as between suburbs and downtown). Conventional buses are most appropriate on urban and suburban roadways. Demand response is most appropriate in lower-density areas as well as for serving people with special needs.

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Although public transportation accounts for only a small portion of total travel in North America, it accommodates trips that are particularly important and costly to serve by other modes. In big cities, public transportation typically serves five to 15 percent of all commutes (figure 1) and as much as 20 to 60 percent of trips to major activity centers such as downtowns and university campuses. It provides mobility to people who are physically, economically, and socially disadvantaged and who would otherwise need to walk, bicycle, pay for a taxi, or simply not travel, sometimes to critical activities such as a doctor’s appointment, work, or school.

High-quality public transportation (either rail or

bus service that is convenient, fast, comfortable, and affordable) reduces automobile travel directly, by attracting travelers who would otherwise drive, and indirectly, by serving as a catalyst to help create more compact, walkable communities where residents drive less and rely more on alternative modes.2 These indirect, or leveraged, impacts often produce bigger results: studies indicate that each passenger-mile traveled in quality public transportation reduces the number of automobile vehicle-miles traveled by two to nine automobile vehicle-miles.3 As a result, residents of communities with access to good public transportation systems tend to drive 20 to 40 percent fewer annual miles than they would if they lived in more automobile- dependent communities.4

Public Transportation and Health

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Figure 1. Transit Commute Mode Split in Selected Cities

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16.9% 15.8%

13.2% 12.6%

9.9% 9.9% 8.7% 8.5%

7.8% 7.6% 7.1% 6.5% 6.3% 5.9% 5.8% 5.3% 5.2% 5.1% 5.0%

Although public transit serves only a small portion of total travel, it serves a significant portion of urban trips.

Figure 1. Transit Commute Mode Split in Selected Cities 1

Although transit serves only a small portion of total travel, it serves a significant portion of urban trips.

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Feature Description Indicators

Availability Where and when transit service is available

• Annual service-kilometers and service-hours per capita

• Daily hours of service

Frequency Frequency of service and average wait time

• Trips per hour or day • Headways (time between trips) • Average waiting times

Travel speed Transit travel speed • Average vehicle speeds • Transit travel speed relative to driving speed

for the same trip

Reliability How well service actually follows published schedules

• On-time operation • Portion of transfer connections made

Boarding speed

Vehicle loading and unloading speed

• Dwell time (time spent waiting at a stop or station)

• Boarding and alighting speeds

Safety and security

Users’ perceived safety and security

• Perceived transit passenger security • Number of accidents and injuries • Reported security incidents

Price and affordability

Fare prices, structure, payment options, ease of purchase

• Fares relative to average incomes • Fares relative to other travel mode costs • Targeted discounts or exemptions as

appropriate • Payment options (cash, credit cards, etc.)

Integration Ease of transferring between transit and other travel modes (bus, train, ferry, airport, etc.)

• Quality of transit service to transport terminals • Ease of accessing transit service information

from transport terminals

Comfort Passenger comfort • Seating availability and quality • Space (lack of crowding) • Quiet (lack of excessive noise) • Temperature (neither too hot nor too cold)

and air quality • Cleanliness

Accessibility Ease of reaching transit stations and stops

• Transit oriented development • Distance from transit stations and stops to

destinations • Walkability in areas serviced by transit

Baggage capacity

Accommodation of baggage • Ability to carry onboard baggage, including special items such as pets

• Ease and cost of carrying on baggage

Table 1. Transit Level-of-Service Indicators 5

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There are many ways to improve transit service and increase ridership (table 1). For instance, in the short-term, it is often possible to add new routes, increase service frequency, improve security, offer fare discounts, provide new amenities such as on-board refreshments and wireless Internet service (particularly for longer-distance express commuter service), and provide incentives such as parking cash out (offering commuters who currently receive subsidized parking the option of choosing its cash equivalent if they use alternative modes) and other rewards. In the medium-term, it is often possible to accelerate transit travel speeds,

increase reliability, improve stops and stations, provide real-time vehicle arrival information, upgrade vehicles for smoother and quieter rides, make trips more comfortable through better temperature control and fresh air, and provide park-and-ride facilities. In the long-term, it is often possible to create more transit oriented development so that more destinations (homes, worksites, and recreation and cultural centers) are located along major transit routes, with convenient pedestrian and bicycle access.

People sometimes mistakenly assume that these strategies are only feasible in large cities, but

Public Transportation and Health

Feature Description Indicators

Universal design

Accommodation of diverse users, including people with special needs

• Accessible design for transit vehicles, stations, and nearby areas

• Accommodation for people with limited language ability

User information

Ease of obtaining user information

• Availability, accuracy, and understandability of route, schedule, and fare information

• Real-time transit vehicle arrival information

Courtesy and responsiveness

Courtesy with which passengers are treated

• How passengers are treated by transit staff • Ease of filing a complaint • Responsiveness with which complaints are

treated

Attractiveness The attractiveness of public transportation facilities

• Attractiveness of vehicles and facilities • Attractiveness of documents and websites • Quality of nearby buildings and landscaping • Parks and recreational areas accessible by

transit • Provision of public art

Marketing Effectiveness of efforts to encourage using public transportation

• Popularity of promotion programs • Effectiveness at raising the social status of

transit travel • Increase in public transportation ridership in

response to marketing efforts

This table summarizes various factors to consider when evaluating public transportation services.

Table 1 continued

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some alternative modes are suitable for use in suburban and rural areas.6 These include ridesharing (car- and vanpooling), demand response transit (shuttle vans and buses that operate on flexible routes to provide door-to- door service in more dispersed areas), improved walking and cycling facilities (such as wider road shoulders and separated paths), telework (use of telecommunications as a substitute for physical travel, such as improving Internet networks and having more online public services in rural areas), and delivery services.7 Rural and suburban areas can become more accessible and multi-modal by encouraging village

development, where shops, public services, and housing (particularly for older adults and other nondrivers) are located close together and served by regional public transportation.

Improving and encouraging public transportation is a timely issue. During the past century, transportation planning focused primarily on cars, and transit systems were evaluated primarily in terms of automobile travel speed, affordability, and safety. Transportation improvements consisted primarily of building more roads and parking facilities. Planners barely considered other modes, which were

Figure 2. Cycle of Automobile Dependency and Sprawl

This figure illustrates the self-reinforcing cycle of increased automobile dependency and sprawl.

Automobile-Oriented

Transport Planning

Reduced Travel

Options

CYCLE OF AUTOMOBILE DEPENDENCY

Alternative

Modes Stigmatized

Suburbanization and

Degradation of Cities

Automobile-Oriented

Land

Use Planning

Generous Parking

Supply

Dispersed

Development Patterns

Increased Vehicle Ownership

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Public Transportation and Health

A N

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P E

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1970 1980 1990 2000

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Switzerland

Sweden

Spain

Portugal

Norway

Netherlands

Italy

Ireland

Greece

Germany

France

Denmark

Belgium

US

Per capita vehicle travel grew rapidly between 1970 and 1990 but has since leveled off in most OECD (Organizations for Economic Cooperation and Development) countries and is much lower in European countries than in the United States.

Figure 3. International Vehicle Travel Trends 8

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considered of declining relevance in a culture increasingly dependent on automobile travel. The result was a self-reinforcing cycle of increasing automobile dependency and sprawl, as illustrated in figure 2.

But per capita automobile travel has peaked and has recently started to decline slightly in most economically developed countries, as illustrated in figure 3.

These changes reflect demographic and economic trends that are reducing demands for automobile travel and increasing demands for alternative modes9:

• Increasing health and environmental concerns. Numerous individuals, organizations, and jurisdictions are now committed to reducing pollution and increasing physical fitness.

• Aging population. As the baby boom generation retires, per capita vehicle travel will decline and their demand for alternatives will increase.

Figure 4. Annual Change in Transit and Vehicle Travel 10

Transit trips increased more than vehicle mileage during seven of the last 10 years. Note: Annual percent change in 2002 was zero. Therefore the chart does not include a visible bar for transit trips.

Transit Trips

Vehicle Mileage

A N

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G E

-5

-4

-3

-2

-1

0

1

2

3

4

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6

1999 2000 2001 2002 2003 2004

YEAR 2005 2006 2007 2008

Figure 4. Annual Change in Transit and Vehicle Travel

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• Uncertain future fuel prices. This uncertainty increases demand for energy- efficient travel options and more accessible, multi-modal locations for homes and businesses.

• Increasing urbanization. An increasing portion of households are choosing to live in existing cities, and many suburbs are becoming more urbanized. This increases demand for urban modes (walking, bicycling, and public transportation).

• Increasing traffic congestion and roadway construction costs. This increases the relative value of alternative modes that reduce congestion.

• Shifting consumer preferences. Various indicators suggest that an increasing number of consumers prefer living in more densely populated urban neighbourhoods and using multiple modes of travel.

As a result of these shifts, public transportation travel grew more than automobile travel during seven of the last 10 years and each of the last four years, as illustrated in figure 4. During this period, transit travel increased 24 percent compared to a 10 percent increase in automobile vehicle miles traveled. Many transit systems now carry their maximum capacity during peak periods, constraining further growth. Increasing capacity and improving service quality would allow further growth in

Public Transportation and Health

Figure 5. Transport Fatalities 13

Public transportation travel has lower crash rates than automobile travel, taking into account risks to all road users.

F A

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Passenger Car Light Trucks Intercity Bus Transit Bus Heavy Rail Commuter Rail

1.3

9.2

7.9

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.3

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2.2

8.2

8.2

.3

0.4

1.8

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.1

4.4

.6

Other Road Users

Vehicle Occupants

Figure 5. Transport Fatalities

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public transportation ridership and additional reductions in automobile travel.

There is also growing demand for housing in multi-modal communities.11 The 2004 American Community Survey found that consumers place a high value on urban amenities such as shorter commute time and neighborhood walkability. Sixty percent of prospective homebuyers surveyed indicated that they preferred a neighborhood that offered sidewalks, a shorter commute, and amenities such as shops, restaurants, libraries, schools, and public transportation over more sparsely populated areas with larger lots but longer commutes and poorer walking conditions.12

P u b l i c T r a n s p o r t a t i o n H e a lt h i m p a c t s

This section describes ways that improving public transportation can help achieve health objectives.

Traffic Crashes

Public transportation is relatively safe, as indicated in figure 5. Transit vehicle occupants have about one-tenth the fatality rate as car occupants, and even considering the risk to other road users, public transportation causes fewer than half the total deaths per passenger- mile as automobile travel.

Figure 6. Annual Traffic Death Rates 15

The smartest growth counties in the United States have one-fifth of the average per capita traffic fatality rate as the most sprawled counties.

Figure 6. Annual Traffic Death Rates

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Smartest Growth

0

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30

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ga C

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y, O H

Cl in

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ty , M

I

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, O H

Go oc

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, V A

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W al

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A

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St ok

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Ba lti

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4.42 4.46 4.2 4.58 6.31 5.91

8.04

4.49 5.63

7.68

15.66

38.80

25.84

12.78

19.77

38.52

35.58

38.02

16.99

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High-quality public transportation provides even greater safety benefits than indicated by these distance-based fatality rates because it tends to leverage additional reductions in per capita vehicle travel. People who live or work in transit oriented areas tend to drive less (due to more accessible, multi-modal community design), drive at lower traffic speeds (due to more compact development), and do less high- risk driving (for example, teenagers are less likely to have a driver’s license and own a vehicle). 14 As a result, such communities have about one- fifth of the total per capita traffic fatality rate as sprawled, automobile-dependent communities, taking into account all traffic deaths, including risks to pedestrians, bicyclists, and public transportation travelers (figure 6). Traffic deaths

are a subcategory of violent deaths and overall, urban residents have significantly lower rates of violent deaths, even taking into account homicide risk.16

Per capita traffic fatalities decline as transit ridership increases in a community, as indicated in figure 7. The reduction in per capita crash rates is much larger than the reduction in per capita mileage in these cities, reflecting the combined effects of various transportation and land use factors associated with transit oriented development that increase safety, as previously described.

Public Transportation and Health

Figure 7. U.S. Traffic Deaths 17

Per capita traffic deaths (including transit and automobile occupants as well as pedestrians) tend to decline with increased transit ridership and are particularly low in cities with strong rail transit systems.

0

5

10

15

20

25

0 200 400 600 800 1000 1200

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Weak Rail

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ANNUAL PER- CAPITA TRANSIT PASSENGER-MILES

R2 = 0.352

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Pollution Emissions

A second category of transport-related health impacts involves vehicle pollution emissions, including tailpipe emissions; also included are emissions from fuel production and distribution (“upstream” emissions), hot soak (evaporative emissions that occur after an engine is turned off), and particulates from road dust, brake linings, and tire wear.18

Many factors affect vehicle pollutant human health impacts, including emission rates per vehicle mile, per capita mileage, and exposure (the number of people located in areas where emissions are concentrated). Motor vehicle air pollution is estimated to cause a similar order of magnitude of total premature deaths as traffic crashes, although the victims tend to be older; thus air pollution causes smaller reductions in Potential Years of Life Lost (PYLL) than traffic crashes.19

Public transportation tends to produce less pollution per passenger-mile, particularly electric-powered trains and newer buses with state-of-the-art engines. And, as previously discussed, transit oriented development tends to reduce automobile travel and, therefore, emissions. On the other hand, older diesel buses tend to have high emission rates; public transportation tends to concentrate activity close to roadways; and bus depots are often located in low-income communities. Consequently, in some situations, increased transportation service and transit oriented development may increase human exposure to harmful air pollutants such as particulates and carbon monoxide unless implemented with bus emission reduction programs.

Physical Activity and Fitness

Another category of health impacts concerns the effects transport has on physical activity and fitness.20 Public health officials have become increasingly alarmed about declining physical fitness, increasing body weight, and

resulting increases in diseases associated with a sedentary lifestyle.21 There are many ways to be physically active, but many, such as team sports and gym exercise, require special time, skill, and expense, which discourage consistent, ongoing participation. Many experts believe that increasing community walking and bicycling (together called “active transportation”) are the most practical ways to improve public fitness, particularly for vulnerable populations— children, older adults, and people with low incomes who may be unable to participate in structured exercise programs due to financial and time constraints.22

Public transportation and active transportation tend to be complementary: most public transportation trips involve walking links; transit oriented development includes walking and biking improvements; and efficient transit systems incorporate amenities such as bike racks on buses and bike lockers at transit stations.23 As a result, increased transit travel tends to increase physical activity.

The National Household Travel Survey (NHTS) indicates that people who use public transportation on a particular day spend a median of 19 minutes daily walking to and from transit, and 29 percent achieve 30 minutes of physical activity during transit access trips—much higher than the rates by nontransit users.24 Using pedometers and surveys to track walking activity, Wener and Evans found that train commuters walked an average of 30 percent more steps daily, more frequently reported walking for 10 minutes or more, and were four times more likely than automobile commuters to achieve the 10,000 steps daily recommended for fitness and health.25

Similarly, a travel survey conducted in Atlanta, GA, found that public transportation users are more likely to walk, to walk longer average distances, and to meet recommended physical activity targets by walking than nontransit users.26 The study revealed that the chance a person meets minimum walking targets (2.4

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kilometers walked daily) increases by 3.87 for each transit trip taken and is 2.23 times greater for commuters who use an employer-sponsored public transportation pass. Public transportation travel increased walking activity for all income classes, as illustrated in figure 8, indicating that encouraging transit travel can support public health for a variety of demographic groups.

Residents of transit oriented communities tend to walk more and have lower rates of obesity and hypertension than residents in sprawled areas. A recent study collected transportation mode split and obesity rate data for various economically developed countries, as summarized in table 2 and figure 9. Two important points are illustrated: travel

patterns are highly variable, even among similar countries, and national obesity rates tend to be inversely related to rates of active transportation (walking and biking), suggesting that transport policy affects public fitness and health.

As a result, policies and planning practices that support public transportation tend to increase public fitness and health. Sturm estimates that shifting from a sprawled area such as San Bernardino, CA, to a areas which reflect smart growth principles such as Boston, MA, reduces chronic medical conditions about 16 percent, with greater reductions for older adults and low-income people because they tend to be most sedentary.30

Public Transportation and Health

Public transportation users are much more likely to take walking trips and walk much farther than nontransit users.

Transit Users

Nontransit Users

0%

10%

20%

30%

40%

50%

60%

70%

80%

59.6%

11.6%

60.9%

9.0%

56.3%

8.9%

58.9%

9.3%

Figure 8. Daily Walking Trips and Transit Travel

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O K

A T

L E

A S

T O

N E

W A

L K

T R

IP

ANNUAL INCOME CLASS

Under $30k $30–60k Over $60k Total

Figure 8. Daily Walking Trips and Transit Travel 27

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The total health costs that result from inadequate physical activity are far greater than those from traffic crashes. Cardiovascular diseases cause about 10 times the loss in productivity as do road crashes, and sedentary living contributes to a variety of other health problems—hypertension, non–insulin- dependent diabetes, colon cancer, osteoarthritis, osteoporosis, and probably depression. Even modest reductions in these illnesses could provide large health benefits. However, it is difficult to determine how a particular transportation policy will affect these diseases overall because it depends on the ability of otherwise sedentary people to increase their physical activity. The Health Benefits Economic

Model provides a methodology for valuing the health benefits of more active transportation.31

Community Cohesion

Community cohesion refers to the quantity and quality of positive interactions among residents in a local community.32 It affects human health in various ways, including the mental health benefits of friendly social interactions and the health benefits of increased neighborhood security.33 Although many demographic and geographic factors affect neighborhood interactions, cohesion tends to increase with walkability and local services.34 High-quality public transportation and transit oriented

Country Year Transit Bike Walk Obesity Rates*

Latvia 2003 32% 5% 30% (13.7%*)

Switzerland 2005 12% 5% 45% 8%

Netherlands 2006 5% 25% 22% 8.1% (11.2%*)

Spain 2000 12% N/A 35% 12.8%

Sweden 2006 11% 9% 23% 9.4%

Germany 2002 8% 9% 23% 12.1%

Finland 2005 8% 9% 22% 13.3%

Denmark 2003 8% 15% 16% 12.2%

Norway 2001 10% 4% 22% 14.3%*

U.K. 2006 9% 2% 24% 24%*

France 1994 8% 3% 19% 11%

Ireland 2006 11% 2% 13% 18%

Canada 2001 11% 1% 7% 15.2 (22.7%*)

Australia 2006 8% 1% 5% 16.2% (20.8%*)

U.S. 2001 2% 1% 9% 34.3%*

Table 2. Personal Travel Mode Split of Various Countries28

* Combined male and female obesity prevalence based on body mass index (BMI). Values in parentheses are from national health examination surveys. Other values are based on self-reported weight and height.

Source: D. Bassett et al., “Walking, Cycling, and Obesity Rates in Europe, North America, and Australia,” 2008.

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development can increase community cohesion by creating opportunities for residents to interact while walking, waiting at transit stops, and riding on transit vehicles. Further, they reduce total automobile traffic, which improves the public realm, for example, by reducing traffic noise on sidewalks and front yards.35 This can increase connections and contacts among dissimilar groups, helping to bridge social distance and widening opportunities by introducing disadvantaged children to more affluent families and broadening the pool of role models and mentors available to low- income youths.36 Long-term social and economic benefits can result by increasing educational and

employment opportunities and reducing crime and dependence on social assistance.

Mental Health Impacts

Public transportation improvements such as increased service, improved climate control, more comfortable waiting conditions, and improved service reliability can improve mental health by reducing physical and emotional stresses (crowding, fear, and frustration), increasing affordability (and therefore reduced financial stress), influencing access to education and employment activities (and therefore long- term economic opportunities), and helping

Public Transportation and Health

Figure 9. Mode Split vs. National Obesity Rates29

This data set indicates that transportation mode split is highly variable, even among economically developed countries, and national obesity rates are inversely related to rates of active transportation (walking and bicycling).

Walk

Obesity Rates

Bike

Transit

0%

10%

20%

30%

40%

50%

60%

70%

80%

43%

32

67%

12

62%

22

52%

25

5 12

35

47%

5

8% 11.2%

12.8% 9.4%

12.1% 13.3% 12.2%

14.3%

24%

11%

18%

22.7%

34.3%

45

5

30

13.7% 9

11

23

40% 39% 39% 36% 35%

30%

26%

19%

14% 12%

23

9

8

22

9

8

16

15

8

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4

10

24

2

9

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8

13

2

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7

1

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1

8

9

1

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Au st ra

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Ca na

da

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nd

Fr an

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ay

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ar k

Fi nl

an d

Ge rm

an y

Sw ed

en Sp

ai n

Ne th

er la

nd s

Sw itz

er la

nd

La tv

ia

Figure 9. Mode Split vs. National Obesity Rates29

3-9

2

Source: D. Bassett et al., “Walking, Cycling, and Obesity Rates in Europe, North America, and Australia,” 2008.

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to create more walkable communities, which increases physical activity and fitness.37 With high-quality service, many commuters find public transportation less stressful than driving.38 These mental health benefits are difficult to quantify but potentially large.

Basic Mobility

Basic mobility refers to people’s ability to access services and activities that society considers basic or essential, including medical and dental services, food and other basic goods, banking, education, and employment opportunities.39 Basic mobility is important for physical and mental health and is a critical equity objective. Public transportation provides basic mobility and accessibility, including access to medical services, affordable and healthy food, education, and employment. Inadequate transport options can result in patients missing appointments, which can exacerbate medical problems and waste medical resources, or force patients or medical service providers to pay for more costly transport services such as taxis.40 One survey found that four percent of U.S. children (3.2 million in total) either missed a scheduled healthcare visit or did not schedule a visit during the preceding year because of transportation restrictions.41 Although it is difficult to quantify the ultimate health benefits from basic mobility provided by public transportation, anecdotal evidence suggests that these impacts can be significant.

P o l i c y O p p o r t u n i t i e s a n d B a r r i e r s

As noted, alternative modes—walking, cycling, and public transportation—can provide many economic, social, and environmental benefits. Yet current policy analysis and planning practices tend to undervalue alternative

modes and thus provide less support for and investment in them than is optimal.42 Some specific ways that alternative modes are undervalued are described below.

Conventional transportation planning analysis tends to focus on a limited set of impacts and objectives and overlooks others, as summarized in table 3. The impacts that conventional planning focuses on most—travel speed, congestion, and vehicle operating costs—tend to favor automobile transportation. Many benefits of public transportation, such as basic mobility for nondrivers and parking cost savings, are generally overlooked in conventional policy and planning analysis. Some of these omissions reflect the difficulty of quantifying impacts such as equity and sprawl costs, but others (parking costs and mileage-based depreciation, for example) are ignored simply out of tradition.

For example, when comparing highway expansion projects with public transportation improvements, conventional planning generally ignores the effects of generated traffic (the additional peak-period vehicle travel that results if congested roads are expanded), additional downstream congestion (additional traffic on surface streets), parking costs, vehicle ownership costs, traffic accidents, energy consumption, and pollution emissions—all costs that can be reduced if improved service allows the same trips to be made by public transportation. In addition, conventional analysis assumes that everybody (or, at least, everybody who matters) has a vehicle and can drive and thus assigns no explicit value to improving mobility for nondrivers.

Conventional analysis assigns no value to the fitness, health, and enjoyment benefits of increased walking and cycling activity44; conventional planning analysis would recognize

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the value of a motor vehicle trip to a gym to allow passengers to exercise on a treadmill, or to a park to walk or bike on public paths, but would not recognize the value of being able to walk or bike, rather than drive, for local errands.

Conventional planning tends to evaluate transport system performance based on the speed, convenience, and affordability of automobile travel, using indicators such as roadway level of service, average traffic speeds, congestion delay, parking supply per 1,000 square feet of building floor area, crash risk per 100 million vehicle-miles, and vehicle operating costs (particularly fuel costs). Comparable indicators are not usually provided for alternative modes, so it is more difficult to identify walking, cycling, and public transportation problems

as well as opportunities to improve these modes. For example, urban transportation models are often used to produce maps that show roadway congestion delays, indicated by roadway level-of-service grades from A to F, but no comparable indicators are provided for walking, cycling, and public transportation problems, putting these modes at a competitive disadvantage for investment.

This type of analysis often implies that public transportation investments are not cost effective, but this results, in part, from biases in conventional traffic models that tend to exaggerate the benefits of highway expansion and understate the benefits of improving alternative modes, particularly high-quality public transportation.

Public Transportation and Health

Usually Considered Often Overlooked

Financial costs to governments

Travel speed (reduced congestion delays)

Vehicle operating costs (fuel, tolls, tire wear)

Per-mile crash risk

Project construction environmental impacts

Downstream congestion impacts

Generated traffic impacts

Nondriver mobility, convenience, and comfort

Transportation diversity value (e.g., mobility for nondrivers)

Parking costs

Vehicle ownership and mileage-based depreciation costs

Project construction traffic delays

Total energy consumption and pollution emissions

Strategic land use objectives

Per capita crash risk

Impacts on physical activity and public health

Some travelers’ preference for transit (lower travel time costs)

Table 3. Scope of Conventional Planning Analysis 43

Conventional transportation planning tends to focus on a limited set of impacts, exaggerating the benefits of highway expansion and undervaluing transit improvements.

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Transportation financing is also biased in favor of roadway improvements. A major portion of transportation funding is legally or practically restricted to automobile facilities and cannot be used to improve public transportation services, even when such improvements are more cost effective and beneficial overall.45 Thirty of the 50 states have constitutional amendments that limit fuel tax revenue to be spent only on highways, and most zoning codes require developers to provide generous amounts of vehicle parking—a large subsidy of driving that is difficult to convert into transit subsidy, even if preferred by some travelers (a concept called parking cash out). More neutral financing (sometimes called least cost planning) tends to increase funding for alternative modes and mobility management strategies.

Current transportation markets are further distorted in favor of automobile travel by underpricing. Although automobiles are expensive to own, they are relatively cheap to drive because most of the costs are either fixed or external. This gives motorists an incentive to drive more annual miles than optimal. An efficient transportation market would require increased road, parking, and fuel prices, along with distance-based insurance and registration fees, which would significantly increase the marginal cost of driving, particularly under urban peak conditions.

Together, these planning and market distortions increase automobile travel beyond what is economically optimal, reduce use of alternative modes, and stimulate more dispersed, automobile-oriented land use development. Described differently, with more optimal transport planning and pricing, consumers would choose to drive less, rely more on alternative modes, select more multi-modal communities, and be better off overall as a result.46 Although it is difficult to predict the exact magnitude of these changes, they are likely to be large, particularly over the long-term.

r e c o m m e n d a t i o n s

Various transportation policy and planning reforms can improve public safety, fitness, and health by creating more efficient and multi-modal transportation systems where people drive less and rely more on alternative modes.47 Improved public safety, fitness and health are just three of many possible justifications for these reforms: they would help solve a variety of transportation problems, they reflect market principles and so increase economic efficiency, and they respond to changing consumer demands.48

The following are specific policies and planning strategies that can help create more diverse, more efficient, and healthier transportation systems:

• Educate decision makers concerning the relationships among transportation, land use, and public health; the full benefits of a more diverse, less automobile-dependent transportation system; and the trends that are changing future travel demands and strategic objectives.49 These all tend to increase the value of alternative modes, mobility management solutions, and smart growth land use development.

• Create a strategic vision of a more efficient and diverse transportation system and supportive land use development to accommodate changing demands and planning objectives, including public health objectives. This vision, which should be created by the federal government, should guide individual transportation and land use policies and planning practices, such as how transportation system quality is evaluated and how transportation funding is allocated.

• Increase public transportation funding for capital and operation costs. Transportation funding practices that currently favor investments in roads and parking facilities should be changed to allow significant new investments

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in public transportation. For example, economic stimulation and other economic development funds should be invested in public transportation. Transportation funds currently dedicated to roadways should be spent on public transportation improvements whenever it is more cost effective overall, taking into account all benefits and costs. Similarly, resources currently spent by governments and developers on parking facilities should be reinvested in public transportation whenever it is a cost-effective way to provide access. New funding sources should be developed to help finance public transit improvements, including parking taxes, congestion pricing, local property taxes, land value capture, and dedicated sales taxes.50 Higher levels of government (federal and state) should provide grants that leverage additional regional and local match funding. Regional and local governments must create stable sources of transit funding through dedicated fuel, sales, property, and parking taxes.

• Improve public transportation affordability. Insure that public transit services are affordable, particularly for lower- income users. This may include targeted discounts and exemptions, and research to identify better ways to meet the mobility needs of economically, physically and socially disadvantaged people.

• Establish transportation and land use policies that support transit oriented development so that more people are able to live and work in areas with high-quality public transportation services, good walking and biking conditions, compact and mixed land use development, and other supportive features.

• Implement transportation and land use policies that increase housing affordability in transit oriented communities.51 This includes changing development practices to encourage development of more compact and diverse housing types (small-lot single- family, townhouses, multi-family, etc.) with

unbundled parking in transit-rich, walkable areas with mixed land use and appropriate public services (schools, shops, parks, etc.), and employment.52 Public infrastructure investments and housing subsidies should be structured to support these objectives.

• Improve walking and bicycling conditions and promote active transportation. Encourage transportation professionals to recognize the importance of walking as a transport mode and to develop tools for evaluating the full benefits of improved walking and biking conditions and increased active transportation. Improve walking and bicycling access to transit stops and stations. Have bike racks on buses and trains, bike parking at stations, and bike rental services. Promote “walk and bike to school” and community walking and cycling events.

• Work to integrate affordable housing and affordable transportation so that physically, economically, and socially disadvantaged households can live in accessible, multi-modal communities. This requires a suitable mix of housing (affordable and subsidized housing included), public services (stores, medical and dental clinics, schools, parks, etc.), and high-quality public transportation located within convenient walking distance, with universal design features to ensure that everybody (including people using wheelchairs, walkers, pushing strollers, and hand carts) can easily travel to common destinations.

• Develop and apply multi-modal level-of- service standards to evaluate the service quality of various modes, including walking, biking, public transportation, taxi, car-sharing, and telecommunications within a community. Transportation agencies and professionals should use these to identify mobility and accessibility problems, particularly for the most vulnerable populations (children, older adults, people with disabilities, people with low incomes, immigrants, etc.).

• Apply least-cost planning so that transportation improvement resources (public funds and land) are invested in the most cost-effective improvements and consider all impacts and objectives, including public health objectives. Allow funds currently dedicated to roads and parking to be used for alternative modes and management strategies when they are more beneficial overall or support strategic planning objectives.

• Implement mobility management strategies and programs that encourage the use of alternative modes, such as efficient road and parking pricing, distance-based vehicle fees, and commute-trip reduction programs. Implement these in conjunction with transit service improvements.

• Develop and apply more comprehensive transportation planning tools for evaluating transit service quality,

transportation affordability, basic mobility, equity, affordability, and public health impacts.

• Sponsor research to improve public transit vehicles so that they are quieter, smoother, more spacious, climate controlled, less polluting, and easier to board; they should accommodate people with disabilities and offer amenities such as wireless Internet service. Give transit priority in traffic (bus lanes and signal control systems).

• Sponsor research and development to improve transit stops and stations so that they are more spacious, more comfortable, and safer; they should include amenities such as washrooms and refreshments.

• Develop convenient, integrated fares (for example, one payment system that can be used on various public transportation systems within a region) using electronic payment systems.

• Improve transit user information and marketing, such as real-time vehicle arrival signs, better-way finding, and culturally appropriate promotion programs.

• Apply more efficient parking management, such as efficient sharing, regulation, and pricing of parking facilities. Apply more flexible and reduced minimum parking requirements in transit oriented areas, particularly to increase housing affordability.

• Build coalitions involving public health and safety advocates and other interest groups that can benefit from transportation policy and planning reforms creating more efficient and diverse transportation systems—existing transit and community advocacy groups, transportation professionals, environmental organizations, local public officials, and economic development advocates. Use these coalitions to create the political support needed to achieve this vision.

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Reforms and Actions

Leaders Federal Legislative Role

Educate decision makers

Professional and advocacy organizations

Support policy analysis, research, and information sharing

Create a strategic vision

All levels of government; professional and advocacy organizations

Establish a national vision and encourage other levels of government to develop complementary visions

Increase public transportation funding

All levels of government Change transport funding to support public transportation, increase federal funding for public transportation programs, and use federal policies to leverage funding by other levels of government

Insure public transport affordability

All levels of government Provide funding, research and other support to insure that transit service is affordable and responds to the needs of disadvantaged people.

Support transit oriented development

All levels of government; transportation and land use planning agencies and professions

Change transport and land use policies to support transit oriented development and smart growth

Improve walking and cycling conditions

All levels of government; transportation and land use planning agencies and professions

Change transport funding and planning practices to support active transportation and walkable community development

Integrate affordable housing and affordable transportation

All levels of government Change transport and housing policies to support development of affordable housing in transit oriented areas

Apply multi- modal level- of-service standards

All levels of government; transportation agencies and professions

Change transport funding and planning practices so they are based on multi-modal performance evaluation

Apply least-cost planning

All levels of government; transportation agencies and professions

Change transport funding and planning practices to allow alternative modes and mobility management strategies to be funded whenever they are most cost effective, considering all impacts and objectives

Implement mobility management strategies and programs

All levels of government; transportation agencies and professions

Change transport funding and planning practices to support mobility management whenever it is cost effective, considering all impacts and objectives; support pricing reforms such as increased fuel taxes, road pricing, and distance-based insurance and registration fees

Table 4. Healthy Transportation Policy Implementation

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Implementing these reforms will require action by various stakeholders, including federal, state, regional, and local governments, as well as diverse interest groups and advocates. Federal legislation can help support many of these reforms and actions by providing guidance and incentives. Such leadership and guidance can significantly accelerate the implementation of these reforms and avoid conflicts between existing and desired transportation policies. Table 4 indicates the level of government,

organization, or interest group that can provide leadership for implementing these recommendations and outlining the role of federal legislation.

C o n v e r g e n c e O p p o r t u n i t i e s

Many interest groups and organizations with a wide range of objectives and perspectives have reasons to support policies to create a more efficient and diverse transportation system.

Reforms and Actions

Leaders Federal Legislative Role

Develop more comprehensive transportation planning tools

All levels of government; transportation agencies and professions

Support research for more comprehensive transport planning tools

Improve transit vehicles

Vehicle engineers, manufacturers, transit agencies, and governments

Support research; develop procurement guidelines

Improve transit stops and stations

All levels of government; transportation and land use planning agencies; private companies; and developers

Support innovative design and business models; support transit oriented development

Develop convenient, integrated fares

Regional governments and transit agencies

Support research, design, and implementation

Improve transit user information and marketing

Regional governments and transit agencies

Support research, design, and implementation

Apply more efficient parking management

All levels of government; transportation and land use planning agencies; private companies; and developers

Support transit oriented development and smart growth; provide incentives for local and regional governments to implement parking management

Build coalitions Professional and advocacy organizations

N/A

This table indicates how various stakeholders can help implement transportation policy reforms to improve public fitness and health. Public transit improvements can play a key role in many of these strategies.

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This diverse interest offers an opportunity to build broader support for transit investments and supportive transportation and land use policies. For example, this is an ideal time to create collaborations among existing public transportation and community advocacy groups (wanting to achieve equity objectives), transportation professionals (wanting to reduce problems such as traffic and parking congestion), environmental organizations (wanting to reduce energy consumption, pollution emissions, and land use damages), local public officials (wanting to support urban redevelopment), senior advocacy groups (wanting to improve mobility options for nondrivers, to increase affordability, and to provide practical ways for older Americans to safely exercise), and health professionals (wanting to improve public fitness and health).

To fully achieve the potential benefits of high- quality public transportation, these diverse interest groups will need to overcome cultural and practical barriers. For example, correcting existing policy and planning biases that favor mobility over accessibility and automobile transportation over other modes will probably require a combination of professional education, planning agency reforms, and political advocacy to change laws and funding practices. No single interest group can achieve all these changes, but a collaborative effort can succeed.

Public transportation improvements can play a much greater role in creating a more diversified and efficient transportation system than indicated by its relatively modest share of total travel. High-quality public transportation often provides a catalyst for creating a more diverse transportation system and accessible, multi-modal land use development. Public transportation travel both supports and is supported by walking and biking trips. As a result, public transportation improvements can leverage large reductions in automobile travel and increases in walking and cycling activity.

The involvement of health professionals can significantly improve the chances for success because they can contribute a new sense of urgency, expertise, and leadership into transportation and land use policy reform debates. Previous public health successes, such as reduced tobacco use and increased breastfeeding, can provide models.

C o n c l u s i o n

Transportation planning decisions impact public health in various ways: by affecting traffic risk, pollution exposure, physical activity and fitness, community cohesion, mental health, basic mobility, and affordability. Communities where people drive less and rely more on alternative modes are healthier places to live and work, particularly for physically, economically, and socially disadvantaged people. Transportation policy and planning reform improvements can play a significant role in creating healthier communities. High-quality public transportation (convenient, comfortable, frequent, fast, reliable, and safe) provides significant direct benefits when people shift from automobile to transit for individual trips. It provides even larger indirect benefits by providing a catalyst for development of more accessible, multi- modal communities where people own fewer

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automobiles; drive less; and rely more on walking, biking, and public transportation for utilitarian trips and recreation.

This is a timely issue. Current demographic, economic, and market trends are reducing the demand for automobile travel and increasing the demand for alternative modes. This is not to suggest that Americans will give up driving altogether; but at the margin, that is, relative to current travel patterns, many people would prefer to drive less and rely more on alternative modes, provided that these alternatives are convenient, comfortable, safe, and affordable. This means that many consumers will choose healthier transport habits if given appropriate options, including high-quality public transportation and accessible, multi-modal communities.

Current transportation and land use planning practices favor automobile transportation and undervalue alternative modes and smart growth development. Various transportation policy and planning reforms can help achieve public health and social equity objectives by helping to create more diverse and efficient transportation systems. More comprehensive analysis is needed that accounts for the additional indirect costs of policy and planning decisions that increase automobile travel and sprawl and the additional indirect benefits of more compact, walkable, and transit oriented communities. Current funding is inadequate, causing public transportation service quality to decline and fares to increase in many communities. Budgeting practices must be reformed to provide adequate, reliable funding to ensure high-quality and affordable public transportation services. Land use development policies should change to better support smart growth and reduce sprawl.

These reforms are justified for a number of reasons, due to the diverse economic, social, and environmental benefits provided by public transportation improvements. When all impacts are considered, improving public transportation may be among the most cost-effective ways to improve public health, and improving public health is one of the best reasons to improve public transportation.

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Wa lking, Bicycling, and Hea lth ch. 4 SUSA N L . H A NDY, Ph.D. Professor, Depa r tment of Environmenta l Science a nd Policy University of Ca lifornia Davis, CA

ABSTRACT >> Walking and bicycling are efficient modes of travel and effective forms of exercise. Starting with the passage of the Intermodal Surface Transportation Efficiency Act (ISTEA) in 1991, the federal government has provided various forms of financial support for non-motorized transportation, but increasing walking and bicycling without increasing fatalities and injuries requires more than the limited federal resources to date. State, regional, and local policies determine the extent to which communities capitalize on the federal programs to expand walking and bicycling and help close the gap in health disparities between low-income communities and their more affluent neighbors. To increase non-motorized modes of travel—travel by walking and bicycling— safely, the authorization of the next federal transportation bill should:

• Assist: by providing state, regional, and local governments with the tools they need to plan for non- motorized travel

• Enable: by making it easier for state, regional, and local governments to spend federal funding on non-motorized modes

• Encourage: by providing incentives for state, regional, and local governments to pay more attention to non- motorized modes

• Require: by putting in place policies that compel state, regional, and local governments to improve conditions for non- motorized modes

Increased walking and bicycling would yield many health benefits and reduce disparities in health for low-income communities and others. The federal transportation bill can establish policies that will help to achieve the goal of increasing walking and bicycling safely.

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Walking, Bicycling, and Health

CONTENTS

Introduction .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 65

Health and Non-motorized Transportation.. .. .. 68

Transportation Goals . .. .. .. .. .. .. .. .. .. .. .. .. .. 70

Strategic Targets .. .. .. .. .. .. .. .. .. .. .. .. .. .. 70

Measuring Progress.. .. .. .. .. .. .. .. .. .. .. .. .. 73

Transportation Policy: Opportunities and Barriers .. .. .. .. .. .. .. .. .. 74

Convergence Opportunities .. .. .. .. .. .. .. .. .. .. 77

Conclusion.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 77

LIST OF ILLUSTRATIONS

Figures

1. Share of Trips by Walking, Bicycling, and Transit, by Country .. .. .. .. .. .. .. .. .. .. .. 65

2. Percent Usually Bicycling to Work in Selected U.S. Cities, 2000 .. .. .. .. .. .. .. .. 66

3. Cyclist Fatality and Injury Rates, by Country .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 69

4. Percent Walk and Bike Trips by Trip Length, Germany vs. United States .. .. .. .. .. .. .. .. .. 71

5. Trends in Mode of Travel to School in the United States, 1969–2001 .. .. .. .. .. .. 72

Tables

1. Factors Influencing Non-motorized Travel.. .. 67

2. Recommendations for Federal Policy on Walking and Bicycling .. .. .. .. .. .. .. .. .. .. 76

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Walking and bicycling as modes of transportation—known as “non-motorized” or, more recently, “active” travel—are low- cost, low-polluting, calorie-burning, health- improving alternatives to driving. Despite these advantages, non-motorized modes represent a small share of all travel in the United States, or fewer than 10 percent of all daily trips in urban areas as of 2001.1 Increasing this number, without a congruent increase in fatalities and injuries, would yield considerable benefits, especially among low-income communities and people of color, the young and older adults, by helping to close wide gaps in health in this country. But what policies would achieve this aim?

For guidance, we can look to other developed countries, where rates of walking and bicycling are significantly higher than in the United States, particularly in Denmark, Germany, and the Netherlands (figure 1). We can also look to communities in the United States, where bicycle commuting is significantly more common than the national average of less than one percent of workers (figure 2). Common to these places is a supportive environment combined with a population motivated to walk and bicycle. These conditions have not come about by chance; they are the outcome of aggressive policies that address both environment and motivation.3

Figure 1. Share of Trips by Walking, Bicycling, and Transit, by Country 2

* work trips only ** walk and bike combined for Spain Source: D. Bassett et al., “Walking, Cycling, and Obesity Rates in Europe, North America, and Australia,” 2008.

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Figure 1. Share of Trips by Walking, Bicycling, and Transit, by Country

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*Work trips only **walk and bike combined for spain

Source: J. Pucher and L. Buehler, “Making Cycling Irresistible,” 2008.

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A concerted and sustained effort is required to motivate people to walk and bike more and make their environment more conducive to doing so. The quality of the pedestrian and bicycle environment depends on several elements (see table 1), including land use patterns, network configuration, and facility design, all of which play an important role and are shaped by public investments and development policies over time. Natural features, particularly weather and topography, are also important, though obviously beyond the direct reach of policy. Motivation to

walk or bicycle also depends on personal characteristics—ability, comfort, confidence, habits, and perceptions—that can evolve over one’s lifespan but may also be modified by targeted intervention programs. Community norms also affect individual motivation but may be difficult to shift. Despite the challenges, a growing number of cities have demonstrated that it is possible to assemble a cost-effective package of policies, projects, and programs addressing both environment and motivation that significantly increases non-motorized travel.4

Walking, Bicycling, and Health

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Irvine, CAIthaca, NYTuscon, AZMadison, WISanta Barbara, CASan Luis Obispo, CASanta Cruz, CAEugene, ORBerkeley, CAPalo Alto, CABoulder, COCorvallis, ORDavis, CA

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Figure 2. Percent Usually Bicycling to Work in Selected U.S. Cities, 2000

Source: 2000 U.S. Census, as compiled by the author.

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Two converging forces make this the right time to elevate non-motorized modes of travel. First, with health, economic, and environmental concerns on the rise, there seems to be a renewed interest in bicycling as evidenced by increased attention in the popular media. Second, Congress is now considering the authorization of the federal transportation bill, the Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users, or SAFETEA-LU, which will set policy and dictate

funding levels for surface transportation well into the next decade. These forces together create an unprecedented opportunity to work toward the goal of increasing safe non- motorized travel.

Category Factor Definition Importance

Environmental Land use patterns The arrangement of land uses such as housing, shops, offices, etc., across the community

Determines the straight-line distance among different activities, such as housing, shopping, and offices

Network structure The layout of streets and trails throughout the community

Determines how direct the connections from one place to another are and thus influences the travel distance

Facility quality Characteristics of streets, including presence of sidewalks and bike lanes, widths, pavement conditions, crosswalks, signals, etc.

Influences how comfortable, safe, and attractive it is to walk or bicycle that route

Natural features Topography, weather, scenery

Influences the energy needed to walk or bicycle as well as comfort and enjoyment

Motivational Individual factors Ability, experience, comfort level, confidence, preferences, habits, etc.

Influences the willingness and desire of an individual to walk or bike

Community norms Social acceptability of bicycling, dominant attitude toward bicycling, bicycling culture

Influences the willingness and desire of an individual to walk or bike

Table 1. Factors Influencing Non-motorized Travel

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H e a lt h a n d n o n - M o t o r i z e d T r a n s p o r t a t i o n

Whether for transportation or recreation, walking and bicycling are important forms of physical activity. Federal guidelines categorize brisk walking and bicycling on level ground as moderate physical activity, while bicycling at more than 10 miles per hour qualifies as rigorous physical activity. The U.S. Department of Health and Human Services (DHHS) recommends that children engage in 60 minutes of physical activity each day and that adults engage in two hours and 30 minutes of moderate physical activity per week,5 a standard that more than one- third of all adults nationwide fail to meet.6 A 15-minute non-motorized commute twice a day for five days a week is enough to meet the adult recommendations. The DHHS identifies walking and biking as effective measures for increasing overall physical activity and notes that non-motorized commuting has a low risk of injury compared to many other forms of physical activity. Walking, in particular, has been described by health researchers as “near perfect exercise”7 and “a popular, familiar, convenient, and free form of exercise that can be incorporated into everyday life and sustained into old age.”8 The health benefits of achieving the recommended levels of physical activity are numerous: prevention of weight gain; improved cardio respiratory and muscular fitness; and lower risk of type 2 diabetes, heart disease, stroke, and other unhealthy conditions.

From an equity standpoint, non-motorized transportation presents both challenges and opportunities. Non-motorized modes can improve access to jobs, healthcare, and shopping for households with limited access to cars. Additionally, walking and bicycling reduce health disparities between low-income and more affluent communities. Safety, however, remains a significant concern: in 2007, there were 4,654 pedestrian and 698 bicyclist fatalities in the United States, with combined

injuries of more than 100,000.9 Indeed, public officials often use safety concerns to beat back arguments to do more to encourage walking and bicycling. The challenge is to increase non- motorized modes safely, primarily because the population groups that could most benefit from increased walking and bicycling are also the most vulnerable to traffic dangers.

Low-income and minority populations fall into this category. Ample evidence indicates that physical activity levels are lower among low-income and minority populations,10 despite the fact that only 73.5 percent of low- income households own cars and are more dependent on walking and public transit. That number compares with 91.7 percent of all U.S. households. Forty percent of the lowest-income transit users meet the recommended levels of physical activity solely from walking to and from transit.11 Without this, their total physical activity would be far less. However, the quality of non- motorized infrastructure is often lower in low- income and minority communities, contributing to higher pedestrian fatality rates.12 The confluence of these circumstances underscores the importance of improving walking and bicycling conditions in these communities.

Youth are also vulnerable. Across the country, adolescents depend on parents and other adults to drive them to school and other activities.13 If children were able to walk or bike more, they would get more physical activity and their parents (predominantly mothers) would have less need to drive them. Again, however, safety is a concern: rates of pedestrian and bicyclist fatalities and injuries per capita are highest for those under the age of 15.14 Parental fears about traffic as well as fear of abductions help explain why children now walk and bike less than in the past. Consequently, increasing walking and bicycling for children means removing threats— actual and perceived—to their safety.

Older adults, too, could benefit from increased walking and bicycling, but safety, once again, is an issue. One in five adults ages 65 years and

Walking, Bicycling, and Health

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older does not drive, and more than 50 percent of the nondrivers stay home on any given day because they lack transportation options.15 For nondrivers, walking, bicycling, and transit can provide an important means of getting to the doctor’s office, the store, or a friend’s house. However, the decline in physical and mental abilities that make driving no longer safe can also make walking and bicycling less safe. Uneven sidewalks, for instance, can pose a perilous hazard to frail older adults. The highest rate of pedestrian fatalities per capita is for those over age 70.16 Where safe conditions exist, increased walking and bicycling can improve physical and mental health.17

The good news is that safety is likely to improve for low-income households, children, older adults, and others as more people walk and bicycle. Countries with high levels of non- motorized travel also have fewer fatalities and injuries per mile than does the United States (figure 3).In part, this difference is explained by better infrastructure, particularly the separation of pedestrians and bicyclists from motor vehicles. But the higher number of pedestrians and bicyclists using thoroughfares itself improves safety by heightening driver awareness and attentiveness.19 Larger numbers of pedestrians and bicyclists also spur elected officials to invest more in better, safer infrastructure, which, in turn, helps to encourage more walking and bicycling.

Figure 3. Cyclist Fatality and Injury Rates, by Country 18

Note: The symbol // in the graph represents a break in the consecutive numbering of the Y-axis. Source: Pucher and Buehler, “Making Cycling Irresistible,” 2008.

Cyclists killed per 100 million kilometers cycled

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Source: Pucher and Buehler, “Making Cycling Irresistable,” 2008.

Netherlands Denmark Germany United Kingdom USA

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The potential economic benefits of increased walking and bicycling are numerous. Improved health as a result of increased physical activity can reduce healthcare costs. Cheaper modes of travel can reduce household spending on transportation: the typical household in this country spent an average of $7,896 to own and drive their cars in 2005.20 Making walking and bicycling more viable, particularly in conjunction with improvements to transit, could increase access to jobs. Improvements to walking and bicycling facilities can contribute to economic development efforts by, for example, encouraging stores to locate within walking distance of residential areas, particularly in low- income areas.

The potential environmental benefits of non- motorized modes are also abundant and include reductions in air pollution, water pollution, noise, and greenhouse gas emissions. However, these benefits accrue only if the increase in the use of non-motorized modes comes with a reduction in the use of motorized modes. A substantial share of walking and bicycling in the United States is for recreation rather than for transportation, and even some non-motorized trips to destinations are made in addition to, rather than instead of, driving trips.21 Walking and bicycling trips that do not replace driving trips do not have a direct environmental benefit, though they still have important health benefits.

T r a n s p o r t a t i o n G o a l s

The goal for non-motorized modes is straightforward: increase walking and bicycling without increasing fatalities and injuries, particularly for low-income households, communities of color, the young, and older adults. But what is a realistic increase to aim for? Although walking and bicycling have virtually boundless potential as forms of recreational physical activity, their potential as modes of transportation are limited by practical constraints. Given the low levels of use in this country, significant increases as a percentage of

all travel may be possible even if they remain a relatively small share of all trips. The potential for the two modes is likely different: walking is possible for more people because it requires no equipment and less confidence and skill, but it is considerably slower than bicycling; bicycling is at least theoretically possible for more trips because it is considerably faster than walking, but it requires equipment as well as skills and confidence that many lack. Given the low- density patterns of development in the United States, which put destinations beyond walking distance in most places, bicycling seems to offer greater potential for expansion.

Strategic Targets

In aiming to increase safe non-motorized modes of transit, particularly among those with the greatest needs but also the greatest vulnerabilities, it makes sense to take a strategic approach and target the following: types of travel most conducive to non-motorized modes, communities with greater potential for change, and communities with greater potential benefits from change.

Short trips are an obvious target. According to the 2001 National Household Transportation Survey, 28 percent of all trips are less than one mile, a reasonable distance for walking, and 41 percent of trips are less than two miles, a distance that is reasonable for biking.22 The shares of these short-distance trips that are made by non-motorized modes are much lower in the United States than in European countries: 71.4 percent of trips shorter than one mile are by walking or bicycling in Germany versus 31.2 percent in America (figure 4). In other words, while trip distances are longer on average in the United States than in Europe, distance is not the only issue; environmental and motivational factors must explain differences in non- motorized rates at these short distances.

School trips are another obvious target and, indeed, the federal Centers for Disease Control and Prevention has set a goal of increasing

Walking, Bicycling, and Health

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walking to school. This makes sense from a practical standpoint, given that these are frequent trips with regular routes and fixed destinations. Walking to school dropped from 40.7 percent of all school trips in 1969 to 12.9 percent in 2001, while bicycling remained roughly constant at around one percent (figure 5). Increasing walking and biking to school is generally a good starting point for increasing physical activity in children. For example, it could contribute to an increase in non-motorized travel to other destinations, as skills and habits change. Current efforts fall into two categories: changes in where schools are located to put more children within walking distances of school, and Safe Routes to School programs, which aim to improve safety around schools for walkers and bicyclists.

Some communities have greater potential for change than others. One target should be areas where walking and bicycling are already significant. For example, Davis, CA, has high levels of bicycling, but levels could clearly be even higher. The environment there supports bicycling, but not all residents take advantage of the opportunity: over three-fourths of children are driven to their Saturday morning soccer games.25 Motivational rather than environmental barriers are often the issue—habit, perceptions, confidence, etc. A second target should be places where land use patterns put destinations within walkable or bikeable distances of homes, that is, areas with higher densities and mixed land uses. In these places, the quality of sidewalks and other facilities may be a problem

Figure 4. Percent Walk and Bike Trips by Trip Length, Germany vs. United States 23

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4-4

Source: R. Buehler, “Transport Policies, Travel Behavior, and Sustainability,” 2008.

Source: R. Buehler, “Transport Policies, Travel Behavior, and Sustainability,” 2008.

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in addition to motivational barriers.

Of lower priority, because they are harder to change, are low-density areas with limited walking and bicycling infrastructure, particularly rural areas. In these areas, however, it is still important to look for specific opportunities to reduce environmental barriers, e.g., by improving the shoulders of rural roads or through a trail project that connects rural residents to the town center. Finding such opportunities should be more of a priority in areas where residents have limited access to cars and where transit service is sparse or nonexistent.

Potential benefits from increases in non- motorized travel are greater in some areas than others. Increases are most important in low-income and minority communities, where efforts are needed to improve safety when residents of these communities do walk and bicycle and to make more places accessible by these modes. Bicycling, in particular, offers a way to fill the gap between places accessible by foot and those accessible by bus. Anecdotal evidence suggests that bicycles are an important mode for recent Hispanic immigrants in California, though bicycling often occurs in environments not designed for it.26 Hispanics walk and bike to work in greater shares than

Walking, Bicycling, and Health

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Figure 5. Trends in Mode of Travel to School in United States, 1969–2001 24

Source: N. C. McDonald, “Active Transportation to School,” 2007.

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other Americans; not surprisingly, their rates of pedestrian and bicycle fatalities are also higher.27 Environmental improvements are essential in these communities.

Retirement communities, formal or informal, are another important target. It used to be that those who aged in place lived mostly in older communities that were designed for walking. Increasingly older adults now live in suburban environments that are not designed for walking. Improving the walking environment in these areas is not easy, though strategic projects coupled with programs to encourage walking or even bicycling could make a difference. In so- called active retirement communities, bicycling could be encouraged over golf carts as a way to get around within the community.

Measuring Progress

Achieving the goal of an increase in walking and biking safely requires development of new performance measures, both to assess current conditions and to monitor the effectiveness of new policies. Traditional transportation performance measures focus on vehicle traffic in support of the goal of maximizing vehicle flow and to the detriment of walking and bicycling. Without performance measures for non- motorized travel, policies are likely to continue to favor cars over pedestrians and bicyclists; transportation goals for which performance is not measured will get less attention in the planning process.28

Admittedly, developing such measures is difficult. If the goal—the desired outcome— is to increase walking and bicycling without increasing fatalities and injuries, then these factors are what should be measured. But increases in non-motorized travel are hard to measure.29 The best available data come from travel surveys, conducted at the regional or national level. Yet non-motorized trips have historically been undercounted in these surveys, which have primarily been concerned with driving trips. The surveys are also not frequent

enough to be useful for annual monitoring (the national survey occurs every five to seven years, while regional surveys are typically separated by 10 years or more). Although data on fatalities and injuries are arguably better than data on the amount of walking and bicycling, without the latter, it is impossible to adequately gauge the former. For example, the numbers of pedestrian and bicyclist fatalities and injuries have been going down on a per capita basis,30 but this likely reflects a decline in the use of these modes rather than a decline in danger. Improved data collection is needed.

As an alternative to measuring increases in non- motorized travel, performance measurement might focus on what might be called inputs rather than outcomes. One input is funding for bicycle and pedestrian projects. Another is the adoption of policies to promote non- motorized transportation, such as changes in zoning designed to bring about mixed-use land use patterns that reduce walking distances, or complete street policies that ensure that bicycles and pedestrians are given consideration in the design of all thoroughfares. Unfortunately, these inputs do not guarantee favorable changes in the environment, let alone the desired outcome of an increase in safe walking and biking. The input option for performance measures is the easiest to implement but the least effective in showing progress toward the goal.

An option that is better than measuring inputs but more feasible than measuring outcomes is to focus on outputs, that is, on changes in the environment that are expected to lead to increases in non-motorized travel, rather than changes in non-motorized travel that are difficult to measure. Outputs could be measured as projects actually constructed. However, non-motorized projects are not well tracked; categorizing such projects can be difficult, and bicycle and pedestrian improvements are often incorporated into larger road projects.31 Another option is to measure changes in the “walkability” or “bikeability” of a community. Many tools for measuring walkability and

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bikeability have already been developed,32 with increasingly frequent implementation in the transportation planning process. However, collecting data to calculate walkability and bikeability at a community scale can be labor intensive.

T r a n s p o r t a t i o n P o l i c y : O p p o r t u n i t i e s a n d B a r r i e r s

The next authorization of the federal transportation bill offers a tremendous opportunity for non-motorized transportation. For almost two decades, federal policy has contributed to an expansion of investments in walking and bicycling infrastructure. However, many barriers have hindered progress toward the goal of increased walking and bicycling, including federal policy itself. The new transportation bill could overcome many of these barriers by putting in place stronger federal policy toward non-motorized modes.

Starting with the passage of the Intermodal Surface Transportation Efficiency Act (ISTEA) in 1991, the federal government has provided support for non-motorized transportation through a number of policies. Most importantly, federal transportation funding can be used for bicycle and pedestrian projects through the Transportation Enhancements (TE) Program, the CMAQ (Congestion Management and Air Quality) Program, the Surface Transportation Program (STP), the Safe Routes to School (SRTS) Program, the Non-Motorized Transportation Pilot Program, and several others, including the Highway Safety Improvement Program (HSIP).33

Other policies also support non-motorized modes. Federal policy specifies seven “planning factors” that must be considered in the development of long-range transportation plans at state and regional levels. These factors include increased safety and security for non- motorized users, increased mobility and

accessibility options, and increased integration of the transportation system across modes. States are also now required to have bicycle coordinators. Finally, the Federal Highway Administration has pushed the concept of context sensitive design, which has increased attention to bicycle and pedestrian needs.

Under current policies, however, the availability of federal funds is insufficient to ensure improvements to the walking and bicycling environment. State, regional, and local policy decisions determine the degree to which communities take advantage of the federal programs for bicycling and walking facilities. For example, through the regional transportation planning process, metropolitan planning organizations evaluate and prioritize regional needs and decide what share of federal funding in these categories will go to non-motorized projects. The availability of federal funds for bicycle and pedestrian facilities has created an important opportunity, but one that only some states and regions have taken advantage of. Indeed, spending on non-motorized projects has varied significantly across the major metropolitan regions, ranging from $0.20 per capita in Los Angeles to $2.32 per capita in Providence, RI, from 1992 through 2006.34

At the same time, many federal programs and policies hinder rather than support efforts to increase non-motorized travel.35 The TE program as administered by the states can present insurmountable bureaucratic hurdles, particularly for communities with limited resources. The CMAQ program requires proof of air quality benefits, yet the models used to forecast emissions are not usually sensitive to bicycle and pedestrian improvements. Most significantly, an overarching concern with congestion at the federal level as well as at state and local levels undervalues non-motorized projects relative to highway projects in the planning process. The current focus on job creation and economic stimulus also threatens to perpetuate the top priority given to highway projects.

Walking, Bicycling, and Health

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One of the most intractable barriers to improving the walking and bicycling environment on a wide scale is local control of land use planning, a long-standing tradition throughout the country.36 The viability of non-motorized modes depends on land use patterns that put potential destinations within walking and bicycling distances of home. Similarly, transit viability increases as population and employment densities increase. These environmental characteristics are shaped by local policies such as zoning and subdivision ordinances. Investments in non-motorized infrastructure will be of little benefit without concomitant changes in local land use policies. Although land use planning authority is likely to remain at the local level for the foreseeable future, federal policy can and does influence the decisions of local governments, and this influence can be channeled toward the support of non-motorized modes.

Thus, federal policy alone will not bring about the needed changes, but it can help to expand non-motorized transportation by assisting, enabling, encouraging, or requiring agencies at the state, regional, and local levels to both improve the environment and

motivate people. To safely increase walking and bicycling, the upcoming authorization of the federal transportation bill should include the following policies, focusing on types of travel most conducive to non-motorized modes, communities with greater potential for change, and communities with greater potential benefits from change (see also table 2).

Assist: provide state, regional, and local governments with the tools they need to plan for non-motorized modes. Funding for more frequent and standardized travel surveys and for development of survey methods that collect more accurate and more comprehensive information on non-motorized modes would provide for better monitoring of progress. Such data could also provide a means of calibrating improved travel forecasting models that incorporate non-motorized modes. Resources should especially be directed towards low- income communities that may have a greater need for planning assistance.

Enable: make it easier for state, regional, and local governments to spend federal funding on non-motorized modes. Reducing bureaucratic barriers in current programs, particularly in the TE program, would likely increase the use of these funds for non-motorized projects, such as sidewalks and bicycle paths, particularly in low-income communities with fewer resources available for overcoming these barriers. Further increasing flexibility in federal programs would enable communities to give greater priority to non- motorized modes. In addition to infrastructure projects, educational and promotional programs should be eligible for funding.

Encourage: provide incentives to state, regional, and local governments to pay more attention to non-motorized modes. Specialized funding programs, such as Safe Routes to School, encourage spending on non-motorized modes. Targeted incentives, such as supplemental grants, could encourage attention to pedestrian and bicyclist needs, with

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priority given to low-income areas. Incentives that encourage coordination of land use and transportation planning could also enhance the viability of non-motorized modes; for example, jurisdictions that adopt land use policies promoting greater densities and mixed land uses might earn bonus funding for bicycle and pedestrian projects.

require: put in place policies that compel state, regional, and local governments to improve conditions for non-motorized modes. A federal complete streets policy would require that the needs of bicyclists and pedestrians are considered in all federally- funded projects. Federal transportation funding could be allocated based on the degree to which jurisdictions meet performance requirements for non-motorized modes. These

requirements could use the performance measures described earlier, such as increases in safe walkability and bikeability, with extra weight given to performance in lower-income areas and for key segments of the population. Performance standards could also be set with respect to land use policies; for example, jurisdictions might be eligible for funding only if they have adopted land use policies that are supportive of non-motorized modes.

As outlined, these approaches progress from least to most forceful; some combination of all four would have the best chance at success. But they must be accompanied by a shift in the focus of the federal program away from congestion reduction to goals related to health, equity, economic, and environmental benefits. Tying federal funding to demonstration of

Walking, Bicycling, and Health

Assist Help provide state, regional, and local governments with the tools they need to plan for non-motorized modes: fund travel surveys; support development of improved planning tools

Enable Make it easier for state, regional, and local governments to spend federal funding on non-motorized modes: reduce bureaucratic barriers; increase funding flexibility; expand eligibility of promotional programs

Encourage Provide incentives for state, regional, and local governments to pay more attention to non-motorized modes: continue and expand specialized funding programs; target incentives for prioritizing bicycle and pedestrian projects and for supportive land use policies

Require Put in place policies that compel improvements in conditions for non-motorized modes on the part of state, regional, and local governments: adopt federal complete streets policy; tie funding to performance requirements; tie funding to supportive land use policies

Table 2. Recommendations for Federal Policy on Walking and Bicycling

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progress toward these goals would ensure that the shift in focus is not just rhetorical. Such an approach could provide a powerful mechanism for improving walking and bicycling conditions.

C o n v e r g e n c e O p p o r t u n i t i e s

Credit for the existence of federal policies supporting non-motorized modes goes to a strong coalition of bicycle and pedestrian advocacy groups operating at the national level. This coalition is increasingly working in partnership with other interest groups, including those focused on public health, social equity, and environment issues, reflecting the broad benefits of non-motorized travel in all these realms, as described previously. This effective coalition is well positioned to influence the authorization of the upcoming federal transportation bill, though it must

continue to battle the traditional focus on congestion reduction and the new emphasis on highway investments as a way to stimulate the economy. Making the case that bicycle and pedestrian projects create jobs, too, while also helping to reduce our economically detrimental dependence on fossil fuels will be important for this coalition.

Because federal policy alone does not determine improvements to the bicycle and pedestrian environment, effective coalitions are also needed at the state, regional, and local levels. The local scale is especially important but also especially challenging, and the potential for building the needed partnerships varies from community to community. The Active Living by Design program, among others, has helped to foster such partnerships in communities throughout the country, including many low- income communities.37 The evaluation of this program should yield important lessons for other communities in their efforts to build partnerships in support of improvements to the bicycle and pedestrian environment.

C o n c l u s i o n

A “perfect storm” of higher gas prices, strained household budgets, and declining public resources, coupled with emerging mandates to reduce greenhouse gas emissions and deepening concerns about the growing obesity epidemic, could produce a surge in interest in non-motorized travel modes. Indeed, recent media reports suggest that a new bicycling culture has begun to take hold. Surveys also suggest a growing interest nationwide in walkable communities.38 If federal, state, regional, and local lawmakers follow the public’s lead, walking and bicycling could move the United States toward a healthier, more equitable future.

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Roadways and Hea lth: ch. 5 Ma king the Case for Collaboration CATHER INE L . ROSS, Ph.D. Director, Center for Qua lity Grow th a nd Reg iona l Development (CQGR D), a nd Ha rr y West Cha ir

MICHELLE M A RCUS, M.P.H. CQGR D Graduate Resea rch Assista nt Georg ia Institute of Technolog y Atla nta, GA

ABSTRACT >> Our streets and highways are inextricably linked with the very fabric of America. Roadways are used for many different modes of transportation, and constitute a major portion of the public space in our towns and cities. The limited inclusion of health considerations in the operation and construction of our roadways results in negative health outcomes. Lack of safe, convenient walking and bicycling routes have led to sedentary lifestyles, feeding a massive epidemic of obesity and chronic diseases. Motor vehicle emissions contribute to many negative health outcomes including asthma, lung disease, and cardiovascular disease. Transportation is the fastest-growing source of green house gases in the U.S., adding to climate instability which can result in natural disasters, food scarcity, and premature deaths. In addition to environmental impacts traffic crashes result in nearly 42,000 deaths and three million injuries every year. The authorization of the federal transportation bill is an opportunity to increase resources and focus on improving the negative health consequences associated with roadway construction and use. Fundamental changes in the way we measure and rank mobility needs, distribute funding, design, construct, operate and evaluate our roadways are possible and necessary.

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Roadways and Health

CONTENTS

Introduction .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 81

Connecting Roadways, Health, and Equity .. .. .. 82

Injury . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 83

Impact .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 83

Mechanism .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 84

Mitigation: Reducing Injury .. .. .. .. .. .. .. .. .. 85

Environmental Quality .. .. .. .. .. .. .. .. .. .. .. .. .. 85

Impact .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 85

Mechanism .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 86

Mitigation: Improving Air Quality and the Environment .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 87

Mode Share .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 87

Impact .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 87

Mechanism .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 88

Mitigation: Diversifying Mode Share and Reducing Automobile/Roadway Use. .. .. .. .. .. .. .. .. .. 89

Federal Legislation: Equity, Health, and Highways . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 89

Transportation Policy Barriers . .. .. .. .. .. .. .. .. .. 90

Transportation Policy Opportunities .. .. .. .. .. .. 91

Convergence Opportunities .. .. .. .. .. .. .. .. .. .. 92

Conclusion.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 93

Appendix A: Policies and Strategies for Healthy Transportation .. .. .. .. .. .. .. .. .. 94

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i n t r o d u c t i o n

A vast proportion of travel—and life—in the United States occurs on our roadways. This travel is made by car, foot, bicycle, wheelchair, bus, and streetcar. “Roadway” refers to the entire right-of-way—sidewalks, roadside, medians and verges, and in-street rails; it constitutes a major portion of the public space in our towns and cities. Roadways are used not only for transport, but also for socializing and support of public life. Our streets and highways are inextricably linked with the very fabric of America and impact our lives, cities, and environment in complex and pervasive ways. They have considerable impact on health and can be harmful if potential negative impacts are not mitigated.

Roadways, including highways, streets, and parkways, are linked to health outcomes in numerous ways. Foremost are physical inactivity, crashes, vehicle emissions, and equitable access to jobs and services. Lack of safe, convenient places and ways to walk and bicycle have led to sedentary lifestyles, feeding a massive epidemic of obesity and chronic diseases. Current levels of motor vehicle emissions contribute to many negative health outcomes, including increased incidence of asthma, lung disease, and cardiovascular disease. Increased levels of greenhouse gases, to which cars and trucks are a major contributor, are causing climate instability resulting in natural disasters, food scarcity, unhealthy ecological and weather patterns, and premature deaths. Traffic crashes result in nearly 42,000 deaths and three million injuries every year on American highways. Even the economic health of a community and its residents is affected by the cost, availability, and mode of transportation used for daily activities. Emotional well-being is challenged by traffic congestion, long and stressful commutes, and noise. Every community is affected, and often vulnerable populations face the greatest risk.

There is compelling evidence that poverty, race, ethnicity, disability, age, and urban or

rural setting are correlated with persistent and expanding health disparities among U.S. populations. The pursuit of good health requires safe and convenient access to a source of steady income, goods and services, and a wholesome environment. However, nearly one-third of Americans do not drive due to disability, age, financial constraint, or other personal circumstances. The majority is located in metropolitan areas, but even in rural areas about 14 percent of trips are made by those without access to a car.1 These Americans live in an automobile-oriented society without access to an automobile and are therefore both socially and economically disadvantaged. Their access to goods and services and their inclusion in the larger society are dependent on greater accessibility in the transportation system. The impending increase in the proportion of older Americans, constituting 20 percent of the population, will only add to this dependency. Without roadway system design and funding priorities that accommodate their travel needs, these individuals and their families often have limited access to jobs, hospitals, supermarkets, and more. Their level of access is also affected by land use patterns that have been formed by decades of automobile-oriented road planning and engineering.

Major roads and highways have turned into barriers as they become more difficult to cross by foot or by vehicle. Homes and stores have tried to withdraw from heavy motor vehicle traffic through use of the cul-de-sac and large setbacks from the edge of the street, reducing overall connectivity. Limited street connectivity forces use of a few heavily used, congested roadways, exposing travelers to greater risk from air pollution and car crashes. Cities have given over large tracts of valuable—and taxable—land to pavement for roads and parking that have depleted “Main Street,” drained the tax base, and created sprawling regions where businesses are dwarfed by their parking lots and roadways are often barren and dangerous. Designing for automobile use on every trip, no matter how short, has evolved into a self-reinforcing

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spiral of decentralizing communities, expanding pavement, and increasing per capita vehicle miles traveled (VMT). This trend has created many of the issues contributing to poor health outcomes.

Health is influenced by roads, but roads are influenced by infrastructure construction programs, public policy, and funding practices. A large proportion of funding and policy for roads is determined at the federal level; much of it is contained in the Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (SAFETEA-LU), which expires on September 30, 2009. The impending new authorization is an opportunity to make fundamental changes in the way we measure and rank mobility needs, the way we distribute funding, the way we conduct and design projects, and the way we evaluate our results. Ultimately, it is a chance to adopt powerful strategies that will help us achieve a healthy, equitable, and sustainable national infrastructure that supports robust economic development and the well-being of people and communities.

The upcoming authorization presents the opportunity to rethink transportation system design and operation in ways that are more supportive of positive health outcomes. Many of the policy changes that help achieve health objectives also address other planning objectives, including congestion reduction, road and parking facility cost savings, energy conservation, and economic development. For instance, designing our transportation system for shorter travel distances to enable walking and bicycling would increase physical activity, curb foreign oil dependence, and reduce the need for new or upgraded transportation facilities to accommodate vehicular travel. Given the importance of health to a viable, productive nation, and given the effect of transportation on health, we cannot reasonably design and fund our transportation system without addressing its health impacts.

C o n n e c t i n g r o a d w a y s , H e a lt h , a n d E q u i t y

The impact of roadways on health is summarized by examining the level of injury (intentional and unintentional), environmental impact (climate change and air pollution), and mode share (including level of access, physical activity, and mental/social health). The mechanism, extent, and mitigation of roadway- related health impacts are detailed below, with additional attention to the distribution of these impacts across the population. The major principles for mitigating the health impacts of roadways are to reduce injury, improve air quality and the environment, diversify mode share, and reduce automobile dependency.

The following characteristics of roadways all have an impact on health:

• Modal Level of Service—refers to the proportion of roadway dedicated to each travel mode (automobile, bus and light rail, truck, bicycle, and pedestrian). While general

Roadways and Health

Highways built to past standards are unable to support safe multi-modal travel.

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purpose lanes can be used by cars, trucks, buses, and bicycles, the inclusion of facilities intended exclusively for one of these modes can greatly modify the user behavior and utilization of the road. For instance, bicycle lanes or bus-only lanes may increase the safety and speed of travel in a corridor, and more people may choose these modes.

• roadway Design—focuses on features that impact behavior and safety. It addresses speed limit and design speed for motor vehicles, number and width of general purpose lanes (in each direction), presence of medians, and intersection design, including turn lane and free-flow turn/merge lane usage, corner radii, signal phasing, robustness of bicycle and pedestrian facilities, and more. A roadway will typically carry pedestrian and bicycle traffic, even if no facilities are provided for them.

• Access Management—refers to the regulation of interchanges, intersections, driveways, and median openings on a

roadway. Prohibiting turns or prohibiting certain users from part of or the entire road can improve operations. For instance, a left turn may be restricted to buses only, one leg of an intersection may be closed to pedestrians, or the quantity and placement of driveways along the roadway may be restricted. In doing so, conflicts between road users are reduced sometimes at the expense of freedom of movement. The right balance of access management can improve safety and level of service (LOS) for all road users.

• Streetscape—measures the degree of treatment of the roadway with trees and other plantings; placement of amenities such as lights, benches, and garbage cans; and general roadside appearance, including placement of buildings, artwork, or plazas. These influence motorist behavior, transportation access, and pedestrian and bicycle LOS.

• Density, Land Use, and Connectivity— refers to the types and intensity of uses along the roadway and the connectedness of the streets that support it. Research indicates that mixed land uses, higher land use density, and short block lengths have a strong relationship with higher levels of physical activity and social capital, as well as with lower levels of air pollution, greenhouse gas emissions, and fatal crashes.

i nj u r y

Impact

There were 41,059 traffic-related deaths reported in the United States in 2007.2 This constituted the leading cause of death for individuals ages one to 34.3 After age 34, deaths from heart disease, stroke, and cancer—which are largely affected by physical activity levels, another outcome of transportation practices—exceed deaths due to traffic crashes. Additionally, crashes result in almost three million injuries per year. This creates an economic burden of about

Road policies have impacted land use.

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$150 billion each year, including $52 billion in property damage, $42 billion in lost productivity, and $17 billion in medical expenses.4 Of the 41,059 traffic fatalities, 4,654 were pedestrians, 5,154 motorcyclists, and 698 bicyclists.5

Crashes were more likely to occur at an unsignalized intersection than a signalized one.6 Rural crashes were more likely to occur away from an intersection and appear to be most attributable to speed or driver distraction. In 2002, more than one-third of pedestrian travel took place on a roadway or shoulder. Crashes in urban areas alone result in about $160 billion in expenses (according to 2005 data) and may be responsible for half of the roadway congestion there.7

Vulnerable populations typically have a higher risk of unintentional injury.8 There are disparities by income, age, ethnicity, gender, and urban or rural residency. People of color and those earning less than $25,000 per year are much more likely to walk or bicycle.9 Traffic-related crashes are the leading cause of death for children,10 and poor children die at higher rates. The pedestrian victim of a car collision is statistically more likely to be a person of color.11 Higher pedestrian fatalities have also been noted around low- income neighborhoods. Schools with a high proportion of students of color are less likely to have continuous, well-maintained pedestrian facilities. Older adults and people with disabilities are at greater risk because of physical or mental limitations on their perception and movement. Pedestrians, bicyclists, and motorcyclists (including mopeds and scooters) are much more vulnerable than car or truck occupants in a crash. Recent studies have shown that per- cyclist risk of crash is reduced as the proportion of bicycle mode share increases.12 There is a similar effect for pedestrians.13 Although less than one-quarter of all driving takes place in a rural setting,14 more than half of all fatal motor vehicle crashes occur there.15 Rates of pedestrian fatalities are higher in urban areas.16

Mechanism

Collisions or crashes involving road users often result in physical traumas, which can lead to disability or death. A crash may involve a single bicycle or motor vehicle, multiple vehicles, or any number of vehicles and pedestrians. Conventional wisdom has held that roads can be made safer for motor vehicles by moving fixed objects back from the roadside; widening travel lanes; and employing channelization, acceleration lanes, and grade separation at intersections. However, researchers are finding that this type of design may not provide the anticipated safety benefits. Health professionals now believe that such designs promote speeding and reduce driver awareness, leading to much higher rates of pedestrian and bicycle fatalities.17

Road design can increase crash risk by determining where and how traffic movements will occur. This can exacerbate conflicts between two or more road users; changes in speed or direction; safety of at-grade rail crossings; and road user speeds, visibility, and attentiveness. Designing a road to control traffic flow as well as to accommodate all of the movements that any user might want to make, safely and without excessive delay, is the key. In urban areas, access management plays a large role. In a rural setting, the challenge can be accommodating slow or non-motorized traffic without promoting higher speeds. It even appears that rural roads with many curves have fewer crashes than flat, straight roads, perhaps due to increased vehicle speeds on the latter. Areas on the metropolitan fringe may be particularly vulnerable as they begin to carry more traffic on roads intended for rural use. While each road is different, users of all types must be anticipated, and design should be context sensitive. The principles of injury mitigation are outlined below.

Roadways and Health

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Mitigation: reducing Injury

• Base road design decisions on state-of-the- art transportation and health research and ensure that such research is disseminated to both planning and engineering staff.

• Constrain vehicle speeds as appropriate to the road context.18

• Incorporate treatments to control conflict points, such as medians, alleys, traffic signals, and movement restrictions.19

• Design roads to reduce risky driving behavior, rather than to accommodate it.

• Increase the share of bicycle facilities to reduce per-cyclist risk.

• Increase the share and quality of pedestrian facilities to protect pedestrians from traffic, reduce individual risk, and minimize fear of crime.20

• Include public transportation facilities and shift travel to this mode, reducing risk of injury.

• Provide sidewalks and frequent crosswalks to improve pedestrian safety.21

• Reduce corner radii where possible to minimize pedestrian exposure and reduce vehicle speed.22

• Provide more transportation choices to reduce vehicle volume.

• Utilize a network of streets to disperse traffic volume and provide smaller, safer roads for pedestrians and bicyclists.23

• Create landscaped, tree-lined roads.24

• Reduce roadside distractions such as billboards.

• Improve street and roadside lighting, especially at conflict points.25

• Review universal design standards and seek to implement road design that accommodates all users safely, regardless of their limitations.

• Institute and enforce maintenance schedules for all facilities.

E n v i r o n m e n t a l Q u a l i t y

Impact

Motor vehicle traffic presents a unique public health risk because of the toxicity of its emissions and its extensive integration within communities. Recent research links diesel exhaust to lung cancer, cardiopulmonary disease, and other causes of death. More than 42 percent of Americans live in places that exceed national air quality standards for ozone or fine particulate matter. Asthma affects nine percent of U.S. children and seven percent of adults.26 Climate change may already be responsible for more than 150,000 deaths per

Context sensitive roads designed for all users can enhance safety.

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year and is expected to have a devastating effect on global climate patterns. Vehicle- related fine particulate matter becomes highly concentrated in areas immediately adjacent (200 meters) to major roadways. Outdoor particulate matter concentrations (PM2.5 and PM10) are an estimated 15 to 20 percent higher at homes located on high-traffic intensity streets compared to homes located on low-traffic intensity streets and at intersections.27

Children, older adults, pregnant women, and low-income households are especially vulnerable.28 Vehicle-related pollutants have been associated with increased respiratory illness, impaired lung development and function, and increased infant mortality. Also, pregnant women living within 200 to 300 meters of high-volume roads face a 10 to 20 percent higher risk of early birth and of low-birthweight babies. Children living near busy roads are six to eight times more likely to have certain forms of cancer. Additionally, fine particulate matter (PM2.5) has an adverse effect on lung development in adolescents that can lead to lifelong lung deficiency,29 and even small amounts of air pollutants are associated with small changes in cardiac function in older adults.30 In addition, low-income and minority communities are more at risk for higher levels of pollutant exposure, as their homes are more likely to be located near busy roadways.31

Mechanism

Road-based airborne emissions result from tailpipe exhaust, fuel delivery, road surface wear, deterioration of vehicle parts, and electricity production for electric-powered vehicles. Particulate matter (PM), carbon monoxide, nitrogen oxides (NOx), and volatile organic compounds (VOCs) are all major concerns, as well as ozone, which form from NOx and VOCs, and black carbon and sulfur dioxide, which are emitted by diesel-burning vehicles. Exposure to these pollutants significantly increases the incidence of asthma, respiratory diseases, lung cancer, and cardiovascular disease. Additionally,

carbon dioxide and other greenhouse gas (GHG) emissions cause climate instability and stimulate natural disasters, food scarcity, and unhealthful weather and ecological patterns such as heat waves and the spread of disease-carrying insects.

The actual level of pollution from all cars and trucks is a function of vehicle miles traveled, the number of trips, the condition of the vehicle, the weather, and the driving conditions. In particular, traffic congestion can increase emissions because it leads to extra accelerating, braking, and idling. The highest level of tailpipe emissions is generated when the vehicle is started, making even short motor vehicle trips a culprit in air pollution. Additionally, large expanses of pavement for highways and parking can exacerbate emissions by increasing air temperature, which facilitates ozone formation; trees, shrubs, and some plantings can reduce pollution by keeping the area cooler and by absorbing some carbon dioxide and VOCs from the air. Both passenger and freight movement are relevant to emissions levels, as freight transport accounts for a large percentage of air pollution.

Motorists experience high exposure to vehicle emissions while driving, especially in stopped

Roadways and Health

This congested roadway is exposing individuals on or near it to air pollutants, including children on a school bus. Alternative modes are often lacking, even for short trips.

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traffic. People living in immediate proximities (200 meters) of major diesel thoroughfares are more likely to suffer from respiratory ailments, childhood cancer, brain cancer, leukemia, and higher mortality rates than those who live farther away. Adults with asthma who walk along these thoroughfares are more likely to suffer acute symptoms.32 Airborne outdoor pollutants can penetrate any building through small gaps, ventilation systems, and open doors or windows.

Mitigation: Improving Air Quality and the Environment

• Increase the level of service for non- motorized travel to reduce automobile trips.

• Use roadway design and transportation alternatives to reduce congestion and make motor vehicle travel more efficient.

• Avoid road projects that compete directly with existing or planned lower-emission freight and passenger rail transport.

• Seek alternatives to road projects that will increase motor vehicle traffic near populated areas.

• Manage access to control congestion and freight traffic.

• Permit trees and plants along roadways to provide cooling, shelter for pedestrians, and capture some emissions.

• Promote higher-density land use to reduce the distances traveled by motor vehicle.

• Promote a connected network of streets to allow bicyclists and pedestrians to avoid using major thoroughfares.

M o d e S h a r e

Impact

Physical inactivity and elevated body mass index (BMI) are among the most pressing health concerns today. Thirty-four percent of Americans are obese, and more than two-thirds are overweight or obese. Obesity, defined as a BMI over 30, leads to elevated risk for heart disease, type 2 diabetes, cancer (including breast cancer and colon cancer), high blood pressure, stroke, liver disease, sleep disorders, arthritis, and infertility. Obese individuals are twice as likely to die prematurely as their non-obese counterparts. Sixteen percent of American children are obese, many of them already at risk for heart disease and type 2 diabetes.33 Physical inactivity is a primary factor in obesity, and it is thought to contribute to approximately 30 percent of all U.S. deaths. Physical inactivity is estimated to have cost the United States more than $250 billion in 2006.34

Social capital—the collective benefits conferred by social networks—decreases 10 percent for each additional 10 minutes spent commuting35 and is lower for people who live on streets with high traffic volume.36 Mental health is assailed as traffic congestion, traffic danger, and commuting add to daily stress and prevent people from spending enough time with their families or engaging in more productive and enjoyable activities.37 Transportation expenditures are the second-largest expense for an American household, and some households spend more than 22 percent of their income on transportation. In 1998, this expense approached $9,000 per household.38

Low-income households are more affected by transportation expenses than others and can spend up to 40 percent of their income on transportation. These underserved populations tend to be minority or of lower economic status.39 Affected by high unemployment rates

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and lack of services, these populations rely on walking, bicycling, and public transportation to achieve economic stability. In many low-income communities, transportation to a hospital or medical office is completely lacking, except by ambulance. Additionally, almost one-third of Americans do not drive.40 This group includes children under age 16, older adults who can no longer drive safely, people who cannot afford to own and operate a car, and people with disabilities, among others. These individuals constitute a significant part of the economy, as both workers and consumers. Without transportation, they experience difficulty accessing jobs, healthcare, churches, stores, government services, and friends or family.

Mechanism

Over-reliance on private motor vehicle travel eliminates a major source of regular physical activity. Average BMI has increased as walking and bicycling trips have declined, but a greater share of pedestrian or bicycle travel leads to gains in physical activity. In many localities, it is unsafe, unpleasant, or simply impossible to walk, even across the street or to an adjacent property. Excessive travel times decrease social capital, which can lead to mental health issues, substance abuse, and degraded relationships between family members or neighbors. Increased pedestrian travel contributes to overall lower household transportation costs and gains in social capital. Additionally, a greater share of transportation facilities increases transportation ridership, which increases pedestrian travel and enhances physical activity levels. The more time an individual spends driving a car, the more likely that driver is to have an elevated BMI.41 Automobile transportation is vastly more expensive than walking or bicycling and generally much more expensive than mass transit. Therefore, families in automobile- dependent regions may have to spend more money on transportation.

Wide, continuous sidewalks increase the comfort and efficiency of walking, especially for groups or people employing wheelchairs or strollers, and lead to more people walking.42 Planting zones or furniture zones improve the comfort and efficiency of walking by buffering pedestrians from traffic, leaving room for pedestrians to pass behind turning vehicles, and removing obstacles from the main walkway. Good aesthetics, amenities, and sidewalk-oriented building frontage and design create a lively social environment and increase personal safety. Sidewalk-oriented building frontage and design improves access to homes, stores, and services for persons on foot. Street lighting increases walking43 and improves actual and perceived personal safety. Shorter distance to destinations has a strong correlation with increased walking and bicycling,44 and higher connectivity has a strong correlation with increased walking and bicycling. Trees provide shade, without which walking or bicycling may be unbearable on warmer days. Greater intensity of usage can also increase actual and perceived personal safety for non- motorized transport, while actual or perceived

Roadways and Health

Roads can accommodate the needs of all road users, regardless of travel mode and ability.

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danger from high-speed or high-volume traffic discourages walking and bicycling. Shorter distance to destinations improves access for low- income families and people with disabilities, while higher-density retail and commercial development is linked to more pedestrian travel. ADA-compliant facilities allow persons with disabilities to travel along the sidewalks.

Mitigation: Diversifying Mode Share and reducing Automobile/ roadway Use

• Control speed and conflict points to improve the pedestrian and bicycle environment.

• Design intersections to serve all types of users with an equal degree of priority and minimum delay.

• Develop more accurate ways to evaluate level of service for all travel modes and road users, and use them to increase and improve bicycle, pedestrian, and transit travel as appropriate to location (including lower- volume rural roads).

• Enhance access to transportation services and eliminate roadway barriers such as infrequent pedestrian crossings or turn lanes that affect bus access to a bus stop.

• Promote higher-density land use to increase the number of destinations in walking or bicycling distance.

• Ensure that the entire roadway, including sidewalks and bicycle lanes, is adequately cleaned and maintained.

• Enhance street networks to minimize wide or high-volume roadways.

• Keep block lengths short and well-connected.

• Create pedestrian-friendly environments: wide sidewalks, planting or furniture zones between the vehicle lanes and the sidewalk, benches, waste and recycling receptacles, shade trees, sidewalk-oriented building frontage and design, street and sidewalk lighting, and pleasant streetscape.

fe d e r a l l e g i s l a t i o n : E q u i t y, H e a lt h , a n d H i g h w a y s

It is appropriate to argue for a redefinition of highways. Historically, the highway system has been designed to move large numbers of passenger and freight vehicles at fast speeds. It connects homes and jobs for motorists but is not sensitive to other needs of highway users. Highways define the travel experience of people with diverse backgrounds, socioeconomic status, and lifestyle preferences. They disrupt communities and begin to structure the social interaction of residents. Highways must become entities that integrate physical activity, minimize negative health impacts, enhance social interaction, preserve environmental quality, promote community health, increase safety, and promote sustainability even as they

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become more responsive to global demands providing equitable access and participation in daily life.

The current federal transportation bill— SAFETEA-LU—has an enormous influence on roads throughout this country. Approximately 40 percent of the transportation dollars spent nationally emanate from the U.S. Department of Transportation (DOT) and the Federal Highway Administration (FHWA).45 It comes with extensive stipulations, but very little evaluation or enforcement. It both sustained and introduced a number of notable programs, including the Highway Safety Improvement Program, various highway safety grants, Congestion Mitigation and Air Quality (CMAQ) funds, Safe Routes to School, and Transportation Enhancement funds. It promoted the Environmental Review Process, routine consideration of non-motorized travel needs, funding for routine maintenance, endorsement of standards for roadway design, and endorsement of the Americans with Disabilities Act Accessibility Guidelines; it added flexibility to National Highway System and Surface Transportation Program funds. SAFETEA-LU reinforced coordination, public participation, and planning requirements for states and metropolitan planning organizations (MPOs). These have been notable because they introduce the possibility of integrating comprehensive health considerations into transportation planning.

Roadway funding in the next federal authorization will need to place transportation in a larger context, rather than focusing narrowly on the movement of people and goods (or even more narrowly on the movement of cars and trucks). The legislation must explicitly address ways to mitigate climate change. It must continue to address casualties on our highways through requirements to restrict alcohol- impaired driving and seat belt legislation. And it must expand this effort through evidence- based road design, increased funding flexibility, and increased monies for research. As stated

in the final report of the National Surface Transportation Policy and Revenue Study Commission, highway policies should not conflict with other national policy goals.46

SAFETEA-LU implemented many initiatives aimed at making roads safer, less harmful to the environment, more equitable, and more efficient, yet such initiatives have only tinkered with the edges of highway policy and had little impact on the overall results. The current challenge is to strengthen these goals, integrate them into every decision, and provide a much wider set of mitigation options—all in a situation of shrinking fuel tax revenues and widespread economic decline.

T r a n s p o r t a t i o n P o l i c y B a r r i e r s

Although SAFETEA-LU included a number of well-intentioned programs and policies addressing safety, environmental quality, and effects on vulnerable populations, it also contained fundamental operational practices that prevented these initiatives from being truly effective. An important first step in the new authorization will be to eliminate these barriers.

For example, transportation funding intake and allocation has been too heavily based on motor vehicle travel, motorized-vehicle lane miles, and trucking. Approximately 50 percent of the monies received by the states are based on VMT (vehicle miles traveled), arterial lane miles, diesel fuel usage, and the ratio of lane miles to population.47 It may not be desirable to link funding to increased VMT. Compare two states or localities that have created different road systems. One has roadways that primarily serve motor vehicle traffic; the other has constructed a complete, quality travel environment for pedestrians, bicyclists, cars, trucks, and buses. In this example the second location may be able to move as many people and goods at a comparable or better level of service and may do so with greatly reduced

Roadways and Health

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externalities (emissions, crashes, and inequities for nondrivers). While they may have similar amounts of total infrastructure to maintain, the second location may have lower lane miles and lower VMT, thus receiving less funding. In this example, the community with a roadway system more supportive of positive health outcomes would be penalized. Congestion Mitigation and Air Quality (CMAQ) funding share, which is based on air quality non-attainment, and Minimum Guarantee share, which is based on the states’ tax contribution (which is a function of the amount of fuel consumed) do little to rectify the situation.

Currently, very limited resources are allocated to non-motorized transportation, while enormous sums are committed to motor vehicle movement. A particularly large share goes to limited-access highways such as the Interstate Highway System (IHS). While the IHS fills a necessary transportation role, it is not sufficient to meet current or future travel and mobility needs. SAFETEA-LU and its predecessors have not allowed the flexibility in funding, nor the guidance, to allow more context sensitive, equitable funding of transportation projects. Local fund match requirements have not been equitable across travel modes, and previous transportation bills have not provided good mechanisms for assessing the effects of proposed highways on the roadside environment, on overall connectivity, or on the level of service for bicycles, pedestrians, or public transportation.

Overall, the use of federal transportation allocations has not been closely monitored. Although Environmental Impact Statements (EIS) are required, they have not adequately assessed health impacts (they are not sufficiently explicit on health). The needs of low-income communities and nondrivers have been routinely overlooked without consequence. In general, the entire bill has failed to sufficiently evaluate the outcome of the projects it has funded, especially with regard to vulnerable populations.

T r a n s p o r t a t i o n P o l i c y O p p o r t u n i t i e s

A handful of policies are in use today to create healthy roads that function well for all users. These policies can be found at the federal, state, and local levels. The most relevant policies are Health Impact Assessment (HIA), Context Sensitive Design, Complete Streets, Local Area Traffic Management (LATM)/Traffic Calming, Environmental Review Toolkit, Livable Centers Initiative (LCI), Road Diets, and Green Streets (see appendix A for more detail about these policies). These policy examples go far beyond vehicle level of service to consider a project for its comprehensive effect on the immediate area and the region, often creating extra opportunities to consider equity and health concerns and to implement more meaningful public participation.

A $3.2 billion deficit is forecast for the highway trust fund in 2009, presenting both a challenge and an opportunity to revisit our transportation strategy. It is also likely that fuel purchases will decline or grow less quickly. The National Surface Transportation Policy and Revenue Study Commission final report, Transportation for Tomorrow, suggests increasing the highway trust fund revenue tax from 25 to 40 percent a gallon over the next five to eight years and indexing it to inflation. However, the report also champions environmental stewardship and the development of alternative and renewable fuels.48

Many other strategies are being put forth to help finance the priorities to be set in the upcoming authorization. Prioritizing long- term investment, developing more accurate and comprehensive cost-benefit analyses, and reducing earmarks can all help to control transportation financing. Another option is increasing collaboration with local and national advocates, planning organizations, and others to take advantage of innovations and research and facilitate private-sector funding of some initiatives. Finally, the cost-reduction benefits

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associated with other modes, travelways, and strategies are potentially substantial. There are already some innovative proposals, including:

• The Lieberman-Warner Climate Security Act, which includes some transportation funding that might be appropriate for Health Impact Assessment.

• Senator Benjamin Cardin of Maryland and others have recommended a Transportation Sector Emissions Reduction (TSER) Fund that would permit the auctioning of emission allowances. Approximately five percent of TSER funds would be available to state and local authorities for transportation alternatives that reduce travel demand, including regional planning organizations.

• Senator Tom Carper of Delaware has proposed CLEAN TEA (Clean Low-Emissions Affordable New Transportation Equity Act). This act reduces greenhouse gas emissions by promoting alternatives to driving. CLEAN TEA provides low-emissions transportation options by directing cities with more than 200,000 residents and state departments of transportation to review their transportation plans and determine how they could reduce greenhouse gas emissions. Federal funding for projects in those transportation plans would be distributed to states and localities based on the expected reductions in greenhouse gas emissions in each plan. States and cities with more ambitious plans would receive greater funding.

C o n v e r g e n c e O p p o r t u n i t i e s

The upcoming transportation authorization presents many opportunities to create partnerships and take advantage of mutual interests to create healthier road networks. A number of innovative policies have been identified above. A small cross-section of entities and programs representing convergence opportunities follow:

• Medicare and Medicaid programs spend almost 10 percent of their budget each year treating conditions related to obesity and physical inactivity.

• State and local police departments incur significant costs responding to crashes. Many have already funded their own road safety programs.

• State and local tax dollars are being used to bus students, even though many live within walking distance. Some are participating in the federal Safe Routes to School program to reconstruct the road infrastructure near school property and develop programs to encourage physical activity.

• High-cost roadway capacity projects are becoming less feasible for transportation department budgets and less popular among taxpayers and residents.

• Industry, freight, and automakers will bear the brunt of climate change legislation without more opportunities for change in personal travel behavior.

• Emergency services for crash victims are overwhelmed and strapped for cash.

• Health insurance providers spend billions each year treating conditions related to physical inactivity, air pollution, and roadway casualties.

• Labor departments are aware that transport and child care are the biggest barriers to employment and are seeking solutions.

• Federal and state agriculture and environmental protection divisions are devoting resources toward environmental quality.

• The federal Centers for Disease Control and Prevention (CDC) and countless public and nonprofit organizations are investing

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in physical activity programs, road emission mitigation programs, and more.

• Public health research is building evidence for design of safe and healthy road environments, but the work may not be translated to engineering and planning practices.

Many of these opportunities involve various branches of the federal government, if only as a funding source. They allow addressing multiple issues at once by including health, equity, and road programs in the same planning process. This would prevent duplication of activities, take advantage of existing expertise, and avoid having federal programs work at cross-purposes to one another.

C o n c l u s i o n

Roadway systems are set in a context of towns and cities, commerce and agriculture, ecological systems, neighborhoods, regions, state and local governments. Our public spaces and our travel along them have a profound effect on all of these settings. They are extensive and

thoroughly integrated into all aspects of the American landscape. As a result, they play a large role in the health and quality of life of the general population.

While the purpose of the upcoming authorization is to address highway funding and the movement of people and goods, within the entire national context, it plays a much larger role in the health outcomes of citizens. The biggest impacts result from crash- related injuries, vehicle emissions that pollute the air and contribute to climate change, automobile dependency leading to sedentary behavior, and the lack of equitable access for all Americans. The implementation of the mitigation strategies, policies, programs, and design guidelines outlined earlier result in significant improvement in the positive effect of roadway systems on health. The recommended steps to improve safety, reduce emissions, and create high levels of service for all travel modes change the role of the roadway system, causing it to be more supportive of good health and increased prosperity. In this way, it expands its contribution to improving the health status of Americans.

ch. 5

Appendix A. Policies and Strategies for Healthy Transportation

Health Impact Assessment (HIA)

Principles Addressed: • Injury Scope: • Local • Environmental Quality • State • Mode Share • Regional • Federal Description: A combination of procedures, methods, and tools by which a policy,

program, or project may be judged as to its potential effects on the health of a population and the distribution of those effects within the population. Public participation is an important part of health impact assessment.

References: http://www.cdc.gov/healthyplaces/hia.htm http://www.hc-sc.gc.ca/ewh-semt/pubs/eval/handbook-guide/vol_4/

table-tableau-3-eng.php#Table-3-1a

Context Sensitive Design

Principles Addressed: • Injury Scope: • Local • Mode Share • State • Regional • Federal Description: A collaborative, interdisciplinary approach that involves all stakeholders

to develop a transportation facility that fits its physical setting and preserves scenic, aesthetic, historic, and environmental resources while maintaining safety and mobility. An approach that considers the total context within which a transportation improvement project will exist.

References: http://www.cnu.org/streets http://www.fhwa.dot.gov/context/index.cfm http://www.contextsensitivesolutions.org/content/topics/css_design/

design-examples/

Complete Streets

Principles Addressed: • Injury Scope: • Local • Environmental Quality • State • Mode Share • Regional Description: Complete Streets are designed and operated to enable safe access for

all users. Pedestrians, bicyclists, motorists, and bus riders of all ages and abilities are able to safely move along and across a complete street.

References: http://www.completestreets.org/ http://www.completestreets.org/federal.html (S. 584/H.R. 1433)

Local Area Traffic Management (LATM)/Traffic Calming

Principles Addressed: • Injury Scope: • Local • Mode Share • Federal (non-U.S.) Description: Traffic calming is a system of design and management strategies that

aim to balance traffic on streets with other uses. The tools of traffic calming provide an example of a different approach from treating the street only as a conduit for vehicles passing through at the greatest possible speed.

References: http://www.cochrane.org/reviews/en/ab003110.html http://www.fhwa.dot.gov/environment/tcalm/part3.htm http://www.pps.org/info/placemakingtools/casesforplaces/

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Environmental review Toolkit

Principles Addressed: • Environmental Quality Scope: • Federal • Mode Share Description: Environmental stewardship and streamlining resources for FHWA offices,

state departments of transportation, resource agencies, and consultants. The website includes a guide to practices by state, links between planning and the environment, and the National Environmental Policy Act (NEPA).

References: http://www.environment.fhwa.dot.gov/

Roadways and Health H

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Livable Centers Initiative (LCI)

Principles Addressed: • Environmental Quality Scope: • Local • Mode Share • Federal Description: The LCI is a program offered by the Atlanta Regional Commission. It

is an example of promoting local strategies to plan and implement a link between transportation improvements and land use development policies to create sustainable, livable communities consistent with regional development plans.

References: http://www.atlantaregional.com/html/308.aspx

road Diets

Principles Addressed: • Injury Scope: • Local • Mode Share • State • Regional Description: "Road diets" are typically conversions of four-lane undivided roads into

two through lanes and a center turn lane or two through lanes and a median. The fourth lane may then be converted into bicycle lanes, sidewalks, or on-street parking. "Road diets" are an example of service reevaluation for all users.

References: http://www.walkable.org/assets/downloads/roaddiets.pdf http://www.tfhrc.gov/safety/hsis/pubs/04082/index.htm http://www.contextsensitivesolutions.org/content/reading/road-diets-2/

Green Streets

Principles Addressed: • Injury Scope: • Local • Environmental Quality • State • Mode Share Description: Sustainable practices associated with the design and construction of

roadways, such as use of recycled or sustainable construction materials, ecologically-sensitive storm water management, and extensive use of vegetation.

References: http://www.lowimpactdevelopment.org/greenstreets/

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ch. 2

Transportation is the lifeline of communities. It connects residents to jobs, stores, family, friends, doctors, schools, parks, clubs, religious institutions, volunteer commitments—everything that allows people to participate and prosper in society. Transportation policy bears on every critical issue facing neighborhoods, regions, and the country.

The chapters in this section cover:

>> Economic development

>> access to healthy foods and healthy food systems

>> Traffic safety

These are by no means the only issues that should be considered in crafting the new transportation bill. Healthy, equitable, forward- thinking transportation policy must address a number of urgent and interconnected issues, among them climate change, environmental justice, freight transport, and workforce development.

KEY ISSUES

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Brea king Down Silos: ch. 6 Transportation, Economic Development, and Hea lth TODD SWA NSTROM, Ph.D. E. Desmond Lee Professor of Community Collaboration a nd Public Policy Administration University of Missouri, St. Louis

ABSTRACT >> Transportation policy in the United States has historically emphasized automobile use and steered land use, development, and investments in infrastructure toward low-density suburbs. This approach has left low-income communities in aging city centers poorer, sicker, and increasingly immobile, unable—more and more—to get to work, their doctor, parks, gyms, or even grocery stores that sell fresh, healthy food. This paper explores an alternative transportation policy designed to create healthy, productive metro regions by closing the gap between affluent, mobile communities and their less mobile, disadvantaged neighbors.

By reconfiguring how we use available land, we can create densely populated, mixed-use communities that expand access to transportation and improve health outcomes. With a focus on equity, these policies can also support economic development that reduces poverty and economic and racial segregation.

This paper considers two approaches: creating mixed-income, transit oriented villages and using transportation funds to promote local workforce development. While the goals of equity and environmental sustainability are not mutually exclusive, the paper concludes by cautioning activists against ignoring the short-term needs of low-income families who live in built environments dominated by the automobile.

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Breaking Down Silos

CONTENTS

Introduction .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 101

Unhealthy Effects of the Highway Policy Silo.. . 102

New Transportation Policies for Healthier Economic Development . .. .. .. .. .. .. .. .. .. . 104

Mixed-Income Transit Oriented Development 104

Policy Recommendations .. .. .. .. .. .. .. .. .. . 107

Transportation . .. .. .. .. .. .. .. .. .. .. .. .. .. . 107

Housing.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 107

Transportation and Local Workforce Development .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 108

Policy Recommendations .. .. .. .. .. .. .. .. .. . 110

Transportation . .. .. .. .. .. .. .. .. .. .. .. .. .. . 110

Labor .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 110

Conclusion.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..111

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i n t r o d u c t i o n

The United States is in the midst of a shift in transportation policy—from mobility to individual and community accessibility. Traditionally, transportation choices in this country have been made inside policy “silos” that isolate decisions on how we commute and travel from decisions on how we live. By making these decisions in a vacuum, transportation policies have promoted sprawl, or low-density patterns of housing that favor automobile use over public transportation and that exact a huge toll on the health of our metro regions, particularly low-income communities.

The goal of making transportation more efficient is not to move people faster and farther but to give them wider access to all the things that are necessary for a good life: jobs, education, family, friends, recreation, culture, etc. Under this approach, for example, it might make sense to spend transportation funds on housing construction near major employment centers. This kind of planning can be especially beneficial for low-income families who don’t own a car. But for it to happen requires a more democratic decision-making process in which all community stakeholders have input. This broad- based effort can produce more environmentally sustainable regions.

The focus of this paper is on vertical equity, or policies that provide the most benefits to the most people, including those at the bottom of the socioeconomic ladder. Equity should not be understood simply in terms of income or wealth, but in terms of what Amartya Sen calls “functionings and capabilities.” According to Sen, “relevant functionings can vary from such elementary things as being adequately nourished, being in good health, avoiding escapable morbidity and premature mortality, etc., to more complex achievements such as being happy, having self-respect, taking part in the life of the community, and so forth.”1 Capabilities refer to the ability to have choices. Other things being equal, people are better off

if they have choices in how they want to live their lives.2 To achieve transportation equity, not all low-income people should be treated alike because, depending on where they live, some people have greater transportation needs than others.3 For example, using transportation funds to develop pedestrian-friendly, transit-rich villages will enable people to have acceptable “capabilities and functionings” without building expensive highways.

This essay will not examine the direct effects of transportation services on health. Providing more bus routes for low-income communities, for example, would help people to access medical care or healthy foods. Instead, the focus here is on how transportation influences economic development that in turn affects health. By facilitating market exchanges, transportation influences what kind of economic development occurs (single use or mixed use), where it occurs (on the suburban fringe or near the center), and who benefits (rich or poor, white or black). The type of economic development that occurs has direct effects on health. Compact, mixed-use developments that rely more on public transportation, walking, and biking support better health outcomes, other things being equal, than auto-dependent, low- density economic development that separates residential, retail, and office functions.4

Besides these direct effects, there are also many indirect effects of transportation systems on health. Transportation policies encourage economic development that either worsens or lessens poverty, inequality, and economic and racial segregation. All of these factors—poverty, inequity, and segregation—are associated with poor health outcomes (see endnotes five and six). The link between poverty and poor health outcomes is well documented, but less well known is that income inequalities across class and space are also associated with poor health.5 Moreover, residents of areas with concentrated poverty not only have little access to health services, but also experience other factors that undermine health,6 including:

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1. Less Exercise: Because people are afraid to go outside in high-crime areas and because high-poverty areas often lack good walking infrastructure, such as parks and sidewalks, living in poverty-impacted neighborhoods discourages physical activity and therefore increases obesity and other negative health outcomes.

2. Poor Air Quality: High-poverty neighborhoods are more likely to be the locations for toxic waste dumps, garbage transfer stations, bus depots, highways and ports, and truck facilities, and therefore suffer from inferior air quality due to toxic fumes as well as gasoline and diesel exhaust.

3. Inadequate Diet: Residents of high-poverty neighborhoods often lack access to low-cost, high-volume grocery stores with fresh fruits and vegetables.

4. High Stress: Finally, residents of poor neighborhoods suffer from the withering effects of stress. High crime, overcrowding, noise, unemployment, lack of retail outlets, and poor public services are all stressful. Chronic stress damages our organs and immune systems and is associated with cardiovascular disease, asthma attacks, and premature death.

The paper concludes with recommendations for transportation policies that can reduce economic inequalities and improve the access of disadvantaged populations to all those things that are necessary for a good life and good health. It cautions that we need both long-term policies—to reduce automobile dependency by changing land use patterns over time—and short-term policies—to meet the needs of low-income families who live in automobile- dependent environments.

Un h e a lt h y E f f e c t s o f t h e H i g h w a y P o l i c y S i l o

Until the 1990s transportation policy in the United States was dominated by what political scientists call a policy monopoly, or silo—an arena of government decision making controlled by industry insiders and insulated from demands by other stakeholders.7 A steady stream of funding for transportation was guaranteed by federal- and state-earmarked gasoline taxes, and decisions about spending that money were made largely by highway engineers within state departments of transportation (DOTs).

The transportation policy silo was influenced by market principles intended to maximize mobility. Building more and more roads was the market’s response to meet demand of customers who had the most money to spend. Highway engineers in state DOTs based their decisions to extend roadways on mathematical projections for increasing automobile travel, and the central tenet was increased mobility—moving more people over greater distances at higher speeds. Highway engineers were not trained to think about how land use patterns influenced travel demand but to focus on how to move people in the most efficient manner given the infrastructure that was in place.

Rather than simply respond to demand, however, highway building created demand for more roads and cars. This is called traffic generation or induced demand: expanding road capacity on the urban fringe promoted low- density suburban sprawl that in turn generated demand for more highways.8 Reinforced by suburban zoning codes, auto-centered transportation policy promoted economic development that separated residential, retail, office, and wholesale functions into distinct geographic zones. Instead of a market equilibrium or balance between different transportation modes and land use patterns, silo-driven transportation policy generated a positive feedback mechanism that encouraged

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one mode (automobiles) and one land use pattern (suburban sprawl) to expand unchecked.

The white middle-class families that moved out to the suburbs to live in single-family homes on large lots generally inhabited environments with plenty of green space, sunshine, low crime, and low stress.9 Most of the negative effects of highway-oriented economic development fell on those left behind by suburban sprawl. Highway construction encouraged the movement of jobs away from the urban core.10 Largely because of suburban zoning codes, lack of access to federally guaranteed mortgages, and racism in housing markets, inner-city working class and minority households were unable to follow jobs out to the suburbs. Unusually long distances between home and jobs for low-income and minority workers are well documented by researchers and are a cause of poverty.11

Auto-driven urban sprawl has also been a mighty engine of economic segregation. Since the 1950s, new home construction on the suburban fringe has shifted from the middle to the top of the income distribution.12 The correlation between new housing and economic segregation is strong: the newer the housing in a neighborhood, the higher the average income in that neighborhood.13 By subsidizing the flight of the middle class out of central cities

and inner-ring suburbs, the auto-dominated transportation system left behind pockets of concentrated poverty, with the negative effects on health cited earlier.

Using the power of eminent domain, state DOTs displaced millions of households to build new highways.14 Highway engineers typically located highways connecting suburbs with central business districts through low-income, usually minority, neighborhoods to save money on land acquisition. Involuntary displacement from highway building severed social connections, which have been shown to be crucial for good health.15 Forced moves can be life threatening for older adults. At the same time that urban neighborhoods were disrupted by highway building, the highway construction jobs went overwhelmingly to white, often suburban, construction workers.16

The highway-dominated transportation system also puts pressure on family budgets, especially among low-income families. The general standard is that no family should spend more than 20 percent of income on transportation; after that, transportation expenditures will begin to eat into other necessities, such as housing and healthcare.17 The average American household devotes about 18 percent of its after-tax income to transportation, but this varies by income and by place of residence. Overall, transportation expenditures are regressive with regard to income.18 Low-income households, and especially those who live in areas without good public transportation, spend a much higher percentage of their incomes on transportation. For example, households earning between $20,000 and $35,000 and living far from employment centers spend 37 percent of their income on transportation.19 To have access to jobs, they must own a car. The necessity of car ownership exacerbates poverty. In 2007 the annual cost of owning an automobile averaged $9,498 (for insurance, gas, maintenance, and the average annual cost of purchasing or leasing an automobile).20

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n e w T r a n s p o r t a t i o n P o l i c i e s f o r H e a lt h i e r E c o n o m i c D e v e l o p m e n t

The 1991 Intermodal Surface Transportation Efficiency Act (ISTEA) was designed to break open the policy silo that had dominated transportation policy for so long.21 As the name suggests, ISTEA aimed to create intermodal systems that balance highways with transit, walking, and bicycling. ISTEA made it easier to “flex” funds from highways to transit. By encouraging the coordination of land use and transportation, ISTEA began the shift from a mobility policy paradigm to an accessibility policy paradigm. It changed the way decisions were made, removing some decision-making power from highway-dominated state DOTs and giving metropolitan planning organizations (MPOs) veto power over projects in their area. ISTEA began to open the transportation policy silo. For example, decisions for spending Congestion Mitigation and Air Quality (CMAQ) funds had to be approved by the air quality district, thus ensuring that environmental interests would be at the table when some transportation decisions were made. ISTEA also required MPOs to publish an overall plan for citizen participation. The intent was to have a broad array of stakeholders at the table when transportation decisions were made.

Although ISTEA and its successor acts (the Transportation Equity Act for the 21st Century, or TEA-21 (1998), and the Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users, or SAFETEA-LU (2005) have activated new networks around transportation policy, the results on the ground have been disappointing. With the exception of California, relatively few dollars have been flexed from highways to other transportation modes.22 Even though transit ridership is up, the proportion of all trips made by public transportation declined steadily from 1990 to 2001.23 In 2007 10.3 billion trips were taken on public transportation, the highest level in 50 years; the third quarter

of 2008 reported the largest annual increase in transit ridership in 25 years.24 In 2009, just as public transportation is serving record numbers of people, many transit agencies are facing deep cuts. Efforts to coordinate transportation investments and land use continue to be halting and fragmented, and in most metropolitan areas, federal dollars are still going to highways, subsidizing energy-intensive, low-density sprawling patterns of land use that shift jobs away from needy urban communities.25 State DOTs still dominate decision making; only about six percent of federal funds are actually controlled by MPOs.26 Even within MPOs, citizen participation is often ritualistic.27 Citizen groups are put in the position of responding to decisions rather than being at the table when the agenda is set.

The upcoming authorization of federal transportation policy needs to take bold steps to correct these problems, completing the transition from a mobility policy paradigm to a focus on accessibility. All major stakeholders— drivers, transit users, local residents, environmental groups, civil rights organizations, pedestrians, and bicyclists—should have a say in how federal transportation dollars are spent in their areas. Above all, federal transportation policy needs to be more equitable. The next two sections examine areas where transportation policy can improve the health and well-being of disadvantaged groups at the same time that it builds a more efficient and environmentally sustainable transportation system. This requires transportation policymakers to step out of their policy silos and talk to those who formulate housing policy and workforce development policy.

M i x e d -i n c o m e T r a n s i t O r i e n t e d D e v e l o p m e n t

Transportation policy and housing policy tend to be developed in separate policy silos; DOTs don’t talk to HUDs. This is a mistake. Transportation investments shape housing demand and housing shapes transportation demand. Low- density suburban development would have

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been impossible without massive investments in suburban road capacity. Similarly, investments in new light-rail systems open up possibilities for higher-density development around transit stations. Well-planned development around such stations can produce broad benefits for society as well as targeted benefits for low- income persons, but only if equity is made a priority in the transportation-housing nexus. The result will be healthier communities, especially for low-income persons.

Starting with San Diego in the early 1980s, a new generation of fixed-rail transit systems has emerged in the United States. The new light- rail systems are faster than trolleys but stop more frequently than the heavy-rail suburban commuter trains. Bus rapid transit (BRT) lines, in which buses are given dedicated lanes and priority at traffic lights, are being developed in many cities and, if properly constructed, can provide many of the same benefits as light rail. Substantial new investments are being made in new light-rail systems. The federal New Starts program, which provides capital funds for light-rail systems, is funded at only about two billion dollars out of the approximately

$50 billion spent by the federal government on transportation each year. Only a handful of metropolitan areas get assistance in any year.

Many metropolitan areas have taken matters into their own hands, passing local taxes to pay for expansion. In 2004 Denver voters passed a half- cent sales tax to fund a $4.7 billion expansion of their light-rail system; Charlotte voters also approved a half-cent sales tax to finance a nine billion dollar light-rail system planned to be completed by 2030. Light-rail systems are sold to the voters for a wide range of benefits, including cutting traffic congestion, reducing gasoline consumption, improving air quality, and attracting new investment to the region.

All of these benefits are enhanced by transit oriented development (TOD), defined as development within a half-mile of a transit station (about a ten-minute walk) that is high density, pedestrian friendly, has mixed use, and includes station-focused public spaces. The development of new light-rail systems opens up possibilities for more efficient, more environmentally sustainable, and more equitable development. The land around light-rail stations increases in value because it is more accessible to housing, jobs, and shopping.28 Higher land values justify denser development. Drawing on these increased land values, public policies can leverage funding for affordable workforce housing with little or no cost to taxpayers. Developers can be offered density bonuses in exchange for building affordable housing. The profits they make by building more units on each plot of land will be used to fund the affordable housing, typically with money left over as additional profits. In weaker markets, mixed-income TOD may need to be subsidized by housing policies.

The demand for housing near light-rail station lines soared until the recent housing crisis, and it will rise again when the economy recovers and gas prices escalate. Today, about six million households live within a half-mile of a transit station. The demand for housing adjacent to

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transit is projected to reach 16 million by 2030.29 To meet this demand, 10 million housing units will need to be built within a 10-minute walk of transit stations. This movement toward denser, mixed-use forms of development presents a golden opportunity to create mixed- income transit villages, providing healthier environments, especially for low-income families. Enabling low-income households to live in TODs will give them access to pedestrian-/ bicycle-friendly environments that encourage an active, healthy lifestyle and that are closer to amenities, such as full-service grocery stores offering fresh fruits and vegetables.

TOD is built primarily by private developers, but it has extensive public benefits that justify government support: TOD increases property values around stations and therefore enhances tax revenues; well-designed TOD reduces crime by creating “eyes on the street” and 24-hour activity; TOD increases transit ridership and reduces traffic congestion by giving residents access to more destinations by transit and on foot; TOD reduces air pollution by cutting down on the need for automobile use; TOD saves infrastructure costs by reducing the need for parking; and TOD promotes active lifestyles that reduce obesity and improve health.

By including affordable housing, TOD can also improve equity and health. As we noted earlier, transportation costs are an onerous burden to low-income families, especially those that must own a car to get to work. TOD can reduce that burden. Higher levels of accessibility enable families to substitute more affordable and healthier forms of transportation—public transit, walking, and bicycling—for more expensive automobiles. A new tool, the Affordability Index, shows how much a household can save by living in a transit-rich environment. In Minneapolis-St. Paul, monthly costs of transportation varied from $446 to $941. Moving from a transit-poor to a transit- rich neighborhood would save the average household $5,940 a year.30 For a low-income

family, this savings would be huge. Locating jobs within TODs can help overcome the job-housing mismatch discussed earlier.

Planners may be tempted to include only higher- income housing in TODs on the ground that it will maximize property values. But this is not necessarily true. Smaller, more affordable rental housing and condos can be quite profitable. Moreover, low-income households are good to have in TODs because they tend to use transportation more than high-income households. In 2001 those earning less than $20,000 a year accounted for 38 percent of all transit riders, far more than their 14 percent share of the urban population.31 Low- income households are less likely to own a car; therefore, the zoning code can reduce the parking requirement by up to 75 percent (from one parking space per middle-income unit to one-quarter of a space per low-income unit).32 At $10,000–$30,000 per parking space, this can be a powerful incentive for developers to include affordable housing.

One of the barriers to realizing the savings of living in transit-rich environments is that it is very rarely possible for households to entirely give up access to a car. Automobile use has high fixed costs, and those costs are more burdensome to low-income households that drive fewer annual miles. Low-income drivers often pay high insurance rates, even though they drive less.33 Even if low-income households can use public transportation to get to work, in most American metropolitan areas, they will still need a car to transport major purchases or to visit friends or relatives in other parts of the region.

The root of the problem is that there is no easy way to own “part” of a car. The invention of car- sharing solves this problem by enabling access to an automobile on a pay-as-you-drive basis. A nonprofit in the Bay Area, City CarShare, opened for business in 2001, and subsequently private companies—such as ZipCar—have entered the business. Flex cars are parked on

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city streets and, after undergoing a background check, people can join the system and use the cars on a per-hour basis, usually for less than $10 an hour. A study of CarShare members found that nearly 30 percent of them had gotten rid of one or more cars and nearly two-thirds said they had decided not to purchase another car.34 This system could be adapted for low-income persons; used cars could be employed instead of new cars. Imagine what it would mean to a family of three earning the federal poverty cutoff ($17,600 in 2008) if they could dispense with the cost of owning a car (average cost $9,498) and instead use public transportation and car-sharing at one-half that amount or less.

To realize the full benefits of mixed-income TOD, new policies are needed to break down the silos that have encased transportation and housing policies and prevented the synergies that would result from coordinating them.35 The upcoming authorization of federal transportation policy presents an opportunity to connect transportation to economic development and health. When energy prices rise, as they will when the economy recovers, the motivation to coordinate housing and transportation policies to reduce energy consumption will also rise. The Obama administration and the new congressional leadership have expressed a desire to overcome policy silos and to begin planning transportation and housing policies together.36

P o l i c y r e c o m m e n d a t i o n s

Transportation

• Authorization of the upcoming federal transportation bill should enable MPOs to flex funds from transportation funding to subsidizing mixed-income TODs.37

• Funding for the New Starts program should be increased and the Federal Transportation Administration (FTA) should give priority to applications that incorporate plans for mixed- income TODs.

• Funds should be set aside in the next bill to provide technical assistance to local governments and community-based organizations (CBOs) to plan mixed-income TODs.

• U.S. DOT should develop a model overlay zoning code that encourages mixed- use, denser, more pedestrian-friendly development around transportation stations and disseminate best practices for TOD from around the country.

• DOT should require that MPOs’ Transportation Improvement Plans (TIPs) report on how transportation investments will address the need for affordable workforce housing near transit.

• DOT should develop a competitive grant program to subsidize car-sharing for low- income households living within half-a-mile of transit stations.

• DOT (or HUD) should develop an affordability index for housing that includes transportation costs to monitor the progress of metropolitan areas, especially for low-income households.

Housing

• The Low-Income Housing Tax Credit (LIHTC) and New Markets Tax Credit programs should be amended to incentivize projects that are located within half-a-mile of a transit stop; the U.S. Treasury should increase the LIHTC bonding cap for states to undertake mixed- income TOD projects.

• HUD should write regulations for the Community Development Block Grant (CDBG), and other grant programs, to give high priority to mixed-income TODs.

• The federal government should enact a homeownership tax credit targeted to low- and moderate-income homes located within half-a-mile of a transit station.

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• HUD should create a program to preserve affordable housing within half-a-mile of a transit station and that is threatened by expiring use restrictions.

• State and local governments should allocate a portion of tax-increment financing (TIF) and other local incentives to mixed-income TODs; economic development incentives should be targeted on jobs that are accessible by transit (“location efficient job incentives”).38

• In strong market regions, local governments should enact TOD overlay zoning districts that reward developers with density bonuses if they include workforce housing.39

T r a n s p o r t a t i o n a n d l o c a l Wo r k f o r c e D e v e l o p m e n t

Just as transportation policy needs to be coordinated with housing policy, it also needs to be coordinated with workforce development policy. Transportation expenditures generate hundreds of thousands of jobs each year in the construction industry. When these jobs are targeted to the neediest communities, transportation policy helps to lift up poor communities and, in the process, improve health outcomes. In effect, connecting transportation to workforce development enables the taxpayers to get “more bang for their bucks.”

The loss of well-paying manufacturing jobs has been devastating to many inner urban, heavily minority communities, creating pockets of concentrated poverty with all of the negative effects on health discussed earlier.40 One of the causes of entrenched poverty is the lack of decent-paying jobs for workers without a college education. The jobs they can get usually pay low wages, have few benefits (including no health insurance), and lack job ladders for advancement. Dead-end jobs offer little hope.

Construction is one industry where a worker

without a college education can get a job with good pay, decent benefits, and the prospects of advancing up a clear job ladder. Even though fewer than 10 percent of construction workers have college degrees, the average wage in construction in 2006 was $18.29 an hour, well above the minimum wage.41 Wages and benefits vary significantly in the industry.42 Unionized construction workers who have access to joint union-contractor apprenticeship systems can advance from apprentice to journey-level status, earning at least $30–$40 an hour. The apprenticeship system is paid for by a modest surcharge on all wages that are part of the collective bargaining agreement. Workers do not need thousands of dollars to access excellent job training services; in construction apprentice programs they can “earn while they learn” on the job.

Unfortunately, blacks and women have historically been blocked from skilled, unionized jobs in the construction trades. According to a recent study of the core counties in the 25 largest metropolitan areas, if blacks were employed in construction in 2006 at the same rate they were employed in the general workforce, an additional 137,044 blacks would be working in construction. In 2005 women represented only 2.6 percent of production workers in construction.43

Successful programs have been set up around the country involving collaboration among unions, community groups, and end users of construction to bring minorities, women, and low-income persons into skilled construction trades. With the exception of the recent downturn in the homebuilding industry, construction jobs are growing, offering the opportunity to bring new workers into skilled construction trades without displacing present workers. Based on retirements, transfers, and job growth, the federal government estimates that the industry will need to recruit 245,900 skilled construction workers each year between 2004 and 2014.44 With guaranteed funding

Breaking Down Silos

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of $244 billion over five years, SAFETEA-LU should have created more than 1.9 million person years of on-site construction jobs by its 2009 expiration.45

The 1931 Davis-Bacon Act, as amended, requires that all workers on federally funded construction projects be paid the “prevailing wage” in each region, which is usually close to the union wage in construction.46 The potential of targeting jobs from transportation projects to disadvantaged communities is illustrated by the Alameda Corridor project. In 1998, a coalition of community groups won a local hiring agreement on a $2.4 billion transportation project serving the ports of Los Angeles and Long Beach, called the Alameda Corridor.47 The project used a combination of federal and state monies. A coalition of 40 community- based organizations negotiated a community benefits agreement (CBA), requiring that at least 30 percent of all the hours on the project be performed by disadvantaged persons from the surrounding low-income zip codes. During the CBA negotiations, the federal government maintained that targeted hiring was prohibited on both statutory and constitutional grounds. The project was able to get around this prohibition by using only state funds for the targeted hiring program. CBOs were funded to run pre-apprenticeship programs to prepare applicants for the rigors of construction. Of the 880 graduates of the pre-apprenticeship programs, 373 were ex-offenders. Eventually, 710 local residents were placed in construction jobs.

The Transportation Equity Network (TEN) —a coalition of 300 grass-roots community groups working to make transportation policies more responsive to low-income persons, minorities, and disadvantaged communities—wanted to spread the Alameda model around the nation. In 2005 it was able to get a “Sense of Congress” inserted into SAFETEA-LU, which specifically upholds the Alameda Corridor project as a model and states that “federal transportation projects should facilitate and encourage” collaboration between state

departments of transportation and other interested parties “to help leverage scarce training and community resources to help ensure local participation in the building of transportation projects” (Public Law 109-59, Stat. 114. Section 1920: Transportation and Local Workforce Investment).

Using this provision, TEN and its allies have negotiated local workforce agreements in states and metropolitan areas around the nation.48 In one successful example community groups in St. Louis used a little-known provision in federal transportation law (23 USC 140) that allows state DOTs to use up to one-half of one percent of surface transportation funds for workforce development. The groups negotiated an agreement with the Missouri Department of Transportation that devoted $2.5 million from the $535 million I-64 project to local workforce development and reserved 30 percent of the work hours on the project for women, minorities, and low-income persons. A similar agreement was negotiated in 2008 for the Kansas City Paseo Bridge Project. In May 2008 Governor Tim Pawlenty of Minnesota signed a law that directs Minnesota’s DOT to spend the maximum amount feasible on job training and supports. Also in 2008 Michigan passed a law that directed $15 million of highway funds into job training over four years.

Successful state and local experiments show that transportation projects can successfully target jobs to needy communities. Federal prohibitions against race- or place-based targeting have been overcome by recruiting participants through “first-source” job training centers. Under first-source hiring provisions, apprenticeships are required to be filled by job training centers that are located within, and have close ties to, low-income and minority neighborhoods. These job training centers provide pre-apprenticeship training that prepares workers for the rigors of the construction trades. Many applicants lack the basic math skills, work habits, and knowledge of the construction industry to succeed

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in an apprentice program. Successful pre- apprenticeship programs impart these skills and weed out those who are unprepared, including those with drug or alcohol problems. The best pre-apprenticeship programs have high success rates placing their graduates in the construction trades, but they cost between $6,000 and 8,000 per participant.49

Successful experiments in local workforce development in the construction trades are encouraging, but they do not come close to meeting the need. This is where transportation policy can make a difference. Current federal transportation law permits states to use federal highway funds for local workforce development; it does not require them to do it. Local workforce development should be mandatory on all large federal transportation projects. The federal departments of transportation and labor should collaborate to develop joint programs on workforce development. Transportation expenditures will generate a steady demand for skilled construction labor, which could be met by targeted job training programs.

P o l i c y r e c o m m e n d a t i o n s

Transportation

• Section 1920 should be changed from a “Sense of Congress” to a mandate requiring that 30 percent of all hours on all large federal transportation projects (over $10 million) be performed by women, minorities, ex-offenders, and low-income persons from the local communities where the project is located.50

• One percent of all funding on large federal transportation projects, transit as well as highways, should be set aside to fund pre- apprenticeship programs and to subsidize the wages of apprentices.51

• State DOTs should be directed to facilitate negotiations among unions, contractors, community groups, local job training agencies, and other interested parties to negotiate agreements to implement mandated local hiring.

Labor

• The U.S. Department of Labor (DOL) should establish a program under the Workforce Investment Act to provide grants in metropolitan areas with demonstrated shortages of skilled construction workers for pre-apprenticeship programs run by unions, community-based organizations, high schools, or community colleges.

• DOL should fund a program to evaluate pre- apprenticeship programs around the country and spread best practices, including offering technical assistance to providers of such programs.

• DOL should gather data on the supply and demand for skilled construction labor

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in each metropolitan area for each major construction trade to guide local workforce development planning.

In short, health, environmental, and equity concerns can and must be addressed at the same time. Win-win policies can help to cement the so-called blue-green alliance between workers and environmentalists. For example, a recent Public Interest Research Group (PIRG) report showed that investment in public transportation produces 19 percent more jobs than equivalent investments in roads and bridges.52 We have shown that mixed-income development around transit stations can address poverty and improve health outcomes at the same time. Equity and health advocates have a natural convergence of interests here.

To realize these policy objectives, we do not need government agencies to just break out of their policy silos; we need citizens to break out of their advocacy silos. Transportation equity advocates need to understand the health implications of the policies they recommend, and health advocates need to be mindful of the impacts of their policies on equity—on the ability of people everywhere to access opportunities. Health advocates need to understand the key role played by land use reform in creating healthier environments and giving low-income persons access to jobs. There is a convergence of interests here that could build powerful coalitions for reform—only if advocates in each area set aside narrow definitions of self-interest and open themselves to new perspectives.

C o n c l u s i o n

It is exciting to develop policies that can shape a new built environment that is healthier and more equitable than today’s norm. This will require working across the silos that have too often constrained effective public policies. For example, Secretary of HUD, Shaun Donovan, and Secretary of Transportation, Ray LaHood, have begun to collaborate on how to coordinate housing and transportation policies (see endnote 36). Using transportation policies to promote affordable housing and housing subsidies to support public transportation will reduce our over-reliance on automobiles and create healthier environments.

Unfortunately, most people today live in a built environment that requires extensive use of cars or buses. To devote the vast bulk of our resources to public transportation in order to shape the built environment in a more progressive direction would be shortsighted.53 We must continue to invest resources in maintaining and improving bus service for low- income persons and people with disabilities (including making buses less polluting), even though buses, unlike light-rail systems, do not create powerful incentives for higher-density TOD. Indeed, we may need to subsidize vans and even car ownership for some people who live in areas not serviced by mass transit.54

Ultimately, we need short-term policies to accommodate the transportation needs of people where they presently live at the same time that we advocate for long-term policies that will shape living patterns to reduce automobile dependence and create healthier environments for everyone.

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Sustainable Food Systems: ch. 7 Perspectives on Transportation Policy K A MI POTHUKUCHI, Ph.D. Associate Professor of Urba n Pla nning, Wayne State University Detroit, MI

R ICH A R D WA LL ACE, M.S. Senior Project Ma nager, Center for Automotive Resea rch A nn A rbor, MI

ABSTRACT >> Global agri-food and transportation systems have dramatically expanded food production and distribution worldwide. This integration, however, also adversely affects human health. The negative effects arise from unequal access to healthy food, unequal access to transportation for agri-food workers, increasing geospatial and economic concentration in the agri-food industry, and an emerging competition between food and fuel. Because the health of individuals is inextricably tied to the health of communities, regions, and ecological systems, health and transportation professionals need to act to both mitigate current disparities and enhance the future viability and sustainability of these systems. This paper offers numerous, specific recommendations for improving health through transportation policy and programs as they relate to agri-food systems.

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Sustainable Food Systems

CONTENTS

Agri-food Systems, Health, and Transportation: An Overview.. .. .. .. .. . 115

Disparities in Urban and Rural Communities’ Access to Healthy Foods . .. .. .. .. .. .. .. .. .. . 116

Lack of Grocery Stores in and near Low-income Neighborhoods .. .. .. .. .. .. .. . 116

Increased Dependence on Use of an Automobile for Grocery Shopping .. .. .. .. . 117

Disparities in Affordable Transportation Alternatives for Agri-food System Workers . .. .. .. .. .. .. .. .. .. .. .. .. .. . 118

Transportation, Agri-food System Sustainability, and Disparate Community and Regional Impacts.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 120

Increased Road- and Air-miles in Food Transportation . .. .. .. .. .. .. .. .. .. .. .. . 120

Increased Consolidation of the Food Industry and Disparate Social and Spatial Impacts .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 121

Food versus Fuel and Related Health Impacts . . 122

Elements of a Sustainable Agri-food System .. . 123

Transportation Goals . .. .. .. .. .. .. .. .. .. .. .. .. . 123

Transportation Policies: Opportunities and Barriers .. .. .. .. .. .. .. .. . 126

Convergence Opportunities .. .. .. .. .. .. .. .. .. . 128

Conclusion.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 129

LIST OF ILLUSTRATIONS

Tables

1. Energy Consumption and Emissions by Different Freight Modes .. .. .. .. .. .. .. .. . 119

2. Average Distance by Truck to Chicago Terminal Market . .. .. .. .. .. .. .. .. .. .. .. .. .. . 119

3. Estimated Fuel Consumption, CO 2 Emissions,

and Distance Traveled for Conventional, Iowa-based Regional, and Iowa-based Local Food Systems for Produce . .. .. .. .. .. . 120

4. Desired Policies and Programs to Address Transportation-Related Agri-food Problems: Opportunities for Success .. .. .. .. .. .. .. .. . 124

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a g r i- fo o d S y s t e m s , H e a lt h , a n d T r a n s p o r t a t i o n : a n O v e r v i e w

Agri-food systems include the production, processing, distribution, and consumption of food; the disposal of wastes; and the resources, actors, rules, and processes involved in the design, implementation, promotion, and regulation of these activities. These systems interact with communities to affect human health, both directly and indirectly. This paper explores these interactions to inform transportation policies that improve health, strengthen communities, and protect the environment.

As a result of linkages between the agri-foods industry and growing transportation networks, most U.S. households have ready access to large quantities of foods from all over the country and abroad; communities in crisis can quickly receive food aid transported from faraway countries; and exporters can efficiently reach grocery store shelves and markets around the world, positioning U.S. corporations at the helm of an international retail food enterprise pegged at four trillion dollars annually.1

But the integrated system for food production and distribution has left behind millions of Americans in low-income communities in the inner cities and sprawling rural areas. Women, people of color, and immigrants have been left particularly vulnerable. To reduce disparities and attendant costs; to distribute benefits more equitably; and to build more sustainable transportation, food, and community systems, transportation policy must focus on health concerns resulting from:

• Lack of access to grocery stores offering affordable, healthy foods. This imbalance is associated with higher rates of obesity, disease, food insecurity,2 and related stress;

• Lack of efficient, affordable transportation access for agri-food workers, such as farm workers and food service staff, whose wages are among the lowest in a region;

• A global agri-food industry that is fueled by cheap energy and transportation subsidies but, paradoxically, poses serious health risks to the community and exacerbates climate change; and

• Competitive market pressures to use crops for fuel, raising the price of food.

Transportation policy has not traditionally considered these issues, but it should, given the increasing rates of obesity and related health costs; climate change; threats to global food security; and inefficient, unsustainable food systems that rely on cheap energy to distribute food to faraway places.

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D i s p a r i t i e s i n Ur b a n a n d r u r a l C o m m u n i t i e s ’ a c c e s s t o H e a lt h y fo o d s

Communities do not enjoy the same access to healthy foods, with inner-city neighborhoods and remote, rural areas faring the worst.3 This disparity occurs for several reasons, including a lack of grocery stores in low-income neighborhoods, a lack of affordable mass transportation, and lower rates of automobile ownership in low-income areas.

Lack of Grocery Stores In and near Low-income neighborhoods

Over the past five decades, the food retail industry has transformed itself in many ways, resulting in fewer corporate chains capturing a larger share of the retail market,4 more big- box stores opened in suburban locations and

fewer in urban and rural ones,5 and supermarket chains with consolidated food supply and distribution systems.6 These shifts, and increasing suburbanization, mean that fewer people now live within walking distance—or a short bus or subway ride—to the grocery store.7 This spatial dislocation has been made possible, in large part, by federal transportation policy that financed highway development, supported increased truck transportation of goods, and encouraged personal automobile use through subsidies that expanded roadways and parking. For example, one study puts the total “tax subsidy” to motor vehicle users in the range of $19–$64 billion per year.8

Today, inner-city9 and rural10 neighborhoods have fewer and smaller grocery supermarkets, with poorer selections of healthy foods and higher prices than their suburban counterparts. Urban neighborhoods, conversely, have an abundance of smaller convenience stores and fast-food outlets, which offer disproportionately higher amounts of foods of poor nutritional quality.11 A decline in wholesale and retail farmers’ markets12 also paralleled the decline of grocery supermarkets in urban and rural locations, although farmers’ markets have recently seen a dramatic rise.13 Nonetheless, farmland in metropolitan areas, where a majority of fruits and vegetables are grown, continues to be consumed by urban sprawl.14

For low-income and urban residents, for people of color, and for immigrants—all of whom tend to own fewer cars than affluent and middle-class whites,15 the paucity of nearby supermarkets leads to higher rates of diet-related morbidity and mortality,16 and even greater stress related to grocery shopping. Conversely, relatively easy access to supermarkets is associated with higher household consumption of fruits and other positive dietary behaviors.17 Disparities in the number and size of supermarkets have been documented by race even after controlling for income, with African American neighborhoods most adversely affected.18 Higher costs,

Sustainable Food Systems

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poorer selections, and lower quality of foods in low-income neighborhoods mean that taxpayer-funded nutrition programs such as the food stamp program (more recently known as SNAP, or the Supplemental Nutrition Assistance Program) don’t go as far as in better-off neighborhoods. Lack of affordable, neighborhood-based food outlets also forces low-income households to rely more on emergency food programs such as food pantries that—dependent on private donations and government surpluses—stock little in the way of healthy foods. What’s more, poor diets conspire with poor air quality, fewer parks and fitness facilities, poor quality housing, high levels of crime, noise, and other social and environmental stressors in low-income neighborhoods.

Increased Dependence on Use of an Automobile for Grocery Shopping

Grocery shoppers tend to prefer to travel to supermarkets by car, in part because of the one- stop design of supermarkets and their proximity to large-scale shopping districts with abundant, available parking, all of which discourage walking or biking. Vehicles save time and can help shoppers reach more stores, combine trips, and transport heavy packages easily, including in inclement weather.19 One Austin, TX, study found that few people substitute walking for driving to the grocery store, even if pedestrian or cycling access is good.20 Even the poor who do not own cars often borrow them, ask for rides from friends, or take taxis to do grocery shopping21; however, transportation and walking remain critical in providing the mobility needed to access grocery outlets for these families.22

Public bus routes and schedules, even in well- serviced communities, are typically planned in ways that disadvantage food-shopping trips needed during weekends and evenings. A typical bus system is also planned around a central hub, a design that often lengthens travel time to more peripherally located supermarkets. And high levels of required parking for supermarkets may make them less of a priority

in transportation system planning. Perversely, such land use policies may exacerbate the peripheral location of supermarkets. Research from the United Kingdom suggests that when land use policies discourage new supermarket development on the urban fringe, stores invest more in expanding and refurbishing the older stores based closer to the urban core.23

People who live in low-income households are underserved by both the food24 and transportation25 systems. In 2007, food insecurity rates in the United States rose even before the sharp economic declines of 2007–08. Overall, 36.2 million persons—or 12.2 percent of Americans, mostly women, minorities, and children—struggled with hunger. In May 2008, more than 28 million persons participated in the food stamp program, a 32 percent increase in five years; yet the program reaches only two out of three eligible households.26 Access to food stamp offices for these populations often is undermined by the distances needed to travel, lack of evening hours of operation, and limited public transportation within communities.27

Food stamp recipients are also vulnerable to losing benefits due to lack of transportation to recertification appointments.28 For a variety of reasons, farm worker households face a higher risk of food insecurity.29 At the same time, the poorest Americans who have cars spend disproportionately more of their household budget than the national average on the purchase, operation, and maintenance of automobiles30; are subject to higher interest rates when attempting to purchase a car; spend disproportionately more on commuting to work31; and are more likely to miss work due to car problems.32

Low-income populations are comprised disproportionately of women, who also tend to make more trips related to childcare and household servicing—including 75 percent more grocery shopping than men do.33 Shoppers tend to mix and match stores for food shopping based on criteria related to product mix, price, quality, and quantities desired and also the

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Sustainable Food Systems

relative proximity of suitable outlets to their homes and workplaces.34 Rural residents shop for groceries at more stores than do urban residents and travel farther to reach the stores.35

Nonetheless, the scarcity of large supermarkets in poor neighborhoods and the economic pressures that force low-income residents to shop in smaller stores in their neighborhoods remain significant factors in why poor people pay more for food.36 Federal nutrition programs such as food stamps and WIC (Women, Infants, and Children) do not pay for transportation costs incurred by households to procure food.37 The Summer Food Service Program, which is under-enrolled in large part because of transportation barriers, provides small multiyear, competitive grants for innovative approaches to overcome such barriers.38

Although transportation costs represent only a modest share of the cost of food consumed at home—an estimated six to 12 percent39— energy disruptions can cause significant hikes in the price of food, as was experienced in the first half of 2008.40 This is because both the food and transportation systems are highly energy intensive. Also, declining diesel oil prices through the 1990s tended to restrain food transportation cost increases; this trend is unlikely to continue for long. Rising energy costs hit low-income households especially hard as they struggle with maintaining an automobile, higher utility costs, and buying enough food for their families.

D i s p a r i t i e s i n a f f o r d a b l e T r a n s p o r t a t i o n a lt e r n a t i v e s f o r a g r i-f o o d S y s t e m Wo r k e r s

Low-income rural households also experience problems with access to affordable transportation.41 Agri-food workers’ burdens in this regard are especially heavy, and the least paid among them also tend to be predominantly members of groups that

are also vulnerable within communities: disproportionately younger (or older), female, immigrant (including those without legal residency status), and people of color. Most farm laborers and food service workers earn close to the minimum wage and get few additional benefits or perks. According to the U.S. Department of Labor, the national median wage in 2007 for waiters and waitresses was $7.62 per hour, and that for farm workers and laborers was $9.78 per hour. By comparison, the median for all occupations was $15.10 per hour. Dependence on public transportation reduces employment access far more than any other factor42; when people who work at or near the minimum wage must make longer journeys to work, their income does not rise.43

Agri-food workers also experience greater transportation challenges because of the dispersal of jobs across the metropolitan and rural landscape. As a subset, farm workers have special difficulties accessing transportation.44 In one study of farm workers in Mendocino County, CA, two out of five workers depended on rides from family members and other acquaintances; those who incurred transportation costs (i.e., were not living on farms) reported a mean cost of $40 per week—or roughly 16 percent of the average weekly wage—with a median of $30 per week.45 As other papers in this collection show, strong evidence exists of a correlation between lack of access to adequate mobility and lack of access to opportunities, social networks, and health-supporting services such as clinics and pharmacies. At the same time, anecdotal evidence suggests that farm workers with transportation issues are at higher risk for injury as a result of their greater reliance on older “junker” cars, traveling in the early hours of the morning, lower safety requirements (such as seatbelts) for farm-worker transport vehicles, and lax enforcement of safety regulations for such vehicles.46

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Rail Water Truck Air

Fuel (kilojoules per ton-kilometer) 677 423 2,890 15,839

Emissions (grams per ton-kilometer)

Carbon Dioxide 41 30 207 1,260

Hydrocarbons 0.06 0.04 0.3 2.0

Volatile Organic Compounds 0.08 0.1 1.1 3.0

Nitrogen Oxide 0.2 0.4 3.6 5.5

Carbon Monoxide 0.05 0.12 2.4 1.4

Average distance by truck to Chicago Terminal Market (continental U.S. only)*

# States supplying this item

% Total from Mexico

Grapes 2,143 miles 1 7

Broccoli 2,095 miles 3 3

Asparagus 1,671 miles 5 37

Apples 1,555 miles 8 0

Sweet Corn 813 miles 16 7

Squash 781 miles 12 43

Pumpkins 233 miles 5 0

* Information for this chart is based on the weighted average source distance—a single distance figure that combines information on distances from production source to consumption or purchase endpoint. For more information on method, refer to Pirog and Van Pelt, 2002 (endnote 55).

Table 1. Energy Consumption and Emissions by Different Freight Modes54

Table 2. Average Distance by Truck to Chicago Terminal Market, 199855

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Sustainable Food Systems

T r a n s p o r t a t i o n , a g r i-f o o d S y s t e m S u s t a i n a b i l i t y, a n d D i s p a r a t e C o m m u n i t y a n d r e g i o n a l i m p a c t s

In global commerce, the agri-food sector presents special opportunities and challenges when it comes to transportation. Food, especially produce, is different from other commodities in that it is perishable and requires timely delivery and careful handling—including temperature control and cooling—to prevent spoilage. Globalized transportation of food enables surpluses from one region to efficiently make up for shortfalls in other regions, and one hemisphere to continue to supply familiar foods to the other following the latter’s growing season; it also makes available new markets for local agriculture.

Because both modern agriculture and transportation today are more energy intensive than in the past, when energy costs go up, food costs rise dramatically, making the global food system especially susceptible to inflationary pressures and communities vulnerable to rising

energy prices.47 Additionally, the greater reliance on faraway sources for food has resulted in a loss of access to markets for many local and smaller-scale farmers, which, when combined with the loss of metropolitan farmland to urban sprawl, only exacerbates the vulnerability of food systems in many parts of the country.48 Increased truck-miles and air-miles in food transportation worsen air pollution and climate change; increased roadway congestion causes more accidents; the loss of nearby slaughter and packing facilities increases travel times and stress for animals. Together, these factors accumulate social, economic, and environmental costs that are greater than what food source communities get in return for their products.

Increased road- and Air-miles in Food Transportation

Environmentalists are increasingly concerned about the distance food travels from field to plate—typically 1,500 road-miles— which creates unsustainable demands on transportation, air quality, climate, and energy systems. One study revealed that the average distance for fruits transported to the Jessup, MD, terminal market was 2,146 miles, while

Table 3. Estimated Fuel Consumption, CO2 Emissions, and Distance Traveled for Conventional, Iowa-based Regional and Iowa-based Local Food Systems for Produce56

Food system type/type of truck Fuel consumption (gal/year)

$ value of fuel (2001 prices)

CO2 emissions (lb/year)

Distance traveled (miles)

Conventional/semitrailer 368,102 581,601 8,392,727 2,245,423

Iowa regional/semitrailer 22,005 35,208 501,714 134,230

Iowa regional/midsize truck 43,564 69,702 993,243 370,289

Iowa local–CSA farmers’ market/ small truck (gas)

49,359 78,974 967,436 848,981

Iowa local–institutional/ small truck (gas)

88,265 141,224 1,729,994 1,518,155

ch. 7

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the average for vegetables was 1,596 miles.49 Transportation accounts for about 11 percent of the energy use in the food system.50 About 93 percent of fresh produce transported between cities in this country was carried by trucks, according to a 1996 USDA study.51 In addition to general emissions that affect our climate, truck emissions create disparate air quality- related health impacts on low-income and minority neighborhoods because of their greater proximity to highways and truck terminals.52 Causing even more concern is the rapidly growing air transport of food, which creates the highest CO

2 emissions per ton.53

Table 1 shows the energy consumption and tailpipe emissions for different modes of transportation. Of course, the actual mode of transportation and the distance traveled varies by specific food product and its origin. Distances traveled by different products shipped from within the continental United States are given in table 2 (which also shows how much averages derived from travel within the continental United States may understate actual distances if a larger share of a product comes from Mexico). Energy consumption and emissions for different kinds of truck transportation participating in distinct local, regional, and the conventional national food system considered by Pirog et al. (2001) are given in table 3. This last table underscores the point that the sustainability of local food systems is mediated by the specific mode and fuel used in transporting foods.

Finally, the transportation sector is responsible for more than one-quarter of all emissions causing climate change.57 Many agri-food advocates are increasingly concerned about the implications of climate change for future agricultural productivity and food security in poorer regions of the world, given the greater likelihood of drought, soil erosion, extreme weather events, and higher pest prevalence.58 More sustainable transportation, together with an agri-food system that reduces energy and transportation demand, would help reduce burdens on future agriculture globally.

Increased Consolidation of the Food Industry and Disparate Social and Spatial Impacts

Industrial agri-food’s specialization in certain crops has concentrated food production in regions and uses large quantities of fossil fuels to ship food around the country and the world. For example, 95 percent of the nation’s processed tomatoes and just under one-third of the fresh tomato crops come from California.59 In 2007, nearly $152 billion of agricultural products crossed U.S. borders as imports and exports, representing more than half the value of agricultural products sold by U.S. farms that year.60 This specialization, however, has reduced many “receiving” regions’ previous diversity of production and made them more vulnerable to shocks in the system. For example, agricultural modernization has favored large farm size, crop monocultures, mechanization, and increased chemical inputs. Moreover, research points to rising food insecurity among low-income farmers in some countries as subsistence production has been replaced by export-oriented mono-cropping.61 These challenges, of course, affect rural communities and predominantly smaller-scale and low-income farmers whose market reach is hurt by the loss of localized infrastructure and support for logistics (management of the movement of goods). Cheap energy and transportation subsidies have therefore enabled the consolidation and globalization of the agri-food sector.

The case of retail supermarkets and resulting disparities in healthy food access was presented in the first section of this paper.62 The increase in food miles traveled results from: (a) restructuring of logistical systems due to stricter requirements from retailers’ management of inventories; (b) realignment of supply chains so that more of the product from farm to supermarket is owned by a single firm or a strategic partnership of firms (which has happened to reduce costs and risks and also increase responsiveness to consumers); (c) shifts in production and distribution scheduling

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decisions, with negotiated coordination replacing market coordination; and (d) changes in management of transport resources such as increasing the use of air instead of road transport for food.63

The consolidation of processing, wholesaling, and distribution operations results in fewer, larger, and more efficient facilities and the closure of more local and regional processing plants, warehouses, and related facilities. As a result, the plant closures cause greater economic insecurity and health risks for nearby communities.

The transportation sector also has experienced consolidation, with somewhat similar results. Railroad consolidations, for example, have increased the number of captive customers and, while the monopolization helps railroads financially, it also tends to distort the location of economic activity, creating or exacerbating regional disparities64—and therefore vulnerabilities—in the food system.

fo o d Ve r s u s f u e l a n d r e l a t e d H e a lt h i m p a c t s

The production of the most popular forms of biofuels—corn ethanol and palm oil—threatens to cause a major increase in greenhouse gas emissions.65 In the United States, corn ethanol poses special concern because of its net negative energy balance (that is, more energy is required to produce a gallon of corn ethanol than can be gained from it) and because its production and use contribute to air, water, and soil pollution.66 Some food security advocates worry that the continued expansion of biofuels is raising food prices in this country67 and elsewhere and causing malnutrition in many developing countries.68 Still others suggest that corn ethanol has a worse impact on the environment and human health than do conventional fuels such as gasoline and diesel.69 There are direct transportation impacts as well: as corn use shifts from exports and animal-feed use to ethanol production, grain transportation

is affected because of changes in quantities transported to diverse destinations and modes of freight used for raw and finished products.70

To summarize the paper’s analysis, transportation policies and subsidies—when combined with cheap energy over the past six decades—have thus created patterns of spatial dispersion of people and food outlets over the metropolitan landscape in ways that pose special hardships for low-income food shoppers as well as agri-food workers in urban and rural communities. Transportation has also enabled structural change in the agri-food sector so that decisions made in the name of economic efficiency have generated many negative environmental, social, health, economic, and spatial consequences, along with increased costs and risks to society as a whole. These consequences call for a review of the basic goals and purposes of transportation policy so that environmental, social, and health needs and goals take priority over private gain.

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E l e m e n t s o f a S u s t a i n a b l e a g r i-f o o d S y s t e m

A primary contribution of the agri-food system is to deliver adequate nutrition to support the health of human communities now and into the future. However, contemporary industrial agri- food practices also create direct health problems (such as through the effects of pesticides on farm workers or widespread obesity among youth and adults) and indirect health problems (through diminished quality of air and ground water and the pervasive use of antibiotics in meat production, for example). These practices also endanger the very base upon which the food system depends, thereby threatening future food security and health. That is, they are unsustainable.

A sustainable food system promotes the health of individuals, communities, and the ecosystem. As this paper shows, transportation is implicated in many of the pathways linking the agri-food system and health. Sustainable food systems are typically organized around the following principles, on which consensus more or less exists:

• produce and distribute food so that all persons have adequate access to nutritious foods within neighborhoods;

• respect and operate within the biological limits of natural resources such as soil, water, and species;

• minimize energy inputs, recycle resources, and use renewable energy and other resources;

• support vital and diverse urban and rural economies;

• enable viable livelihoods and fair trade among producers, processors, distributors, retailers, and consumers;

• provide safe, fair, and satisfying working conditions for workers;

• treat animals humanely;

• sustain the amount and quality of land needed for food production; and

• promote democratic processes in decision making related to food and nutrition.71

T r a n s p o r t a t i o n G o a l s

The following goals are proposed for transportation policy and programs to help build sustainable food systems that promote human, community, and environmental health in the United States and globally.

1. Healthy food access for all, with special focus on the needs of low-income communities and communities of color, through appropriate land use policies and affordable transportation alternatives.

2. Affordable and reliable transportation alternatives for low-income agri-food workers so that they may have access to employment, food sources, and other basic needs.

3. Transportation policies and programs that prioritize regional linkages over national and global ones as they relate to food systems so that local producers are connected with local eaters; regional economic development is promoted through localized networks and infrastructure; small-scale farms are supported; air pollution and climate change impacts are reduced; and risks associated with agri-food concentration, dependence on distant sources, and energy price hikes are mitigated.

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Goals Desired Policies and Programs

Reduce disparities in access to healthy foods

Support local and metropolitan land use policies and planning for increasing neighborhood-based access to food retail sites such as stores, farm stands, and urban agriculture sites72:

• Promote smart growth development that supports multiple transport modes and contains grocery stores, urban agriculture sites, and farm stands.

• Encourage transit oriented neighborhood design to include grocery outlets.

• Retrofit older neighborhoods for pedestrian, bike, and transportation access to food outlets and urban agriculture sites.

• Reduce required parking for grocery stores in exchange for public bus connectivity during peak grocery shopping times (weekends, especially).

Support policies and programs that promote transportation access for low-income residents to grocery outlets and other healthy food sites:

• Promote paratransit or public-private partnerships for shuttle programs sponsored by supermarkets,73 congregate (subsidized) housing facilities and community-based nonprofits to provide affordable rides for grocery shopping.

• Develop and promote “grocery bus” routes74 with weekend service to connect low-income neighborhoods to full-service supermarkets, food pantries, and urban agriculture sites.

• Support community-based programs to create mobile markets or grocery van-delivery in urban and rural communities.75

Require transportation support in federal nutrition programs:

• Include transportation support for WIC, food stamp (SNAP), Summer Food Service, and farmers’ market-related nutrition programs to access healthy foods.76

• Provide transportation support for small-scale farmers to sell at farmers’ markets in or near low-income urban or rural areas.

Table 4. Desired Policies and Programs to Address Transportation-Related Agri-food Problems: Opportunities for Success

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Goals Desired Policies and Programs

Promote safe and affordable transit for agri-food workers

• Increase funding for job access and reverse commutes for low- income employees, including agri-food workers.

• Encourage metropolitan transportation system design to increase access for low-income agri-food workers in processing, wholesale, and retail jobs in metropolitan areas.

• Encourage paratransit options (vanpools) for farm workers.77 • Review rules related to vehicle conversion for farm-worker

transportation and safety equipment/use to increase transportation safety and minimize accidents.

Promote agri-food sustain- ability

• Support within transportation law small-scale farmers’ and processors’ transportation of product to farmers’ markets and other local outlets.

• Encourage and support cleaner and more efficient vehicles, especially smaller trucks used for local food transportation.

• Review and adjust tax structure as it relates to overall transportation subsidy so that social and environmental costs associated with emissions in agri-food transportation are reflected in prices, especially in the case of air transportation of foods.

• Promote use of more sustainable modes of freight for long- distance food transportation, such as rail and water.

• Increase competitive access to rail for food transport (via separation of ownership of rail infrastructure from that of rolling stock, e.g. rail cars), increase subsidy for rail relative to road and air, and break up geographic concentration of control over railway infrastructure (e.g. tracks) to increase competition.

• Prioritize local and regional food transportation networks and infrastructure over long-distance ones.

• Support the development of mobile kitchens and processing facilities in urban and rural communities.

• Promote metropolitan planning to prevent sprawl, preserve farmland, and promote urban agriculture in transportation- related rights of way.78

Prioritize agriculture for food and promote sustainable biofuels

• Minimize competition in agricultural production between food and fuel (since most biofuel is used for transportation) by giving food a clear priority.

• Support the development and promotion of genuinely sustainable biofuels.

• Support the widespread conversion of waste cooking oil into biodiesel.

• Internalize social and environmental costs of corn-ethanol production and end subsidies for biofuels that are sourced from food grains.

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Goals Desired Policies and Programs

General recommendations • Promote greater coordination between transportation and agri- food policies and programs.

• Provide greater support for intra-regional (versus inter-regional) transportation.

• Encourage tighter links among transportation planning, policy, and programs and anti-sprawl and pro-urban planning.

• Facilitate improved regional coordination to support multiple transportation modes and programs and diverse trip purposes and needs.

• Develop transportation systems at the regional level to create positive economic impact, including through regional food systems.

• Consider USDA’s Community Food Projects Competitive Grants Program as a model to promote community- and region-based collaborative approaches to improve food access, market access to small-scale farmers, and affordable agri-food system transportation.79

4. The agri-food system reconfigured as a resource to reduce energy and transportation demands and related problems through the development of more local food systems and truly renewable fuels.

T r a n s p o r t a t i o n P o l i c i e s : O p p o r t u n i t i e s a n d B a r r i e r s

Many of the problems outlined in the first part of this paper are rapidly turning into emergencies—if they are not already emergencies. Their simultaneous occurrence presents something of a perfect storm for health and sustainability concerns. The upcoming authorization of the federal transportation bill offers a significant opportunity to make headway in addressing—and correcting— these problems. The crises related to rising incidence of obesity and diet-related diseases, climate change, and national energy and food security provide impetus to increase access to healthy foods as part of a preventive

approach to improve health, build localized food systems, reduce the energy intensity of the agri-food system, and help the agri-food system contribute to the creation of sustainable transportation systems.

Specific recommendations that link policies and programs to emerging problems are presented in table 4.

Notwithstanding the policy and programmatic opportunities outlined in table 4, those seeking to meet health goals within transportation legislation face many barriers to success. These are outlined below.

The most obvious barrier lies in the structure of transportation funding, legislation, and governance—especially at the federal level. The majority of transportation funds are allocated by formulas tied to modes and trip purposes; this makes it hard to achieve the goals outlined here within the existing structure of transportation policy and policymaking. The

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problem is that, at the national level, we fund and manage transportation programs primarily by mode, rather than by urgent societal needs or compelling national goals. We also allocate funding by state, making achievement of national goals even more difficult. This is further complicated by competition between donor and donee states (that is, states that send more gas taxes to the federal transportation budget than they receive in transportation funding, or vice versa), a situation made worse in the current recession because many of the donee states are in the hard-hit, former manufacturing belt of the Midwest. Moreover, we fund transportation through a myriad of other (non-Department of Transportation) agencies, including the departments of Agriculture (USDA) and Health and Human Services (HHS), leading to further fragmentation by sector. Such fragmentation of the program is the cause of many transportation-related problems experienced by communities and within metropolitan regions.

The problems posed by programmatic fragmentation suggest that addressing food- and health-related transportation problems, as recommended in this paper, could increase overall transportation inefficiency, if they are not coordinated well, that is, more silos are not the solution. Instead, the programs and policies recommended here must be tied to land use policies that reduce transportation demand, improve access and regional connectivity (regardless of trip mode or purpose), and improve coordination between transportation providers and the system as a whole. In addition, policy must prioritize regional food system transportation connectivity over national or international ones, support more energy- efficient and less polluting modes and vehicles, and more effectively use spare capacity in existing programs to support food access for low-income consumers and regional market access for small-scale farmers. This will require coordination across federal agencies such as Department of Transportation (DOT), USDA, and the Environmental Protection Agency (EPA).

Lack of precedence within transportation legislation for key asks: To date, there is little precedence for transportation legislation incorporating many of the policies recommended in this paper. Some policymakers may view the recommendation to increase transportation assistance to low-income households participating in federal nutrition programs as more appropriately falling within the agriculture law. USDA already funds transportation for rural providers of the Summer Food Service Program, which feeds low-income children.80 Similarly, the recommendation to prioritize agriculture for food over fuel may be viewed as falling under agriculture or energy, rather than transportation, even if most of the corn ethanol is destined for transportation-related uses.

Highways and roads (rather than access) as the primary orientation of transportation policy: Despite the progressive changes ushered in by ISTEA and its successors, transportation policy continues to be driven by a dominant orientation toward roads and highways, rather than toward multi-modality that provides access to goods, services, employment, healthy food, etc., thereby meeting community and regional needs and goals. Local land use decisions often follow, rather than drive, regional transportation planning by metropolitan planning organizations. Because land use decisions are local, more support is also needed than is available within the transportation legislation for transportation planning that effectively integrates land use and transportation to promote smart growth, that is, increase mixed-use, transit oriented development and neighborhood-based access to basic needs. Similarly, many advocates believe that transportation programs and funding tend to be designed to serve the interests of powerful groups—highway builders, auto manufacturers, and petroleum corporations— and that relationships of power and patronage, rather than systematically derived community needs, drive transportation policy.

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Impending revenue shortfalls from gas taxes: The expected shortfalls in the Highway Trust Fund present a challenge to funding new programs in the transportation legislation. Policymakers will need to find additional sources of funding that are adequate, sustainable, and fair. To this end, policies that improve health can result in savings in other areas, such as healthcare cost savings81 and can present new funding alternatives to fuel taxes. Such solutions go beyond the oft-suggested road and congestion pricing, both of which may further disadvantage the communities already at risk from current policies. More research is needed related to the net benefits and costs of transportation programs, including those suggested in this paper.

C o n v e r g e n c e O p p o r t u n i t i e s

Efforts to build sustainable food systems are inherently boundary spanning and require work across disciplines, sectors, professions, and geographic scales. The federal transportation law authorization process provides unique opportunities to build partnerships among interests in sustainable agri-food systems, smart growth, public health, community economic development, anti-poverty and social justice, labor, energy security, and climate change mitigation.

Coalitions that have emerged to advocate for transportation policy reform, such as the Transportation Equity Network, Transportation for America, Surface Transportation Policy Project, Complete Street Coalition, and Smart Growth America, are calling for proposals with broadly similar goals as those suggested herein, even if they are largely silent on agri-food issues addressed in this paper.82 Among the coalitions advocating for more sustainable agri-food systems or elements thereof are the Community Food Security Coalition, National Sustainable Agriculture Coalition, Food Research and Action Center, National Family Farm Coalition, and American Farmland Trust.83 Past efforts by these

groups to bring attention to sustainable agri- food issues within the transportation law have borne little, if any, fruit. We hope that the broad health rubric under which these papers are assembled will help coalesce the many groups mentioned above and attract new groups into the fold to add power to related transportation advocacy.

Additionally, the specific proposals made by this paper call for greater collaboration and coordination among various departments at the federal and state levels. For example, the proposals in this paper could benefit from partnerships among:

• DOT and USDA (and Department of Health and Human Services or the Department of Education when applicable) to provide transportation assistance to nutrition program participants in order to procure food, to improve neighborhood-based access to healthy foods through the use of transportation resources, and to support small-scale farmers’ efforts to bring products to local markets in underserved areas. This would increase participation in nutrition programs such as SNAP, WIC, Summer Food Service, and Farmers’ Market Nutrition; it would also increase the benefits of participation, improve health, and reduce healthcare costs.

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• DOT, USDA, and the Department of Labor to provide affordable transportation for urban and rural agri-food workers to access jobs, food, healthcare, and other vital services.

• DOT, USDA, the Department of Energy, and the EPA to support the development of more truly renewable energy sources in environmentally sensitive ways, including through the use of switchgrass and waste cooking oil; to support the development of fuel-efficient vehicle and transportation systems; and to discourage the use of food grains for producing fuel. Such cooperation is sorely needed to eliminate the competition between food and fuel.

• USDA, DOT, and the EPA to mitigate the problems caused by long-distance transportation of food in international trade.

C o n c l u s i o n

This paper presents four clear problems impacting the interaction between agri-food and transportation systems and suggests possible actions that could solve them. Some solutions can be addressed through transportation legislation, but clearly efforts need to extend to legislation that addresses energy, agriculture, child nutrition, labor, and health and human services.

Whatever the final mix of policies, successful efforts will result in affirmative responses to the following questions:

• Do neighborhoods provide convenient access for all residents to healthy foods and other basic goods and services? Do they allow food shopping without the need for a car?

• Beyond basic accessibility, do transportation policies and programs enhance local and regional quality of life through improved multi-modal access for all residents to the region’s resources and destinations and through reduced congestion?

• Does the regional transportation infrastructure support local food producers and processors to efficiently market to local consumers, in addition to national distribution channels?

• Do transportation policies support modes of freight, fuel choices, and vehicle designs such that air and water pollution, greenhouse gas emissions, and energy use are minimized?

• Are the currently externalized social, health, and environmental costs and increased risks posed by the global, industrial food system internalized in the price of food and transportation? Are associated costs and benefits fairly distributed across diverse income and racial groups in urban and rural areas?

• Does the agri-food system support transportation policies with renewable and efficient options for energy that reduce environmental impacts on air, water, and climate; minimize competition with food production; and reduce dependence on foreign sources for energy?

The transportation authorization process presents opportunities to break bad habits, extend positive developments from the past, and launch bold new initiatives that set us on a better course. Promising directions that build on positive aspects of SAFETEA-LU include, for example, correcting inequities in funding across states; providing dedicated funding to states to meet air quality requirements; and creating pilot programs to test alternative transportation funding schemes (which should be extended beyond tolling and road pricing schemes that may hurt the transportation-disadvantaged).

Clearly, other strategies are needed to eliminate disparities and problems caused by the current agri-food–transportation system linkage: extending transportation programs to increase access to healthy food and agri-food employment, reducing railroad concentration, ending competition between food and fuel, and more.

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Traff ic Injur y Prevention: ch. 8 A 21st-Centur y Approach L A R RY COHEN, M.S.W. Founder a nd Executive Director

JA NA NI SR IK A NTH A R AJA H, B. A . Progra m Coordinator

LESLIE MIKKELSEN, R .D., M.P.H. Ma nag ing Director, Prevention Institute, Oa kla nd, CA

ABSTRACT >> Traffic injuries and deaths exact a huge toll on our finances, our families, and our future. There are opportunities in the upcoming authorization of a new federal transportation bill to promote safety for all travelers. More broadly, safety for all travelers must become a national health and transportation priority. Advocates for injury prevention should collaborate with public health experts (specialists in chronic disease prevention, for example) and partners in other sectors (such as economic development) to promote a broad vision for health and equity in transportation policy.

The overarching policy goals that support traffic injury prevention are to: (1) promote the safe transportation of all travelers by improving infrastructure in communities; (2) reduce the number of vehicle miles traveled by promoting alternative modes of transportation, including public transportation, walking, and bicycling; and (3) protect drivers and passengers through continued improvements in vehicle safety, occupant protection, and road safety. This paper describes specific strategies to achieve these goals.

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Traffic Injury Prevention

CONTENTS

Introduction .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 133

Achievements in Traffic Injury Prevention . .. .. . 134

Prioritizing Traffic Injury Prevention for All Modes of Travel .. .. .. .. .. .. .. .. .. .. . 135

The Continuing Burden of Traffic Injuries and Deaths .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 137

Disparities in Traffic Injuries and Deaths . .. . 137

Other Populations with Greater Risk . .. .. .. . 139

Transportation Injury Prevention Strategies . .. . 139

Land Use .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 139

Road Design .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 140

Public Transportation .. .. .. .. .. .. .. .. .. .. .. . 140

Speed Limits .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 141

Impaired Driving Laws . .. .. .. .. .. .. .. .. .. .. . 141

Bicycle Helmet Laws . .. .. .. .. .. .. .. .. .. .. .. . 141

Vehicle Design Standards .. .. .. .. .. .. .. .. .. . 142

Seat Belt Laws. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 142

Motorcycle Safety Laws . .. .. .. .. .. .. .. .. .. . 142

Child Safety Seat Laws .. .. .. .. .. .. .. .. .. .. . 142

Graduated Driver Licensing .. .. .. .. .. .. .. .. . 143

Truck Regulations.. .. .. .. .. .. .. .. .. .. .. .. .. . 143

Challenges to and Opportunities in Traffic Injury Prevention Policy .. .. .. .. .. .. .. .. .. .. . 143

Conclusion.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 145

LIST OF ILLUSTRATIONS

Tables

1. Traffic Injury Prevention Highlights . .. .. .. .. . 134

2. The Haddon Matrix (with examples) . .. .. .. . 135

3. The Spectrum of Prevention.. .. .. .. .. .. .. .. . 136

4. SAFETEA-LU Programs That Support Injury Prevention. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 144

5. Federal and State Government Support for Traffic Injury Prevention .. .. .. .. .. .. .. .. . 145

Graphs

1. U.S. Traffic Fatalities by VMT and Per 10,000 Population .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . 138

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i n t r o d u c t i o n

While getting off a streetcar in New York City on September 9, 1899, Henry Hale Bliss was struck by an electric-powered taxicab and suffered injuries so severe—his skull and chest were crushed—that he died the next day. Bliss thus became the first person killed by a motor vehicle in the United States. The taxicab driver was arrested and charged with manslaughter but was later acquitted on the grounds that the death was unintentional. While the legal proceedings considered where responsibility for Bliss’s death lay, there was no discussion of what could have been done to prevent the crash.1

What was unprecedented in 1899 is unremarkable today. Traffic crashes are the leading cause of death in the United States for people ages one to 34,2 and by 2020, traffic- related deaths will be the third-leading cause of death worldwide.3

Traffic injuries and deaths exact an unnecessary economic toll. In 2000, motor vehicle crashes in the United States cost $230.6 billion in emergency services, medical treatment, legal procedures, insurance administration, property damage, lost workers’ productivity, and travel delays.4 That figure represents 2.3 percent of the nation’s gross domestic product.5

In 1900, motor vehicle travel was considered a novelty, and the risks to health and safety were largely overlooked. Subsequent improvements in manufacturing made cars more affordable and available, benefiting commerce, communications, and personal mobility. In 1900, an estimated 8,000 automobiles were registered in the United States. By 1950 there were 50 million, and by 2001, more than 230 million vehicles and 193 million licensed drivers were on the road.6 The current number of cars and drivers, along with the extensive networks of roads and highways around the nation, would have been inconceivable in 1899 but are accepted as norms of transportation today. Traffic injuries and deaths are frequently

considered uncontrollable aspects of America’s love affair with the car. This may account for the fact that traffic crashes are too often ignored as a major contributor of premature death and disability, the consequence of which is a missed opportunity to improve health and reduce costs.

In light of ever-shrinking federal, state, and local budgets, the authorization of a new federal surface transportation bill is an opportunity to structure transportation programs to reduce the burden on the healthcare system, the economy, and society at large. National and international experts on traffic injury prevention, including the U.S. National Highway Traffic Safety Administration (NHTSA), the U.S. Centers for Disease Control and Prevention (CDC), and the World Health Organization, increasingly reject the notion that traffic injuries are the inevitable price we pay for modern travel.7

Many transportation policies and practices that lead to traffic injuries also contribute to chronic diseases that result from physical inactivity, poor air quality, and other environmental factors that are the consequences of our car culture. Linkages between injury prevention and other health fields should be developed to foster a national transportation strategy that forges solutions to these intersecting problems. Such strategic partnerships can help catalyze a revamped national transportation strategy that is central to policymakers’ efforts to address a range of critical challenges: the economy, climate change, the limited supply of fossil fuels, and soaring healthcare costs. A transportation agenda that emphasizes health, equity, environmental protection, jobs, and an improved quality of life requires collaboration from all sectors.

The overarching policy goals that support traffic injury prevention are to: (1) promote the safe transportation of all travelers by improving the physical infrastructure in communities; (2) reduce vehicle miles traveled by promoting alternative modes of transportation, including public transportation, walking, and bicycling;

Traffic Injury Prevention H

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and (3) protect drivers and passengers through continued improvements in vehicle safety, occupant protection, and road safety.

a c h i e v e m e n t s i n T r a f f i c i nj u r y P r e v e n t i o n

While it is impossible to forecast the exact circumstances of traffic crashes, these incidents are not isolated events but are both predictable and preventable. The news and entertainment media often speak of traffic “accidents,” but the word implies—erroneously—that the event is happenstance and arbitrary.

Dr. William Haddon, Jr., the first director of the National Highway Safety Bureau, which in 1970 became the National Highway Traffic Safety Administration, brought an emphasis on injury prevention to the government’s transportation policies and practices. Dr. Haddon is also recognized for developing the Haddon Matrix (see table 2).

By deconstructing the sequence of events contributing to traffic-related injuries, Dr. Haddon developed effective strategies to prevent crashes and limit injuries. By integrating education, legislation, and enforcement, health and safety advocates as well as government officials have bolstered Dr. Haddon’s research by requiring the

1923: Garrett Augustus Morgan, an African American traffic safety innovator, invents the modern traffic signal to reduce the high risk of collisions he observed on roadways shared by horse- drawn buggies, pedestrians, and automobiles.

1924: President Herbert Hoover convenes the National Conference on Street and Highway Safety, marking the first presidential initiative to bring attention to traffic safety.

1964: Ralph Nader’s book Unsafe at Any Speed: The Designed-In Dangers of the American Automobile is published—another milestone that attributes injuries not just to driver error but also to vehicle design flaws and describes auto executives’ resistance to vehicle safety features, most notably General Motors’ Chevrolet Corvair. Following the book’s release, public pressure mounts, forcing President Lyndon Johnson to call for tighter regulation.

1966: President Johnson signs The Traffic and Motor Vehicle Safety Act and The Highway Safety Act into law, authorizing the National Highway Safety Bureau (now the National Highway Traffic Safety Administration (NHTSA)) to set vehicle and road safety standards and to fund research and programs on traffic safety.

1967: The U.S. Department of Transportation (DOT) is created to oversee transportation issues, including traffic safety (NHTSA is housed within the DOT).

1979: Healthy People – The Surgeon General’s Report on Health Promotion and Disease Prevention is released and is the first call to attention that traffic injury prevention should be part of the country’s public health agenda.

1985: Under the direction of Congress, the National Academy of Sciences releases the report Injury in America which recommends a major national program of research to address injury as a health problem.

1986: Congress creates a center for injury research, surveillance, and education within the Centers for Disease Control and Prevention (CDC), now called the National Center for Injury Prevention and Control.

Table 1. Traffic Injury Prevention Highlights

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use of seat belts, infant car seats, and motorcycle helmets; implementing safe driving laws; and toughening drunk driving laws. The Spectrum of Prevention (table 3) provides a framework for developing comprehensive approaches to preventing injuries.8

P r i o r i t i z i n g T r a f f i c i nj u r y P r e v e n t i o n f o r All M o d e s o f T r a v e l

Diversifying transportation options is emerging as a top priority for policymakers. Preventing injuries, improving air quality, encouraging physical activity, and promoting healthier lifestyles can be addressed by reducing miles traveled via automobile and increasing the use of public transportation, bicycling, and walking. This is no easy feat in a country where the car is king and where driving is central to our identity. Advertising campaigns that associate cars with the desire for affluence and independence reinforce the societal link between mobility and upward mobility. The car has historically been promoted as an instrument of sexuality and

power; it’s the guy with the “sexy car” who gets the girl. Driving is a rite of passage that marks our lives nearly from cradle to grave. It is an exuberant transition for a teen when he or she gets a driver’s license and a moment of loss or fear for the adult who must surrender the car keys. Cars will remain the major source of transportation and continue to pose increasing risks unless other safe and convenient forms of transportation are made generally available to the public.

Building transportation systems for all modes of travel promotes equity. Robert Moses, New York City’s storied planner known as the builder of the modern metropolis, reportedly constructed the overpasses on his Long Island parkways too low to accommodate buses as a means of preventing low-income residents of the city— especially blacks and Latinos—from visiting the beaches and parks.9 Thus, parkways like these served as tools for segregation and economic discrimination by putting suburban communities off limits as places of employment and recreation for someone from the inner city who had no car. Decades later, these thoroughfares

Host Agent/Equipment Physical Environment

Social Environment

Pre-Event Drinking Alcohol ignition lock

Alcohol outlets Drinking norms

Event Seat belts and Car seats

Airbags Safety rails Speeding

Post-Event Emergency phones Healthcare access

The Haddon Matrix delineates factors along the timeline of a traffic incident (pre-event through post- event) with four other elements involved in the occurrence of injury (host [e.g., driver], agent [e.g., vehicle], physical environment, and social environment). Prevention activities can be developed within any of these elements. For example, bicycle lanes separate bicyclists from motorized travelers and can thus prevent a crash in the first place. When a crash does occur, if the bicyclist is wearing a helmet, severe head trauma can be prevented. When trauma occurs, a fast and efficient emergency medical system and healthcare must be in place to treat the injuries and prevent death.

Table 2. The Haddon Matrix (with examples)

stand as monuments to transportation policies that divided the country rather than healed its divisions.

Generally, the safety of public transportation and non-motorized travel (i.e., bicycling and walking) has received relatively little federal support, yet communities with diverse transportation options have been shown to have fewer traffic injuries and deaths.10 Contrary to the widespread belief that increased bicycle

and foot traffic will lead to more cyclist and pedestrian injuries and deaths, increasing the numbers of non-motorized travelers may actually make walking and bicycling safer.11 There is also evidence that residents of transit oriented communities have lower per capita traffic fatality rates.12

Germany and the Netherlands illustrate the benefits of government support for safety improvements for pedestrians and bicyclists.

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Levels of the Spectrum Description

Influencing policy and legislation Developing strategies to change laws and policies to influence outcomes in health, education, and justice

Changing organizational practices Adopting regulations and norms to improve health and safety; creating new models

Fostering coalitions and networks Bringing together groups and individuals for broader goals and greater impact

Educating providers Informing providers who will transmit skills and knowledge to others

Promoting community education Reaching groups of people with information and resources to promote health and safety

Strengthening individual knowledge and skills Enhancing an individual’s ability to prevent injury or illness

Table 3. The Spectrum of Prevention The Spectrum of Prevention* is a tool to guide development of comprehensive strategies that encourage movement beyond the educational or “individual skill-building” approach to address broader environmental and systems-level issues. The Spectrum builds on the Haddon Matrix by providing a method for developing strategies to address traffic safety that are beyond the incident itself and approaches that focus on the individual. The tool has been used across injury fields to integrate individual-oriented efforts with systems change to have the greatest overall effect.

Successful injury prevention strategies have been multifaceted and engaged efforts at multiple levels of the Spectrum of Prevention. In fact, traffic injury prevention has emerged as a model example of prevention.

*The Spectrum of Prevention was originally developed by Larry Cohen in 1983 while working as director of prevention programs at the Contra Costa County Health Department. For application of the Spectrum of Prevention to injury prevention: T. Christoffel and S.S. Gallagher, Injury Prevention and Public Health (Sudbury, MA: Jones and Bartlett Publishers, Inc., 2006).

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Per mile and per trip walked, Americans are roughly three times more likely to get killed than German pedestrians and more than six times as likely as Dutch pedestrians. Per mile and per trip cycled, Americans are twice as likely to be killed as German cyclists and more than three times as likely as Dutch cyclists.13 Furthermore, pedestrian and bicyclist deaths have declined far more in both countries than in the United States. The Netherlands and Germany have invested heavily in high-quality streetscapes for safe walking and bicycling, making non- motorized travel a norm compared to passenger vehicle travel. The United States has seen virtually the opposite—an interplay of land use, housing, and transportation patterns that have promoted low-density sprawl, high-speed roadways, narrow or no sidewalks, unsafe or no crosswalks, the absence of bicycle lanes, and inaccessible or no public transportation at all. All this makes alternatives to cars and driving not only impractical but also less safe.

With its promise of convenience and freedom, the car still has a strong allure. But a growing number of Americans say they want to drive less and walk, bicycle, and use public transportation more. Advocates can use this desire as momentum to raise public awareness about the benefits of these travel options that are good for better health, for the environment, and for the family budget.

T h e C o n t i n u i n g B u r d e n o f T r a f f i c i nj u r i e s a n d D e a t h s

While there have been reductions in death rates per vehicle mile traveled (VMT) over the past four decades, the declines are far less when deaths are measured per capita because Americans drive more than ever (see graph 1).14

In 2007, traffic crashes accounted for 41,059 deaths,15 1,755,247 years of lost life,16 and 2.5 million nonfatal injuries.17 Bicyclists and pedestrians have a disproportionately higher risk

of death in a traffic crash compared to vehicle occupants.18 This greater vulnerability stems from the fact that bicyclists and pedestrians do not have the buffers and protective measures that vehicles offer drivers and passengers. An analysis of 1995 National Household Travel Survey data indicates that the rate of pedestrian fatalities is 36 times higher than car-occupant fatalities per mile traveled, and bicycling fatalities are 11 times higher.19

In 2007, there were 5,504 non-motorized fatalities.20 While walking and bicycling accounted for only 9.5 percent of all trips in 2001, non-motorized fatalities accounted for more than 13 percent of traffic fatalities nationwide.21 Pedestrian fatalities accounted for 84.5 percent of all non-motorized fatalities, bicyclist fatalities accounted for 12.7 percent, and the remaining 2.8 percent were skateboard riders, roller skaters, etc.22

Contrary to the belief that these statistics make a favorable case for continuing to travel exclusively by car, they highlight the lack of infrastructure to support safe non-motorized travel alongside motorized travel. By implementing strategies that reduce the amount of exposure non- motorized travelers have to moving vehicles and reducing the number of cars on the road, it is possible to dually promote alternative modes of transportation and mechanisms to improve the safety of these alternative modes.

Disparities in Traffic Injuries and Deaths

Traffic injuries and deaths are major health concerns for everyone but more so among society’s most vulnerable populations. National data from the Centers for Disease Control and Prevention (CDC) indicate that Native Americans are 1.5 times more likely to die from traffic crashes than other Americans.23 Data collection methods inhibit clarity about the disparate impact of traffic crashes on other racial/ethnic groups, and there is a dearth of data that looks at disparities by income. This is due to the fact

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that the primary source of data comes from police reports, which do not collect race and ethnicity data. However, some studies seem to indicate the existence of such disparities across race/ethnicity. Between 1990 and 1998, death rates from motor vehicle crashes declined least for African Americans and Native Americans, who also continued to have higher age-adjusted death rates for motor vehicle crashes than any other racial or ethnic group.24 An analysis of North Carolina’s licensed drivers, ages 16 to 24, puts the fatality rate for Latinos at nearly 1.5 times greater than that for whites.25

Pedestrian safety is particularly important for populations that have less access to cars

and rely more on walking for transportation. For example, African Americans make up approximately 12 percent of the U.S. population, but they account for 20 percent of pedestrian deaths.26 Another CDC analysis suggests that the pedestrian fatality rate for Latino men in the Atlanta metropolitan statistical area was six times greater than that for whites between 1994 and 1998.27 While Latinos made up 28 percent of the population in Orange County, CA, they accounted for 40 percent of all pedestrian injuries and 43 percent of pedestrian deaths in 1999, according to a study done by the Los Angeles Times.28

While data comparing traffic injury rates by

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1960 1965 1970 1975

YEAR

R A

T E

Graph 1: US Traffic Fatalities by VMT and per 10,000 population

8-1

1980

Per 100 Million Vehicle-Miles Traveled

Per 10,000 Population

1985 1990 1995 2000

5.06

5.3

4.74

3.35 3.35

2.47

2.08

1.73 1.582.03

2.46 2.59

2.07

2.25

1.84 1.79

1.59 1.53

Graph 1. U.S. Traffic Fatalities by VMT and Per 10,000 Population

Primary data collected by the Bureau of Transportation Statistics (2000), available at http://www.bts.gov/ publications/nts/index.html. This graph was originally compiled by Todd Litman, Victoria Transport Policy Institute.

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income level are not readily available, people with low incomes may be more vulnerable to traffic injuries and deaths. Low-income often means less access to products that enhance safety, such as newer, safer vehicles or child safety seats; moreover, low-income communities have fewer resources for safe roads and sidewalks, crosswalks, lighting, and traffic enforcement.

Other Populations with Greater risk

Across all ethnic groups, more males than females die from motor vehicle crashes.29 Compared to females, males have lower rates of seat belt use; and are more likely to be involved in alcohol-related crashes and be alcohol- impaired (whether as drivers, passengers, pedestrians, or cyclists) at the time of the incident.30 Drivers under the age of 25 are also more likely to be involved in fatal traffic crashes than any other age group.31

Additionally, driving skills decline with age; with older adults representing the fastest-growing segment of the U.S. population, protecting them from injuries caused by collision should be a top priority on any health and safety agenda. Although older motorists drive fewer miles, they are more likely to be killed or injured in a crash of the same severity compared to other age groups.32 Not only are older drivers typically frailer than others, they also tend to drive older cars, which typically have fewer safety features.33 Even if older drivers in the future drive at the same modest rates as the current elder population, their growing numbers mean that total miles driven by people ages 65 and older would increase 50 percent by 2020 and more than double by 2040.34 While strategies can focus on mitigating risks for older drivers, the best safety approach is to provide safe pedestrian facilities and accessible, affordable public transportation.

T r a n s p o r t a t i o n i nj u r y P r e v e n t i o n S t r a t e g i e s

Transportation safety practices and policies should be integrated into all relevant agency agendas and across all levels of government. The pending authorization of the federal transportation bill, the Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (SAFETEA-LU), is an opportunity to expand programs that have led to improvements in health and safety. Federal policy has historically succeeded in establishing national standards through a carrot-and- stick approach, encouraging state and local governments to comply with federal targets such as those on seat belt use or car seats by dangling federal funds as the carrot. The federal government thus effectively leverages its resources and expands safety targets.

Land Use

Deciding the best uses for our land has not traditionally been included among injury prevention strategies. However, land use issues strongly influence how we travel, which is a key component in determining our risk for getting hurt in a crash. Zoning laws and general plans influence population density within a community, how streets connect, and the distance between homes and key institutions such as schools and workplaces. These factors affect the feasibility, appeal, and safety of walking, bicycling, or using public transportation to get where we need to go. Smart growth strategies—which encourage compact development combining housing, shops, businesses, and parks—reduce our reliance on car travel, creating communities that are safer, more convenient, and more inclusive of low- income residents, older adults, and people with disabilities. One approach that utilizes smart growth elements is transit oriented development (TOD), which develops compact major activity centers around public transportation hubs.

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By limiting the number of alcohol outlets, zoning laws can also help tackle the problem of impaired driving.

road Design

Road design influences driving behavior and is an important determinant of bicyclists’ and pedestrians’ exposure to traffic, and thus, risk of injury and death.

Road design strategies should emphasize the safety of both motorized and non-motorized travelers. Many road and street improvements can accomplish this: clear road markings and signage to designate crosswalks, bicycle lanes, demarcations between vehicle lanes, and adequate lighting alongside the road to ensure good visibility.35 Additionally, sidewalks, bulb- outs at street corners (which shorten crossing distances and slow the speed of traffic), curb cuts, and separate pathways for pedestrians and bicyclists can limit motor vehicle crashes. Road design strategies should also pay particular attention to improving safe access and mobility for older adults and people with disabilities, beyond Americans with Disabilities Act (ADA) street design requirements.36

Because the risk of death and severe injury in traffic crashes has a direct correlation to speed37 and because speeding is a factor in one-third of all crashes, environmental changes to encourage slower speeds on our roads are vital. Traffic calming, design approaches that acknowledge the relationship between environmental design and behavioral norms, is one of the most important injury prevention strategies in recent decades. Reducing lane widths, curving streets, and adding trees enhance the roadway experience and lead to slower, safer driving. The construction of raised islands, medians, and roundabouts in the roadway also reduces traffic speeds.

These design improvements must reach all neighborhoods. Funds should especially be targeted to low-income communities, where

residents are more likely to walk or bicycle for transportation.

Public Transportation

Safe, efficient, and easily accessible public transportation systems will reduce the frequency of injury and death caused by passenger vehicles and truck traffic. Public transportation systems can solve a number of transportation issues simultaneously, e.g., provide equitable access for vulnerable populations such as older adults, people with disabilities, and low-income populations as well as improve air quality by having fewer vehicles on the road.

Funding should be increased for public transportation improvements and expansions. Public transportation must be fast and affordable; it must link people with the places they need to go. Americans will not give up their cars in significant numbers without realistic public transportation alternatives, including safe routes for walking or bicycling to transit stops. Transit operators can help by providing bicycle lockers and racks, elevators, adequate lighting, and security guards or other safety monitors. Road design features such as crosswalks, sidewalks, and conveniently located transit stops (bus stops and transit lines positioned for easy pedestrian access) are also beneficial. Public transportation accessibility and safety will become increasingly important for older Americans as the U.S. population ages.

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Speed Limits

As noted earlier, speeding is an important factor in traffic injury and death. The 55-mile- per-hour highway speed limit, established by Congress in 1974 and later adopted by all states, was repealed in 1995. When speed limits are increased on major highways, motorists tend to drive faster on secondary roadways, a process known as “speed adaptation.”38 Reducing speed saves not only lives but also energy because speeding reduces fuel efficiency.

Automobile advertising tends to glorify high- speed driving and risky driving behaviors.39 Getting drivers to slow down may also require changes in automobile marketing practices.

Impaired Driving Laws

Alcohol-related motor vehicle crashes kill someone in the United States every 39 minutes.40 Several studies reveal that when alcohol plays a role, crashes tend to be much more severe.41 Strategies that are effective at preventing impaired driving include:

• Maintain strict enforcement of 0.08 percent blood alcohol content (BAC) laws.42

• Consistently enforce the national minimum legal drinking age law and adopt zero tolerance laws (i.e., revoking a driver’s license if impaired) for drivers younger than 21 in all states.43

• Establish sobriety checkpoints,44 coupled with extensive media campaigns to increase public awareness.

• Install alcohol ignition interlocks in vehicles.45

A number of impaired driving prevention strategies focus on organizational interventions such as alcohol licensing, alcohol availability, alcohol bans, reducing alcohol outlet density and server interventions.46 Other effective

strategies include economic interventions such as raising state and federal alcohol excise taxes and reducing the number of alcohol retailers.47

It must be noted that there are higher densities of alcohol retail in low-income communities and communities of color; consequently, strategies should address the saturation of liquor stores in these communities rather than relying exclusively on modifying consumers’ behavior.48

Driver or pedestrian alcohol use was reported in 47 percent of the traffic crashes that resulted in pedestrian fatalities, with pedestrians more likely to be intoxicated than drivers.49 As rates of driving continue to decline and other modes become more prevalent, specific solutions must be explored for preventing alcohol-related traffic crashes among bicyclists and pedestrians.

Bicycle Helmet Laws

More than a half-million people are treated annually in hospital emergency rooms in the United States for bicycle-related injuries.50 Approximately 60 percent of bicycle deaths involve a head injury; research indicates that a helmet can reduce the risk of head injury by up to 85 percent.51 In 1999, the U.S. Consumer Product Safety Commission issued a mandatory safety standard for bicycle helmets.52 Twenty- one states and the District of Columbia have helmet laws but require use only among young riders (often under the age of 16).53 Little political will exists at the federal and state levels to legislate helmets—despite their lifesaving value—for a greater percentage of bicyclists. Municipal ordinances remain the most promising policy approach.

Schools, businesses, and government agencies can also mandate that children and employees wear bicycle helmets when riding to and from school or work. Schools and offices can disseminate information about their importance and value. Stores that sell bicycles and helmets can also be productive partners in this effort, offering reduced-price or free helmets and

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distributing information about their proper use and importance in preventing injuries or deaths.

Vehicle Design Standards

Vehicle design standards play a key role in increasing safety for drivers and their passengers and for bicyclists and pedestrians. Examples include improved braking systems, bumpers and external frame requirements, airbags, shatter- resistant windshields, shock-absorbing steering wheels, and automatic seat belts.

Seat Belt Laws

It’s been proven that seat belts save lives. Yet the United States ranks among the lowest nations in the developed world for seat belt usage—an 83 percent daytime use rate.54 Every state except New Hampshire has seat belt use laws, but only 25 states and the District of Columbia allow primary enforcement,55 which permits officers to ticket a driver for not wearing a seat belt without necessitating another traffic violation. Primary enforcement has been associated with lower fatality rates56; in states with such laws, seat belt use is typically 10 percent to 15 percent higher.57 SAFETEA-LU provided more than $500 million in incentive grant money to encourage states to pass primary enforcement seat belt laws, but only a few states have done so. In addition to incentives, federal transportation dollars should be withheld from states that do not adopt such laws. There should also be safeguards for uniform enforcement of primary seat belt laws to address the concern from many opponents that traffic laws have a history of discriminatory enforcement, with targeting of certain racial and ethnic groups.58 The National Organization of Black Law Enforcement Executives, the nation’s leading group of minority law enforcement executives, has recognized that large numbers of African Americans die because they don’t use seat belts or child safety seats (discussed below); it supports primary enforcement laws covering both strategies.

Motorcycle Helmet Laws

Motorcycles make up more than three percent of registered vehicles and only 0.4 percent of vehicle miles traveled but 11 percent of traffic fatalities.59 Helmet use is the most effective measure to protect motorcyclists. Although helmets do not prevent crashes, they offer significant protection against head and brain injuries. States with all-rider helmet laws have a use rate of nearly 100 percent. Twenty-six states have laws that cover only some riders (e.g., up to age 18), which are nearly impossible to enforce; the trend now is toward repealing such laws rather than enacting them. All states should be required to enact an all-rider motorcycle helmet law, and grant funding should provide incentives for promoting motorcyclists’ safety.

Child Safety Seat Laws

Child safety seats reduce the risk of death in vehicles by 71 percent for infants and by 54 percent for children ages one to four years.60 For the past 20 years, child safety seats have been tremendously successful with nearly 100 percent compliance. The CDC Guide to Community Preventive Services presents strong evidence that child safety seat laws, the distribution of safety seats, and education and enforcement

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campaigns are effective in increasing child safety seat use.61

But more work needs to be done to protect child occupants who remain at heightened risk. The next priority: enacting booster seat laws for children up to age eight, as recommended by the NHTSA. At present, 42 states and the District of Columbia have such laws.62

Lack of access to affordable child safety seats makes their use lower in rural and low-income communities.63 Research reveals, however, that 95 percent of low-income families who own a child safety seat use it.64 The federal surface transportation bill should help low-income families to purchase booster seats.

Graduated Driver Licensing

Graduated driver licensing (GDL) laws, which require newly licensed youth to “graduate” to full licensing, allow young people to practice before assuming the full rights and responsibilities of driving. Research suggests that comprehensive GDL programs can reduce fatal crashes among 16-year-old drivers by up to 38 percent.65

Truck regulations

Although this paper emphasizes safety for passenger vehicles, truck safety is another important area for injury prevention. Strategies include improving built-in truck safety features, regular inspections, restrictions on hours operators can drive without a break, and regulations limiting load size. Federal transportation policy can make roads safer for everyone by supporting expanded rail transport and reducing reliance on trucks.

C h a l l e n g e s t o a n d O p p o r t u n i t i e s i n T r a f f i c i nj u r y P r e v e n t i o n P o l i c y

The current federal transportation bill, SAFETEA- LU, includes programs that advance both health and safety. These programs can benefit greatly from additional funding in the pending authorization of a new bill and an emphasis on expanding best practices and promoting equity. Funding should be prioritized to ensure that injury prevention efforts are designed to benefit the most vulnerable communities. Notably, the Highway Safety Improvement Program (HSIP) was an unprecedented attempt to consolidate safety efforts. Other successes that should be expanded: the Safe Routes to School (SRTS) program, the Transportation Enhancements (TE) program, and The Non-Motorized Transportation Pilot program (see table 4 for details about these programs).

A well-thought-out federal health and safety framework for transportation policy and practice must be reflected at the local level as well. States and locales are the crucibles of change; they do most of the transportation planning and implementation. Yet the quality of safety efforts remains uneven. Without a sufficient federal mandate, some states ignore the imperative for traffic safety, and others have not implemented measures to their greatest potential. Federal mandates should be flexible so locales can choose strategies that best respond to community conditions. HSIP’s mandatory strategic highway safety plan process, which requires states to develop safety priorities and targets in order to receive safety funds from the program, is an opportunity for this type of coordinated traffic safety approach.

The federal government should also require states to include in their transportation planning a wide range of voices, including groups concerned with health and community well-being. An important model for this type of multi-sector collaboration is the Safe

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Program Amount Description

Highway Safety Improvement Program (HSIP)

$5 billion over 5 years

Achieves a significant reduction in traffic fatalities and serious injuries on all public roads by implementing infrastructure- related highway safety improvements. A portion of these funds can be used for safe behavior enhancement programs.

Safe Routes to School (SRTS)

$612 million over 5 years

Funds infrastructure and programming projects to encourage children and their accompanying guardians to walk or bicycle safely to school every day. This program is one of a few existing models that jointly focuses on increasing rates of walking and bicycling and improving safety conditions for non-motorized travelers. It should be authorized with greater investment.

The Non- Motorized Transportation Pilot Program

$125 million over 5 years

Funds infrastructure and programming in four communities to increase bicycling and walking. Expanding it to fund more communities and conduct further evaluation is the next step. Its authorization should require funded communities to include safety goals in their transportation plans so that every new project focuses on reducing traffic injuries and deaths among bicyclists and pedestrians as well as infrastructure improvements that improve safety for all.

Transportation Enhancements (TE)

$3.5 billion Funds bicycle and pedestrian trails and rail-trail conversions, which include safety improvements to these environments; these conversions take up about 55% of TE funding. It is a 10% set-aside from another major program in SAFETEA-LU, the Surface Transportation Program. This is the largest source of federal funds for non-motorized projects and should be increased to reflect growing demand.

* Funds for agencies under the U.S. Department of Transportation that address traffic safety and for the State and Community Highway Safety Grant Program, described in table 5, were also authorized under SAFETEA-LU.

Table 4. SAFETEA-LU Programs That Support Injury Prevention*

Communities Program, funded through Section 402 transportation funds (described in table 5).

Moreover, the authorization should provide states with data, training, and technical assistance to ensure that plans are well tailored to community needs, that they effectively reach low-income communities and communities of color, and that they include a diverse and comprehensive set of strategies. HSIP currently focuses almost exclusively on the safety of

motorized travelers. To equitably distribute transportation safety funds, several advocates are calling for a “Fair Share for Safety” provision, requiring states to spend a portion of their funds, proportional to the percentage of non-motorized travelers’ deaths, on walking and bicycling safety projects.

A complete streets policy—which emphasizes safe, easy, and efficient mobility for all travelers through connected networks of roads, paths,

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• Federal: The U.S. Department of Transportation (DOT) is the agency responsible for the federal transportation system. One of its primary charges is to ensure the safety and security of the traveling public; safety is among its top three priorities. The National Highway Traffic Safety Administration (NHTSA), the Federal Highway Administration (FHWA), and the Federal Motor Carrier Safety Administration (FMCSA) are the three major agencies under the DOT umbrella that provide national leadership and support on transportation safety issues. The Federal Transit Administration (FTA) addresses safety related to public transportation. Congress has also created the National Center for Injury Prevention and Control (NCIP) within the Centers for Disease Control and Prevention (CDC); it funds injury research, provides grants to state and local health agencies, and works to increase awareness about injury prevention.

• State: In addition to the federal agencies and programs dedicated to traffic safety, states also have dedicated funding sources to improve traffic safety. This support comes primarily through Section 402 State and Community Highway Safety Grant Program, first authorized by the Highway Safety Act of 1966 and reauthorized in succeeding federal surface transportation bills. Most state public health departments also support ongoing injury prevention and control programs.

Table 5. Federal and State Government Support for Traffic Injury Prevention

and trails—is not included in SAFETEA-LU, but should be incorporated into the new federal transportation bill.66

Another policy issue that requires attention is deciding the appropriate mechanisms to distribute funds in order to encourage projects that promote safety and convenience by modes other than passenger vehicle travel. The new federal transportation bill should provide alternatives to the current funding formula, which bases allocations on a state’s total number of vehicle miles traveled. One option is to link transportation funds to land use patterns that encourage smart growth development and discourage development patterns that require passenger vehicles for the majority of local travel.

C o n c l u s i o n

Twenty-first century transportation policy must reflect a new vision of mobility and accessibility. Safe travel for all road users and broader considerations of health and equity must be at the center of policy and practice, which would be a difficult task even without the entrenched interests invested in maintaining the status quo. It requires a strong, committed partnership that spans multiple sectors and disciplines.

Building this partnership requires moving beyond past differences and historical positions. Diverse groups must recognize their common interest in opposing policies centered on building more roads, highways, and sprawling developments at the expense of air quality, bicycle and pedestrian access, smart growth, and safety for everyone.

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Author Biographies

T h e T r a n s p o r t a t i o n P r e s c r i p t i o n : a S u m m a r y o f f i n d i n g s a n d a f r a m e w o r k f o r a c t i o n

&

Chapter 1: Health Effects of Transportation Policy

Judith Bell, M.P.A., is the President of PolicyLink in Oakland, CA, and oversees policy development, strategic planning, program implementation, and policy campaign strategy; she leads projects focused on equitable development, such as the fair distribution of affordable housing, equity in public investment, and community strategies to improve health. Bell is a frequent speaker, trainer, and consultant on advocacy strategy. Her work at PolicyLink includes access to healthy foods, transportation, and infrastructure investment. In addition, Bell leads PolicyLink work with the Convergence Partnership, a multi-foundation initiative to support equity-focused efforts to advance policy and environmental changes for healthy people and healthy places. For more information: http://www.policylink.org/JudithBell.

Larry Cohen, M.S.W., is Founder and Executive Director of Prevention Institute, a nonprofit national center that moves beyond approaches that target individuals to create systematic, comprehensive strategies that alter the conditions that impact community health. With an emphasis on health equity, Cohen has led many successful public health efforts at the local, state, and federal levels on injury and violence prevention, mental health, traffic safety, and food- and physical activity-related chronic disease prevention. Prior to founding Prevention Institute in Oakland, CA, Cohen participated in passing the nation’s first multi-city smoking ban. He established the Food and Nutrition Policy Consortium, which catalyzed the nation’s food labeling law. Cohen also helped shape strategy to secure passage of bicycle and motorcycle helmet laws and to strengthen child and adult passenger restraint laws. For more information: http://www.preventioninstitute.org/larry.html.

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Chapter 2: Transportation Authorization 101: A Backgrounder

Susan Polan, Ph.D., is the Associate Executive Director, Public Affairs and Advocacy, for the American Public Health Association in Washington, DC. In this capacity, Polan oversees APHA’s government relations, communications, membership, affiliate affairs, and component affairs departments. She has more than 15 years of experience in health and public health issues. Her doctorate is in Social Ecology from the University of California, Irvine. For more information: http://www.apha.org/about/ board/aphastaff/biopolan.htm.

Tracy Kolian, M.P.H., is a Senior Policy Analyst in the Public Health Policy Center of the American Public Health Association and is responsible for the association’s environmental public health policy issues and initiatives. She holds a bachelor’s degree in Toxicology from Northeastern University and a master’s degree in environmental health from Tulane University, School of Public Health and Tropical Medicine. For more information: http://www.apha.org/ about/board/aphastaff/biokolian.htm.

Shireen Malekafzali, M.P.H., is a Senior Associate at PolicyLink, a national research and action institute dedicated to social and economic equity. She works across topics to create environmental and policy changes aimed at promoting health and equity. Shireen provides research, technical assistance, training, and policy development support to collaborative efforts intended to create health-enabling environments for all, regardless of race, class, or gender. Her expertise focuses at the intersection of health, equity, and the built environment. For more information: http://www.policylink.org/ ShireenMalekafzali.

T r a n s p o r t a t i o n C h o i c e s

Chapter 3: Public Transportation and Health

Todd Litman, M.E.S., is Founder and Executive Director of the Victoria Transport Policy Institute, an independent research organization in Victoria, British Columbia, that is dedicated to developing innovative solutions to transport problems. His work helps expand the range of impacts and options considered in transportation decision making, improve evaluation methods, and make specialized technical concepts accessible to a larger audience. His research is used worldwide in transport planning and policy analysis. For more information: http://www.vtpi.org/documents/ resume.pdf.

Chapter 4: Walking, Bicycling and Health

Susan Handy, Ph.D., is Professor of Environmental Science and Policy and Director of the Sustainable Transportation Center at the University of California, Davis. Her research focuses on the impact of land use on travel behavior, and she is internationally known for her work on the connection between neighborhood design and walking. She is a member of the Committee on Women’s Transportation Issues of the Transportation Research Board and the Institute of Medicine Committee on Childhood Obesity Prevention Actions for Local Governments. For more information: http://www.des.ucdavis.edu/ faculty/handy/.

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Author Biographies

Chapter 5: roadways and Health: Making the Case for Collaboration

Catherine L. ross, Ph.D., is Director of Georgia Tech’s Center for Quality Growth and Regional Development (CQGRD). A nationally recognized transportation expert, Ross is the college’s first endowed faculty member—the Harry West Chair for Quality Growth and Regional Development. She has held a variety of important leadership positions at Georgia Tech, including vice provost for academic affairs, associate vice president for academic affairs, co-director of the Transportation Research and Education Center, and director of the College of Architecture’s Ph.D. program. For more information: http://www.cqgrd.gatech.edu/ about/ross.php.

k e y i s s u e s

Chapter 6: Breaking Down Silos: Transportation, Economic Development and Health

Todd Swanstrom, Ph.D., is the E. Desmond Lee Professor of Community Collaboration and Public Policy Administration at the University of Missouri, St. Louis. A co-author of Place Matters: Metropolitics for the Twenty-first Century (University Press of Kansas, 2004), Swanstrom is presently working with the Transportation Equity Network (TEN) on local workforce development in the construction industry. His most recent report, The Road to Good Jobs: Patterns of Employment in the Construction Industry, is available at http:// www.transportationequity.org. He is also doing research, funded by the MacArthur Foundation’s Building Resilient Regions project, on local responses to the foreclosure crisis in six metropolitan areas. For more information: http://pprc.umsl.edu/base_pages/home/staff. htm#research.

Chapter 7: Sustainable Food Systems: Perspectives on Transportation Policy

Kami Pothukuchi, Ph.D., is Associate Professor of Urban Planning at Wayne State University, Detroit, MI. Her research examines the links between food and community and economic development, and the roles public and nonprofit agencies might play to foster these links. A policy guide, “Community and Regional Food Planning Policy Guide,” co- authored by her, was recently adopted by the American Planning Association (http:// www.planning.org/policyguides/food.htm). She serves on the Detroit Food Policy Council Convening Committee, the Detroit Food and Fitness Collaborative, and several other local and national committees related to community food planning. For more information: http://www. clas.wayne.edu/faculty/Pothukuchi.

richard Wallace, M.S., is a Senior Project Manager with the Center for Automotive Research (CAR) in Ann Arbor, MI. He plays the leading role in CAR’s work in the connected vehicle and transportation infrastructure realms. While with the Altarum Institute, he completed and served as Co- Principal Investigator of a study, “Cost Benefit of Providing Non-emergency Medical Transportation.” This groundbreaking study (TCRP B-27), completed under contract to the Transit Cooperative Research Program of the Transportation Research Board of the National Academies, compared the healthcare costs and benefits to the additional transportation costs of providing nonemergency medical transportation to transportation-disadvantaged persons that face transportation barriers to obtaining needed medical care. He holds a master’s degree in Technology and Science Policy from the Georgia Institute of Technology. For more information: http://www.linkedin.com/in/richardwallacecar.

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Chapter 8: Traffic Injury Prevention: A 21st Century Approach

Larry Cohen, M.S.W., is Founder and Executive Director of Prevention Institute. For more details, see his full profile under the “Framing and Summary” section above.

Janani Srikantharajah, B.A., is a Program Coordinator at Prevention Institute, where she supports the Institute’s built environment, transportation, and health reform efforts. Srikantharajah authored the American Public Health Association’s transportation and land use policy resolution in 2008. Prior to joining Prevention Institute, she spent two years with the Ernest Gallo Research Clinic, at UCSF, studying alcohol addiction pathways. For more information: http://www.preventioninstitute. org/staffbio.html.

Leslie Mikkelsen, R.D, M.P.H., is Managing Director of Prevention Institute, where she leads a team focused on environmental and policy approaches to promoting healthy eating and physical activity. Mikkelsen is a policy consultant to the Healthy Eating Active Living Convergence Partnership. She is also Co-founder and Project Director of the Strategic Alliance for Healthy Food and Activity Environments, a California coalition promoting a broad agenda that has influenced state legislation and the Governor’s California Obesity Prevention plan. For more information: http://www.preventioninstitute. org/staffbio.html.

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Acknowledgments

This publication is a collaborative effort including the insights and assistance of numerous individuals in addition to the authors.

Our sincerest thanks to the following for their contributions to the development of this report:

• Todd Litman, Manuel Pastor, Carli Paine, Jason Corburn, and Larry Frank for their careful reviews of various portions of the report.

• Fran Smith, for her skillful writing, editing, and research assistance, as well as her valuable input throughout the development of this report.

• Victor rubin, Janani Srikantharajah, and Leslie Mikkelsen for their insightful review and input.

• Paulette Jones robinson, Ariana Zeno, Erika Bernabei, and Emma Sarnat, for their thorough and diligent copyediting, fact-checking, and proofing.

• Annie Finkenbinder and Lili Shoup, for sharing their policy expertise.

• The members of the Convergence Partnership, for their guidance throughout this project:

Linda Jo Doctor, W. K. Kellogg Foundation

David Fukuzawa, Kresge Foundation

Allison S. Gertel-rosenberg and rich Killingsworth, Nemours

Laura Kettel Khan, Centers for Disease Control and Prevention

Angie McGowan and Maisha Simmons, Robert Wood Johnson Foundation

Brian raymond and Loel Solomon, Kaiser Permanente

Marion Standish, The California Endowment

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1 John King, “Bus Route Closing Devastates Disabled Couple,” CNN, March 27, 2009, http://www.cnn.com/2009/POLITICS/03/27/ st.louis.no.bus/.

2 Henry K. Lee, “Diesel Exhaust Poses Health Risks in West Oakland, Study Finds,” San Francisco Chronicle, November 16, 2003, http://www.sfgate.com/cgi-bin/article. cgi?file=/chronicle/archive/2003/11/16/ BAGQE334JL1.DTL.

3 Jennifer Langston, “No Easy Access to Fresh Groceries in Many Parts of Seattle,” Seattle Post Intelligencer, May 1, 2008, http://www. seattlepi.com/local/361235_foodvoid01.html.

4 See http://www.investininfrastructure.org/.

5 President Franklin D. Roosevelt took a similar tack during the Great Depression. Addressing transportation needs accounted for much of the work of the WPA. By 1938, the WPA had paved or repaired 280,000 miles of road and had built 29,000 bridges and 150 airfields, according to Jim Couch, professor of economics and finance at the University of North Alabama and co-author of The Political Economy of the New Deal (Williston, VT: Edward Elgar Publishing, 1998).

6 See the policy platform of the Transportation Equity Network, a national coalition of more than 300 grassroots and partner organizations working to reform transportation and land use policies, http://transportationequity.org/index. php?option=com_content&task=view&id =15&Itemid=32. See also American Public Health Association, At the Intersection of Public Health and Transportation: Promoting Healthy Transportation Policy, 2009, http:// www.apha.org/NR/rdonlyres/43F10382- FB68-4112-8C75-49DCB10F8ECF/0/ TransportationBrief.pdf.

7 National Surface Transportation Policy and Revenue Commission, Transportation for Tomorrow, December 2007, http:// transportationfortomorrow.org/final_report/.

8 E. Burgess and A. Rood, Reinventing Transit: American Communities Finding Smarter, Cleaner, Faster Transportation Solutions (New York: Environmental Defense Fund, 2009), http://www.edf.org/documents/9522_ Reinventing_Transit_FINAL.pdf.

9 M. Turner, “Transit Oriented Development Revitalizes Chicago Neighborhood,” Race, Poverty, and the Environment (Winter 2005/2006), http://www.urbanhabitat.org/ files/24.Marcia.Turner.pdf.

10 See http://www.cleanandsafeports.org. Information and resources on the impacts that transporting goods have on health and community life are available from the Trade, Health, & Environment Impact Project, a community-academic partnership, http:// hydra.usc.edu/scehsc/web/Welcome/ Welcome.html.

11 For information on authorizations and allocations under SAFETEA-LU, the surface transportation bill that expires in September 2009, see http://www.fhwa.dot.gov/ safetealu/factsheets/step.htm.

12 Transportation for Tomorrow (see endnote 7).

13 Health impact assessments are a combination of procedures, methods, and tools to evaluate the potential health effects of a policy, program, or project as well as the distribution of those effects within a population. See http://www.cdc.gov/ healthyplaces/hia.htm.

14 Transit oriented development is a planning and design trend that seeks to create compact, mixed-use, pedestrian-friendly

Notes

The Transportation Prescription: A Summary of Findings and a Framework for Action

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communities located around new or existing public transportation stations. For more information, see Todd Swanstrom’s chapter in this book. See also http://www.policylink. org/EDTK/TOD/default.html.

15 See http://www.fhwa.dot.gov/safetealu/ factsheets/stp.htm.

16 J. Pucher and J. L. Renne, “Socioeconomics of Urban Travel: Evidence from the 2001 NHTS,” Transport Quarterly 57 (2003): 49– 77, http://policy.rutgers.edu/faculty/pucher/ TQPuchRenne.pdf.

17 See http://www.fta.dot.gov/funding/grants/ grants_financing_3561.html.

18 Transit Riders for Public Transportation, “Ensuring Non-Discrimination in Transportation Investments,” http://www. publicadvocates.org/ourwork/transportation/ docs/TRPT-Ensuring_Non_Discrimination_in_ Transportation_Investments_04-08-09.pdf.

19 Swanstrom T. The Road to Good Jobs: Patterns of Employment in the Construction Industry, (September 30, 2008), http://www.umsl. edu/services/media/assets/pdf/study.pdf.

Chapter 1: Health Effects of Transportation Policy

1 National Surface Transportation Policy and Revenue Commission, Transportation for Tomorrow, December 2007, http:// transportationfortomorrow.org/final_report.

2 P. Latzin et al., “Air Pollution during Pregnancy and Lung Function in Newborns: A Birth Cohort Study,” European Respiratory Journal 33 (2009): 594–603.

3 W. J. Gauderman et al., “The Effect of Air Pollution on Lung Development from 10 to 18 Years of Age,” New England Journal of Medicine 351, no. 11 (2004): 1057–87.

4 C. A. Pope III et al., “Lung Cancer, Cardiopulmonary Mortality, and Long-Term Exposure to Fine Particulate Pollution,” Journal of the American Medical Association (JAMA) 287, no. 9 (2002): 1132–41.

5 American Lung Association, “Highlights of Recent Research on Particulate Air Pollution: Effects of Long-term Exposure,” 2008, http://www.lungusa.org/atf/cf/{7a8d42c2- fcca-4604-8ade-7f5d5e762256}/ANNUAL-

AVERAGE-PM-STUDIES-OCTOBER-2008.PDF.

6 M. Bell et al., “Ozone and Short-Term Mortality in 95 U.S. Urban Communities, 1987–2000,” Journal of the American Medical Association 292, no. 19 (2004): 2372–89, http://research.yale.edu/ environment/bell/research/files/bell_ mortality_jama.pdf.

7 American Lung Association, “Highlights of Recent Research” (see endnote 5).

8 See http://www.arb.ca.gov/research/health/ fs/pm_ozone-fs.pdf.

9 See http://www.lungusa.org/site/ pp.asp?c=dvLUK9O0E&b= 44567.

10 Centers for Disease Control and Prevention (CDC), “America Breathing Easier,” http:// www.cdc.gov/asthma/pdfs/breathing_easier_ brochure.pdf.

11 S. Nicholas et al., “Addressing the Childhood Asthma Crisis in Harlem: The Harlem Children’s

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Zone Asthma Initiative,” American Journal of Public Health 95, no. 2 (2005): 245–49.

12 W. J. Gauderman et al., “Childhood Asthma and Exposure to Traffic and Nitrogen Dioxide,” Epidemiology 16, no. 6 (2005): 737–43.

13 Meredith Minkler et al., “Promoting Healthy Public Policy Through Community-based Participatory Research,” PolicyLink, 2008, http://www.policylink.org/documents/CBPR_ final.pdf. See also http://www.weact.org.

14 K. L. Ebi et al., “U.S. Funding is Insufficient to Address the Human Health Impacts of and Public Health Responses to Climate Variability,” Environmental Health Perspectives Online, February 27, 2009, doi: 10.1289/ehp.0800088, http://dx.doi.org/.

15 See http://thomas.loc.gov/cgi-bin/query/ z?c111:H.R.2323.

16 T. Brikowski, Y. Lotan, and M. S. Pearle, “Climate-related Increase in the Prevalence of Urolithiasis in the United States,” Proceedings of the National Academy of Sciences 105, no. 28 (2008): 9841–46, http://www.pnas.org/ content/105/28/9841.full.pdf+html.

17 Ebi et al., “U.S. Funding” (see endnote 14).

18 CDC, “Preventing Obesity and Chronic Diseases Through Good Nutrition and Physical Activity,” 2008, http://cdc.gov/ nccdphp/publications/factsheets/Prevention/ pdf/obesity.pdf.

19 CDC, “Prevalence of Regular Physical Activity among Adults—United States, 2001 and 2005,” Morbidity and Mortality Weekly Report 56, no. 46 (November 23, 2007): 1209–12, http://www.cdc.gov/mmwr/ preview/mmwrhtml/mm5646a1.h2tm#tab.

20 Transportation Research Board and Institute of Medicine, “Does the Built Environment

Influence Physical Activity? Examining the Evidence,” Special Report 282 (Washington, DC: National Academy Press, 2005).

21 S. J. Olshansky et al., “A Potential Decline in Life Expectancy in the United States in the 21st Century,” New England Journal of Medicine 352, no. 11 (March 17, 2005): 1138–45, http://www.muni.org/iceimages/ healthchp/life%20expectancy1.pdf.

22 L. D. Frank, M. Andresen, and T. L. Schmid, “Obesity Relationships and Community Design, Physical Activity, and Time Spent in Cars,” American Journal of Preventive Medicine 27, no. 2 (2004): 87–96, http:// www.act-trans.ubc.ca/documents/ajpm- aug04.pdf.

23 U. LaChapelle and L. D. Frank, “Transit and Health: Mode of Transport, Employer- Sponsored Public Transit Pass Programs, and Physical Activity,” Journal of Public Health Policy 30 Supplement (2009): S73–S94, http://www.palgrave-journals.com/jphp/ journal/v30/nS1/pdf/jphp200852a.pdf.

24 L. Besser, M. Marcus, and H. Frumkin, “Commute Time and Social Capital in the U.S.,” American Journal of Preventive Medicine 34, no. 3 (2008): 207–11.

25 U.S. Department of Transportation, “Motor Vehicle Traffic Crashes as a Leading Cause of Death in the United States, 2005,” Research Note DOT HS 810 936 (Washington, DC: National Highway Traffic Safety Administration, 2008).

26 Lawrence J. Blincoe et al., “The Economic Impact of Motor Vehicle Crashes, 2000,” Report no. DOT HS-809-446 (Washington, DC: National Highway Traffic Safety Administration, 2002), http://www. nhtsa.dot.gov/staticfiles/DOT/NHTSA/ Communication%20&%20Consumer%20 Information/Articles/Associated%20Files/ EconomicImpact2000.pdf.

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27 CDC, “Web-based Injury Statistics Query and Reporting System (WISQARS),” http://www. cdc.gov/ncipc/WISQARS/.

28 CDC, “Pedestrian Fatalities—Cobb, DeKalb, Fulton, and Gwinnett Counties, Georgia, 1994–1998,” Morbidity and Mortality Weekly Report 48 (1999): 601–05, http://www.cdc. gov/mmwr/PDF/wk/mm4828.pdf.

29 J. Pucher and J. L. Renne, “Socioeconomics of Urban Travel: Evidence from the 2001 NHTS,” Transport Quarterly 57 (2003): 49– 77, http://policy.rutgers.edu/faculty/pucher/ TQPuchRenne.pdf.

30 David A. Morena et al., Older Drivers at a Crossroads (Washington, DC: Federal Highway Administration, 2007), http://www. tfhrc.gov/pubrds/07jan/02.htm.

31 U.S. Department of Transportation, “National Household Travel Survey,” Older Drivers: Safety Implications (Washington, DC: Federal Highway Administration, 2006).

32 Federal Highway Administration, “National Household Travel Survey,” 2001.

33 Fatality Analysis Reporting System Encyclopedia, http://www-fars.nhtsa.dot. gov/Main/index.aspx.

34 T. Litman and S. Fitzroy, “Safe Travels: Evaluating Mobility Management Traffic Safety Benefits,” Victoria Transport Policy Institute, 2006, http://www.vtpi.org/safetrav. pdf.

35 Peter L. Jacobsen, “Safety in Numbers: More Walkers and Bicyclists, Safer Walking and Bicycling,” Injury Prevention 9 (2003): 205– 09, http://www.tsc.berkeley.edu/newsletter/ Spring04/JacobsenPaper.pdf.

36 Steven Raphael and Alan Berube, “Socioeconomic Differences in Household Automobile Ownership Rates: Implications

for Evacuation Policy,” paper prepared for the Berkeley Symposium on “Real Estate, Catastrophic Risk, and Public Policy,” March 23, 2006, http://urbanpolicy.berkeley.edu/ pdf/raphael.pdf.

37 “Overcoming Obstacles to Health,” Robert Wood Johnson Foundation, 2008, http://www.commissiononhealth.org/PDF/ ObstaclesToHealth-Highlights.pdf. See also R. D. Wilkinson and K. E. Pickett, “Income Inequality and Population Health: A Review and Explanation of the Evidence,” Social Science & Medicine 62 (2006): 1768–84.

38 “Transportation Affordability: Strategies to Increase Transportation Affordability,” TDM Encyclopedia, updated July 2008, Victoria Transport Policy Institute, http://vtpi.org/ affordability.pdf.

39 Barbara Lipman, “A Heavy Load: The Combined Housing and Transportation Burdens of Working Families” (Washington, DC: Center for Housing Policy, October 2006), http://www.nhc.org/pdf/pub_heavy_ load_10_06.pdf.

40 “Realizing the Potential: Expanding Housing Opportunities near Transit,” Reconnecting America’s Center for Transit Oriented Development, 2007, http:// www.reconnectingamerica.org/public/ reports?page=2.

41 See http://www.bts.gov/publications/ issue_briefs/number_03/html/transportation_ difficulties_keep_over_half_a_million_ disabled_at_home.html.

42 L. Bailey, “Aging Americans: Stranded Without Options,” Surface Transportation Policy Project, 2004, http://www.apta.com/ research/info/online/documents/aging_ stranded.pdf.

43 Ibid.

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1 Federal Highway Administration, Safe Routes to Schools Program Factsheet, http://www. fhwa.dot.gov/safetealu/factsheets/saferoutes. htm.

2 American Public Health Association, At the Intersection of Public Health and Transportation: Promoting Healthy Transportation Policy, http://www.apha.org/ NR/rdonlyres/43F10382-FB68-4112-8C75- 49DCB10F8ECF/0/TransportationBrief.pdf .

3 Northeast-Midwest Institute, What is the Highway Trust Fund?, http://www.nemw.org/ HWtrustfund.htm.

4 Federal Highway Administration, Surface Transportation Program Factsheet, http:// www.fhwa.dot.gov/safetealu/factsheets/stp. htm.

5 Federal Transit Agency, Large Cities Program

(5307), http://www.fta.dot.gov/funding/ grants/grants_financing_3561.html.

6 Federal Highway Administration, Highway Safety Improvement Program Factsheet, http://www.fhwa.dot.gov/safetealu/ factsheets/hsip.htm.

7 Federal Transit Agency, Jobs and Reverse Commute Program, http://www.fta.dot.gov/ funding/grants/grants_financing_3550.html.

8 Federal Transit Administration, New Starts Factsheet, http://www.fta.dot.gov/planning/ newstarts/planning_environment_2607.html.

9 Surface Transportation Policy Partnership, From the Margins to the Mainstream, http:// www.transact.org/PDFs/margins2006/STPP_ guidebook_margins.pdf.

10 Ibid.

1 U.S. Census Bureau, 2007 American Community Survey 1-Year Estimates, 2007, http://www.census.gov.

2 Transportation Research Board, Does the Built Environment Influence Physical Activity? Examining the Evidence, Special Report 282, Committee on Physical Activity, Health, Transportation, and Land Use, 2005, http:// onlinepubs.trb.org/onlinepubs/sr/sr282.pdf.

3 ICF International, The Broader Connection between Public Transportation, Energy Conservation and Greenhouse Gas Reduction, American Public Transportation Association, 2008, http://www.apta.com/research/info/

online/documents/land_use.pdf; and Todd Litman, Evaluating Public Transit, Benefits and Costs, Victoria Transport Policy Institute (VTPI), 2008, http://www.vtpi.org/tranben. pdf.

4 John E. Evans and Richard H. Pratt, “Travel Response to Transportation System Changes,” in Transit Oriented Development, TCRP Report 95, Transportation Research Board, 2007, http://www.trb.org/TRBNet/ ProjectDisplay.asp?ProjectID=1034.

5 VTPI, “Multi-modal Level-of-service Indicators,” Online TDM Encyclopedia, 2008, http://www.vtpi.org/tdm/tdm129.htm.

Chapter 2: Transportation Authorization 101: A Backgrounder

Chapter 3: Public Transportation and Health

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Notes

6 Federal Highway Administration (FHWA), Rural Transportation Planning, http://www. fhwa.dot.gov/planning/rural/index.html).

7 PATH, The PATH Guide: Planning Ideas, Tools, and Examples to Achieve Transportation Access and Equity in Rural California, prepared by Natural Resources Services, A Division of Redwood Community Action Agency, Eureka, CA, http://www.nrsrcaa.org/ path, 2006, with funding from The Caltrans Environmental Justice Program, http://www. nrsrcaa.org/path/pdfs/PATHGuide5_06.pdf.

8 European Commission, Energy and Transport in Figures, Directorate-General for Energy and Transport, European Commission, 2007, http://ec.europa.eu/dgs/energy_transport/ figures/pocketbook/doc/2007/pb_1_ general_2007.pdf; and FHWA, Highway Statistics, annual reports, http://www.fhwa. dot.gov/policy/ohpi/hss/index.htm.

9 Robert Puentes, The Road . . . Less Traveled: An Analysis of Vehicle Miles Traveled Trends in the U.S. (Washington, DC: Brookings Institution, 2008); and Todd Litman, “Changing Travel Demand: Implications for Transport Planning,” ITE Journal 76, no. 9 ( September 2006): 27–33, http://www.vtpi. org/future.pdf.

10 APTA, Transit Statistics, various years, http:// www.apta.com/research/stats/agency/index. cfm; and FHWA, Highway Statistics, annual reports, http://www.fhwa.dot.gov/policy/ ohpi/hss/index.htm.

11 Reconnecting America, Hidden in Plain Sight: Capturing the Demand for Housing near Transit, Center for Transit-Oriented Development, for the Federal Transit Administration, 2004, http://www. reconnectingamerica.org/public/download/ hipsi.

12 Belden Russonello & Stewart, 2004 American Community Survey: National Survey on

Communities, conducted for the National Association of Realtors and Smart Growth America, October 2004.

13 APTA, Transit Statistics, various years, http:// www.apta.com/research/stats/agency/ index.cfm; FHWA, Highway Statistics, annual reports, http://www.fhwa.dot.gov/policy/ ohpi/hss/index.htm (see endnote 10 for more details on both citations).

14 Todd Litman and Steven Fitzroy, Safe Travels: Evaluating Mobility Management Traffic Safety Benefits, VTPI, 2006, http://www.vtpi. org/safetrav.pdf.

15 Reid Ewing et al., “Relationship between Urban Sprawl and Physical Activity, Obesity, and Morbidity,” American Journal of Health Promotion 18, no. 1 (September/ October 2003): 47–57, http://www. healthpromotionjournal.com and http:// www.smartgrowth.umd.edu/research/ pdf/EwingSchmidKillingsworthEtAl_ SprawlObesity_DateNA.pdf.

16 William H. Lucy, “Mortality Risk Associated with Leaving Home: Recognizing the Relevance of the Built Environment,” American Journal of Public Health 93, no. 9 (September 2003): 1564–69, http://www. ajph.org/cgi/content/full/93/9/1564.

17 Todd Litman, Rail Transit in America: Comprehensive Evaluation of Benefits, VTPI, 2004, http://www.vtpi.org/railben.pdf.

18 Alison Cassady, Tony Dutzik and Emily Figdor, More Highways, More Pollution: Road- building and Air Pollution in America’s Cities, U.S. PIRG Education Fund, 2004, http://www. uspirg.org; and Anming Zhang et al., Towards Estimating the Social and Environmental Costs of Transportation in Canada, Centre for Transportation Studies, University of British Columbia, for Transport Canada, 2005, http://www.sauder.ubc.ca/cts/docs/Full-TC- report-Updated-November05.pdf.

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19 Christopher J. L. Murray et al., Global Burden of Disease and Injury, Center for Population and Development Studies, Harvard School of Public Health, 1996.

20 Peggy Edwards and Agis D. Tsouros, A Healthy City Is an Active City: A Physical Activity Planning Guide, World Health Organization Europe, 2008, http:// www.euro.who.int/InformationSources/ Publications/Catalogue/20081103_1; and U.S. Surgeon General, Physical Activity and Health, CDC, 1999, http://www.cdc.gov/ nccdphp/sgr/sgr.htm.

21 Oscar H. Franco et al., “Effects of Physical Activity on Life Expectancy with Cardiovascular Disease,” Archives of Internal Medicine 165, no. 20 (November 2005): 2355–60, http://archinte.ama-assn.org/cgi/ content/abstract/165/20/2355.

22 World Health Organization, A Physically Active Life Through Everyday Transport: With a Special Focus on Children and Older People and Examples and Approaches from Europe, Regional Office for Europe, 2003, http:// www.euro.who.int/document/e75662.pdf; and Richard Gilbert and Catherine O’Brien, Child- and Youth-Friendly Land-Use and Transport Planning Guidelines, Centre for Sustainable Transportation, 2005, http://cst. uwinnipeg.ca/documents/Guidelines_ON.pdf.

23 Ewing et al. (see endnote 15).

24 Lilah M. Besser and Andrew L. Dannenberg, “Walking to Public Transit: Steps to Help Meet Physical Activity Recommendations,” American Journal of Preventive Medicine 29, no. 4: 2005, http://www.cdc.gov/ healthyplaces/articles/besser_dannenberg. pdf.

25 Richard E. Wener and Gary W. Evans, “A Morning Stroll: Levels of Physical Activity in Car and Mass Transit Commuting,” Environment and Behavior 39, no. 1 (2007):

62–74, http://eab.sagepub.com/cgi/content/ abstract/39/1/62.

26 Ugo Lachapelle and Lawrence D. Frank, “Mode of Transport, Employer-Sponsored Public Transit Pass, and Physical Activity,” Journal of Public Health Policy 30, Suppl. no.1 (2009): S73–S94.

27 Ibid.

28 David Bassett et al., “Walking, Cycling, and Obesity Rates in Europe, North America, and Australia,” Journal of Physical Activity and Health 5, no. 6 (November 2008): 795–814, http://www.humankinetics.com/jpah/ journalAbout.cfm.

29 Ibid.

30 Roland Sturm, Urban Design, Lifestyle, and the Development of Chronic Conditions, the Built Environment and Childhood Obesity Plenary Session, National Institute of Environmental Health Sciences, 2005, http:// www-apps.niehs.nih.gov/conferences/drcpt/ oe2005/speakerdocs/strum-doc.pdf.

31 International Council for Local Environmental Initiatives, Health Benefits Economic Model, Cities for Climate Protection, 2003, http:// www3.iclei.org/ccp-au/tdm/index.html.

32 Todd Litman, Community Cohesion as a Transport Planning Objective, VTPI, 2007, http://www.vtpi.org/cohesion.pdf.

33 Jane Jacobs, Death and Life of the Great American Cities (New York: Random House, 2001).

34 Ontario College of Family Physicians, The Health Impacts of Urban Sprawl Information Series: Volume Four–Social & Mental Health, 2005, http://www.ocfp.on.ca/local/ files/Urban%20Sprawl/UrbanSpraw-Soc- MentalHlth.pdf.

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35 Donald Appleyard, Livable Streets (Berkeley, CA: University of California Press, 1981).

36 Heather Allen, Sit Next to Someone Different Every Day—How Public Transport Contributes to Inclusive Communities, Thredbo Conference, 2008, http://www.thredbo.itls. usyd.edu.au/downloads/thredbo10_papers/ thredbo10-plenary-Allen.pdf.

37 Ethan M. Berke et al., “Protective Association between Neighborhood Walkability and Depression in Older Men,” Journal of the American Geriatrics Society 55, no. 4 (2007): 526–33, http://www.blackwell-synergy.com.

38 Wener and Evans, “A Morning Stroll” (see endnote 25).

39 VTPI, “Basic Accessibility and Mobility,” TDM Encyclopedia, 2008, http://www.vtpi.org/ tdm/tdm103.htm.

40 APTA, The Route to Better Personal Health, 2003, http://spider.apta.com/lgwf/legtools/ better_health.pdf.

41 Irwin Redlener et al., The Growing Health Care Access Crisis for American Children: One in Four at Risk, The Children’s Health Fund, 2006, http://www.childrenshealthfund.org/ calendar/WhitePaper-May2007-FINAL.pdf.

42 Todd Litman, “Transportation Market Distortions” (issue theme “Sustainable Transport in the United States: From Rhetoric to Reality?”), Berkeley Planning Journal 19 (2006): 19–36, http://www-dcrp.ced. berkeley.edu/bpj, and http://www.vtpi.org/ distortions_BPJ.pdf.

43 Todd Litman, Comprehensive Transport Planning Framework: Best Practices for Evaluating All Options and Impacts, VTPI, 2007, http://www.vtpi.org/comprehensive. pdf.

44 Kjartan Sælensminde, “Cost-benefit Analysis of Walking and Cycling Track Networks Taking into Account Insecurity, Health Effects, and External Costs of Motor Vehicle Traffic,” Transportation Research A 38, no. 8 (October 2004): 593–606, http://www.elsevier.com/ locate/tra) at http://www.toi.no/toi_Data/ Attachments/887/sum_567_02.pdf.

45 Robert Puentes and Ryan Prince, Fueling Transportation Finance: A Primer on the Gas Tax (Washington, DC: Brookings Institution, Center on Urban and Metropolitan Policy, 2003), http://www.brookings.edu/reports/ 2003/03transportation_puentes.aspx.

46 Lawrence Frank, Sarah Kavage, and Todd Litman, Promoting Public Health Through Smart Growth: Building Healthier Communities Through Transportation and Land Use Policies, Smart Growth BC, 2006, http://www.vtpi.org/sgbc_health. pdf; and Richard Killingsworth, Audrey De Nazelle, and Richard Bell, “Building a New Paradigm: Improving Public Health Through Transportation,” ITE Journal 73, no. 6 (June 2003): 28–32, http://www.ite.org.

47 World Health Organization (WHO), World Report on Road Traffic Injury Prevention, WHO and World Bank, 2004, http://www. who.int/entity/world-health-day/2004/ infomaterials/world_report; and International City/County Management Association (ICMA), Creating a Regulatory Blueprint for Healthy Community Design: A Local Government Guide to Reforming Zoning and Land Development Codes, ICMA (http:// www.icma.org) and Active Living By Design (http://www.activelivingleadership.org), 2005.

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48 Dan Emerine and Eric Feldman, Active Living and Social Equity: Creating Healthy Communities for All Residents, International City/County Management Association, 2005, http://bookstore.icma.org.

49 Active Living Research (http://www. activelivingresearch.org).

50 VTPI, “Financing Options,” Online TDM

Encyclopedia, 2008, http://www.vtpi.org/ tdm/tdm119.htm.

51 Center for Neighborhood Technology, Housing + Transportation Affordability Index, 2008, http://htaindex.cnt.org.

52 Congress for the New Urbanism, Parking Requirements and Affordable Housing, 2008, http://www.cnu.org/node/2241.

1 J. Pucher and R. Buehler, “Making Cycling Irresistible: Lessons from the Netherlands, Denmark, and Germany,” Transport Reviews 28 (2008): 495–528.

2 David Bassett et al., “Walking, Cycling, and Obesity Rates in Europe, North America, and Australia,” Journal of Physical Activity and Health 5, no. 6 (November 2008): 795–814, http://www.humankinetics.com/jpah/ journalAbout.cfm.

3 Ibid.

4 J. Pucher, J. Dill, and S. Handy et al., “Infrastructure, Programs, and Policies to Increase Bicycling: An International Review,” Preventative Medicine. Vol 48, No. 2, February 2010.

5 U.S. Department of Health and Human Services, “2008 Physical Activity Guidelines for Americans,” http://www.health.gov/ PAGuidelines/pdf/paguide.pdf (accessed March 27, 2009).

6 Centers for Disease Control and Prevention (CDC), “Prevalence of Regular Physical Activity among Adults – United States, 2001 and 2005,” Morbidity and Mortality Weekly Report 56 (2007): 1209–12.

7 J. N. Morris and A. E. Hardman, “Walking to Health,” Sports Medicine 23 (1997): 306–32.

8 D. Ogilvie et al., “Interventions to Promote Walking: Systematic Review,” British Medical Journal 334 (June 2007): 1204.

9 National Highway Traffic Safety Administration (NHTSA), “Traffic Safety Facts 2007 Data: Pedestrians,” 2008, http:// www.nhtsa.dot.gov/portal/nhtsa_static_ file_downloader.jsp?file=/staticfiles/DOT/ NHTSA/NCSA/Content/TSF/2007/810994. pdf (accessed March 27, 2009); and NHTSA, “Traffic Safety Facts 2007 Data: Bicyclists and Other Cyclists,” 2008, www.nhtsa.dot. gov/portal/nhtsa_static_file_downloader. jsp?file=/staticfiles/DOT/NHTSA/NCSA/ Content/TSF/2007/810986.pdf (accessed March 27, 2009).

10 C. Gidelow et al., “A Systematic Review of the Relationship between Socio-economic Position and Physical Activity,” Health Education Journal 65 (2007): 338–67; and CDC, “Prevalence of Regular Physical Activity among Adults – United States, 2001 and 2005,” Morbidity and Mortality Weekly Report 56 (2007): 1209–12.

11 L. M. Besser and A. L. Dannenberg, “Walking

Chapter 4: Walking, Bicycling, and Health

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to Transit: Steps to Help Meet Physical Activity Recommendations,” American Journal of Preventive Medicine 29 (2005): 273–80.

12 J. Pucher and J. L. Renne, “Socioeconomics of Urban Travel: Evidence from the 2001 NHTSA”; and Besser and Dannenberg, “Walking to Transit” (see endnote 11).

13 N. C. McDonald, “Exploratory Analysis of Children’s Travel Patterns,” Transportation Research Record 1977 (2006): 1–7.

14 NHTSA, “Traffic Safety Facts 2007 Data: Pedestrians” (see endnote 9, citation 1); and NHTSA, “Traffic Safety Facts 2007 Data: Bicyclists and Other Cyclists” (see endnote 9, citation 2).

15 L. Bailey, “Aging Americans: Stranded without Options,” 2004, http://www. transact.org/library/reports_html/seniors/ aging_exec_summ.pdf (accessed March 27, 2009).

16 NHTSA, “Traffic Safety Facts 2007 Data: Pedestrians” (see endnote 9, citation 1).

17 U.S. Department of Health and Human Services, “2008 Physical Activity Guidelines for Americans” (see endnote 5).

18 J. Pucher and R. Buehler, “Making Cycling Irresistible: Lessons from the Netherlands, Denmark, and Germany,” Transport Reviews 28 (2008): 495–528. J. Pucher and L. Dijkstra, “Promoting Safe Walking and Cycling to Improve Public Health: Lessons from the Netherlands and Germany,” American Journal of Public Health 93 (2003): 1509–16.

19 P. L. Jacobsen, “Safety in Numbers: More Walkers and Bicyclists, Safer Walking and Bicycling,” Injury Prevention 9 (2003): 205– 09.

20 Bureau of Transportation Statistics, “Transportation Statistics Annual Report,” 2007, http://www.bts.gov/publications/ transportation_statistics_annual_ report/2007/pdf/entire.pdf (accessed May 7, 2009).

21 S. Handy and K. Clifton, “Local Shopping as a Strategy for Reducing Automobile Travel,” Transportation 28 (2001): 317–46.

22 Pucher and Dijkstra, “Promoting Safe Walking and Cycling” (see endnote 18).

23 R. Buehler, “Transport Policies, Travel Behavior and Sustainability: A Comparison of Germany and the U.S.” 2008, unpublished dissertation.

24 N. C. McDonald, “Active Transportation to School: Trends among U.S. Schoolchildren, 1969–2001,” American Journal of Preventive Medicine 32 (2007): 509–16.

25 G. Tal and S. Handy, “Children’s Biking for Non-school Purposes: Getting to Soccer Games in Davis, CA,” Transportation Research Record 2074 (2008): 40–45.

26 E. Gaona, “Oxnard Plan Focuses on Bicycle Commuters,” Los Angeles Times, August 19, 2002, B-3.

27 R. L. Knoblauch et al., “The Pedestrian and Bicyclist Highway Safety Problem as It Relates to the Hispanic Population in the United States,” 2004, http://safety.fhwa.dot. gov/ped_bike/docs/03p00324/050329.pdf (accessed March 27, 2009).

28 S. Handy, “Regional Transportation Planning in the U.S.: An Examination of Changes in Technical Aspects of the Planning Process in Response to Changing Goals,” Transport Policy 15 (2008): 113–26.

29 K. Krizek et al., “Explaining Changes in Walking and Bicycling Behavior:

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The Transportation Researcher’s Full Employment Act,” Environment and Planning (forthcoming).

30 NHTSA, “Traffic Safety Facts 2007 Data: Pedestrians” (see endnote 9); and NHTSA, “Traffic Safety Facts 2007 Data: Bicyclists and Other Cyclists” (see endnote 9).

31 S. Handy et al., “The Regional Response to Federal Funding for Bicycle and Pedestrian Projects,” 2009, Institute of Transportation Studies, University of California – Davis, working paper.

32 See, for example, http://www.walkinginfo.org, and http://www.bicycleinfo.org.

33 Handy et al., “The Regional Response to Federal Funding” (see endnote 31).

34 Ibid.

35 Ibid.

36 Land use planning powers have not explicitly been taken by the federal government and so are left to states, according to the reserved powers doctrine of the U.S. Constitution; most states have chosen to delegate this power to local governments, with some variation in the degree to which states have chosen to exert influence over local planning.

37 See http://www.activelivingbydesign.org.

38 S. Handy et al., “Is support for traditionally designed communities growing? Evidence from two national surveys,” Journal of the American Planning Association 74 (2008): 209–21.

1 Federal Highway Administration (FHWA), “National Household Travel Survey” (NHTS), Online Analysis Tool, 2001, http://nhts.ornl. gov/tables/ae/TableDesigner.aspx (accessed March 10, 2009).

2 Fatality Analysis Reporting System Encyclopedia, n.d., http://www-fars.nhtsa. dot.gov/Main/index.aspx (accessed October 7, 2008).

3 Centers for Disease Control and Prevention. Web-based Injury Statistics Query and Reporting System (WISQARS), http://www. cdc.gov/injury/wisqars/index.html (accessed June 16, 2009).

4 Task Force on Community Preventive Services, “Motor-Vehicle Occupant Injury: Strategies for Increasing Use of Child Safety Seats, Increasing Use of Safety Belts, and Reducing Alcohol-Impaired Driving,” Morbidity and

Mortality Weekly Report 50 (RR07) (2001): 1–13.

5 U.S. Department of Transportation (DOT), HS 811 017, “A Brief Statistical Summary August 2008 Traffic Safety Facts – Crash Stats: 2007 Traffic Safety Annual Assessment – Highlights.”

6 FHWA, “National Household Travel Survey,” Online Analysis Tool, 2001, http://nhts.ornl. gov/tables/ae/TableDesigner.aspx (accessed March 11, 2009).

7 FHWA, “Making the Case for Transportation Safety – Ideas for Decision Makers,” FHWA- HEP-08-017, 2008.

8 H. G. Garrison and C. E. Crump, “Commentary: Race, Ethnicity and Motor Vehicle Crashes,” Annals of Emergency Medicine 49, no. 2 (2007): 219–20.

Chapter 5: Roadways and Health: Making the Case for Collaboration

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9 J. Pucher and J. Renne, “Socioeconomics of Urban Travel: Evidence from the 2001 NHTS,” Transportation Quarterly 57, no. 3 (Summer 2003).

10 L. J. Paulozzi, “Is It Safe to Walk in the Sunbelt? Geographic Variation among Pedestrian Fatalities in the United States, 1999–2003,” Journal of Safety Research 37, no. 5 (2006): 453–59.

11 F. Cheung et al., “An Analysis of Alcohol- related Motor Vehicle Fatalities by Ethnicity,” Annals of Emergency Medicine 34, no. 4, part 1 (1999): 550–53.

12 University of New South Wales, “A Virtuous Cycle: Safety in Numbers for Bicycle Riders,” Science Daily (September 7, 2008).

13 P. L. Jacobsen, “Safety in Numbers: More Walkers and Bicyclists, Safer Walking and Bicycling,” Injury Prevention 9, no. 3 (2003): 205–09.

14 FHWA, “National Household Travel Survey,” Online Analysis Tool, http://nhts.ornl.gov/ tables/ae/TableDesigner.aspx (accessed March 10, 2009).

15 Fatality Analysis Reporting System Encyclopedia, n.d., http://www-fars.nhtsa. dot.gov/Main/index.aspx (accessed October 7, 2008).

16 M. Zhu et al., “Urban and Rural Variation in Walking Patterns and Pedestrian Crashes,” Injury Prevention 14, no. 6 (2008): 377–80.

17 Todd Litman, Smart Transportation Investments: Reevaluating the Role of Highway Expansion for Improving Urban Transportation (Victoria, BC: Victoria Transport Policy Institute, 2006).

18 M. Abdel-Aty and J. Keller, “Exploring the Overall and Specific Crash Severity Levels at Signalized Intersections,” Accident Analysis & Prevention 37, no. 3 (2005): 417–25.

19 P. Liu, J. J. Lu, and H. Chen, “Safety Effects of the Separation Distances between Driveway Exits and Downstream U-turn Locations,” Accident Analysis & Prevention 40, no. 2 (2008): 760–67.

20 Pedestrian and Bicycle Information Center (PBIC), and Federal Highway Administration (FHWA). PEDSAFE Pedestrian Safety Guide and Countermeasure Selection System: Countermeasures. Federal Highway Administration, U.S. Department of Transportation. (2002); and J. Miller, Impact of Situational Factors on Survey Measured Fear of Crime. International Journal of Social Research Methodology, 11(4). (2008).

21 U. Shankar, Pedestrian Roadway Fatalities, No. DOT HS 809 456, Mathematical Analysis Division, National Center for Statistics and Analysis; National Highway Traffic Safety Administration, U.S. Department of Transportation, 2003.

22 SRTS Guide: Reduced Corner Radii, n.d., http://www.saferoutesinfo.org/guide/ engineering/reduced_corner_radii.cfm (accessed October 20, 2008); and PEDSAFE Pedestrian Safety Guide and Countermeasure Selection System: Curb Extensions, n.d., http://www.walkinginfo.org/pedsafe/ pedsafe_curb1.cfm?CM_NUM=19 (accessed October 20, 2008).

23 M. Ernst, Mean Streets 2004: How Far Have We Come?, Surface Transportation Policy Project, 2004.

24 J.-H. Mok, H. C. Landphair, and J. R. Nader, “Landscape Improvement Impacts on Roadside Safety in Texas,” Landscape and Urban Planning 78, no. 3 (2006): 263–74; K. Dixon and K. Wolf, “Benefits and Risks of Urban Roadside Landscape: Finding a Livable, Balanced Response,” Presentation at the 3rd Urban Street Symposium, Seattle, WA, 2007; and K. L. Wolf and N. Bratton, “Urban Trees and Traffic Safety: Considering U.S. Roadside Policy and Crash Data,” Arboriculture and Urban Forestry 32, no. 4 (2006): 170–79.

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25 J. M. Sullivan and M. J. Flanagan, “Determining the Potential Safety Benefit of Improved Lighting in Three Pedestrian Crash Scenarios,” Accident Analysis & Prevention 39, no. 3 (2007): 638–47.

26 Centers for Disease Control and Prevention (CDC), FastStats – Asthma, n.d., http://www. cdc.gov/nchs/fastats/asthma.htm (accessed March 11, 2009).

27 S. Pandian, S. Gokhale, and A. K. Ghoshal, “Evaluating Effects of Traffic and Vehicle Characteristics on Vehicular Emissions near Traffic Intersections,” Transportation Research Part D: Transport and Environment 14, no. 3 (2009): 180–96; and J. Lin and Y. E. Ge, “Impacts of Traffic Heterogeneity on Roadside Air Pollution Concentration,” Transportation Research Part D: Transport and Environment 11, no. 2 (2006): 166–70.

28 Environmental Protection Agency (EPA), The Plain English Guide to the Clean Air Act: Cleaning Up Commonly Found Air Pollutants, 2006, http://www.epa.gov/air/peg/cleanup. html.

29 W. J. Gauderman et al., “Association between Air Pollution and Lung Function Growth in Southern California Children,” American Journal of Respiratory and Critical Care Medicine 162, no. 4 (2000): 1383–90; and W. J. Gauderman et al., “The Effect of Air Pollution on Lung Development from 10 to 18 Years of Age,” New England Journal of Medicine 351, no. 11 (2004): 1057–67.

30 A. G. Barnett et al., “The Effects of Air Pollution on Hospitalizations for Cardiovascular Disease in Elderly People in Australian and New Zealand Cities,” Environmental Health Perspectives 114, no. 7 (2006); and T. F. Mar et al., “Fine Particulate Air Pollution and Cardiorespiratory Effects in the Elderly,” Epidemiology 16, no. 5 (2005): 681–87.

31 L. K. Baxter et al., “Predicting Residential Indoor Concentrations of Nitrogen

Dioxide, Fine Particulate Matter, and Elemental Carbon Using Questionnaire and Geographic Information System Based Data,” Atmospheric Environment 41, no. 31 (2007): 6561–71.

32 J. McCreanor et al., “Respiratory Effects of Exposure to Diesel Traffic in Persons with Asthma,” New England Journal of Medicine 357, no. 23 (2007): 2348–58.

33 National Center for Chronic Disease Prevention and Health Promotion. Obesity: Halting the Epidemic by Making Health Easier - At A Glance 2009. Centers for Disease Control and Prevention (CDC). (2009).

34 D. Chenoweth and J. Leutzinger, “The Economic Cost of Physical Inactivity and Excess Weight in American Adults,” Journal of Physical Activity & Health 3, no. 2 (2006): 148–63.

35 R. D. Putnam, Bowling Alone: The Collapse and Revival of American Community (New York: Simon & Schuster, 2000).

36 J. Gehl, Life Between Buildings (New York: Van Nostrand Reinhold, 1987).

37 L. E. Jackson, “The Relationship of Urban Design to Human Health and Condition,” Landscape and Urban Planning 64, no. 4 (2003): 191–200.

38 Surface Transportation Policy Project and Center for Neighborhood Technology, Driven to Spend: The Impact of Sprawl on Household Transportation Expenses, 2000.

39 P. Gordon-Larsen et al., “Inequality in the Built Environment Underlies Key Health Disparities in Physical Activity,” Pediatrics 117 (2006): 417–24; S. L. Huston et al., “Neighborhood Environment, Access to Places for Activity, and Leisure-time Physical Activity in a Diverse North Carolina Population,” American Journal of Health Promotion 18, no. 1 (2003): 58–69; S. Parks, R. Houseman, and R. Brownson,

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“Differential Correlates of Physical Activity in Urban and Rural Adults of Various Socioeconomic Backgrounds in the United States," Journal of Epidemiology and Community Health 57 (2003): 29–35; W. Taylor et al., “Environmental Justice: Obesity, Physical Activity, and Healthy Eating,” Journal of Physical Activity and Health 3, Suppl. 1 (2006): S30–S54; and D. Wilson et al., “Socioeconomic Status and Perceptions of Access and Safety for Physical Activity,” Annals of Behavioral Medicine 28 (2004): 20–28.

40 Surface Transportation Policy Project, “Transportation and Social Equity,” n.d., http://www.transact.org/library/factsheets/ equity.asp.

41 L. D. Frank, M. A. Andresen, and T. L. Schmid, “Obesity Relationships with Community Design, Physical Activity, and Time Spent in Cars,” American Journal of Preventive Medicine 27, no. 2 (2004): 87–96.

42 A. V. Moudon, Effects of Site Design on Pedestrian Travel in Mixed-Use, Medium- Density Environments (Seattle, WA: Washington State Transportation Center (TRAC, 1997); and H. C. Borst et al., “Relationships between Street Characteristics and Perceived Attractiveness for Walking Reported by Elderly People,” Journal of Environmental Psychology, in press, corrected proof.

43 C. L. Addy, “Associations of Perceived Social and Physical Environmental Supports with Physical Activity and Walking Behavior,” American Journal of Public Health 94, no. 3 (2004): 440–43.

44 H. M. Badland, G. M. Schofield, and N. Garrett, “Travel Behavior and Objectively Measured Urban Design Variables: Associations for Adults Traveling to Work,” Health & Place 14, no. 1 (2008): 85–95; and A. W. Agrawal, M. Schlossberg, and K. Irvin, “How Far, by Which Route and Why? A Spatial Analysis of Pedestrian Preference,” Journal of Urban Design 13, no. 1 (2008): 81–98.

45 National Surface Transportation Policy and Revenue Study Commission, Final Report: Transportation for Tomorrow, http://www. transportationfortomorrow.org/final_report/.

46 R. Puentes, A Bridge to Somewhere: Rethinking American Transportation for the 21st Century. Metropolitan Infrastructure Initiative, Number 3: The Brookings Institution. (2006).

47 National Surface Transportation Policy and Revenue Study Commission, Final Report: Transportation for Tomorrow, http://www. transportationfortomorrow.org/final_report/.

48 Ibid.

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1 Amartya Sen, Inequality Reexamined (Cambridge, MA: Harvard University Press, 1992), 39.

2 Research has shown, for example, that lacking control over one’s work is associated, after controlling for a range of variables, with cardiovascular symptoms and other health problems. This research is summarized in Richard G. Wilkinson, Unhealthy Societies: The Afflictions of Inequality (New York: Routledge, 1996), 181. In general, living in concentrated-poverty neighborhoods is associated with a sense of fatalism, the belief that nothing can be done to improve the situation, which leads to the internalization of stress that has shown to be highly correlated with poor health outcomes. For the connection between concentrated poverty and fatalism, see James E. Rosenbaum, Lisa Reynolds, and Stefanie DeLuca, “How Do Places Matter? The Geography of Opportunity, Self-Efficacy, and a Look inside the Black Box of Residential Mobility,” Housing Studies 17, no. 1 (2002): 71–82. For a nontechnical synthesis of the research on the connection between stress and disease, see Grace Budrys, Unequal Health: How Inequality Contributes to Health of Illness (Lanham, MD: Rowman & Littlefield, 2003), ch. 9.

3 Transportation needs also vary with age, gender, and disabilities. A full treatment of transportation equity, which is beyond the scope of this essay, would need to take into account these conditions as well. See “Equity Evaluation: Perspectives and Methods for Evaluating the Equity Impacts of Transportation,” TDM Encyclopedia (updated July 23, 2008), http://www.vtpi.org/tdm/ tdm13.htm.

4 The literature on the health effects of urban sprawl is voluminous. For a short overview, see Robert Burchell et al, Sprawl Costs: Economic Impacts of Unchecked Development (Washington, DC: Island Press, 2005). See also Howard Frumkin, Lawrence Frank, and Richard Jackson, Urban Sprawl and Public Health: Designing, Planning, and Building for Healthier Communities (Washington, DC: Island Press, 2004).

5 For evidence of the negative impact of inequality in general and geographical inequalities in particular on health, see Ichiro Kawachi, Bruce P. Kennedy, and Richard G. Wilkinson, eds., The Society and Population Health Reader: Income Inequality and Health (New York: New Press, 1999).

6 The following account of the health effects of concentrated poverty is based on Peter Dreier, John Mollenkopf, and Todd Swanstrom, Place Matters: Metropolitics for the Twenty-First Century, rev. ed. (Lawrence, KS: University Press of Kansas, 2004), 76–82.

7 For an insightful discussion of policy monopolies (also called subgovernments, iron triangles, or policy silos), see Frank R. Baumgartner and Bryan D. Jones, Agendas and Instability in American Politics (Chicago: University of Chicago Press, 1993), 6–9. For analysis of the highway policy silo in its heyday, see Alan Altschuler, The City Planning Process: A Political Analysis (Ithaca, NY: Cornell University Press, 1965) and John Mollenkopf, The Contested City (Princeton, NJ: Princeton University Press, 1983).

8 According to a survey of urban scholars, the 41,000-mile federal interstate highway program was the most important influence

Chapter 6: Breaking Down Policy Silos: Transportation, Economic Development, and Health

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shaping America’s metropolitan areas in the past half-century. Reported in Robert Fishman, “The American Metropolis at Century’s End: Past and Future Influences,” Housing Policy Debate 11, no. 1 (2000): 199–213.

9 Over time, however, the urbanization of the suburbs and the almost complete reliance on the automobile has generated serious health costs, including higher levels of air pollution and low activity levels related to obesity. The increased stress from long commutes and traffic congestion negatively affect health. According to a study of eight metropolitan areas, even though rates of homicide by strangers are higher in inner urban areas than in outlying suburbs, the higher traffic fatality rates in outlying areas swamp this effect, making outlying areas less safe than central cities and inner suburbs. See William H. Lucy, “Mortality Risk Associated with Leaving Home: Recognize the Significance of the Built Environment,” American Journal of Public Health 93, no. 9 (September 2003): 1564–69.

10 Elizabeth Kneebone, “Job Sprawl Revisited: The Changing Geography of Metropolitan Employment,” The Brookings Institution, Center on Urban and Metropolitan Policy, May 2009.

11 According to Ingrid Gould Ellen and Margery Austin Turner, of six literature reviews on the spatial mismatch, three find substantial support for it, two find moderate support, and one finds the evidence too mixed to reach a conclusion. See “Do Neighborhoods Matter and Why?,” in Choosing a Better Life: Evaluating the Moving to Opportunity Social Experiment, eds. John Goering and Judith D. Feins (Washington, DC: Urban Institute Press, 2003), 328.

12 Between 1950 and 2000 the average size of a new home increased by more than 50 percent (from 1,470 square feet to 2,265 square feet). In 2000 the average new house

was almost two-thirds more expensive than in 1960 (in constant dollars), and the share of new housing purchased by the top 20 percent of the income range increased dramatically. Rachel Dwyer, “Expanding Homes and Increasing Inequalities: U.S. Housing Development and the Residential Segregation of the Affluent,” Social Problems 54, no. 1 (2007): 23–46.

13 Paul Jargowsky, “Sprawl, Concentration of Poverty, and Urban Inequality,” in Urban Sprawl: Causes, Consequences, and Policy Responses, ed. Gregory D. Squires (Washington, DC: Urban Institute Press, 2002), 57.

14 Between 1956 and 1972, highway building and urban renewal displaced an estimated 3.8 million persons, overwhelmingly poor and minorities, from their homes. Susan Fainstein and Norman Fainstein, eds., Restructuring the City: The Political Economy of Urban Development (New York: Longman, 1986), 49.

15 In Bowling Alone Robert Putnam reports that joining your first group will “cut your risk of dying over the first year in half.” Bowling Alone: The Collapse and Revival of American Community (New York: Simon and Schuster, 2000), 331. For a comprehensive analysis of the costs of displacement on African American communities by urban renewal (and highway building), see Mindy Thompson Fullilove, Root Shock: How Tearing Up City Neighborhoods Hurts America (New York: Ballantine, One World, 2004).

16 To this day, African Americans are underrepresented in the construction workforce relative to their participation in the overall workforce. See Todd Swanstrom, The Road to Good Jobs: Patterns of Employment in the Construction Industry in the Top Twenty-five Metropolitan Areas (St. Louis, MO: Transportation Equity Network, Public Policy Research Center, University of Missouri – St. Louis, 2008).

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17 “Transportation Affordability: Strategies to Increase Transportation Affordability,” TDM Encyclopedia, updated July 2008, Victoria Transport Policy Institute, http://www.vtpi. org/tdm/tdm106/htm.

18 Transportation expenditures are not regressive with respect to family expenditures because many low-income households, such as older adults, live on savings and therefore spend more than they earn. However, for all vehicle-owning households, transportation expenditures are regressive as a proportion of household expenditures. See Todd Litman, “Transportation Affordability: Evaluation and Improvement Strategies,” Victoria Transport Policy Institute, November 10, 2008, http:// www.vtpi.org/affordability.pdf.

19 Barbara Lipman, A Heavy Load: The Combined Housing and Transportation Burdens of Working Families (Washington, DC: Center for Housing Policy, October 2006), http://www.nhc.org/pdf/pub_heavy_ load_10_06.pdf.

20 American Automobile Association, Your Driving Costs (Heathrow, FL: AAA, 2007). The estimate is based on gasoline costing $2.256 a gallon. Low-income persons can own a car for less by purchasing a cheap used car, but then they are subject to repairs, and unreliable transportation can cost them their job. Also, insurance costs tend to be higher in poor communities.

21 Reauthorizations of ISTEA in 1998 and 2005 strengthened the law, for example, creating incentives to link transportation and land use (Transportation and Community and System Preservation [TCSP] Pilot Program) and funding reverse commuting programs to transport inner-city workers to suburban jobs (Job Access and Reverse Commute Program [JARC]).

22 For a comprehensive and largely critical review of federal transportation policy, see Bruce Katz, Robert Puentes, and Scott Bernstein, “Getting Transportation Right

for Metropolitan America,” in Taking the High Road: A Metropolitan Agenda for Transportation Reform, eds. Bruce Katz and Robert Puentes (Washington, DC: Brookings Institution Press, 2005), 15–42.

23 John Pucher, “Public Transportation,” in The Geography of Urban Transportation, 3rd ed., eds. Susan Hanson and Genevieve Giuliano (New York: Guilford Press, 2004), 207.

24 http://www.apta.com/media/ releases/081208_ridership_surges.cfm.

25 Margaret Weir, Jane Rongerude, and Christopher K. Ansell, “Collaboration is Not Enough: Virtuous Cycles of Reform in Transportation Policy,” Urban Affairs Review 44, no. 4 (March 2009): 455–89.

26 Katz, Puentes, and Bernstein (see endnote 22).

27 For example, to demonstrate that the public had been consulted, the Chicago MPO (CATS) produced a 15-pound compilation of public comments that had never been analyzed. Weir, Rongerude, and Ansell, “Collaboration is Not Enough,” 476 (see endnote 25).

28 See Robert Cervero, “Effects of Light Rail and Commuter Rail Transit on Land Prices: Experiences in San Diego County,” Journal of the Transportation Research Forum 43, no. 1 (2004): 121–38.

29 Shelley Poticha, “Building Housing Near Transit: A Long-Lasting Affordability Strategy,” Congressional Testimony before the Appropriations Subcommittee on Transportation, Housing and Urban Development, and Related Agencies, U.S. House of Representatives, March 8, 2007. Poticha is President and CEO of Reconnecting America, Oakland, CA.

30 Center for Transit-Oriented Development and Center for Neighborhood Technology, The Affordability Index: A New Tool for Measuring the True Affordability of Housing

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Choice, Brookings Institution Urban Markets Initiative, Innovation Brief (January 2006), 10. Recognizing this saving, Fannie Mae created a Location Efficient Mortgage that enables borrowers to qualify for a larger loan if they are buying in areas that have lower average transportation costs.

31 John Pucher, “Public Transportation,” 212 (see endnote 23).

32 Dena Belzer et al., The Case for Mixed- Income, Transit-Oriented Development in the Denver Region (Oakland, CA: Center for Transit-Oriented Development, February 2007), 42.

33 One way to address this problem would be Pay-As-You-Drive car insurance. See “Transportation Affordability” (endnote 17).

34 Robert Cervero and Yu-Hsin Tsai, “San Francisco City CarShare: Travel-Demand Trends and Second-Year Impacts,” Institute of Urban & Regional Development, IURD Working Paper Series, Paper WP-2003-05 (August 1, 2003), http://repositories.cdlib. org/iurd/wps/WP-2003-05.

35 Directed by Congress, U.S. DOT and HUD have begun to collaborate on policies to promote affordable housing near transit. See Better Coordination of Transportation and Housing Programs to Promote Affordable Housing Near Transit, a Report to Congress from the U.S. Department of Transportation, Federal Transit Administration, and the U.S. Department of Housing and Urban Development, 2008. The HUD-FTA Interagency Working Group should continue to operate to identify legislation and administrative actions to better coordinate housing and transportation policies.

36 For example, the House Appropriations Subcommittee on Housing, Transportation and Urban Development, chaired by Rep. John Olver (D-MA), held a hearing with

a joint appearance by DOT Secretary Ray LaHood and HUD Secretary Shaun Donovan. In a joint press release, LaHood and Donovan announced a new partnership to coordinate housing and transportation to cut costs for working families, http://www.hud.gov/ news/release.cfm?content=pr09-023.cfm.

37 Present federal regulations do permit limited funds to be used for this purpose. The Metro system in Portland, OR, has used Congestion Mitigation and Air Quality (CMAQ) funds to acquire and sell land around transit stations for TOD, usually with an affordable housing component. PolicyLink, Equitable Development Toolkit: Transit Oriented Development, available at http://www. policylink.org.

38 Sarah Grady with Greg Leroy, Making the Connection: Transit-Oriented Development and Jobs (Washington, DC: Good Jobs First, March 2006).

39 Workforce housing is usually defined as housing that costs no more than 35 percent of the median wage in the area.

40 For a penetrating account of what happens “when work disappears” from communities, see William Julius Wilson, When Work Disappears: The World of the New Urban Poor (New York: Alfred A. Knopf, 1996).

41 Center to Protect Workers’ Rights, The Construction Chart Book: The U.S. Construction Industry and Its Workers, 4th ed. (Silver Spring, MD: Center to Protect Workers’ Rights, Center for Construction Research and Training, December 2007).

42 A recent study of 25 metropolitan areas found that hourly wages in construction (2004–2007) varied from $15.65 in the Dallas metropolitan area to $27.70 in the Chicago region. Todd Swanstrom, The Road to Good Jobs: Patterns of Employment in the Construction Industry (St. Louis, MO:

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Transportation Equity Network and Public Policy Research Center, U. of Missouri – St. Louis, 2008).

43 Center to Protect Workers’ Rights, The Construction Chart Book (see endnote 41).

44 Daniel Hecker, “Occupational Employment Projections to 2014,” Monthly Labor Review (November 2005): 70–101.

45 Calculation of the number of jobs produced is based on Thomas P. Keane, “The Economic Importance of the National Highway System,” Public Roads 59, no. 4 (1996): 16–21.

46 The act is named after its Republican sponsors, James J. Davis, a Senator from Pennsylvania who was Secretary of Labor under three presidents, and Representative Robert L. Bacon of Long Island, NY. For Davis- Bacon wage rates state by state: see http:// www.gpo.gov/davisbacon/allstates.html.

47 Lisa Ranghelli, Replicating Success: The Alameda Corridor Job Training & Employment Program (Washington, DC: Center for Community Change, 2002).

48 For more examples of TEN’s successes: see http://www.transportationequity.org.

49 For best practices in pre-apprenticeship programs, see Kathleen Mulligan-Hansel, Making Development Work for Local Residents: Local Hire Programs and Implementation Strategies That Serve Low- Income Communities (Milwaukee, WI: Partnership for Working Families, 2008), http://www.communitybenefits.org/ downloads/Making%20Development%20 Work%20for%20Local%20Residents.pdf.

50 The 30 percent standard has been shown to be achievable in a number of projects around the country, such as in the St. Louis I-64 partnering agreement. A copy of that agreement is available on the Transportation Equity Network website, http://www.

transportationequity.org.

51 Presently, the federal law permits one-half of one percent of surface transportation funds to be used for local workforce development. One percent would do a better job of meeting the need while still representing a small cost to the overall project.

52 See http://www.uspirg.org/home/ reports/report-archives/transportation/ transportation2/a-better-way-to-go. Similarly, research has shown smart growth transportation policies, such as “fix-it-first” highway projects or public transportation, create more jobs than new highways that fuel more sprawl. Phillip Mattera with Greg Leroy, The Jobs are Back in Town: Urban Smart Growth and Construction Employment (Washington, DC: Good Jobs First, 2003).

53 An example of the political problems this can cause is the lawsuit filed by the Los Angeles Bus Riders’ Union against massive expenditures on a light-rail system at the same time that bus service was being cut. In March 1999, the Bus Riders’ Union won a court ruling for 532 new buses and 1,500 new union jobs for drivers and mechanics. For a discussion of the tensions between environmentalists and advocates of the poor in the transportation arena, see Joel Rast, “Environmental Justice and the New Regionalism,” Journal of Planning Education and Research 25 (2006): 249–63.

54 Research has demonstrated that car ownership increases employment and wages for low-income persons. See Steven Raphael and Michael Stoll, “Can Boosting Minority Car-Ownership Rates Narrow Inter-Racial Employment Gaps?,” Working Paper W00- 002, Program on Housing and Urban Policy, University of California – Berkeley, http:// urbanpolicy.berkeley.edu, and Paul Ong, “Car Ownership and Welfare-to-Work,” School of Public Policy and Social Research, University of California – Los Angeles, February 26, 2001, http://www.uctc.net/papers/540.pdf.

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1 U.S. Department of Agriculture, Economic Research Service, “Global Food Markets: Global Industry Structure,” 2008, http://www.ers.usda.gov/Briefing/ GlobalFoodMarkets/Industry.htm (accessed January 31, 2009).

2 Food insecurity is said to exist whenever “the availability of nutritionally adequate and safe food, or the ability to acquire acceptable foods in socially acceptable ways, is limited or uncertain.” S. A. Anderson, ed., “Core Indicators of Nutritional Status for Difficult-to-sample Populations,” Journal of Nutrition 120 (1990): 1559–1600, 1560. Food insecurity ranges from a painful sensation of hunger, at its most severe, to families being relegated to a few inexpensive staple foods—such as macaroni and cheese—that do not alone make up a nutritious and varied diet. Inconsistent availability of food, lack of transportation to grocery stores, and skipping meals to keep food costs down all are indicators of food insecurity. Conversely, food security refers to access by all people at all times to a sufficient quantity of safe, nutritious, affordable, and culturally appropriate food for an active, healthy life, obtained through conventional sources.

3 In this paper, “access” is used to signify spatial proximity or convenient and affordable transportation to destinations. Proximity is central because low-income urban households display lower rates of automobile ownership and may need to rely for grocery shopping on walking, taking the bus, or rides from acquaintances. Social, cultural, and economic categories of access of food are also key to this paper; they are defined, however, by the term “food security” (see endnote 2).

4 For example, the top five grocery retail chains captured 48 percent of the market in 2007, double that in 1997, http://www.nfu.org/wp-

content/2007-heffernanreport.pdf (accessed January 19, 2009).

5 Brookings Institution, From Poverty, Opportunity: Putting the Market to Work for Lower-income Families (Washington, DC: Brookings Institution, 2006), http://www. brookings.edu/reports/2006/07poverty_ fellowes.aspx (accessed January 19, 2009); K. Pothukuchi, “Attracting Supermarkets to Inner-city Neighborhoods: Economic Development Outside the Box,” Economic Development Quarterly 19 (2005): 232–44; E. Eisenhauer, “In Poor Health: Supermarket Redlining and Urban Nutrition,” GeoJournal 53 (2004): 125; and R. W. Cotterill and A. W. Franklin, “The Urban Grocery Store Gap,” Food Marketing Policy Issue Paper 8 (Storrs, CT: Food Marketing Policy Center, University of Connecticut, April 1995).

6 Today, the top food retailers control their own supply chains and manage their own fleets of trucks, warehouses, and buying offices. For example, Kroger has roughly 30 distribution centers to serve its 2,500 supermarkets, and other leading chains do the same to fully integrate their supply chains as a key strategy for remaining profitable. See Oakland Institute Report, “Food Chain Consolidation in U.S., 2007,” http://www. foodpolicy.in/html/archive/2007/rep/ oakland1.htm (accessed January 19, 2009). See also M. Hendrickson et al., “The Global Food System and Nodes of Power,” Report prepared for Oxfam America, August 2008 (accessed March 24, 2009), paper can be downloaded by clicking on SSRN at http:// papers.ssrn.com/sol3/papers.cfm?abstract_ id=1337273; and Competition Commission, Groceries Market Roundtable Meeting (Amended Notes) (London, UK: October 9, 2006).

7 See, for example, a Canadian study: K. Larsen and J. Gilliland, “Mapping the

Chapter 7: Sustainable Food Systems: Perspectives on Transportation Policy

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Evolution of Food Deserts in a Canadian City: Supermarket Accessibility in London, Ontario, 1961–2005,” International Journal of Health Geographics 7 (2008), http://www. ij-healthgeographics.com/content/pdf/1476- 072X-7-16.pdf (accessed January 31, 2009). The study showed that in 1961, more than 75 percent of London’s downtown population lived within convenient access to grocery stores (i.e., a 10-minute bus ride combined with a 500-meter walk at the beginning or end of a bus trip). Because Canadian cities saw similar patterns of urban sprawl but at a lower intensity or scale than did most U.S. cities, it is safe to apply this study to U.S. cities as a general pattern.

8 M. A. Delucchi and J. Murphy, “How Large Are Tax Subsidies to Motor-vehicle Users in the U.S.?,” Journal of Transport Policy 15 (2008): 196–208.

9 For elaborations on this theme, see Brookings Institution, From Poverty, Opportunity: Putting the Market to Work for Lower- income Families (see endnote 5); D. Hendrickson, C. Smith, and N. Eikenberry, “Fruit and Vegetable Access in 4 Low-income Food Desert Communities in Minnesota,” Agriculture and Human Values 23 (2006): 371–83; M. Gallagher, Examining the Impact of Food Deserts on Public Health in Detroit (Chicago: Mari Gallagher Research and Consulting Group, 2007); M. Gallagher, Examining the Impact of Food Deserts on Public Health in Chicago (Chicago: Mari Gallagher Research and Consulting Group, 2006); S. N. Zenk et al., “Neighborhood Racial Composition, Neighborhood Poverty, and Spatial Accessibility of Supermarkets in Metropolitan Detroit,” American Journal of Public Health 95 (2005): 660–67; E. Bolen and K. Hecht, Neighborhood Groceries New Access to Healthy Food in Low-income Communities (San Francisco: California Food Policy Advocates, January 2003); and many others. The Brookings Institution study found, for example, that the average grocery

store in its sample of 2,384 low-income neighborhoods is 2.5 times smaller than the average grocery store in a high-income neighborhood. Also, there is about one mid- or large-sized grocer for every 69,055 residents in low-income neighborhoods, half the availability found in other neighborhoods. Access to only small grocery stores results in higher food prices for low-income shoppers. In particular, more than 67 percent of the same food products in its sample of 132 different products are more expensive in small grocery stores than in larger grocery stores.

10 T. C. Blanchard and T. A. Lyson, “Retail Concentration, Food Deserts, and Food Disadvantaged Communities in Rural America,” in Remaking the North American Food System, eds. C. C. Hinrichs and T. A. Lyson (Lincoln, NE: University of Nebraska Press, 2007); C. Wirth, R. Strochlic, and C. Getz, Hunger in the Fields: Food Insecurity among Farmworkers in Fresno County (CA: California Institute for Rural Studies, 2007); A. D. Liese et al., “Food Store Types, Availability, and Cost of Foods in a Rural Environment,” Journal of the American Dietetic Association 107 (November 2007): 1916–23; T. Blanchard and T. Lyson, “Food Availability & Food Deserts in the Nonmetropolitan South,” Southern Rural Development Center, 2006, http://srdc.msstate.edu/focusareas/health/ fa/fa_12_blanchard.pdf (accessed January 19, 2009); L. W. Morton et al., “Solving the Problems of Iowa Food Deserts: Food Insecurity and Civic Structure,” Rural Sociology 70 (2005): 94–112; L. W. Morton and T. C. Blanchard, “Starved for Access: Life in Rural America’s Food Deserts,” Rural Realities 1 (2007): 10; E. A. Bitto et al., “Grocery Store Access Patterns in Rural Food Deserts,” Journal for the Study of Food and Society 6 (2003): 35–48; C. Getz, “Perceived High Cost Deters Farmworkers from Eating Produce, According to UC Study,” University of California, News and Information Outreach, 2006, http://news.ucanr.org/

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newsstorymain.cfm?story=899 (accessed January 19, 2009); and P. Kaufman and S. M. Lutz, “Competing Forces Affect Food Prices for Low-income Households,” Food Review 20 (May–August, 1997): 8–12.

11 K. Morland and S. Filomena, “Disparities in the Availability of Fruits and Vegetables between Racially Segregated Urban Neighbourhoods,” Cambridge Journals Online 10 (2007): 1481–89; L. V. Moore, A. V. Diez-Roux, “Associations of Neighborhood Characteristics with the Location and Type of Food Stores,” American Journal of Public Health 96 (2006): 325–31; D. Block and J. Kouba, “A Comparison of the Availability and Affordability of a Market Basket in Two Communities in the Chicago Area,” Public Health Nutrition 9 (2007): 837–45; M. Gallagher, 2007 and 2006 (see endnote 9); J. Block, R. A. Scribner, and K. B. De Salvo, “Fast Food, Race/Ethnicity, and Income: A Geographic Analysis,” American Journal of Preventive Medicine 27 (2004): 211–17; K. Morland et al., “Neighborhood Characteristics Associated with the Location of Food Stores and Food Service Places,” American Journal of Preventive Medicine 22 (2002): 23–29, and many others.

12 For a documentation of the decline and rise of farmers’ markets over the 20th century, see H. Tangires, Public Markets and Civic Culture in Nineteenth Century America (Baltimore: Johns Hopkins University Press, 2003); A. Brown, “Farmers’ Market Research 1940– 2000: An Inventory and Review,” American Journal of Alternative Agriculture 17 (2002): 167–76.

13 Since 1994, when the USDA started to track growth in farmers’ markets, more than 3,000 farmers’ markets have opened nationally, reaching a total of 4,685 markets in August 2008. USDA, Economic Research Service, “Global Food Markets: Global Industry Structure,” 2008, http://www.ers.usda.gov/ Briefing/GlobalFoodMarkets/Industry.htm

(accessed January 31, 2009).

14 American Farmland Trust, “Farming on the Edge Report,” http://www.farmland.org/ resources/fote/default.asp (accessed January 19, 2009).

15 Surface Transportation Policy Project, “Surface Transportation and Poverty Alleviation,” n.d., http://www.transact.org/ library/factsheets/poverty.asp (accessed January 19, 2009); R. D. Bullard and G. S. Johnson, eds., Just Transportation: Dismantling Race and Class Barriers to Mobility (Gabriola Island, BC: New Society Publishers, 1997); and A. D. Gardenshire, “Economic and Sociodemographic Influences on Autolessness: Are Missing Variables Skewing Results?,” Transportation Research Record 1670 (1999): 13–16.

16 S. H. Babey et al., Designed for Disease: The Link Between Local Food Environments and Obesity and Diabetes (Los Angeles: California Center for Public Health Advocacy, PolicyLink, and UCLA Center for Health Policy Research, 2008), http://www.healthpolicy. ucla.edu/pubs/publication.asp?pubID=250 (accessed January 19, 2009); L. Mikkelsen, S. Chehimi, and L. Cohen, Healthy Eating & Physical Activity: Addressing Inequities in Urban Environments (Oakland, CA: Prevention Institute, 2007); M. Gallagher, 2007 and 2006 (see endnote 9); M. C. Wang et al., “Changes in Neighbourhood Food Store Environment, Food Behaviour and Body Mass Index, 1981–1990,” Cambridge Journals Online 11 (2007): 963–70; K. Morland, S. Wing, and A. V. Diez-Roux, “The Contextual Effect of the Local Environment on Residents’ Diets: The Atherosclerosis Risk in Communities Study,” American Journal of Public Health 11 (2002): 1761–67; and The Food Trust, “Food Geography: How Food Access Affects Diet and Health,” http://www.thefoodtrust. org/catalog/download.php?product_id=120 (accessed January 19, 2009).

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17 D. Rose and R. Richards, “Food Store Access and Household Fruit and Vegetable Use among Participants in the U.S. Food Stamp Program,” Public Health Nutrition 7 (2007): 1081–88; and K. Morland et al., “The Contextual Effect of the Local Environment on Residents’ Diets” (see endnote 16).

18 See, for example, Zenk et al., “Neighborhood Racial Composition” (endnote 9).

19 S. L. Handy, “Understanding the Link between Urban Form and Nontravel Behavior,” Journal of Planning Education and Research 15 (1996): 183–98; and J. Boivin and P. Matharu, “Bus Transit and Grocery Shopping in Detroit, Wayne State University Department of Geography and Urban Planning, unpublished paper, 2008.

20 S. L. Handy and K. Clifton, “Local Shopping as a Strategy for Reducing Automobile Travel,” Transportation 28 (2001): 317–46.

21 See, for example, K. Clifton, “Mobility Strategies and Food Shopping for Low- Income Families: A Case Study,” Journal of Planning Education and Research 23 (2004): 402–13.

22 This is an especially significant problem for the rural elderly. Food Security, Insecurity, and Hunger: Rural Food Access Patterns: Elderly Open-Country and In-Town Residents (Ames, IA: Iowa State University Extension, 2004); and K. Clifton, “Mobility Strategies” (see endnote 21).

23 N. Wrigley, “Understanding Store Development Programmes in Post-property- crisis UK Food Retailing,” Environment and Planning A 30 (1998): 15–35.

24 For recent statistics on national food insecurity, see, for example, M. Nord, M. Andrews, and S. Carlson, “Household Food Security in the United States, 2007,” USDA, Economic Research Service, Report #66,

2008, http://ers.usda.gov/Publications/ERR66/ ERR66.pdf (accessed January 19, 2009).

25 R. D. Bullard, G. S. Johnson, and A. O. Torres, eds., Sprawl City (Washington, DC: Island Press, 2000); R. D. Bullard and G. S. Johnson, eds., Just Transportation: Dismantling Race and Class Barriers to Mobility (Gabriola Island, BC: New Society Publishers, 1997); and Surface Transportation Policy Project, “Surface Transportation and Poverty Alleviation,” http://www.transact.org/library/factsheets/ poverty.asp (accessed January 19, 2009).

26 Food Research and Action Center, “Food Stamp Participation in May 2008 Sets Another Record High,” http://www.frac.org/ html/news/fsp/2008.05_FSP.htm (accessed January 19, 2009).

27 Food Research and Action Center, “A Guide to Food Stamp Outreach,” http://www.frac. org/html/federal_food_programs/programs/ fsoutreachprg.html#anchor826588 (accessed March 22, 2009).

28 C. Hefflin, “Who Exits the Food Stamp Program after Welfare Reform?,” http://www.ers.usda.gov/Briefing/ FoodNutritionAssistance/Funding/ RIDGEprojectSummary.asp?Summary_ID= 46. (accessed January 19, 2009).

29 A Fresno County, CA, study found that nearly half of all farm worker households were food insecure compared to 36 percent of all county households. The same study also found that just over half and only about 36 percent of those eligible used food stamps in the winter and summer, respectively. C. Getz, “Perceived High Cost Deters Farmworkers from Eating Produce, According to UC Study,” University of California, News and Information Outreach, 2006, http://news. ucanr.org/newsstorymain.cfm?story=899 (accessed January 19, 2009).

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30 T. Litman, “Transportation Affordability: Evaluation and Improvement Strategies,” Victoria Transport Policy Institute, 2007, http://www.vtpi.org/affordability.pdf. (accessed February 13, 2009).

31 E. Roberto, “Commuting to Opportunity: The Working Poor and Commuting in the United States,” Brookings Institution, 2008, http://www.brookings.edu/~/media/Files/ rc/reports/2008/0314_transportation_ puentes/0314_transportation_puentes.pdf (accessed February 13, 2009).

32 Surface Transportation Policy Project, “Surface Transportation and Poverty Alleviation,” http://www.transact.org/library/ factsheets/poverty.asp (accessed January 19, 2009).

33 M. Mauch and B. D. Taylor, “Gender, Race, and Travel Behavior: An Analysis of Household Serving Travel and Commuting in the San Francisco-Bay Area,” Transportation Research Record 1607 (1997): 147–53; and M. L. DeVault, Feeding the Family: The Social Organization of Caring as Gendered Work (Chicago: University of Chicago Press, 1991).

34 S. L. Handy and K. Clifton, “Local Shopping as a Strategy,” 331 (see endnote 20).

35 E. A. Bitto et al., “Grocery Store Access Patterns in Rural Food Deserts,” Journal for the Study of Food and Society 6 (2003): 35–48.

36 L. F. Alwitt and T. D. Donley, “Retail Stores in Poor Urban Neighborhoods,” Journal of Consumer Affairs 31 (1997): 139–64; C. Chung and S. L. Myers, “Do the Poor Pay More for Food? An Analysis of Grocery Store Availability and Price Disparities,” The Journal of Consumer Affairs 33 (1999): 276–96; and P. Kaufman and S. M. Lutz, “Competing Forces Affect Food Prices” (see endnote 10).

37 However, WIC rules do allow states leeway in deciding whether or how to

address transportation issues in making healthcare appointments. USDA, Food and Nutrition Service, Federal Register: “Special Supplemental Nutrition Program for Women, Infants, and Children (WIC): Miscellaneous Provisions,” Proposed Rule, 2002, http://www.fns.usda.gov/ cga/Federal-Register/2002/120202.pdf (accessed January 19, 2009). For example, in Michigan, WIC participants are allowed to seek transportation assistance for both healthcare as well as nutrition counseling appointments, whereas in West Virginia, only healthcare appointments are funded for transportation assistance. Other programs such as the Summer Food Service Program and senior nutrition programs are more sensitive to the transportation needs of their younger and older clients, respectively, and provide community grants for transportation assistance, http://www.summerfood.usda. gov/Community/transportation-grants.html (accessed March 24, 2009). Additionally, a small pot of USDA funding exists for farmers to bring product to market. Few studies exist on who benefits from this funding and how it is used.

38 Food Research and Action Center, “Rural Transportation Grants Successfully Increase Summer Food Participation,” 2006, http:// www.frac.org/afterschool/pdf/rural_ transportation_grants_report_2006.pdf (accessed February 12, 2009).

39 V. James Rhodes, The Agricultural Marketing System, 4th Ed. (Scottsdale, AZ: Gorsuch, Scarisbrick Publishers, 1993), cited in R. Pirog et al., Food, Fuel, and Freeways: An Iowa Perspective on How Far Food Travels, Fuel Usage, and Greenhouse Gas Emissions (Ames, IA: Iowa State University, Leopold Center for Sustainable Agriculture, 2001).

40 In March 2008, for example, wholesale food prices, an indicator of retail prices, rose the previous month at the fastest rate since 2003, with egg prices jumping 60

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percent from a year ago, pasta products 30 percent, and fruits and vegetables 20 percent, according to the Labor Department. R. Gavin, “Surging Costs of Groceries Hits Home,” Boston Globe, March 9, 2008, http:// www.boston.com/business/personalfinance/ articles/2008/03/09/surging_costs_of_ groceries_hit_home/ (accessed January 19, 2009).

41 R. D. Bullard et al., Sprawl City; R. D. Bullard and G. S. Johnson, Just Transportation: Dismantling Race and Class Barriers to Mobility (see endnote 25, first two citations); E. Roberto, “Commuting to Opportunity” (see endnote 31); and T. Litman, “Transportation Affordability” (see endnote 30).

42 B. Taylor and P. Ong, “Spatial Mismatch or Automobile Mismatch? An Examination of Race, Residence and Commuting in U.S. Metropolitan Areas,” Urban Studies 32 (1995): 1453–73.

43 P. Ong and E. Blumenberg, “Job Access, Commute and Travel Burden among Welfare Recipients,” Urban Studies 35 (1998): 77–94.

44 R. Strochlic et al., “An Assessment of the Demand for Farm Worker Housing and Transportation in Mendicino County” (California Institute for Rural Studies, August 2008). See also Rural Assistance Center (RAC), http://www.raconline.org/info_ guides/transportation/ (accessed January 30, 2009). According to the RAC, 40 percent of all rural residents live in areas with no public transportation, and another 28 percent live in areas with limited levels of service.

45 R. Strochlic et al., “An Assessment of the Demand for Farm Worker Housing and Transportation in Mendicino County” (see endnote 44).

46 For one 2007 example, see CBC News, “Van Packed with Farm Workers Crashes in B.C.,

Killing 3,” March 7, 2007, http://www.cbc.ca/ canada/british-columbia/story/2007/03/07/ bc-van-crash.html?ref=rss (accessed February 12, 2009). The article reports an accident in which three people were killed and several others injured after a van designed for 10 people but carrying 17 workers rolled over Highway 1 in B.C.’s Fraser Valley.

47 See, for example, M. C. Heller and G. A. Keoleian, Life Cycle-Based Sustainability Indicators for Assessment of the U.S. Food System (CSS00-04) (Ann Arbor, MI: University of Michigan, Center for Sustainable Systems, 2000). From a personal communication with Ken Dahlberg, Professor Emeritus at Western Michigan University (September 27, 2006), of the energy used in the U.S. food system, roughly 21 percent is used for agricultural production, 14 percent for transportation, 16 percent for processing, 7 percent for packaging, 7 percent for eating establishments, 4 percent for food retailing, and 31 percent for home food refrigeration and cooking.

48 In Michigan, the nation’s second most agriculturally diverse state (California is first), only about 10 percent of the $25.7 billion spent on groceries at home and for eating out went to the state’s producers. P. Cantrell, The New Entrepreneurial Agriculture (Benzie, MI: Michigan Land Use Institute, 2003), http://mlui.org/downloads/newag.pdf (accessed January 19, 2009). Similar trends exist in Iowa and other agricultural states. For example, see Pirog et al., Food, Fuel, and Freeways (see endnote 39).

49 M. Hora and J. Tick, From Farm to Table: Making the Connection in the Mid-Atlantic Food System (Washington, DC: Capital Area Food Bank of Washington, DC, 2001) (citation derived from R. Pirog et al., 2001; see endnote 39).

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50 This figure varies between 11 percent (Pirog et al., 2001) and 14 percent (Dahlberg, personal communication), suggesting that more new research is needed on this topic.

51 R. Pirog et al., Food, Fuel, and Freeways (see endnote 39).

52 For example, see D. Houston, J. Wu, and P. Ong, “Structural Disparities of Urban Traffic in Southern California: Implications for Vehicle-related Air Pollution Exposure in Minority and High-poverty Neighborhoods,” Journal of Urban Affairs 26 (2008): 565–92, for research related to the traffic that is generated by the Los Angeles (CA) port and its impacts on low-income and minority communities that are located nearby. Container traffic at the Ports of Los Angeles and Long Beach, CA, has tripled in the past 15 years, resulting in massive port-related heavy-duty diesel truck (HDDT) traffic on surface streets in the low-income and minority communities of Wilmington and western Long Beach adjacent to the ports. The volumes of HDDTs often reached 400 to 600/hour for several hours immediately upwind of sensitive land uses, such as schools, open-field parks, and residences. The documented health and environmental consequences of HDDT emissions raise serious public health concerns for the inhabitants who reside, work, attend school, or recreate in close proximity to roadways with HDDT traffic.

53 R. Pirog et al., Food, Fuel, and Freeways (see endnote 39).

54 Ibid.

55 R. Pirog and T. Van Pelt, “How Far Do Your Fruits and Vegetables Travel?,” Iowa State University, Leopold Center for Sustainable Agriculture, 2002, http://www.leopold. iastate.edu/pubs/staff/ppp/food_chart0402. pdf (accessed January 19, 2009).

56 R. Pirog et al., Food, Fuel, and Freeways, 33 (see endnote 39).

57 Pew Center on Global Climate Change, 2004, http://www.pewclimate.org/global-warming- basics/facts_and_figures/us_emissions/ usghgemsector.cfm (accessed March 24, 2009).

58 Roy Darwin, USDA, Economic Research Service, “Climate Change and Food Security,” 2001, http://www.ers.usda.gov/ publications/aib765/aib765-8.pdf (accessed March 23, 2009); and Food and Agriculture Organization, “Climate Change and Food Security,” 2007, http://www.un.org/ climatechange/pdfs/bali/fao-bali07-6.pdf (accessed March 23, 2009).

59 USDA, Economic Research Service, “Vegetables and Melons,” 2008, http:// www.ers.usda.gov/Briefing/Vegetables/ tomatoes.htm (accessed March 23, 2009).

60 USDA, “Foreign Agriculture Trade of the United States, Value of U.S. trade— Agricultural, Nonagricultural, and Total—and Trade Balance, by Fiscal Year,” updated January 13, 2009, http://www.ers.usda. gov/data/FATUS/index.htm#value (accessed January 19, 2009). According to the Census of Agriculture, in 2007, U.S. farms sold $297 billion in agricultural products while incurring $241 billion in production expenses, http:// www.agcensus.usda.gov/Publications/2007/ Online_Highlights/Fact_Sheets/economics. pdf (accessed March 22, 2009).

61 For example, see B. Meertens, “Agricultural Performance in Tanzania under Structural Adjustment Programs: Is It Really So Positive?,” Agriculture and Human Values 17 (2000): 333–46.

62 Indeed, both the history of supermarket development—seen, for example, in the rise of the first supermarkets of the Great Atlantic and Pacific Tea Company—and the

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current dominance of Wal-mart underscore the preeminent contribution of logistics and transportation to their retail dominance.

63 A. Smith et al., “Validity of Food Miles as an Indicator of Sustainable Development,” AEA Technology Environment, commissioned by Defra, 2005, https://statistics.defra.gov. uk/esg/reports/foodmiles/execsumm.pdf (accessed January 19, 2009); A. C. McKinnon and A. Woodburn, “Logistical Restructuring and Road Freight Traffic Growth: An Empirical Assessment,” Transportation 23 (1996): 141–61; M. D. Boehlje, S. L. Hofing, and R. C. Shroeder, “Value Chains in the Agricultural Industries,” Staff Paper # 99-10, August 31, 1999, http://www.centrec.com/ Articles/value_chain_ag_industry/value_ chains_in_ag_industry.pdf (accessed March 24, 2009); and A. Potter and B. Gardner, “Management of Transport Resources: Investigating the External Cost Impact of Integrated Inbound Logistics,” Logistics and Operations Management Section, Cardiff Business School, December 2006, http:// www.cardiff.ac.uk/carbs/research/working_ papers/logistics/Investigating%20the%20 external%20cost%20impact%20of%20 integrated%20inbound%20logistics.pdf (accessed March 24, 2009).

64 M. H. Sonstegaard, “Competitive Access to North American Rail,” Transportation Quarterly 57 (2003): 61–67.

65 See, for example, D. Pimental, “The Ecological and Energy Integrity of Corn Ethanol Production,” in Reconciling Human Existence with Ecological Integrity eds. L. Westra, K. Bossellmann, and R. Westra (London: Earthscan, 2008); and J. P. W. Scharlemann and W. F. Laurance, “How Green Are Biofuels?,” Science 319 (2008): 43–44. Relative to petroleum, nearly all biofuels diminish greenhouse gas emissions, although crops such as switchgrass easily outperform soy and corn. Scharlemann and Laurance argue, however, that the process

for selecting one biofuel over another needs to consider its full environmental effects. When deforestation by palm oil producers or nitrogen use by corn producers is considered and their energy and emissions taken into account, they conclude that corn or canola biofuels may be worse for global warming than simply burning fossil fuels.

66 Pimental, “The Ecological and Energy Integrity of Corn Ethanol Production,” 252– 53 (see endnote 67).

67 See, for example, C. F. Runge and B. Senauer, “How Biofuels Could Starve the Poor,” Foreign Affairs (May/June 2007); and USDA, Agricultural Marketing Service, Ethanol Transportation Backgrounder: “Expansion of U.S. Corn-based Ethanol from the Agricultural Transportation Perspective,” 2007, http://www.ams.usda.gov/AMSv1.0/ge tfile?dDocName=STELPRDC5063605&acct= atpub (accessed January 19, 2009). Increased demand for ethanol has raised prices, which has resulted in increased production but also the diversion of corn from food-related uses to fuel.

68 D. Cronin, Inter Press Service, “Development: ‘Food Miles’ Hard to Digest,” 2008, http:// ipsnews.net/news.asp?idnews= 41183 (accessed January 19, 2009).

69 Corn-based bioethanol has higher burden on environment and human health. A. Jha, “Biofuels More Harmful to Humans than Petrol and Diesel, Warn Scientists,” Guardian, February 2, 2009, http://www. guardian.co.uk/environment/2009/feb/02/ biofuels-health (accessed January 30, 2009). Researchers found the total environmental and health costs of gasoline are about 71 cents per gallon, while an equivalent amount of corn-ethanol fuel has associated costs of 72 cents to $1.45, depending on the use of chemicals in its production. However, there are high hopes for the next generation of biofuels, which can be made from organic

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waste or plants grown on marginal land that is not used to grow foods. These have less than half the combined health and environmental costs of standard gasoline and one-third of current biofuels.

70 USDA, Agricultural Marketing Service, Ethanol Transportation Backgrounder: “Expansion of U.S. Corn-based Ethanol” (see endnote 67).

71 Prevention Institute, “Setting the Record Straight: Nutritionists Define Healthful Food,” 2009, http://www.preventioninstitute.org/ sa/documents/SettingtheRecordStraight_ final_031309_000.pdf (accessed March 24, 2009). See also policy guides by American Planning Association, http://www.planning. org/policy/guides/adopted/food.htm; and American Public Health Association, http:// www.apha.org/advocacy/policy/policysearch/ default.htm?id=1361 (both accessed March 23, 2009); and Catholic Healthcare West Food and Nutrition Vision Statement, n.d.

72 The recommendations also have other benefits, such as household savings and job creation. For example, see T. Litman, “Smart Transportation Economic Stimulation: Infrastructure Investments That Support Strategic Planning,” 2009, http://www. vtpi.org/econ_stim.pdf (accessed: February 6, 2009). Litman argues that a reasonable scenario of aggressive fuel economy targets, investments in alternative modes, and supportive land use policies can reduce U.S. fuel consumption 20 percent–40 percent, saving future consumers $150–$350 billion annually in fuel and vehicle expenses; providing economic benefits from reduced fuel import costs of similar magnitude; producing additional economic, social, and environmental benefits; and generating one to two million additional annual domestic jobs.

73 For example, Numero Uno Market in Los Angeles, CA, capitalized on the population density and high transit-dependence in the inner city to establish a van shuttle

service that takes shoppers who spend at least $30 to their door. Coordinated with two Metropolitan Transportation Authority bus routes as a means for people to get to the store, Numero Uno’s nine-van shuttle service made it one of the top-five grossing supermarkets in Los Angeles. M. Vallianatos, A. Shaffer, and R. Gottlieb, Transportation and Food: The Importance of Access (Los Angeles: Occidental College, Center for Food and Justice, Urban and Environmental Policy Institute, 2002). See also a feasibility study, for example, which makes a business case for such shuttles when provided by supermarkets. D. Cassady and V. Mohan, “Doing Well by Doing Good? A Supermarket Shuttle Feasibility Study,” Journal of Nutrition Education Behavior 36 (2004): 67–70.

74 Dedicated or special bus routes to connect low-income consumers have been provided by Austin, TX, and Hartford, CT. See Vallianatos et al., Transportation and Food (see endnote 73).

75 For example, Belo Horizonte’s (Brazil) municipal food programs include vans that act as mobile grocery stores. Together, these programs—along with special stores that sell foods in bulk, farm stands, and popular restaurants in low-income neighborhoods— cost less than one percent of the city’s budget. C. Rocha, “Urban Food Security Policy: The Case of Belo Horizonte, Brazil,” Journal for the Study of Food and Society 5 (2001): 36–47.

76 Research on nonemergency medical transportation shows cost savings as well as increased welfare as a result of transportation subsidies. R. Wallace et al., “Access to Health Care and Non-emergency Medical Transportation: Two Missing Links,” Transportation Research Record 1924 (2005): 76–84; and P. Hughes-Cromwick and R. Wallace, Executive Summary: Cost- benefit Analysis of Providing Nonemergency Medical Transportation (Washington, DC:

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Transit Cooperative Research Program, Transportation Research Board, January 2006). Such a preventive health approach should be adopted in integrating transportation into federal nutrition programs.

77 An innovative example of farm worker transportation is demonstrated by Agricultural Industries Transportation Services, which provides vanpools to qualified farm workers in Kings, Tulare, and Fresno counties (CA), http://www.kartaits.com/ aitshome.htm (accessed January 19, 2009).

78 In addition to connecting rural food production with urban consumers, some cities are linking transportation and food production within the urban setting. In Tennessee, ISTEA funded a program that constructs community gardens along recreational corridors such as bike and walking trails. In Madison, WI, low-income gardeners working with the Community Action Coalition set up food gardens in highway rights of way, within cloverleaf intersections, and by the side of roads. See Vallianatos et al., Transportation and Food (endnote 73).

79 USDA, Cooperative State Research, Education and Extension Services, http://www.csrees. usda.gov/fo/communityfoodprojects.cfm (accessed March 24, 2009).

80 USDA, Summer Food Service Program, http:// www.summerfood.usda.gov/Community/ transportation-grants.html (accessed March 24, 2009).

81 R. Wallace et al., “Access to Health Care and Non-emergency Medical Transportation,” and P. Hughes-Cromwick and R. Wallace, Executive Summary: Cost-benefit Analysis (see endnote 76 for both citations).

82 For more information about these coalitions and organizations see: http://www.

transportationequity.org/; http://www. transportationforamerica.org/; http://www.transact.org/; http://www. completestreets.org/; and http://www. smartgrowthamerica.org/transportation.html.

83 For more information about these coalitions and organizations see: http://www.foodsecurity.org; http:// sustainableagriculture.net/; http://www.frac. org/; http://www.nffc.net/; and http://www. farmland.org/.

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1 “Fatally Hurt by Automobile,” The New York Times, September 14, 1899.

2 U.S. Department of Transportation, National Highway Traffic Safety Administration (NHTSA), Motor Vehicle Traffic Crashes as a Leading Cause of Death in the United States, 2005, Research Note DOT HS 810 936 (Washington, DC: National Highway Traffic Safety Administration, 2008).

3 Margie Peden et al., eds., World Report on Road Traffic Injury Prevention (Geneva, Switzerland: The World Health Organization, 2004).

4 Lawrence J. Blincoe et al., The Economic Impact of Motor Vehicle Crashes 2000, Report no. DOT HS-809-446 (Washington, DC: National Highway Traffic Safety Administration, 2002).

5 Ibid.

6 David Sleet, T. Bella Dinh-Zarr, and Ann Dellinger, “Traffic Safety in the Context of Public Health and Medicine,” in Improving Traffic Safety Culture in the United States: The Journey Forward, ed. AAA Foundation for Traffic Safety (Washington, DC: AAA Foundation, 2007).

7 National Center for Injury Prevention and Control, CDC Injury Fact Book (Atlanta: Centers for Disease Control and Prevention, 2006).

8 Larry Cohen and Susan Swift, “The Spectrum of Prevention: Developing a Comprehensive Approach to Injury Prevention,” Injury Prevention 5 (1999): 203–07.

9 Robert A. Caro, The Power Broker: Robert Moses and the Fall of New York (New York: Random House, Inc., 1975).

10 Reid Ewing et al., “Relationship between Urban Sprawl and Physical Activity, Obesity, and Morbidity,” American Journal of Health Promotion 18 (2003): 47–57.

11 Peter L. Jacobsen, “Safety in Numbers: More Walkers and Bicyclists, Safer Walking and Bicycling,” Injury Prevention 9 (2003): 205– 09.

12 Todd Litman, “Safe Travels: Evaluating Mobility Management Traffic Safety Benefits,” Victoria Transport Policy Institute, 2006, http://www.vtpi.org/safetr.pdf.

13 John Pucher and Lewis Dijkstra, “Promoting Safe Walking and Cycling to Improve Public Health: Lessons from the Netherlands and Germany,” American Journal of Public Health 93 (2003): 1509–16.

14 Fatality Analysis Reporting System, “National Statistics,” http://www-fars.nhtsa.dot.gov/ Main/index.aspx; and Centers for Disease Control and Prevention (CDC), “Web-based Injury Statistics Query and Reporting System (WISQARS),” http://www.cdc.gov/injury/ wisqars/index.html.

15 U.S. Department of Transportation, National Highway Traffic Safety Administration, 2007 Traffic Safety Annual Assessment, a brief statistical summary, DOT HS 811 017 (Washington, DC: National Highway Traffic Safety Administration, 2008).

16 NHTSA, Motor Vehicle Traffic Crashes (see endnote 2).

17 NHTSA, 2007 Traffic Safety Annual Assessment (see endnote 16).

18 Michelle Ernst, Mean Streets 2004: How Far Have We Come (Washington, DC: Surface Transportation Policy Partnership, 2004).

Chapter 8: Traffic Injury Prevention: A 21st-Century Approach

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19 John Pucher and Lewis Dijkstra, “Promoting Safe Walking and Cycling” (see endnote 13).

20 Fatality Analysis Reporting System, “National Statistics” (see endnote 14).

21 John Pucher and John L. Renne, “Socioeconomics of Urban Travel: Evidence from the 2001 NHTS,” Transport Quarterly 57 (2003): 49–77.

22 Fatality Analysis Reporting System, “National Statistics” (see endnote 14); and U.S. Department of Transportation, NHTSA, Traffic Safety Facts: Pedestrians, Data DOT- HS-810-994, (Washington, DC: National Highway Traffic Safety Administration, 2007).

23 CDC, “Web-based Injury Statistics Query and Reporting System” (see endnote 14).

24 Kenneth G. Keppel et al., Trends in Racial and Ethnic-specific Rates for the Health Status Indicators: United States, 1990–98 (Hyattsville, MD: National Center for Health Statistics, Centers for Disease Control and Prevention, 2002).

25 Satomi Imai and Christopher Mansfield, “Disparities in Motor Vehicle Crash Fatalities of Young Drivers in North Carolina,” North Carolina Medical Journal 69 (2008): 182–87.

26 John Pucher and John L. Renne, “Socioeconomics of urban travel” (see endnote 21).

27 CDC, “Pedestrian Fatalities—Cobb, DeKalb, Fulton, and Gwinnett Counties, Georgia, 1994–1998,” Morbidity and Mortality Weekly Report 48 (1999): 601–05.

28 Richard Marosi, “Pedestrian Deaths Reveal O.C.’s Car Culture Clash,” Los Angeles Times Orange County Edition, November 28, 1999.

29 Robert B. Voas, A. Scott Tippetts, and Deborah A. Fisher, Ethnicity and Alcohol-

Related Fatalities: 1990 to 1994 (Washington, DC: National Highway Traffic Safety Administration, 2000).

30 David Shinar, “Demographic and Socioeconomic Correlates of Safety Belt Use,” Accident Analysis and Prevention 25 (1993): 745–55; Joann K. Wells, Allan F. Williams, and Charles M. Farmer, Seat Belt Use among African Americans, Hispanics, and Whites (Arlington, VA: Insurance Institute for Highway Safety, 2001); Robert B. Voas, A. Scott Tippetts, and Deborah A. Fisher, Ethnicity and Alcohol-Related Fatalities (see endnote 29); and U.S. Department of Transportation, NHTSA, N.C.f.S.a.A., Traffic Safety Facts 2001: Pedestrians (Washington, DC: U.S. Dept. of Transportation, 2001).

31 U.S. Department of Transportation, NHTSA, N.C.f.S.a.A., Traffic Safety Facts 2001: Overview (Washington, DC: U.S. Department of Transportation, 2001).

32 U.S. Department of Transportation, Federal Highway Administration (FHWA), National Household Travel Survey. Older Drivers: Safety Implications (Washington, DC: Federal Highway Administration, 2006).

33 Ibid.

34 Ibid.

35 Catherine E. Staunton, Howard Frumkin, and Andrew L. Dannenberg, “Changing the Built Environment to Prevent Injury,” in Handbook of Injury and Violence Prevention, eds. L. Bonzo Doll et al. (New York: Springer, 2007)

36 The Americans with Disabilities Act (ADA) of 1990 is a civil rights law that protects against discrimination based on disability. Title III delineates how public accommodations, including transportation, should be accessible to disabled persons.

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37 Insurance Institute for Highway Safety, “Q&As: Speed and speed limits,” http:// www.iihs.org/research/qanda/speed_limits. html.

38 The National Committee for Injury Prevention and Control, Injury Prevention Meeting the Challenge (New York: Oxford University Press, 1989).

39 Ibid.

40 U.S. Department of Transportation, NHTSA, Traffic Safety Facts: Alcohol-Impaired Driving (Washington, DC: National Highway Traffic Safety Administration, 2008).

41 The National Committee for Injury Prevention and Control, Injury Prevention Meeting the Challenge (see endnote 38).

42 A blood alcohol content (BAC) of 0.08 percent means 0.08 grams of pure alcohol per 100 milliliters of a person’s blood. BAC laws with a 0.05 percent threshold are believed to be ideal and recommended by the American Medical Association because driving skills begin to deteriorate markedly at 0.05 percent BAC. Current political will, however, makes 0.08 percent BAC laws more politically feasible. Laws with a 0.08 BAC exist in all states and the District of Columbia; and Ruth A. Shults, Randy W. Elder, and David A. Sleet, “Reviews of Evidence Regarding Interventions to Reduce Alcohol-impaired Driving,” American Journal of Preventive Medicine 21 (2001): 66–88.

43 Ruth A. Shults et al., “Reviews of Evidence” (see endnote 42); and CDC, “Impaired Driving,” http://www.cdc.gov/ncipc/ factsheets/drving.htm.

44 Randy W. Elder et al., “Effectiveness of Sobriety Checkpoints for Reducing Alcohol- involved Crashes,” Traffic Injury Prevention 3 (2002): 266–74.

45 Vehicles with breathalyzers installed cannot start if the alcohol ignition interlock equipment determines that the driver is intoxicated. These mechanisms can be required in the automobile manufacturing process, but there is some controversy with regards to infringing on personal privacy; and U.S. Department of Transportation, NHTSA, Reducing Impaired-driving Recidivism Using Advanced Vehicle-based Alcohol Detection Systems, a report to Congress (Washington, DC: National Highway Traffic Safety Administration, 2007).

46 Ralph W. Hingson, Monica H. Swahn, and David A. Sleet, “Interventions to Prevent Alcohol-related Injuries,” in Handbook of Injury and Violence Prevention, eds. L. S. Doll et al. (New York: Springer, 2007).

47 David A. Sleet et al., “Interventions to Reduce Impaired Driving and Traffic Injury,” in Drugs, Driving and Traffic Safety, eds. J. C. Verster et al. (Basel, Switzerland: Birkhauser, 2009).

48 Maria L. Alaniz, “Alcohol Availability and Targeted Advertising in Racial/Ethnic Minority Communities,” Alcohol Health and Research World 22 (1998): 286–89; and Thomas A. LaVeist and John M. Wallace, Jr., “Health Risk and Inequitable Distribution of Liquor Stores in African American Neighborhood,” Social Science and Medicine 51 (2000): 613–17.

49 U.S. Department of Transportation, NHTSA, Overview Traffic Safety Facts 1996 (Washington, DC: National Highway Traffic Safety Administration 1996).

50 CDC, “Bicycle-related Injuries: Data from the National Electronic Injury Surveillance System,” Morbidity and Mortality Weekly Report 36 (1987): 269–71.

51 U.S. Consumer Product Safety Commission, “NEWS from CPSC: CPSC Issues New Safety Standard for Bike Helmets,” http://www.cpsc. gov/cpscpub/prerel/prhtml98/98062.html.

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Notes

52 Ibid.

53 Insurance Institute for Highway Safety, “Helmet Use Laws: Current U.S. Motorcycle and Bicycle Helmet Laws, http://www.iihs. org/laws/HelmetUseOverview.aspx.

54 U.S. Department of Transportation, NHTSA, Seat Belt Use in 2008—Overall Results (Washington, DC: National Highway Traffic Safety Administration, 2008).

55 Advocates for Highway and Auto Safety, “2009 Roadmap to State Highway Safety Laws,” http://www.saferoads.org/2009- roadmap-state-highway-safety-laws

57 U.S. Department of Transportation, NHTSA, States with Primary Enforcement Laws Have Lower Fatality Rates, Research Note DOT HS 810 557 (Washington, DC: National Highway Traffic Safety Administration, 2006).

58 U.S. Department of Transportation, NHTSA, Strengthening Safety Belt Use Laws— Increase Belt Use, Decrease Crash Fatalities and Injuries (Washington, DC: National Highway Traffic Safety Administration, 2004).

59 U.S. Department of Transportation, NHTSA, Traffic Safety Facts 2006: Motorcycles. (Washington, DC: National Highway Traffic Safety Administration, 2006).

60 NHTSA, Traffic Safety Facts 2006: Children (Washington, DC: National Highway Traffic Safety Administration, 2008).

61 Stephanie Zaza et al., Task Force on Community Preventive Services, “Reviews of Evidence Regarding Interventions to Increase the Use of Child Safety Seats,” American Journal of Preventive Medicine 21 (2001): 31–47.

62 U.S. Department of Transportation, 2009. Identifying Strategies to Reduce the Percentage of Unrestrained Young Children (Washington, DC: National Highway Traffic Safety Administration, 2009).

63 U.S. Department of Transportation, NHTSA, Announcement for Section 2003(b): Child Passenger Protection Education Grants (Washington, DC: National Highway Traffic Safety Administration, 2003).

64 Ibid.

65 National Safety Council, Special Issue: “Novice Teen Driving GDL and Beyond— Research Foundations for Policy and Practice Symposium,” Journal of Safety Research 38 (2007): 129–266.

66 Complete streets legislation was introduced in Congress by Rep. Doris Matsui (H.R. 1443) and Sen. Tom Harkin (S. 584) in 2008, but neither bill passed. Several states have passed their own complete streets bills, but broad federal recognition of the value and priority of complete streets in the next authorization of the surface transportation bill could encompass the versions in the Senate and the House of Representatives and signal a commitment to safe mobility among all travelers.

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Photo Credits: p.9 (left to right): Frances Twitty, www.pedbikeimages.org / Dan Burden p.21 (left to right): www.pedbikeimages.org / Dan Burden, www.pedbikeimages.org / Dan Burden p.22: Tim McCaig p.24: Jacom Stephens p.27 (left to right): D. Samuel Marsh Photography, Dave Huss p.33: D. Samuel Marsh Photography p.37: Todd Litman, Todd Litman p.57: Tomaz Levstek p.60: John Zellmer p.61: ©iStockphoto.com (ddoorly) p.63 (left to right): www.pedbikeimages.org / Dan Burden, David H. Lewis p.75: www.pedbikeimages.org / Dan Burden p.77: www.pedbikeimages.org / Dan Burden p.79 (left to right): www.pedbikeimages.org / Dan Burden, Atlanta Regional Commission p.82: PEDS.org p.83: Clevelandskyscrapers.com p.85: www.pedbikeimages.org / Dan Burden p.86: David Kolb (www.dkolb.org) p.88: www.pedbikeimages.org / Dan Burden p.89: www.pedbikeimages.org / Dan Burden p.99 (left to right): D. Samuel Marsh Photography, Jeffrey Zavitski p.103: ©iStockphoto.com (Rhoberazzi) p.105: Mario Savoia p.110: Lisa F. Young p.113 (left to right): Anna Bryukhanova, Claudia Dewald p.116: Lorie Slater p.122: Britta Kasholm-Tengve p.128: Bruce Block p.131 (left to right): Duncan Walker, www.pedbikeimages.org / Austin Brown p.140: Izabela Habur p.142: ©iStockphoto.com (tillsonburg)

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assignment 2/Inagami.pdf

Journal of Urban Health: Bulletin of the New York Academy of Medicine, Vol. 86, No. 5 doi:10.1007/s11524-009-9379-y * 2009 The Author(s). This article is published with open access at Springerlink.com

Body Mass Index, Neighborhood Fast Food and Restaurant Concentration, and Car Ownership

Sanae Inagami, Deborah A. Cohen, Arleen F. Brown, and Steven M. Asch

ABSTRACT Eating away from home and particularly fast food consumption have been

shown to contribute to weight gain. Increased geographic access to fast food outlets and other restaurants may contribute to higher levels of obesity, especially in individuals who rely largely on the local environment for their food purchases. We examined whether fast food and restaurant concentrations are associated with body mass index and whether car ownership might moderate this association. We linked the 2000 US Census data and information on locations of fast food and other restaurants with the Los Angeles Family and Neighborhood Study database, which consists of 2,156 adults sampled from 63 neighborhoods in Los Angeles County. Multilevel modeling was used to estimate associations between body mass index (BMI), fast food and restaurant concentration, and car ownership after adjustment for individual-level factors and socioeconomic characteristics of residential neighborhoods. A high concentration of local restaurants is associated with BMI. Car owners have higher BMIs than non-car owners; however, individuals who do not own cars and reside in areas with a high concentration of fast food outlets have higher BMIs than non-car owners who live in areas with no fast food outlets, approximately 12 lb more (p=0.02) for an individual with a height of 5 ft. 5 in. Higher restaurant density is associated with higher BMI among local residents. The local fast food environment has a stronger association with BMI for local residents who do not have access to cars.

KEYWORDS Multilevel, Fast food, BMI, Obesity, Mobility, Neighborhood, Restaurant

INTRODUCTION

In 2003, 41% of family food budgets in the USA were spent eating out.1 Fast food sales, which comprise more than 41% of restaurant sales, have increased from $16.1 billion in 1975 to $123.9 billion in 2003,1 and because consumption of fast food is associated with higher body mass index (BMI) in adults and children,2–4 there has been recent interest in understanding whether fast food consumption is causally related to the US obesity epidemic.2–7

Inagami is with the General Internal Medicine, Center for Health Equity Research and Promotion (CHERP) of the VA Pittsburgh Healthcare System and University of Pittsburgh in Pittsburgh, Pittsburgh, PA, USA; Cohen is with the Health, RAND Corporation, Santa Monica, CA, USA; Brown is with the General Internal Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Asch is with the HSR&D, VA Greater Los Angeles Healthcare System and University of California, Los Angeles, CA, USA.

Correspondence: Sanae Inagami, MD, MPH, General Internal Medicine, Center for Health Equity Research and Promotion (CHERP) of the VA Pittsburgh Healthcare System and University of Pittsburgh in Pittsburgh, Pittsburgh, PA, USA. (E-mail: [email protected])

683

It is unclear whether proximity to fast food outlets can explain the higher prevalence of obesity in low-income minority populations. Studies examining the location of outlets in relation to at-risk populations in Europe and the USA have yielded mixed results8–14,37,41–43; furthermore, the association between access to fast food restaurants and obesity has also been mixed.5,7,15–17,37–40 Mehta and Chang5

found an association between higher US county concentration of fast food restaurants and increased BMI; they also found that higher county concentration of full-service restaurants and total restaurants (fast food+full service restaurants) were associated with lower BMI. In another US study, Chou et al.7 found that higher concentration of total restaurants at the state level made the largest contribution to increasing weight. All the other cited studies showed no association between obesity and geographic access to fast food restaurants.

One reason for the mixed results in fast food studies may be due to how access and proximity are measured. Studies have used distance to the nearest fast food site15 and number of fast food outlets per 1,000 people16,17 to measure fast food exposure. Distance to the closest fast food site may be insensitive in measuring spatial accessibility in congested urban areas where one may find many fast food outlet options at similar distance from any reference point. Additionally, fast food per population measure is a supply ratio that grossly compares supply of fast food between different areas, which may misrepresent access because it does not incorporate any measure of distance or travel impedance.18 Concentration of fast food outlets as measured by locations per roadway mile may be a more appropriate measure of fast food access in modern urban environments because it accounts for spatial dispersion,19,20 which captures not only the fast food environment but its interaction with people.21 This may be particularly relevant in cities where individuals traverse the city and access fast food outlets along major and minor arterial roadways. Studies of alcohol outlet density measures have used alcohol outlet stores per roadway miles to show an association with violent assaults and with alcohol-related motor vehicle accidents.22,23

Related to this issue, fast food associations with BMI may not have been seen if factors, such as car ownership, that reduce barriers to alternative healthier food choices were not taken into account. Early studies have shown that neighborhood associations with health outcomes are stronger in individuals who do not own cars.27,44 No study has yet examined the role of car ownership in the association between access to fast food and obesity.

In this multilevel study, we examined whether fast food and general restaurant access, defined as the number of fast food outlets (or restaurants) per roadway miles per residential census tract, is associated with neighborhood socioeconomic levels and the BMI of its residents and whether this association is moderated by car ownership.

MATERIALS AND METHODS

Sample The Los Angeles Family and Neighborhood Survey (L.A.FANS) is a longitudinal study that was undertaken to understand how neighborhoods affect a variety of outcomes, including health in adults. We used data from L.A.FANS 2000–2001, the first wave of the study, a stratified random sample of 65 neighborhoods (census tracts from the 1990 Census) in Los Angeles County designed to oversample poor neighborhoods or those census tracts with a high proportion of residents living below the poverty line. Twenty

INAGAMI ET AL.684

tracts were selected from the very poor group (the top 10% of the poverty distribution in Los Angeles County), 20 from the poor strata (tracts in the 60th–89th percentile) and the remaining 25 tracts comprise the non-poor (tracts in the bottom 60% of the distribution). The choice of three strata and the specific cutoffs were based on analysis that examined the trade-off under different schemes between likely yield of welfare recipients and the concentration of the sample in a small number of high poverty areas.24 The household survey asked adults about household economic status, education, employment, income, marital history, and neighborhoods of residence. We eliminated respondents for whom either income (n=37) or BMI (n=273) was missing and for whom BMI was >47 (n=10) as well as those who listed their income as “0” but who were also employed (n=23). We also eliminated “other race/ethnicity” (n=74) because of small sample size. Our final sample size was 2,156 after eliminating two very large census tracts (n=88) that differed substantially from other tracts that were sampled, with areas larger than 126,000 acres and roadway miles greater than 350 miles. With these two tracts deleted, the largest census tract was 2,467 acres and contained 79 roadway miles.

Residential neighborhoods were identified at the census-tract level. The L.A. FANS sampling strategy was based on census tract boundaries identified from the 1990 Census (before data from the 2000 Census was available). When the survey was undertaken, in 2000–2001, data were extracted from the 2000 decennial census file. Because the 2000 census tract boundaries were somewhat different from the 1990 census tract boundaries, we computed census tract values for the old boundaries as a population-weighted average of all new census tracts falling within the old boundaries (only the population of the new census tract that falls within the old boundaries is used in constructing weights). For example, if a 1990 census tract was split into two 2000 census tracts, we computed a weighted average of the two census tracts where the weights are proportional to the 2000 tract population.

Measures Dependent Variable Respondents were asked to provide their height and weight; from this information, each respondent's BMI was calculated in kilograms per square meter. BMI was analyzed as a continuous outcome.

Fast Food Restaurants We obtained a list of all restaurants in Los Angeles County from the L.A. County Department of Public Health, Environmental Health Division and used the 1997 North American Industry Classification system codes to identify fast food restaurants (limited-service restaurants considered chains or franchises). Data on the fast food outlets were merged with individual-level data using census tracts (see Appendix A for complete list of outlets included). The number of fast food outlets within a census tract was divided by census tract roadway miles to create a fast food density measure for each census tract. Roadway miles came from Department of Commerce-2000 Census boundary files.

The fast food density measure was divided into three groups. The reference group included all census tracts with no fast food outlets. The second and third groups were created by dividing the remaining census tracts at the midpoint, defined as “low fast food density” (range, 0.025–0.15 fast food outlets/roadway miles) and “high fast food density” (range, 0.16–0.43 fast food outlets/roadway miles).

BMI, FAST FOOD AND RESTAURANT CONCENTRATION, AND CAR OWNERSHIP 685

Other Food Outlets Total food outlets per roadway miles within the census tract were also calculated using the list of all restaurants provided by the L.A. County Department of Public Health, Environmental Health Division. We specifically excluded restaurants that did not have public access, such as catering businesses, and those that were located within sports arenas, private clubs, cinemas, senior citizen centers, airports and hotels; we also excluded restaurants that were located in bars, pool halls, stores such as Kmart and Target, and restaurants within supermarkets (i.e., delis and bakeries).

The total restaurant measure was divided into three groups. The reference group included all census tracts with no restaurants. The second and third groups were created by dividing the remaining census tracts at the midpoint, defined as “total restaurants: low density” (range, 0.04–0.57 restaurants/roadway miles) and “total restaurants: high density” (range, 0.59–9.93 restaurants/roadway miles). The total restaurant measure included fast food outlets.

Residential Neighborhood Disadvantage Four summary statistics of census tracts in Los Angeles County were each standardized and combined to create a neighborhood “disadvantage score,” a well-described and often-used measure of socioeconomic status (SES)25: (1) percent living below the poverty line, (2) percent of households that are headed by a woman, (3) percent male unemployment, and (4) percent of families receiving public assistance. The continuous disadvantage score of residential neighborhoods was used for regression analysis, lower scores referring to higher SES areas. The score was categorized into four quartiles based on the distribution of all census tracts in Los Angeles and referred to as Very Low (the most disadvantaged), Lower Middle, Upper Middle, and Very High SES areas for Tables 1 and 2.

Car Ownership Respondents were asked in the survey whether or not they or their spouse/partner had one or more working cars. Car ownership was separated into two categories, those who had access to a working car and those who did not; the reference category refers to those respondents who did not have access to a working car.

Sociodemographic Controls Models were controlled for (1) gender; (2) age (logged); (3) education; (4) race/ethnicity (Latino, African-American, Asian, white); (5) employment; (6) marital status; (7) annual household income (logged); (8) immigrant status; and (9) car ownership (respondent or spouse/partner owns one or more working cars).

Weights The study used a multistage stratified sample design in which tracts, blocks within tracts, and households within tracts were sampled. Tracts were stratified by the percentage of the population in the tract who were in high poverty and by whether household included children under age 18. Sampling weights provided by L.A.FANS reflect both unequal probabilities of sample selection and household nonresponse.24

Weights were used as probability weights in HLM 6.02 (2004).26

Statistical Analyses Multilevel weighted linear regression models using HLM 6.02 (2004)26 were used to estimate simultaneously the association between BMI and the individual socio- demographic variables and residential neighborhood characteristics.

INAGAMI ET AL.686

Cross level interactions between fast food/total restaurant concentration (level 2) and car ownership (level 1) were examined to determine whether car ownership moderated the effect of fast food concentration on BMI.

RESULTS

Descriptive Statistics The 2,156 L.A.FANS respondents were predominantly young (mean age 39 years) and Latino (58%) as shown in the last column of Table 1. Thirty-eight percent of the adult sample resided in the lowest SES neighborhood quartile; nearly 70% of the total sample lived in the two lowest SES neighborhood quartiles.

Respondents missing BMI information had lower median income and were significantly (pG0.05) less likely to own a car, less likely to live in a Very High SES Area, and less likely to be white, employed, and college educated. Concentration of neighborhood fast food establishments did not differ between those missing and those not missing BMI information.

TABLE 1 Individual characteristics of respondents: L.A.FANS 2000–2001

Characteristics Values

Total Sample 2,156 Family income ($) Median (range) 26,550 (0–1,303,000) Mean (range) 52,338 Age Mean (range) 39.4 (18–91) BMI Mean (range) 26.6 (14.2–46.6) % Married 50 % Own car 76 % Female 57.6 % Employed 66 % College 20 % Immigrant 57 Race/ethnicity Latino 1,243 (58)a

African-American 198 (9)a

White 552 (26)a

Asian 158 (7)a

Residential area SES Very Low 824 (38)a

Lower Middle 651 (30)a

Upper Middle 346 (16)a

Very High 335 (16)a

Concentration fast food High 563 (26)a

Low 409 (19)a

Zero 1,184 (55)a

Concentration total restaurant High 868 (40)a

Low 874 (41)a

Zero 414 (19)a

aN (% total sample)

BMI, FAST FOOD AND RESTAURANT CONCENTRATION, AND CAR OWNERSHIP 687

Fast Food and other Restaurant Locations On average, Lower Middle SES census tracts had the highest total number of restaurants (15.7); Very High SES areas had the least, 5.7 (see Table 2). The number of restaurant establishments per roadway miles remained highest in the Lower Middle SES areas and lowest in the Very High SES areas.

On average, Upper Middle SES census tracts had the highest absolute number of fast food outlets, with 2.2 outlets; Very Low SES areas had the least, with 0.6 outlets (see Table 2). However, because census tract acreage and roadway miles increase as SES increases, the density of fast food outlets (per roadway mile) was highest in Lower Middle SES areas: 0.12 fast food outlets/roadway mile.

Multilevel Analyses Individual and neighborhood factors associated with BMI are shown in Table 3. Model A examines the role of total restaurant density, and model B, fast food outlet density; model C examines the interaction between car ownership and fast food outlet density, and model D examines the interaction between car ownership and total restaurant density. All models in Table 3 show that BMI was positively associated with car ownership and being Latino, older, and female.

Model A shows that higher density of total restaurants was associated with about a 1.0 BMI unit increase in residents who lived in the same census tract. In contrast to total restaurants, neither high nor low concentration of fast food outlets was associated with BMI (see model B). However, when we included the interaction between fast food establishments and car ownership (model C), residents living within an area of high fast food concentration were found to weigh 2.03 BMI units more than residents living in areas with no fast food outlets; this effect was nearly erased in those residents who owned cars living in areas with high fast food concentration (-1.86 BMI units). In addition, model fit was significantly improved (a decrease in deviance of two/variable is considered a statistically significant

TABLE 2 Measures of the fast food environment in the 63 census tracts* included in the analyses L.A.FANS 2000–2001

Very Low Lower Middle Upper Middle Very High Total

# Census tracts 25 19 10 9 63 # Total restaurants/tract Mean (SD) 9.1 (10.9) 15.7 (15.4) 15.3 (16.5) 5.7 (8.1) 11.6 (13.8) Range 0–58 0–58 0–52 0–23 0–58

# Fast food/tract Mean (SD) 0.6 (1.2) 1.7 (1.9) 2.2 (2.4) 1.6 (1.9) 1.3 (1.9) Range 0–4 0–6 0–8 0–5 0–8

# Fast food/roadway miles/tract Mean (SD) 0.05 (0.10) 0.12 (0.14) 0.10 (0.08) 0.09 (0.12) 1.3 (1.9) Range 0–0.35 0–0.43 0–0.23 0–0.37 0–0.43 Roadway miles/tract Mean (SD) 15 (7.6) 17 (13) 20 (6.2) 24 (11) 17.8(10.4) Range 6–37 9–79 13–35 9–46 6–79 Acres/tract Mean (SD) 389 (382) 425 (431) 559 (317) 866 (553) 498 (448) Range 83–1,664 159–2,467 245–1,223 176–1,725 83–2,467

*Two census tracts were eliminated. These census tracts had disproportionately large acreages (126,000 and 129,714 acres) and roadway miles (726 and 355 miles) compared to other census tracts. The largest census tract in the sample used for analysis contains 2,467 acres and 79 roadway miles.

INAGAMI ET AL.688

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BMI, FAST FOOD AND RESTAURANT CONCENTRATION, AND CAR OWNERSHIP 689

improvement in model fit). Though including the interaction between total restaurants and car ownership improved model fit, the interaction was not significant and did not change the association between BMI and total restaurant concentration. Eighty percent of respondents who lived in areas with high fast food concentration and 75% in areas with low fast food concentration owned cars; 73% of those who lived in areas with no fast food establishments owned cars.

Table 4 estimates the impact of fast food concentration (from model C) on weight for a reference individual who is 5 ft 5 in. tall, in whom 1 BMI unit would be equivalent to about 6 lb. Women who are 5 ft 5 in. would weigh 5.6 lb less than a 5 ft 5 in. man. Those of Latino ethnicity would be approximately 7.6 lb greater in weight compared to whites. Car owners on average weigh 8.5 lb more than non-car owners. Non-car owners who live in areas of high fast food concentration weigh 12 lb more than non-car owners who live in areas without fast food outlets and 2.7 lb (0.45 BMI units) more than car owners who live in areas of high fast food concentration. Those who do not own cars who live in areas without any fast food outlets (reference group) weigh the least (low concentration of census tract fast food alone was not associated with BMI). We found no significant interactions between race/ethnicity and immigration status. We also found no interactions between gender and car ownership, between gender and concentration of fast food, between gender and African-American race (β=0.88; p=0.49), nor between gender and Asian ethnicity (β=−1.93; p=0.10). We did note an interaction effect between Latino race and female gender (β=1.21; p=0.034), suggesting that increased weight in Latinos associated with proximity to restaurants is manifested by increased weight in women alone. Introducing the gender interaction with race/ethnicity did not alter the association between fast food and BMI nor the association among fast food, car ownership, and BMI. Though these interactions for the most part were not statistically significant, we suspect that, given greater power, there may be more gender, race/ethnicity, car ownership, and environmental interactions.

We also explored other measures to characterize the fast food environment. The number of fast food outlets/census tract area behaved similarly to fast food/ roadway miles. In contrast, number of fast food outlets/population density was not associated with BMI. We did not measure distance to nearest fast food establishment for this analysis.

TABLE 4 Predicted change in weight for a person 5 ft 5 in. tall

Characteristic Change in predicted weight (lb)a

Gender −5.6 Race/ethnicity Latino (vs. white) +7.6 African-American (vs. white) NS Asian (vs. white) NS Owns car High fast food concentration +9.5 Zero fast food concentration +8.5 Does not own car High fast food concentration +12.2 Zero fast food concentration 0

aAverage change in weight as derived from model C of Table 3 for a 5 ft 5 in. individual where 1 BMI unit is equivalent to approximately 6 lb

INAGAMI ET AL.690

DISCUSSION

Our study supports the possibility that local food environments influence the risk of obesity, especially among adults without cars and living in proximity to a large number of fast food outlets.27 Those able to travel farther may have wider access to healthier food products, while those limited to their neighborhoods may be more likely to purchase energy-dense foods that contribute to weight gain.28–31 While all residents appear to be affected by the concentration of restaurants, the magnitude of the magnitude of effect of fast food outlets is much smaller for residents able to travel by car than for individuals without cars. Car ownership may reduce the local effect of fast food outlets in the neighborhood, while lack of car access appears to exacerbate it. Those who do not own cars may be more likely to visit fast food outlets than most costly full-service restaurants in their neighborhood.

Our use of roadway miles as a measure of fast food and restaurant density in Los Angeles suggests that measures of access by car or by foot for day-to-day activities may be a more relevant measure of exposure than the number of fast food establishments per population density or most proximate fast food location. The measure appears to be particularly germane in urban environments where fast food establishments may be located along roads in strip mall developments. However, these findings may not be applicable to data from Europe or in cities with high population density and with well-developed public transportation systems. Furthermore, our findings underscore the need to take local development and planning patterns into account when considering neighborhood effects on public health indicators.

Our study showed that total restaurant concentration was associated with higher BMI, whereas Mehta and Chang5 found that it was associated with lower BMI. Two factors may explain the different outcomes in our study; they did not include car ownership in their models and also analyzed their data at the level of the county. While Mehta and Chang5 focused on county differences in BMI of its residents, our study focused on the differences in the local environments within one county and sought to explain whether these local differences were associated with the differences in BMI amongst disparate populations. Our study suggests that it is the widespread easy access to prepared food locally, regardless of whether or not it is “fast food,” that is associated with increased weight, but that “fast food” appears to be particularly associated to increased weight in residents not owning cars. Though populations within urban counties like Los Angeles are increasing in weight, urban residents have been shown to have lower BMI compared to their rural counter- parts32–34; this may explain Mehta and Chang's findings that showed lower BMI in residents of counties with greater number of total restaurants.

Although some studies have found fast food access to be more concentrated in low-income and ethnic minority areas,8–10 in our study the density of fast food outlets appears to be more concentrated in middle-income areas and least concentrated in the lowest income areas.12,13 Therefore, fast food access alone cannot explain residential SES associations with BMI in Los Angeles. The food environment is complex, and exposure to different types of food outlets depends upon both urban design and access to transportation.

Limitations The study is cross-sectional in nature and thus cannot prove causality. Our study cannot determine whether the effect we are seeing using the fast food measure is due to fast food access specifically or general access to restaurants or to other factors

BMI, FAST FOOD AND RESTAURANT CONCENTRATION, AND CAR OWNERSHIP 691

related to commercial development. In addition, detailed individual information regarding measures of the specific food eaten and physical activity was not available. Another concern is that self-reported height and weight are often underestimated and vary significantly among different race/ethnic groups35 and gender.36 However, underestimation would most likely underestimate the associations found in our study; on the other hand, variations in self-report among different race/ethnic groups would bias our study in directions unknown. While eliminating those missing BMI could have biased the results, they were equally distributed among the groups residing in high and low fast food concentration areas, so the likelihood of bias resulting from confounding is reduced. Bias may also result from the sampling strategy used, but weights were used to offset oversampling from poor areas in Los Angeles County. Lastly, boundaries that affect people's health are not necessarily fixed within census tracts.

CONCLUSIONS

Combating the obesity epidemic requires an understanding of the factors that contribute to it, both at the individual and neighborhood level. Those residents most vulnerable to barriers to healthy eating in their local food environment appear to be those who do not own cars. The relationship of access to fast food and BMI, illuminated by the interaction with car ownership, suggests that limiting fast food density, especially where a large proportion of the population do not have cars, may be an important measure to help curb the obesity epidemic. Facing higher levels of obesity and diabetes levels and the highest concentrations of fast food restaurants, the City Council currently is considering a proposal to ban new fast food restaurants in South Los Angeles.

ACKNOWLEDGMENTS

We are indebted to Aimée Bower for statistical programming. We thank ATS statistical consulting group for assistance with statistical modeling. We thank Los Angeles County Department of Public Health—Terrance Powell, Bureau Director Food Inspection Bureau and Michael Doom Environmental Health Specialist IV, MIS.

This study was supported in part by HRSA-MCH Grant # R40MC00303 (Deborah Cohen, PI) and the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, and is the result of work supported with resources and the use of facilities at the Center for Health Equity Research and Promotion at VA Pittsburgh Healthcare System in Pittsburgh, PA.

OPEN ACCESS This article is distributed under the terms of the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

APPENDIX A

Fast food establishments: McDonald's, Starbucks, Baskin-Robbins, Carl's Jr., Burger King, Taco Bell, Jack in the Box, Arby's, 7-Eleven, Subway, In-N-Out Burger, Kentucky Fried Chicken, Domino's Pizza, El Pollo Loco, Panda Express, Pizza Hut,

INAGAMI ET AL.692

Quiznos, Little Caesar's Pizza, Der Wienerschnitzel, Winchell's Donuts, Popeye's Chicken, Papa John's Pizza, Wendy's, Baja Fresh Mexican Grill, Hong Kong Express, Yoshinoya, Del Taco, Pizza Man, China Express, Tacos Mexico, Togo's Eatery, Round Table Pizza, Fatburger, La Salsa.

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BMI, FAST FOOD AND RESTAURANT CONCENTRATION, AND CAR OWNERSHIP 695

  • Body Mass Index, Neighborhood Fast Food and Restaurant Concentration, and Car Ownership
    • Abstract
    • Introduction
    • Materials and Methods
      • Sample
      • Measures
      • Statistical Analyses
    • Results
      • Descriptive Statistics
      • Fast Food and other Restaurant Locations
      • Multilevel Analyses
    • Discussion
      • Limitations
    • Conclusions
    • Acknowledgments
    • Appendix A
    • References

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Journal of Planning Literature

DOI: 10.1177/0885412204267680 2004; 19; 147 Journal of Planning Literature

Chanam Lee and Anne Vernez Moudon Transportation Planning Practice and Research

Physical Activity and Environment Research in the Health Field: Implications for Urban and

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10.1177/0885412204267680ARTICLEJournal of Planning LiteraturePhysical Activity

Physical Activity and Environment Research in the Health Field: Implications for Urban and Transportation Planning Practice and Research

Chanam Lee Anne Vernez Moudon

This article reviews literature from the health field investigat- ing the characteristics of environments that support or hinder physical activity. This literature shows that physical activity is associated with objective and subjective measures of acces- sibility to recreational facilities and local destinations, as well as with neighborhood safety and visual quality. Walking and biking emerge as prominent forms of physical activity and occur primarily in neighborhood streets and public facilities, suggesting that building walkable and bikable communities can address health as well as transportation concerns. The studies help advance environment-behavior research related to urban and transportation planning. They identify behav- ioral and environmental determinants of physical activity and employ rigorous data collection methods and theoretical frameworks that are new to the planning field. The article concludes that multidisciplinary research will likely yield promising results in identifying the aspects of environments that can be modified to encourage physical activity and physi- cally active travel.

Keywords: physical activity; walking; biking; environmental determinants; transportation

This article introduces urban and transportation planning audiences to a body of literature originating from the public health field. The literature consists of twenty recently published empirical studies address- ing the environmental characteristics that influence physical activity, including walking and biking.

Understanding and promoting physical activity demand multidisciplinary approaches (Sallis, Bauman, and Pratt 1998; King et al. 2002). This article relies on a

CHANAM LEE is an assistant professor at Texas A&M Univer- sity, College Station. This work was conducted during her doctoral studies at the University of Washington, Seattle. Her research areas are physical activity, health, urban form, and nonmotorized trans- portation. She has worked professionally as a land planning consul- tant, landscape architect, and urban planner.

ANNE VERNEZ MOUDONIS, Dr. ès. Sc., is a professor of archi- tecture, landscape architecture, and urban design and planning at the University of Washington, Seattle. She is president of the Inter- national Seminar on Urban Morphology, a faculty associate at the Lincoln Institute of Land Policy, a fellow of the Urban Land Insti- tute, and a national adviser to the Robert Wood Johnson Foundation Program on Active Living Research. Her books include Built for Change: Neighborhood Architecture in San Francisco (MIT Press, 1986), Public Streets for Public Use (Columbia University Press, 1991), and Monitoring Land Supply With Geographic Information Systems (with M. Hubner, John Wiley, 2000).

Journal of Planning Literature, Vol. 19, No. 2 (November 2004). DOI: 10.1177/0885412204267680 Copyright © 2004 by Sage Publications

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multidisciplinary framework that connects physical activity from the health perspective to the transporta- tion perspective. Also, the importance of physical envi- ronments in supporting walking and biking brings in a third player, the urban design and planning profes- sions, that have the capability to intervene in the envi- ronment (Figure 1) (Lee and Moudon 2001).

A few recently published review articles have taken a similar multidisciplinary approach to physical activ- ity. Frank and Engelke (2001) connect public health and urban planning. They review selected empirical evi- dence showing the health benefits of physical activity and environmental influences on physical activity and on modes of travel. Handy et al. (2002) bring the urban and transportation planning literature to the public health audience. Saelens, Sallis, and Frank (2003) address the same audience with a focus on empirical studies from transportation planning that analyze the impact of environments on walking and biking. Miss- ing is a systematic review for planning audiences of the public health literature dealing with the environmental determinants of physical activity. This article fills the gap and examines lessons for future practice and research.

Public health research sorts physical activity into four purpose-related categories: (1) recreational or lei- sure time activity, (2) work-related activity, (3) house-

hold-related activity, and (4) transportation-related activity (Centers for Disease Control and Prevention [CDC] 1996). Roberts et al. (1996) state that walking and biking are unique forms of physical activity because they transcend these traditional physical activity classi- fications. Walking and biking figure prominently as popular forms of physical activity, as they are accessi- ble, affordable, and readily incorporated into one’s daily routine. They also begin to address challenges that both health and transportation professionals face, namely, the preponderance of sedentary life styles and the increased dependence on automobile travel. At the same time, any effort to promote walking and biking as means of active transportation must take into account the impediments to walking and biking brought by environments built after World War II, which have been shaped primarily for and by automobiles. As the major- ity of the country’s population now lives in postwar, automobile-oriented environments (Pendall, Fulton, and Harrison 2000), health and transportation profes- sionals need to work closely with urban designers and planners to address environmental factors that support or hinder physically active travel.

The studies reviewed in this article have already shaped large research- and community-based pro- grams promoting active living environments.1 They provide insights into the relationship between, and the

148 Journal of Planning Literature

FIGURE 1. Conceptual Framework for Multidisciplinary Research and Polity for Physical Activity Promotion

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methodological challenges of research on, physical activity and environment.

SIGNIFICANCE AND PURPOSE

Urban and transportation planning professionals have paid a considerable amount of attention to the impact of the built environment on travel patterns (e.g., Ewing and Cervero 2001; Boarnet and Crane 2001; Handy 1996; Steiner 1994). The effects of the built envi- ronment on travel mode choice and the potential for the environment to be modified to reduce automobile use have been extensively studied. However, research find- ings still remain tentative especially on nonmotorized travel behaviors and, therefore, the subject of continued debates (Crane 1996). Methodological problems generic to this type of study include (1) complex and interrelated variables that are often spatially clustered and/or nested, (2) numerous confounding factors, (3) limited data availability on nonautomobile travel and environments, (4) difficulty in effectively quantifying the built environment, (5) the use of large spatial and analytic units of analyses, and (6) difficulties in estab- lishing causality (Federal Highway Administration [FHWA] 1999; U.S. Department of Transportation [USDOT] 2000). Also, parallel transportation research focuses on environmental variables limited to roadway conditions. Personal and social determinants of walking and biking are rarely addressed (Moudon and Lee 2003).

A few reviews of the public health research on the determinants of physical activity exist already (e.g., Humpel, Owen, and Eva 2002; National Public Health Partnership [NPHP] 2001; Sallis, Bauman and Pratt 1998: Seefeldt, Malina, and Clark 2002). These reviews are written primarily for the health audience, and, with the exception of Humpel et al., they tend to focus on studies dealing with personal and social determinants of physical activity. Their discussion of physical envi- ronmental determinants is limited, possibly due to a broad and often loose definition of environments in the public health research published to date (Saelens, Sallis, and Frank 2003). In contrast, this article provides a structured review of empirical studies concerned with community-based, physical environmental determi- nants of physical activity. These studies contribute to urban and transportation planning in the following ways: (1) they further the testing of specific physical environmental variables that are associated with physi- cal activity, including walking and biking; (2) they point to neighborhood places where people are engaged in physical activity; (3) they identify barriers perceived to be present in their environment discouraging people from being more active; and (4) they introduce method-

ological and theoretical approaches that can be useful for planning research. In addition, this article employs a c o n c e p t u a l f r a m e w o r k t h a t c a n f a c i l i t a t e t h e c l a s s i f i c a t i o n a n d e v a l u a t i o n p r o c e s s o f t h e environmental variables used in the studies reviewed.

This review has three purposes. The first is to high- light the studies’ key findings confirming walking as the most common type of physical activity and identify preferred places for, and perceived barriers to, physical activity. The review proceeds to examine the environ- mental variables used, acknowledging those with strong empirical evidence for supporting physical activity (see the appendix for a classification of the stud- ies based on the type of measures, objective and/or sub- jective, used for the independent variables capturing environments). Third, lessons are drawn from both the findings and the theoretical and methodological frame- works of the reviewed studies. The article concludes with a discussion of the findings’ implications for prac- tice and research in promoting active living, possibly filling gaps or strengthening existing knowledge in urban and transportation planning fields.

METHODOLOGICAL FRAMEWORK OF THIS REVIEW

The structure of this review is based on the criteria employed for the literature selection and the Behavioral Model of Environment (BME) as a conceptual construct to evaluate the chosen studies’ environmental variables and key findings.

Criteria for Literature Selection

Twenty public health studies are chosen for this review, based on their contribution to building empiri- cal evidence of community-based physical environ- mental determinants of physical activity. The studies focus on outdoor environments and lifestyle-based physical activities. They consider various types of physical activity, including, but not limited to, walking and biking. Excluded is research dealing solely with private and indoor environments (e.g., home, school or work-site environment, interior building design), small environmental cues (e.g., signs next to elevators), or social and policy-related environmental factors (e.g., advocacy efforts, school-based programs, and laws and regulations).

Keyword searches of several computerized data- bases, including MedLINE, PsycINFO, and Web of Sci- ence, and publication searches from the federal and local public health agencies identified the twenty stud- ies. Keywords included walk, bike, bicycle, cycle, physical activity, environment, community, determinant, environ- mental determinant, environmental factor, facilitator, enabler, barrier, correlate, neighborhood, neighborhood factor,

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and neighborhood effect. The initial literature search was conducted during September 2002 and periodically updated until June 2003.

Use of the Behavioral Model of Environment

Physical environmental factors influencing physical activity are numerous and subject to complex interac- tions among themselves. A theoretical model can become useful, as it serves to conceptualize and operationalize environmental factors and their rela- tionships (Saelens, Sallis, and Frank 2003). This review employs a BME (Moudon and Lee 2003), which identi- fies the generic parts of environments affecting outdoor physical activity, specifically walking and biking. The BME also points to areas where interventions can be

made to better support these activities (Figure 2). The model organizes classes of variables characterizing the three components of the environment for promoting walking and biking: origin/destination (OD), route (R), and area (A).

THE ORIGIN AND DESTINATION OF THE WALKING

OR BIKING TRIP (ORIGIN/DESTINATION OR OD)

Any given walking and biking trip starts and ends at certain points. The types and locations of origins and destinations play a determinant role in one’s decision to walk or bike (e.g., Goldsmith 1992; USDOT 1995; Steiner 1998; Rutherford et al. 1995; Handy 1996). Trip destinations also relate to trip purpose. Regular com- mute-trip destinations include work site and school,

150 Journal of Planning Literature

FIGURE 2. Behavioral Model of Environment: Three Components of Origin/Destination, Route, and Area. SOURCE: Moudon and Lee (2003, 23). Used with permission. NOTE: R1 = airline route to destination; R2 = street network route to destination; R3 = recreational route.

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and social or shopping-trip destinations include gro- cery stores, malls, restaurants, coffee shops, parks, and so on. Trip origins can vary depending on how an indi- vidual trip or a trip chain is defined, but home or work locations generally serve as common origins. Destina- tions must be relatively proximate to origins in order to allow for the option to walk or bike. Points of origin and destination are spatially different for transportation but may be the same for recreation or exercise (e.g., walking around the neighborhood).

THE CHARACTERISTICS OF THE ROUTE

TAKEN FOR THESE TRIPS (ROUTE OR R)

The characteristics of the route between origin and destination consist of not only the physical conditions of, and along, the roadway but also the quality influenc- ing the safety, convenience, comfort, and enjoyment of walkers and bikers. The combination of these character- istics affects one’s decision to walk or bike and how long one is willing to walk or bike (e.g., Rapoport 1987; Corti, Donovan, and Holman 1997). Roadway charac- teristics are commonly measured as the number of vehi- cle lanes, vehicular speed, slope, and presence of side- walks and bike lanes, as well as the number of cars, bikers, or people on the roadway. Route qualities are often measured subjectively as the users’ rating of per- ceived safety, convenience, and visual quality of the roadway and roadside environments.

THE CHARACTERISTICS OF THE AREAS AROUND

ORIGIN AND DESTINATION PLACES (AREA OR A)

Area characteristics consist of social and behavioral aspects of the physical environment, such as the uses of land, activities that take place, and the intensity of these uses and activities. Population density, floor area of commercial buildings, street block size, and number of street intersections are a few common examples of vari- ables used. They are often measured objectively, using publicly available spatial and/or tabular databases (Ewing and Cervero 2001). Subjective measures of the area component include people’s perception of the area or neighborhood quality, such as safety from crime, friendliness, and enjoyable scenery.

The area component concerns the volumes of, and the choices of, routes and activities available for walk- ers and bikers. The intensity and mix of land uses in an area affect how much potential and actual walking or biking activities the area will generate or attract (FHWA 1999; Moudon et al. 2001). The overall patterns of street networks (e.g., small grid, large grid, culs-de-sac, loops) are considered as an area component in this model, while the characteristics of individual street seg- ments belong to the route component. The types of street networks along with the land uses patterns affect

the level of choices that people can have in the area. For example, small gridlike streets and mixed land uses provide more alternative routes and often various travel modes, such as transit, when moving from the origin to destination.

Considerations of environment from all three com- ponents of the BME are important, and these compo- nents are not mutually exclusive of each other. Many variables address more than one component of the BME (Figure 3). For example, measures of accessibility to destinations often overlap with both the OD and the R components, and both aspects of accessibility influence one’s decision to walk or bike. Having a destination located within a walkable or bikable distance from home (OD) allows for the option to walk or bike. At the same time, the route quality (R), such as sidewalk or bike lane connectivity, quality of the roadside environ- ment, and street-crossing conditions, influence one’s actual decision to engage in walking or biking.

This model serves as a conceptual framework for discussing the findings of this review, especially in the review of environmental variables tested in the studies to influence physical activity, walking, and biking.

METHODS USED IN THE STUDIES

Tables A1 through A4 in the appendix provide an overview of the methodologies used in the chosen stud- ies. Table columns are lettered (A through I) to guide the discussion of each element of the methods. Included in this section are the study population and sample; theo- retical framework; dependent variables capturing dimensions of physical activity, including walking and biking; independent variables classified into objective and/or subjective measures; confounding variables controlled for; data collection methods; and statistical techniques for data analyses.

Study Population (A) and Sample (B)

Study populations are mainly adults in general but also include children, older adults, minorities, stu- dents, and women. Sample sizes for the quantitative studies (Tables A1 through A3) are large, ranging from a few hundreds to more than one hundred thousand. Several studies use existing population-based surveys, resulting in relatively large sample sizes. The surveys include the Behavioral Risk Factors Surveillance Sys- tem (BRFSS) (CDC n.d.) and the National Health and Nutrition Examination Survey (NHNES) from the United States and the Australian Activity Survey (AAS) from Australia.

A majority of the studies employ probability (or ran- dom) sampling techniques, often incorporating cluster- ing and stratification strategies. Probability sampling

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ensures the generalizability of study findings to large populations. The technique is less common in the plan- ning field where primary data collection efforts are less frequent and limited.

Theoretical Framework (C)

The social ecological perspective provides a broad frame of reference for studies reviewed here, emphasiz- ing the dynamic interplay between the personal behav- ioral and environmental factors (Sallis and Owen 1997; Stokols 1992). In contrast to traditional health behavior theories that focus on the role of personal factors on behavior, this perspective stresses the importance of both sociocultural and physical environmental factors in behavior change.

The social ecological approach has a foundation in social cognitive theory (Bandura 1986). First introduced as social learning theory by Bandura (1977), social cog- nitive theory is based on the assumption that individu- als are generally motivated to engage in behaviors that will result in rewards and to avoid punishments (Bandura 2001). The theory focuses on motivational fac- tors and self-regulatory mechanisms that contribute to a person’s behavior, in addition to environmental fac- tors. It explains human behavior in terms of a continu- ous reciprocal interaction between individual, behavioral, and environmental influences.

Social cognitive theory has been widely adopted in the area of health promotion (Seefeldt, Malina, and Clark 2002). The same concepts of multi-level, interac- tive influences on behavior change are used in the social ecological perspective (e.g., Baker et al. 2000; McLeroy et al. 1988; Sallis and Owen 1997; Stokols 1992). The lat-

ter views behavior as determined by personal, social, organizational, community and policy factors, and emphasizes the need for the environmental interven- tions in health promotion programs (McLeroy et al. 1988).

Additional theories contribute to the construction of reviewed studies: the theory of planned behavior, emphasizing the role of intention to perform the behav- ior and perceived behavior control to influence actual behavior (Ajzen 1988, 1991); the theory of trying, focus- ing on the conscious process of forming the intention to behave before performing the behavior (Bagozzi and Warshaw 1990); and the theory of behavior setting, emphasizing the importance of dynamic and interac- tive real-life settings in which human behaviors take place (Baker 1968).

Many theories share core constructs that are applied in the studies as attitude toward physical activity, social environment, perception of neighborhood resources, opportunities and benefits of physical activity, skills needed to perform physical activity, and so on. Six stud- ies have a basis in social cognitive theory, three of which (King et al. 2000; Booth et al. 2000; Hovell et al. 1992) derive their independent variables directly from its constructs. Another study (Giles-Corti and Donovan 2002) selects individual factors associated with physi- cal activity based on the theory of planned behavior and the theory of trying. Sallis et al. (1997) consider the the- ory of behavior setting by focusing on two common behavior settings, home and neighborhood, to investi- gate the influences of perceived environmental factors on physical activity.

152 Journal of Planning Literature

FIGURE 3. Behavioral Model of Environment: Conceptual Structure, and Examples of Variables

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Dependent Variables (D)

Dependent variables in public health studies often include engagement in, or total amount of, physical activity. While all types of physical activity are consid- ered, most studies focus on unstructured, moderate activities such as walking and biking, with seven stud- ies using walking specifically as their dependent variable.

Dependent variables are often self-reported and dichotomized or categorized for analysis. They include engagement in (1) overall physical activity, (2) sufficient level of physical activity for health benefits2—based on energy expenditure or total amount of physical activity, (3) leisure or exercise physical activity, and (4) specific types of physical activity such as walking, jogging, swimming, and so on. Other dichotomous variables include whether participants use specific types of recre- ational facilities, such as gyms, parks, sidewalks, bike lanes, trails, swimming pools, tennis courts, health clubs, open spaces, golf courses, and so on.

Continuous dependent variables considered include total amount (frequency and duration combined) of (1) physical activity, (2) leisure time physical activity, (3) household-related physical activity, (4) walking, and (5) vigorous activities. Also studied is the prevalence of walking to work. These continuous variables are some- times transformed into categorical or dichotomized variables for analyses (e.g., Berrigan and Troiano 2002; Booth et al. 2000; Wilcox et al. 2000; Bauman et al. 1999).

Independent Variables (E, F)

A large number of independent variables measure personal and social determinants of physical activity, some of which are considered also as control variables (see G below). Environmental factors as independent variables, the focus of this review, are classified into objective and subjective variables. Out of the total twenty studies, only three include both objective and subjective measures (Table A1), four use objective mea- sures only (Table A2), and ten use subjective measures only (Table A3). The remaining three studies are explor- atory, and no independent variables are specified.

Objective measures cover the spatial characteristics of residential locations in terms of accessibility, density of people or development, and geographic locations (e.g., urban or costal location). These variables are derived from maps and measurements using the Geo- graphic Information System (GIS). One study of pre- schoolers uses a direct observation method to measure both dependent and independent variables (Klesges et al. 1990). Two studies identify road network dis- tances to recreational facilities, one of which also con- siders the presence of barriers (hills and heavy traffic)

along the route (Troped et al. 2001). An early study based on objective measures (Sallis et al. 1990) uses the total number and density of pay and free exercise facili- ties near home to estimate accessibility to these facili- ties. Berrigan and Troiano (2002) use housing stock age as a proxy for the neighborhood’s urban form characteristics.

Subjective measures of physical environmental fac- tors address perception of safety, convenience, comfort, visual quality, neighborhood character, and presence of or proximity to exercise facilities and shops.

Confounding Variables (G)

Most studies control for one or more of the con- founding factors, such as age, sex, education, and income. However, reporting of their relationship with the dependent variable is often brief and vague. Such factors as transit service and objectively measured traf- fic conditions, which often confound the relationship between physical activity and environment, are not addressed in any of the studies. Neither are socioeco- nomic factors specific to transportation behaviors, such as car ownership.

Data Collection (H)

Data are collected specifically for the individual study (13 out of the 20 studies) or come from reliable secondary sources. Primary self-reported data come from telephone interviews, or less frequently, mail sur- veys. Many of the surveys use questions from the exist- ing questionnaires mentioned earlier (e.g., Berrigan and Troiano 2002; Ball et al. 2001; CDC 1998, 1999). The three exploratory studies (Table A4) use focus-group methods to generate the data. Primary data sources for objective variables include observations (Giles-Corti and Donovan 2002; Klesges et al. 1990), mappings (Sallis et al. 1990), and GIS-based measurements (Troped et al. 2001).

Statistical Analyses (I)

Descriptive statistics and correlation analyses are often complemented by logistic regression analysis, which is a common choice with a dichotomized dependent variable. Almost half of the studies use logistic regression alone or combined with other analy- ses. The popularity of the logistic regression method likely comes from the health field’s traditional interest in achieving a sufficient level of physical activity for health purposes. This method is effective in explaining the likelihood of achieving a threshold. Yet, the dichotomization may result in loss of information that can only be examined at a more fine-grained scale. Three studies (Craig et al. 2002; Rutten et al. 2001; Hovell et al. 1992) use hierarchical regression models to

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consider nested data structures, as they include vari- ables at multiple levels (e.g., individual- and neighbor- hood-level variables). Ball et al. (2001) use a structural equation model, which is a multivariate analysis for investigating the underlying structure of usually a large number of variables, to analyze perceived envi- ronmental factors. All but Hovell et al.’s study (1992) are cross-sectional, and therefore causality assumption of the statistical analyses may not hold.

FINDINGS FROM THE STUDIES

The studies together yield general findings about (1) walking as the most common type of physical activity, (2) preferred places for physical activity, and (3) barriers to physical activity. An inventory of empirically tested environmental variables associated with physical activ- ity is included and discussed in terms of the BME.

Walking as the Most Common Type of Physical Activity

Four studies (Ball et al. 2001; Booth et al. 1997; Giles- Corti and Donovan 2002; Troped et al. 2001) report walking as the most frequently engaged physical activ- ity. Walking is confirmed to be a preferred form of phys- ical activity by an overwhelming majority of study pop- ulations across different gender, age, and income groups (Table 1). However, the degrees of popularity vary across subgroups (Table 1). Findings show that walking is more prevalent among women and older adults (Booth et al. 1997). Stephens et al. (1985) report that walking is more popular among typically inactive segments of the population, such as ethnic minorities and the elders. Gardening, swimming, and jogging are among other frequently reported activities.

The preference of walking is further supported in studies outside the twenty selected articles included here (e.g., Bull et al. 2000; Siegel, Brackbill, and Heath 1995; Statistics Canada 1998-99; Go for Green 1998; CDC 2000a, 2000b). These studies together help affirm that promoting walking is the most practical way to achieve healthful levels of physical activity. U.S., Aus- tralian, and Canadian populations appear to practice walking and biking for recreation more so than for transportation. The CDC (2000b) found that most peo- ple when they walk for recreation walk at least 30 min- utes at a time, reaching a sufficient threshold of daily activity for health benefits. Yet walking for utilitarian purposes may be shorter: for example, the Nationwide Personal Transportation Survey (USDOT 1995) reports that most walking trips last only about five to ten min- utes. Additional research will help sort out the purposes behind the total amount of walking people do.

Preferred Places for Physical Activity

Outdoor and freely available neighborhood facilities are most frequently used for physical activity (Table 2). Neighborhood streets are most commonly used places in the Giles-Corti and Donovan (2002) and Troped et al. (2001) studies. Giles-Corti and Donovan (2002) find that 46 percent of the respondents use their neighbor- hood streets for exercise, compared with only 11 per- cent using gyms, health clubs, or exercise centers, and 9 percent using sport or recreation centers. There are studies outside the twenty articles that further demon- strate the popularity of neighborhood streets as places for physical activity (Brownson et al. 2001; Bull et al. 2000). Brownson et al. (2001) report that neighborhood streets are used by more than 66 percent of the respon- dents who reported some degree of physical activity, while only 21 percent used an indoor gym and 25 per- cent used a treadmill. Other freely available public open spaces, such as parks and trails, are also common places for exercise (e.g., Giles-Corti and Donovan 2002).

The popularity of neighborhood streets may be explained in part by their easy accessibility from home and potential to serve a dual purpose: in BME terms, they are both destinations for recreational activities and routes to get to places. The prevalence of walking as physical activity also explains the attractiveness of streets that are natural venues for walkers. This finding points to opportunities for increasing walking and bik- ing for transportation purposes.

Barriers to Physical Activity

The studies also show that people feel the built envi- ronment is not supportive enough to induce physical activity. Long distances separating places, lack of safe places and facilities for recreation, and poor accessibil- ity to recreational facilities are among the common bar- riers people perceive exist in their environment (Table 3). While some environmental barriers are difficult to modify, such as bad weather conditions (e.g., Brownson et al. 2000) and short daylight hours (Hahn and Craythorn 1994), many can be modified or eliminated.

Table 3 summarizes the barriers into four broad cate- gories, including opportunity, distance, access, and safety barriers. Both opportunity and distance barriers relate to the OD component of BME, as they concern availability of proximate destinations from origins. Access barriers include both OD and R components and focus on lack of high-quality, route-related facilities for walkers and bikers. Safety barriers involve unsafe roadway condi- tions often due to poor maintenance and perceived fear of crime, traffic, accident, injury, dogs, and people. Access and safety barriers include perhaps some of the easiest ones to lift to support physical activity.

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Physical Activity 155

TABLE 1. Preferred Type of Physical Activity

Preferred Type of 1st Author and Physical Activity Level of Preference Subjects Year Published

Walking for recreation

86.1% in previous 4 weeks (1) American adults living in Arlington, MA

Troped 2001

38% of young and 68% of older adults (1) in previous 2 weeks

Young and older sedentary Australian adults

Booth 1997

68.5% in the previous 2 weeks (1) Australian adults Giles-Corti 2002 38-52% males and 41-64% females (depending

on sex, age, education, and environmental factors) in the past 2 weeks

Australian adults Ball 2001

Walking for transportation

72.1% in the past 2 weeks Australian adults Giles-Corti 2002

Other Studies (outside the 20 selected articles)

Preferred Type of 1st Author and Physical Activity Level of Preference Subjects Year Published

Walking for recreation

80.6% of females and 73.4% of males during a week (1)

Western Australian adults Bull 2000

50.4% of males and 69.2% of females during a week (1)

Western Australian adults Bull 2000

44.1% during a week (1) American adults CDC 1996 42% (walking was the only leisure time

physical activity for 21% of them) during a week

American adults CDC 2000b

37.7% of males and 52.5% of females during a week

Overweight American adults CDC 2000a

69% (75% females and 64% males) (1) Canadian adults Statistics Canada 1998-99

85% at least sometimes (1) Canadian adults Go for Green 1998 35.6% (1) American adults Siegel 1995

Walking for transportation

58% at least some times Canadian adults Go for Green 1998

42% in previous 2 weeks Western Australian adults Bauman 1996 25% during a week Western Australian adults Bull 2000 21% to local facilities Western Australian adults

living in Perth Seaton 2001

4% to work (8% used public transport, of which 55% walked 15+ minutes as part of trip)

Western Australian adults living in Perth

Seaton 2001

24.6% of males and 25.1% of females during a week (3)

Western Australian adults Bull 2000

Biking for recreation

48% biked for leisure or recreation Canadian adults Go for Green 1998

9.8% of males and 7.4% of females during a week (8)

Western Australian adults Bull 2000

15.4% during a week (4) American adults CDC 1996 24% (19% females and 28% males) (4) Canadian adults Statistics Canada

1998-99

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Personal and social factors are also reported to hin- der physical activity. Lack of time (e.g., Brownson et al. 2001; King et al. 2000; Eyler et al. 1998) is the leading fac- tor that discourages physical activity. This finding sug- gests that supporting walking for the dual purpose of exercise and transportation may help increase levels of physical activity. Other personal barriers include poor health (Eyler et al. 1998; Owen and Bauman 1992), child care responsibility (Hahn and Craythorn 1994), and lack of energy (King et al. 2000). Personal safety con- cerns raised pertain to injuries, falls, traffic accidents, and so on. Common social barriers include not having company (Hahn and Craythorn 1994) and not seeing other people exercising (Wilcox et al. 2000). Studies out- side the twenty articles report additional deterrents of physical activity, including lack of interest (Vuori, Oja, and Paronen 1994; Owen and Bauman 1992), self- consciousness about one’s appearance (Brownson et al. 2001), and costs of structured physical activity pro- grams (Booth et al. 1997). However, it must be noted that these findings still remain inconclusive, and sev- eral variables have shown both positive and negative

impact on physical activity (i.e., hills, self-conscious- ness about physical appearance, and unattended dogs). These mixed findings may be partly due to lack of rep- resentativeness in the studies’ participants and their environmental conditions (e.g. Eyler et al. 1998; Hahn and Craythorn 1994; King et al. 2000). Because the impact of these variables on physical activity differs depending on age, gender, and ethnic background, i n t e r v e n t i o n s t r a t e g i e s t a i l o r e d t o t h e sociodemographic composition of the specific commu- nity are likely to be effective in promoting both physical activity and nonmotorized travel.

Environmental Variables Empirically Tested to Influence Physical Activity

The twenty studies address the three components of the BME in varying degrees. Individual studies typi- cally consider only one or two of the components, and variables included often do not capture comprehen- sively the forms and characteristics of the built environ- ment. As a result, the relative strength of association between individual environmental variables and phys-

156 Journal of Planning Literature

Biking for transportation

26% at least sometimes Canadian adults Go for Green 1998

2% to local facilities Western Australian adults living in Perth

Seaton 2001

1% to work Western Australian adults living in Perth

Seaton 2001

4.9% of males and 2.6% of females during a week (12)

Western Australian adults Bull 2000

Gardening/yard work

37.0% males and 38.2% females during a week (2)

Western Australian adults Bull 2000

29.4% during a week (2) American adults CDC 1996 48% (45% females and 51% males) Canadian adults Statistics Canada

1998-99 8.2% during a week Overweight American adults CDC 2000a

Swimming/ surfing

13.4% of males and 11.2% of females during a week (4)

Western Australian adults Bull 2000

6.5% during a week (9) American adults CDC 1996 24% (24% females and 24% males) (4) Canadian adults Statistics Canada

1998-99 19% in previous 2 weeks (2) Young and older sedentary

Australian adults Booth 1997

Jogging/running 12.1% of males and 6.1% of females during a week (6)

Western Australian adults Bull 2000

9.1% during a week (7) American adults CDC 1996 9.6% of males during a week Overweight American adults CDC 2000a

NOTE: Numbers in parentheses show the rank based on the activity’s level of prevalence reported in the study: recall period (or frequency of engagement in the activity) and the rank based on the prevalence of activity are reported only when the information is available from the corresponding study. CDC = Centers for Disease Control and Prevention.

TABLE 1 (continued)

Preferred Type of 1st Author and Physical Activity Level of Preference Subjects Year Published

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ical activity is not systematically examined, nor is the issue of likely covariance between environmental vari-

ables assessed. Nonetheless, significant correlations are found between some of the individual environmental

Physical Activity 157

TABLE 2. Preferred Place for Physical Activity

Preferred Place to Do Physical Type of 1st Author and Activity Physical Activity Level of Preference Subjects Year Published

Neighborhood streets

Physical activity 45.6% (1) Western Australian adults Giles-Corti 2002

Physical activity for recreation

79.1% (2 among the bikeway users after the bikeway); 64.1% (1 among the nonusers)

American adults living in Arlington, MA

Troped 2001

Parks Physical activity for recreation

20.7% Parks and recreation facilities (2 among the nonusers of the Minuteman Bikeway, parks and recre- ational facilities combined)

American adults living in Arlington, MA

Troped 2001

Public open space Physical activity 28.8% (2) Western Australian adults Giles-Corti 2002 Beach Physical activity 22.7% (3) Western Australian adults Giles-Corti 2002

Other Studies (outside the 20 selected articles)

Preferred Place to Do Physical Type of 1st Author and Activity Physical Activity Level of Preference Subjects Year Published

Neighborhood streets

Physical activity 66.1% of the respondents who reported some degree of physical activity (1)

American adults Brownson 2001

Walking for recreation

52.3% (1) Western Australian adults Bull 2000

Running/jogging for recreation

33.3% (1) Western Australian adults Bull 2000

Shopping malls Physical activity for recreation

37.0% of the respondents who reported some degree of physical activity (2)

American adults Brownson 2001

Parks Physical activity for recreation

29.6% of the respondents who reported some degree of physical activity (3)

American adults Brownson 2001

Walking for recreation

12% (2) Western Australian adults Bull 2000

Running/jogging 18.5% (2) Western Australian adults Bull 2000 Walking and jog-

ging trails Physical activity

for recreation 24.8% of the respondents

who reported some degree of physical activity (4)

American adults Brownson 2001

Cycle paths Walking for recreation

8.9% (4) Western Australian adults Bull 2000

Running/jogging 8.4% (4) Western Australian adults Bull 2000 Beach Walking for

recreation 9.9% (3) Western Australian adults Bull 2000

Running/jogging 16.5% (3) Western Australian adults Bull 2000

NOTE: Numbers in parentheses show the rank based on the place’s level of prevalence for the particular physical activity reported in the study: level of preference is reported based on the entire population, not on those who are active only, unless noted.

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158 Journal of Planning Literature

TABLE 3. Physical Environmental Barriers to Physical Activity

BME Perceived Type of 1st Author and Component Criteria Environmental Barriers Physical Activity Subjects Year Published

OD Opportunity barrier

No facilities Physical activity Older Australian Booth 2000

Lack of land for recreation (unstructured and passive activities)

Physical activity Focus group of Australian adults

Hahn 1994

Distance barrier

Travel distance Physical activity Focus group of Australian adults

Hahn 1994

OD/R Access barrier

Access (cost, lack of transporta- tion and programs)

Physical activity Focus group of older minority American adults

Eyler 1998

(Rural residents) Lack of a walking trail or malls

Physical activity Focus group of older minority American adults

Eyler 1998

Limited footpaths and cycle ways

Physical activity Focus group of Australian adults

Hahn 1994

Access difficulties include badly maintained or unsafe foot or cycle paths, unsafe pedestrian crossings, and road safety for pedestrians and cyclists

Physical activity Focus group of Australian adults

Hahn 1994

Lack or poor access to facilities (lack of pedestrian or bike routes)

Walking American adults Brownson 2000

OD/R/A Safety barrier

Unsafe footpaths and cycle ways

Physical activity Focus group of Australian adults

Hahn 1994

Safety (traffic, people, dogs) Physical activity Focus group of older minority American adults

Eyler 1998

(Rural, suburban and urban) Fear of the surroundings and crime

Physical activity Focus group of older minority American adults

Eyler 1998

Lack of safe places to exercise Walking American adults Brownson 2000 Lack of safe places to exercise Physical activity for

recreation Older female minority

American adults King 2000

Fear of injury Walking American adults Brownson 2000 Fear of injury Physical activity Older Australian Booth 2000 Fear of injury Physical activity for

recreation Older female minority

American adults King 2000

Fear for personal safety Physical activity Focus group of Australian adults

Hahn 1994

Other Studies (outside the 20 selected articles)

BME Perceived Type of 1st Author and Component Criteria Environmental Barriers Perceived Activity Subjects Year Published

OD Distance barrier

Distance Walking and biking for transportation

Canadian adults Go for Green 1998

Distance too far to get to places on foot

Walking for transportation

West Australian adults James 2001

OD/R Access barrier

Too uncomfortable to walk Walking for transportation

West Australian adults James 2001

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variables and physical activity, after controlling for sociodemographic factors. Tables 4 and 5 list the vari- ables as objective and subjective measures, respectively, classifying them according to the components of the BME, and specifying the type of physical activity envi- ronmental variable associated with them, along with the direction of the association.

Generally, objective measures emphasize accessibil- ity to destinations in the residential neighborhood envi- ronment, corresponding mainly to the OD and Route components of the BME. Subjective measures include a wide range of variables considering all three compo- nents of the BME. Most route- and area-based attributes are measured subjectively.

OD-related variables, such as the presence of, and proximity to, exercise facilities in the neighborhood, whether perceived or actual, play a role in people’s lev- els of physical activity. This is consistent with findings in the planning literature that distance to destinations is a determinant factor for transportation mode choice (USDOT 1995). Most destinations included in the stud- ies are considered for their recreational opportunities. As a result, some of the typical route-related variables in the planning research, such as neighborhood streets and walking trails, are often treated as destination. This reflects the health research’s focus on engagement in physical activity itself, rather than on means of travel. Most studies emphasize residential location as the ori- gin for physical activity and travel. Specific destination facilities found to foster physical activity include public facilities such as footpaths, trails, parks, public open spaces, and cycle tracks, as well as private facilities such as gyms, health clubs, recreation centers, and swim- ming pools.

A relatively small number of studies show associa- tions between route-related variables and levels of physical activity (e.g., Corti, Donovan, and Holman 1997; Craig et al. 2002; Troped et al. 2001). In Craig et al. (2002), subjectively measured variables, including con- tinuity and choices of walking route, as well as traffic threats and other obstacles along the route, contribute to explain variations in the composite environmental score used to evaluate the routes. The scores are found to be associated with levels of walking to work. Troped et al. (2001), on one hand, find the objectively measured presence of hills to negatively influence the use of a local bikeway. King et al. (2000), on the other hand, find the perceived presence of hills to be positively related with physical activity. This apparent discrepancy is likely due to the different measurement types (objective versus subjective) and different dependent variables used by the studies (i.e., respondents seeking to reach a bikeway perceive hills as a barrier to accessing the bike- way, but respondents seeking leisure time activity or household-related physical activity perceive hills as an attractor, possibly because they afford good views). Positive associations are also reported between levels of physical activity and the perception of tamed traffic conditions, pedestrian-friendly facilities (e.g., foot- paths, signage, street lights, etc.), and effective traffic control measures, as well as with increased visual quality, perceived safety, and convenience.

Important objective area-based variables include steep terrain, home age, and costal and urban residen- tial locations. The latter three variables are used as prox- ies for general urban form characteristics. While prox- ies may be an efficient means to address the multiple, highly interrelated variables that represent the built

Physical Activity 159

Lack of pleasant route Walking and biking for transportation

Canadian adults Go for Green 1998

Lack or poor access to facilities Walking and biking to work

Finnish adult workers Vuori 1994

R/A Safety barrier

Fear of accident Walking and biking to work

Finnish adult workers Vuori 1994

Fear of injury Walking and biking to work

Finnish adult workers Vuori 1994

Traffic safety/bad road Walking and biking for transportation

Canadian adults Go for Green 1998

NOTE: BME = Behavioral Model of Environment; OD = origin/destination; R = route; A = area.

TABLE 3 (continued)

Other Studies (outside the 20 selected articles)

BME Perceived Type of 1st Author and Component Criteria Environmental Barriers Perceived Activity Subjects Year Published

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environment, they may not pass the test of external validity if they fail to show any effect after controlling for other sociodemographic factors and/or more exten- sively studied individual environmental factors such as density or land use mix. Subjectively measured area-

based variables, such as the perception of enjoyable scenery, are also found to influence physical activity (King et al. 2000). Amenities and aesthetic features are shown to increase the use of local parks (Corti, Dono- van, and Holman 1997). Perception of environmental

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TABLE 4. Objective Measures Influencing Physical Activity

BME Objective Measures of Relationship with 1st Author and Component Criteria Physical Environmental Variables Dependent Variable Found Year Published

OD Destination quality

Park size 1 Use of local parks Corti 1997

Other amenities available at the facility

1 Use of pay exercise facility Corti 1997

OD/A Availability of destinations

Number of local shops 1 Walking around their neighborhood Corti 1997

Number of destinations Contribute to explain variations of environment score among neighborhood

Craig 2002

OD/R Accessibility to destinations

Access to facilities (this relationship stronger for beach, river, golf courses, and tennis courts; less clear for other facilities)

1 Use of facilities Giles-Corti 2002

Access to exercise facilities 1 Likelihood of achieving physical activity as recommended

Giles-Corti 2002

GIS road network distance to trail 2 Bikeway use Troped 2001 Distance from home to pay facilities Contribute to explain difference

between sedentary and exerciser groups

Sallis 1990

Convenience of destinations

Rating of perceived convenience of specific facilities

Contribute to explain difference between sedentary and exerciser groups

Sallis 1990

R Route quality Steep hill barrier along the route to the facility

2 Bikeway use Troped 2001

A Density Density of total exercise facilities within 1 km

Contribute to explain difference between sedentary and exerciser groups

Sallis 1990

Density of pay facility 1 Exercise Sallis 1990 House age Living in housing built before 1973

(as a proxy for the residential neighborhood’s urban form)

1 Likelihood of walking 20+ times/ week (only in urban/suburban area); this relationship did not hold for rural area

Berrigan 2002

Geographic location

Costal residential location 2 Likelihood of being sedentary Bauman 1999

Costal residential location 1 Likelihood of being adequately active

Bauman 1999

Costal residential location 1 Likelihood of being vigorously active

Bauman 1999

Neighborhood characteristics

Degree of urbanization 1 Physical activity CDC 1998

Degree of urbanization 2 Physical inactivity (strongest in South region: 12.3% higher prevalence of physical inactivity in rural area)

CDC 1998

NOTE: 1 or 2 sign shows the direction of association that the independent variable has with the dependent variable (1 = positive, 2 = negative). BME = Behavioral Model of Environment; OD = origin/destination; R = route; A = area; GIS = Geographic Informa- tion System; CDC = Centers for Disease Control and Prevention.

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Physical Activity 161

TABLE 5. Subjective Measures Influencing Physical Activity

BME Subjective Measures of Relationship with 1st Author and Component Criteria Physical Environmental Variables Dependent Variable Found Year Published

OD Availability of destinations

Perceived presence of park 1 Likelihood of being sufficiently active

Booth 2000

Perceived presence of recreation center (correl)*

1 Likelihood of being sufficiently active

Booth 2000

Perceived presence of cycle track (correl)

1 Likelihood of being sufficiently active

Booth 2000

Perceived presence of golf course (correl)

1 Likelihood of being sufficiently active

Booth 2000

Perceived presence of swimming pool (correl)

1 Likelihood of being sufficiently active

Booth 2000

Self-reported distance to trail—trail as destination

2 Bikeway use Troped 2001

Perceived opportunities 1 Physical activity (weak but significant)

Rutten 2001

OD/R Proximity/ accessibility

Perceived proximity and accessibility 1 Use of local parks Corti 1997

Facility’s accessibility and proximity to home or work, or facility’s location along the route to work

1 Use of pay exercise facility Corti 1997

OD/A Mix of destinations

Variety of destinations Contribute to explain variations of environment score among neighbor- hood*

Craig 2002

OD/R/A Accessibility to destinations

Baseline number of convenient facilities (number of exercise facilities, such as aerobic dance studios, bike lanes, and running tracks, perceived as convenient)

1 Walking Hovell 1992

R Walking route availability

Presence of footpath 1 Walking around their neighborhood Corti 1997

Presence of walking paths 1 Walking around their neighborhood Corti 1997 Availability of walking routes

(sidewalks, paths) Contribute to explain variations of envi-

ronment score among neighborhood* Craig 2002

Walking route quality

Safe footpath for walking 1 Likelihood of being sufficiently active Booth 2000

Traffic control measures 1 Walking around their neighborhood Corti 1997 Little difficulty using footpaths

(correl) 1 Likelihood of being sufficiently active Booth 2000

R/A Walking system quality

Inclusive of pedestrian (people- oriented buildings, signage, amenities)

Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

Meets pedestrian’s need (route continuity, route choices, crossing lights, topography, traffic, obstacles)

Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

Traffic threats (amount, speed, separation from traffic)

Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

Obstacles (debris, construction, maintenance)

Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

Time and effort required to walk— more specific (route directness, topography, obstacles, characteristics of intersections)

Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

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aesthetics and convenience are associated with increased level of walking for exercise (Ball et al. 2001).

Overall, the studies use relatively specific objective measures of route and destination related to recreational facilities, but general and aggregated objective area- based measures. Compared to urban and transporta- tion planning research, considerations of land use pat- terns, such as density, mix, and route characteristics, remain limited in the health field. Only Craig et al. (2002) find density and variety of destinations to be sig- nificant contributors to the composite neighborhood score, which is correlated with walking to work. Also, measures to capture proximity, accessibility, or conve-

nience remain loosely specified; clear definitions of, and distinctions between, these terms will be needed in future research.

LESSONS FOR FUTURE PRACTICE AND RESEARCH IN PROMOTING ACTIVE LIVING

This review suggests the development of comple- mentary knowledge bases in health and urban/trans- portation planning and unveils new promising ave- nues for urban and transportation practice and research on the relationship between land use and transporta- tion behavior. At the level of professional practice, envi-

162 Journal of Planning Literature

A Walking system quality

Walking system (continuity) Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

Transportation system quality

Transportation system (connection to other modes of transportation, bike parking, benches at transit stops)

Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

Neighborhood characteristics

Neighborhood character perceived as residential compared to mixed or commercial

2 Bikeway use Troped 2001

Availability of amenities 1 Use of local parks Corti 1997 Visual quality Aesthetic features including lakes

and bird life 1 Use of local parks Corti 1997

Complexity of stimulus (amount and variety of visual and auditory stimuli)

Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

Potential overload of stimulus (amount and variety of visual and auditory stimuli)

Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

Perceived presence of enjoyable scenery (total sample)

1 Physical activity King 2000

Perception of environmental aesthetics 1 Walking for exercise Ball 2001 Area quality Perceived presence of hills (total

sample) 1 Physical activity King 2000

Perception of convenience of environment

1 Walking for exercise Ball 2001

Perceived safety

Safety from crime (lighting, front porches, escape routes, people around, street type, etc.)

Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

Potential for crime (graffiti, vandalism, disrepair, street lighting, etc.)

Contribute to explain variations of envi- ronment score among neighborhood*

Craig 2002

Perceived safety 2 Physical inactivity (this relationship strongest among persons aged 65+ years and minorities) (correl)**

CDC 1999

Perceived safety 2 Physical inactivity among older adults (controlling for race, education, age, sex)

CDC 1999

NOTE: 1 or 2 sign shows the direction of association that the independent variable has with the dependent variable (1 = positive, 2 = negative). *(correl) means that the associations are tested as bivariate relations only, without controlling for confounding fac-

TABLE 5 (continued)

BME Subjective Measures of Relationship with 1st Author and Component Criteria Physical Environmental Variables Dependent Variable Found Year Published

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ronmental interventions involving the design of streets and the location of destinations in neighborhoods show potential to support increased levels of physical activity and physically active travel. At the level of research, the public health field offers advanced theoretical and methodological perspectives on human behavior and provides useful insights into conceptual frameworks that can guide further empirical testing of the relationship between behavior and environment.

Lessons for Practice: Areas of Possible Intervention

EVIDENCE SUPPORTING LATENT DEMAND FOR

WALKING AND BIKING AS MEANS OF TRAVEL

Consistent evidence of people’s predilection for walking and, to a lesser degree, biking, suggests that walking and biking can become more common forms of both exercise and transportation in the future. Further supporting the potential of walking and biking as means of achieving high active living standards is the seemingly unfailing predominance of neighborhood streets as popular places for exercise. Given that current street environments often poorly accommodate these activities, the large reported amounts of recreational walking and biking on streets suggests that providing appropriate street design and proximate routine desti- nations (e.g., retail shops and service facilities) will likely increase levels of walking and biking for travel.

Transportation behavior research has long pointed to a latent demand for walking and biking trips. Many automobile trips are short enough to be substituted by walking or biking. In the United States, 27 percent of automobile trips are shorter than 1 mile, and 40 percent are shorter than 2 miles (USDOT 1990). These distances are well within the reported walkable and bikable ranges of 0.74 mile to 2 miles, as conditioned by peo- ple’s general health, perception, and attitude (Bernhoft 1998; USDOT 1995; Puget Sound Regional Council [PSRC] 2001). In addition, the majority of vehicular trips are made for nonwork purposes, some of which could feasibly be replaced by slower travel modes—38 percent of total trips are for social and recreation pur- poses, and another 35 percent are for family and per- sonal businesses (USDOT 1995). In Canada, people report that they not only can but also want to increase their participation in walking and biking for transpor- tation purposes (Go for Green 1998, 17). Most people also recognize the health value of walking (NPHP 2001, 7). As a result, the potential to convert latent demand for walking and biking into actual travel behavior change seems high; one of the key approaches to this change will likely be through changes in the built environment.

PROMOTING LAND USE INTENSITY AND

MIX, AND INVESTING IN PEDESTRIAN

AND BICYCLE FACILITIES

The studies confirm the importance of proximate and attractive destinations to support walking and bik- ing. They strengthen and complement existing evi- dence in urban and transportation planning research, where such route-oriented variables as the presence of pedestrian and bicycle infrastructure (e.g., sidewalks, bike lanes, etc.), and area-related ones, such as density, land use mix, and street types, can be associated with increased levels of walking and biking (e.g., Cervero and Kockelman 1997; Ewing, Deanna, and Li 1996; Frank and Pivo 1994; Handy 1996; Hess et al. 1999; Kitamura, Mokhtarian, and Laidet 1997; Moudon et al. 1997).

During the past several decades, the lack of sufficient coordination between land use and transportation planning and the limited public expenditures in nonmotorized facilities—less than 2 percent of total federal transportation budgets are allocated for pedes- trian and bicycle facilities and programs (FHWA 2002)—have contributed to creating urban environ- ments where walking and biking are marginalized or disregarded as transportation modes. The studies’ find- ings imply that, to enhance the health and well-being of the population, infrastructure for walking and biking needs to become an integral part of public transporta- tion systems and services. Mixing land uses within short distances of each other must also be actively pur- sued to entice increases in walking and biking for trans- portation (Rutherford et al. 1995; Hess et al. 1999; Moudon and Hess 2000).

TARGETING ENVIRONMENTAL ENABLERS

AND BARRIERS TO PHYSICAL ACTIVITY,

WALKING, AND BIKING

Tables 4 and 5 point to specific physical environmen- tal enablers of physical activity. Perceived area-related enablers encompass various visual characteristics of the neighborhood, such as presence of aesthetic fea- tures, appropriate levels of visual stimuli, and enjoy- able scenery. Also positively associated with physical activity are such objective measures of neighborhood as urban and costal locations, older housing, and mixed or commercial-dominant neighborhoods.

Because neighborhood streets are found to be the most frequently used places for physical activity, inter- ventions involving maintenance, comfort, connectivity, continuity, and safety of the transportation infrastruc- ture, and especially route-oriented components such as sidewalks and bike lanes, will likely serve as effective

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facilitators of walking and biking. Provision and enhancement of trails also seem to increase activity levels (Brownson et al. 2001).

Environmental barriers to physical activity encom- pass various negative qualities of neighborhoods— mostly area-related safety factors including perceived fear of crime, personal injury, traffic, and dogs. Interest- ingly, the presence of other people in the neighborhood and in places of exercise is found to be a source of both fear and social support, an indicator of the complex influences of environment on perceptions. Removing impediments to physical activity that exist in the physi- cal environment will be a logical first step in promoting active living. Examples of environmental modification toward creating activity-friendly neighborhoods are (1) providing safe places for exercise near homes; (2) locat- ing attractive, routine destinations near homes; (3) con- necting destinations with safe, convenient, and pleas- ant transportation systems; and (4) providing well- maintained, well-lit, and continuous sidewalks and bike lanes.

A socially supportive atmosphere (e.g., the presence of other people exercising in the neighborhood and the opportunity to be physically active with friends or fam- ily) will also help remove some of the barriers or further bolster physical environmental enablers of physical activity. Brownson et al. (2001) note that an easy access to supportive environments is a necessary, but not a suf- ficient, condition to promote physical activity and point to the importance of personal and social factors, such as time, motivation, encouragement, and social support. The concept of reciprocal determinism drawn from social cognitive theory helps explain how personal bar- riers to physical activity may interact with environmen- tal factors. For example, while it may seem difficult to overcome the fact that people have insufficient time to be active, providing them with an environment that encourages integrating walking/biking with other daily activities such as work, commuting and child care, may get them to walk regularly (Booth et al. 1997, 135). Furthermore, implementing physical environ- ments for active living likely will interact positively with improvements in the social environment, offering people new opportunities to meet with others. As such, reciprocal determinism invites further research in neighborhood environment and behavior to develop effective approaches to modifying environments.

Lessons for Research: Theories and Methods

CONSIDERATION OF ENVIRONMENTS

WITHIN SOCIAL ECOLOGICAL THEORIES

As discussed earlier, multiple theories guide health research, and complex theoretical frameworks focusing

on behavior and behavior change direct the classifica- tion and selection of variables, their interdependencies, and the identification of thresholds related to stated goals for behavior change. These theories have also pro- vided a natural link between research findings and edu- cational programs promoting public awareness of the health benefits of physical activity, as well as its social and psychological rewards at the personal and commu- nity levels. They can also add to urban and transporta- tion planning research, which has traditionally been focused on economics, and in which location theory (Alonso 1964), consumer choice, and random utility theory (McFadden 2001) have dominated as explicitly stated research frameworks.

The social ecological model highlights the social, physical, and policy or institutional dimensions of envi- ronments (McLeroy et al. 1988). Theoretically grounded social environmental variables included in the reviewed studies rely on social modeling (e.g., Booth et al. 2000; Giles-Corti and Donovan 2002; Hovell et al. 1992), social support (e.g., Ball et al. 2001; Booth et al. 2000; Wilcox et al. 2000), and social reinforcement (Booth et al. 2000). Those are interpersonal variables capturing the relationships between persons and were first addressed in Bandura’s (1977) Social Learning The- ory. Social modeling refers to people’s capability to learn a new behavior from observing others (Bandura 1977, 1989). For example, one can be stimulated to walk or bike after observing others in the neighborhood walking or biking. Similarly, social support puts for- ward the role of one’s “significant other” in influencing behavior by doing certain activities together. Social r e i n f o r c e m e n t c a n t a k e t h e f o r m o f v e r b a l encouragement to do these activities.

The physical environmental dimension captured in some of the studies also adds such variables as accessi- bility to recreational facilities (e.g., Giles-Corti and Donovan 2002; Sallis et al. 1990; Troped et al. 2001) and the presence of supportive physical facilities (e.g., Sallis et al. 1997; Wilcox et al. 2000).

Associations between these theory-driven variables and physical activity appear to hold in the studies reviewed. The primary concern at this point is to match the highly developed scope of social environmental theoretical frameworks with similarly sophisticated and rigorous constructs of the physical environment in order to successfully identify physical environmental variables associated with physical activity. Stokols (1992) and Sallis and Owen (1997) call for future research to consider explicitly community-based, phys- ical environmental influences on physical activity. King et al. (2002) propose to place theoretical perspectives along a continuum of personal choice—including the cognitive and behavioral factors affecting physical

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activity—and, on the other end of the spectrum, activ- ity-related choice, which is shaped by physical environments and related policies.

BEHAVIOR MODEL OF ENVIRONMENT

AS A CONCEPTUAL FRAMEWORK FOR

UNDERSTANDING THE BUILT ENVIRONMENT

The BME or a version of the BME, offers a theoretical framework for better understanding the physical envi- ronment and, thus, complementing the social ecologi- cal approach. The BME helps define environmental variables characterizing activity settings, as they may shape the behavior change. Future research needs to assess systematically which of the BME components has the strongest effect on behavior or which of the vari- ables defining each BME components affect behavior. Such variables as length of route, route attributes (e.g., sidewalks, lighting, etc.), and area characteristics (e.g., number of residents, number of destinations) need to be further investigated to establish their association with levels of physical activity. The influence of the BME components and variables on different types of behav- iors, such as walking versus biking, and on different purposes of behavior, such as recreational versus transportation activities, also requires attention.

APPROACHES TO RESEARCH DESIGN,

SAMPLING, AND DATA COLLECTION

The studies employ rigorous research design and methods on the behavioral and psychological compo- nents of physical activity by (1) ensuring randomness in the sample populations, (2) using tested or validated instruments for data collection, (3) employing a disaggregated approach to data analysis, and (4) con- sidering a broad range of theory-driven psychosocial confounders. Furthermore, the common use of primary data provides targeted and high-quality information tailored to answer specific research questions. It also helps control for confounding factors. Elaborate testing and validation processes for data collection are well established. For example, telephone interviews follow strict protocols to ensure a high response rate and valid- ity of responses. Questionnaires are tested for the ques- tion order, wording, recall period (e.g., frequency of walking during the past week vs. past month), and appropriate use of closed- and open-ended questions. Clearly, approaches to collect behavioral data are far more advanced than the approaches to deal with physi- cal environmental conditions. For example, the current research emphasizes a statistically rigorous sampling of the participants but disregards the need to appropri- ately select the types of environments. To date, many studies rely on an imprecisely measured, or an insuffi- cient range of variations in, the environment, which

may limit the ability to detect associations with physical activity.

The idea that people choose to live in an environment that meets their behavioral inclination, commonly called self-selection, can weaken some of the findings on the environmental determinants of physical activity. While none of the reviewed studies address this issue explicitly, they indirectly approach this issue by consid- ering various demographic and psychological factors that underlie the self-selection issue. Further attention is still required to determine the nature and extent of the self-selection problem itself, and the specific factors leading to household location choice.

The timing of data collection is also important to con- sider for further methodological improvements. Because levels of physical activity and walking and bik- ing vary by season, day of the week, and time of the day (e.g., Vuori, Oja, and Paronen 1994), data collection times must account for these variations. Furthermore, times for behavioral and environmental data collection must be coordinated, especially when using secondary data, which is common in planning research. Other- wise, the findings are subject to misinterpretation or overgeneralization. Longitudinal studies (e.g., before and after intervention study including both case and control samples) should be considered to help establish causality of the environment-behavior relationship. However, direct causality may never be established due to the time, cost, and technical difficulties involving free-living individuals in ever-changing, dynamic environments.

CONSIDERATION OF BOTH OBJECTIVE

AND SUBJECTIVE DATA

Objective and subjective measures of environmental factors tend to be correlated, yet differences exist between the two (Sallis et al. 1990). Both types of mea- sures have strengths and weaknesses when used to cap- ture the environmental conditions for walking and bik- ing. The advantages of objective measures may include (1) reduced measurement errors, (2) easy quantification and standardization, and (3) easy translation into pol- icy implications. At the same time, theories of behavior change commonly employed in physical activity pro- motion suggest that the perceptual characteristics of environment may be more closely related to actual behavior outcomes than the objective characteristics of environment. According to these theories, changes in behavior involve an internalization process assessing the environmental information. Further studies are needed regarding the relative influence of objective and subjective measures on levels of physical activity.

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IMPORTANCE OF SPATIAL SCALE

AND SPATIAL DEPENDENCY

Many of the studies use the individual respondent as a unit of analysis, creating consistency among the vari- ables. This disaggregated approach allows consider- ation of individual-level extraneous factors. Neighbor- hood effects are less well addressed, however, and only a few studies employ hierarchical modeling techniques to deal statistically with multi-level effects, such as indi- vidual- versus neighborhood-level effects (Klesges et al. 1990; Craig et al. 2002; Rutten et al. 2001). Also, because most objective measures of neighborhood characteristics come from large aggregated spatial units, such as zip codes, counties, or even larger geo- graphic regions (e.g., Bauman et al. 1999; CDC 1998; Wilcox et al. 2000), the many fine-grained variations in environments that matter for walking and biking are evened out (Hess 2001; Krizek 2001). As a result, associ- ations between physical activity and environment, which may be present at small-area scales, can get lost when data are aggregated to large areas. Potential effects of aggregation and disaggregation of data on behavior need to be investigated.

In addition, spatial dependency or autocorrelations (i.e., people living nearby share similar environmental conditions) are largely overlooked. Measures of envi- ronmental variables are known to covary spatially. However, most statistical analyses falsely assume their independency. The simple hierarchical analyses used in several of the studies reviewed offer only limited solu- tions to this problem. The nature of spatial dependency remains to be understood, and the utility of such tech- niques as spatial statistics and hierarchical modeling should be examined further (Miller 2001).

MEASUREMENT ISSUES IN BEHAVIORAL

AND ENVIRONMENTAL FACTORS

The studies’ dependent variables are commonly dichotomized, begging further examination of the potential dilution of patterns of associations that could be observed at a more fine-grained or continuous scale. Systematically comparing associations that the envi- ronmental factors have with different measures of dependent variables, such as total amounts, frequen- cies, and temporal distribution (daily, weekly, season- ally, etc.) of walking and biking, will likely improve our understanding of how supportive environments can help achieve specific types of behaviors.

In most studies, measurements of environmental factors focus on the OD component of the BME (e.g., recreational destinations). Specific area-based mea- sures, along with objective measures of traffic condi- tions, quality of transit service, and the characteristics

of street networks, and so forth, will need to be included in future research (Moudon and Lee 2003).

CONCLUSION

Public health research on the physical environmen- tal determinants of physical activity identifies walking and biking as popular and desirable means of being active. The studies provide evidence that creating activ- ity-friendly communities will increase levels of recre- ational physical activity. Effective strategies for pro- moting walking and biking likely will involve adding a transportation function to the existing popularity of recreational walking and biking. Combining recre- ational and travel-based walking and biking will cir- cumvent the issue of limited time, which people often report as a major barrier to physical activity, and therefore may increase the frequency of physically active travel.

The popularity of neighborhood streets as places for active living further reinforces the potential for walking and biking as means of travel that can contribute to increased levels of physical activity. Yet, multipurpose walking and biking will require environmental inter- ventions to ensure easy, safe, and pleasant access to rou- tine destinations. Intervention strategies must be grounded on empirical evidence, and their successful implementation is conditioned by various factors, including the responsiveness to the existing local envi- ronments, resources available, and ease and cost of intervention. Strategies likely to be successful include those targeting specific types of community, such as schools and work sites, and specific groups of people, such as the elders, children, and female, minority, and low-income groups. Consideration of both incentive- based and regulatory interventions seems promising. Corresponding changes will be necessary in current transportation investment procedures that continue to favor vehicular, rather than nonmotorized, modes of travel. Also, the current dependence on automobile travel suggests the need for reevaluating people’s life- styles and preferences. Only by reducing automobile use can walking and biking become widely accepted, readily achievable, habitual, and routine in people’s daily life.

Aspects of public health research methods are worth emulating in urban and transportation planning fields. The social ecological model provides a rich theoretical framework to understand the multi-level (social, physi- cal environmental as well as psychological) influences on behavior. Also, systematic validation and testing of survey instruments, and careful consideration of con- founding factors and multi-level variables can serve to strengthen urban and transportation planning

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research. Published literature in the health field pro- vides exacting details about research protocols, includ- i n g s t u d y l i m i t a t i o n s , p o t e n t i a l b i a s , a n d generalizability of the findings. These strict publication standards establish connections between research find- ings from different projects and help build a systematic and collective research agenda.

The studies point to the need for a theoretical frame- work to conceptualize and measure physical environ- ments comprehensively. The BME used in this article begins to provide such a conceptual setting. The model indicates that so far, health studies have limited envi- ronmental factors to a few of the route and destination components of environments. Future research needs to address the characteristics of areas (neighborhoods and districts) where active living can take place as well as consider correlations between environmental vari- ables. Theoretical frameworks of the environmental conditions will also help sample the full range of variability in environmental factors.

Research in health and urban/transportation fields is complementary. Future multidisciplinary research is likely to promise a better understanding of both the behavioral and environmental aspects of physical activity and physically active travel.

ACKNOWLEDGMENTS

This work is part of a project supported by the Cen- ters for Disease Control and Prevention (CDC) and car- ried out through the University of Washington Health Promotion Research Center (HPRC) to develop valid prospective environmental audit instruments to be used for communities and professionals to support neighborhood walking and biking. The project officer at the CDC is Dr. Thomas Schmid. Co-Principal Investi- gators are Drs. Allen Cheadle, Cheza Collier, and Donna Johnson, at the University of Washington, and Robert Weathers, at Seattle Pacific University.

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l f re

e an

d p

ay e

xe rc

is e

fa ci

li ti

es w

it h

in 1

, 2 , 3

, 4 , 5

k m

fr o

m h

o m

e

P er

ce iv

ed c

o n

v en

ie n

ce o

f 15

t y

p es

o f

ex er

ci se

fa ci

li ti

es (

ra te

d )

P er

ce iv

ed b

ar ri

er s

to ex

er ci

se

A g

e E

d u

ca ti

o n

In co

m e

M ai

l s u

rv ey

F ie

ld m

ap p

in g

D es

cr ip

ti v

e st

at is

ti cs

F -t

es t

fo r

tw o

g ro

u p

d if

fe re

n ce

s

3 Tr

o p

ed 20

01 A

d u

lt s

li v

in g

in A

rl in

g to

n ,

M A

R an

d o

m sa

m p

le o

f 41

3

N o

U se

o f

th e

M in

u te

m an

B ik

ew ay

R ec

re at

io n

al p

h y

si ca

l a ct

iv -

it y

d u

ri n

g t

h e

p as

t 4

w ee

k s

Ty p

e o

f p

h y

si ca

l ac

ti v

it y

L o

ca ti

o n

s fo

r p

h y

si ca

l ac

ti v

it y

R o

ad n

et w

o rk

d is

ta n

ce t

o th

e b

ik ew

ay f

ro m

h o

m e

(c lo

se st

o ff

ic ia

l a cc

es s

p o

in t)

B u

sy s

tr ee

t b

ar ri

er a

lo n

g th

e sh

o rt

es t

n et

w o

rk r

o u

te to

a cc

es s

th e

b ik

ew ay

St ee

p h

il l b

ar ri

er a

lo n

g t

h e

sh o

rt es

t n

et w

o rk

r o

u te

ac ce

ss t

o t

h e

b ik

ew ay

(1 0+

% s

lo p

e fo

r at

le as

t 10

0 m

— v

is u

al ex

am in

at io

n )

N ei

g h

b o

rh o

o d

f ea

tu re

s (i

n cl

u d

in g

s id

ew al

k , h

il l,

cr im

e) P

er ce

iv ed

s af

et y

N ei

g h

b o

rh o

o d

c h

ar ac

te r

(r es

id en

ti al

, m ix

ed ,

co m

m er

ci al

) D

is ta

n ce

t o

b ik

ew ay

St ee

p h

il l b

ar ri

er B

u sy

s tr

ee t

b ar

ri er

A g

e Se

x E

d u

ca ti

o n

P h

y si

ca l

ac ti

v it

y li

m it

at io

n

M ai

l s u

rv ey

G IS

P ea

rs o

n ’s

co rr

el at

io n

L o

g is

ti c

re g

re ss

io n

M u

lt ip

le lo

g is

ti c

re g

re ss

io n

L ik

el ih

o o

d r

at io

te st

in g (c on

ti n

u ed

)

at UNIV OF MARYLAND on December 16, 2009 http://jpl.sagepub.comDownloaded from

170

A P

P E

N D

IX (

co n

ti n

u ed

)

TA B

L E

A 2.

St u

d ie

s U

si n

g O

b je

ct iv

e M

ea su

re s

O n

ly

A B

C D

E G

H I

C o

n fo

u n

d in

g 1s

t A

u th

o r

O b

je ct

iv e

F ac

to rs

D at

a St

at is

ti ca

l So

u rc

e an

d Y

ea r

St u

d y

Sa m

p le

T h

eo re

ti ca

l D

ep en

d en

t In

d ep

en d

en t

C o

n tr

o ll

ed /

C o

ll ec

ti o

n A

n al

y si

s K

ey P

u b

li sh

ed P

o p

u la

ti o

n Ty

p e/

Si ze

F ra

m ew

o rk

V ar

ia b

le s

V ar

ia b

le s

C o

n si

d er

ed M

et h

o d

P er

fo rm

ed

4 B

er ri

g an

20 02

U .S

. a d

u lt

s ag

ed 2

0+ St

ra ti

fi ed

m u

lt is

ta g

e p

ro b

ab il

it y

sa m

p li

n g

o f

14 ,8

27 a

d u

lt s

(w it

h o

v er

sa m

p li

n g

o f

A fr

ic an

a n

d M

ex ic

an A

m er

ic an

s)

Y es

: l o

o se

ly b

as ed

o n

ec o

lo g

ic al

m o

d el

W al

k in

g f

re q

u en

cy ca

te g

o ri

ze d

a s:

1. N

o n

e/ m

o n

th 2.

1 -1

9 ti

m es

/ m

o n

th 3.

2 0+

t im

es /

m o

n th

H o

u si

n g

a g

e ca

te g

o ri

ze d

a s:

1. B

ef o

re 1

94 6

2. 1

94 6-

19 73

3. A

ft er

1 97

3 Su

b u

rb an

/ u

rb an

v s.

r u

ra l

ar ea

A g

e Se

x R

ac e/

et h

n ic

it y

E d

u ca

ti o

n H

o u

se h

o ld

in co

m e

A ct

iv it

y li

m it

at io

n

U se

d t

h e

th ir

d N

at io

n al

H ea

lt h

a n

d N

u tr

it io

n E

xa m

in at

io n

Su rv

ey C

en su

sL o

g is

ti c

re g

re ss

io n

5 B

au m

an 19

99 A

d u

lt s

ag ed

18 +

y ea

rs li

v in

g in

si xt

ee n

h ea

lt h

s er

v ic

e re

g io

n s

in N

ew S

o u

th W

al es

St ra

ti fi

ed ra

n d

o m

sa m

p le

o f

1, 00

0

N o

3 v

ar ia

b le

s co

n st

ru ct

ed (b

as ed

o n

e n

er g

y ex

p en

d it

u re

d ra

w n

fr o

m t

h e

se lf

-r ep

o rt

ed ac

ti v

it y

a n

d w

ei g

h t)

: 1.

B ei

n g

t o

ta ll

y se

d en

ta ry

( 50

– k

ca l/

w ee

k )

2. B

ei n

g a

d eq

u at

el y

ac ti

v e

fo r

h ea

lt h

(8 00

+ k

ca l/

w ee

k )

3. B

ei n

g v

ig o

ro u

sl y

ac ti

v e

(1 ,6

00 +

k ca

l/ w

ee k

)

L o

ca ti

o n

o f

re si

d en

ce —

co st

al v

er su

s in

la n

d b

as ed

o n

p o

st co

d e

G en

d er

A g

e C

o u

n tr

y o

f b

ir th

E d

u ca

ti o

n E

m p

lo y

m en

t

U se

d 1

6, 17

8- re

sp o

n d

en t

te le

p h

o n

e su

r- v

ey o

f N

ew So

u th

W al

es re

si d

en ts

P o

st co

d e

L o

g is

ti c

re g

re ss

io n

6 C

D C

19 98

A d

u lt

s ag

ed 18

+ y

ea rs

li v

in g

in th

e U

n it

ed St

at es

P o

p u

la ti

o n

- b

as ed

r an

d o

m sa

m p

le o

f 11

8, 77

8

N o

E n

g ag

em en

t in

e xe

rc is

e, re

cr ea

ti o

n , o

r p

h y

si ca

l ac

ti v

it y

o th

er t

h an

th ei

r re

g u

la r

jo b

d u

ti es

d u

ri n

g t

h e

p as

t m

o n

th

D eg

re e

o f

u rb

an iz

at io

n cl

as si

fi ed

b y

u si

n g

t h

e U

.S . D

ep ar

tm en

t o

f A

g ri

cu lt

u re

’s r

u ra

l- u

rb an

c o

n ti

n u

u m

c o

d es

(p o

p u

la ti

o n

b as

ed )—

te n

co d

es c

o ll

ap se

d in

to f

iv e

ca te

g o

ri es

( sp

at ia

l u n

it :

co u

n ty

)

A g

e Se

x E

d u

ca ti

o n

H o

u se

h o

ld in

co m

e

U se

d B

eh av

- io

ra l R

is k

F ac

- to

rs S

u rv

ei l-

la n

ce S

y st

em (B

R F

SS )

G IS

L o

g is

ti c

re g

re ss

io n

C o

rr el

at io

n an

al y

si s

at UNIV OF MARYLAND on December 16, 2009 http://jpl.sagepub.comDownloaded from

171

7 K

le sg

es 19

90 Se

lf -s

el ec

te d

re sp

o n

d en

ts re

cr u

it ed

b y

re sp

o n

se fo

rm s

d is

tr ib

u te

d t

o lo

ca l

p ed

ia tr

ic ia

n s’

o ff

ic es

, d ay

ca re

c en

te rs

, an

d c

h u

rc h

es

22 2

p re

- sc

h o

o le

rs N

o A

ct iv

it y

le v

el o

f th

e ch

il d

( st

at io

n ar

y, m

in im

al a

ct iv

it y,

sl o

w m

o v

em en

t, ra

p id

m o

v em

en t)

D ir

ec t

o b

se rv

at io

n s

o n

: 1.

T y

p e

o f

p h

y si

ca l

en v

ir o

n m

en t

in w

h ic

h th

e ac

ti v

it y

w as

o cc

u rr

in g

( h

o m

e, o

w n

y ar

d , p

u b

li c

p la

y g

ro u

n d

, st

re et

/ si

d ew

al k

) 2.

T h

e p

er so

n s

w h

o w

er e

p re

se n

t d

u ri

n g

t h

e ac

ti v

it y

3. T

h e

ty p

e o

f in

te ra

ct io

n b

et w

ee n

t h

e ch

il d

a n

d th

e p

er so

n s

p re

se n

t in

th e

en v

ir o

n m

en t

A g

e Se

x R

ac e

(a ll

w h

it e)

W ei

g h

t W

ea th

er co

n d

it io

n s

al lo

w in

g f

o r

o u

td o

o r

ac ti

v it

y d

u ri

n g

o b

se rv

at io

n ti

m e

O b

se rv

at io

n C

o rr

el at

io n

an al

y si

s H

ie ra

rc h

ic al

li n

ea r

re g

re ss

io n

(c on

ti n

u ed

)

at UNIV OF MARYLAND on December 16, 2009 http://jpl.sagepub.comDownloaded from

172

A P

P E

N D

IX (

co n

ti n

u ed

)

TA B

L E

A 3.

St u

d ie

s U

si n

g S

u b

je ct

iv e

M ea

su re

s O

n ly

A B

C D

F G

H I

C o

n fo

u n

d in

g 1s

t A

u th

o r

F ac

to rs

D at

a St

at is

ti ca

l So

u rc

e an

d Y

ea r

St u

d y

Sa m

p le

T h

eo re

ti ca

l D

ep en

d en

t Su

b je

ct iv

e C

o n

tr o

ll ed

/ C

o ll

ec ti

o n

A n

al y

si s

K ey

P u

b li

sh ed

P o

p u

la ti

o n

Ty p

e/ Si

ze F

ra m

ew o

rk V

ar ia

b le

s In

d ep

en d

en t

V ar

ia b

le s

C o

n si

d er

ed M

et h

o d

P er

fo rm

ed

8 B

al l

20 01

A d

u lt

s li

v in

g in

S o

u th

W al

es ,

A u

st ra

li a

R an

d o

m s

am p

le o

f 3,

39 2

Y es

: s o

ci al

ec o

lo g

ic al

fr am

ew o

rk

F re

q u

en cy

a n

d d

u ra

ti o

n o

f w

al k

in g

f o

r ex

er ci

se in

t h

e p

as t

2 w

ee k

s (c

o n

si d

er w

al k

in g

o f

10 +

m in

u te

s o

n ly

)— d

ic h

o to

m iz

ed in

to an

y o

r n

o w

al k

in g

A es

th et

ic s

co re

m ea

su re

d as

r at

in g

s (L

ik er

t- ty

p e

sc al

e) o

f: 1.

N ei

g h

b o

rh o

o d

fr ie

n d

li n

es s

2. N

ei g

h b

o rh

o o

d at

tr ac

ti v

en es

s 3.

P le

as an

tn es

s in

w al

k in

g

C o

n v

en ie

n ce

s co

re m

ea su

re d

b y

r at

in g

o f:

1. S

h o

p s

w it

h in

w al

k in

g d

is ta

n ce

2. P

ar k

o r

b ea

ch w

it h

in w

al k

in g

d is

ta n

ce 3.

C y

cl e

p at

h a

cc es

si b

le

So ci

al e

n v

ir o

n m

en t

(c o

m -

p an

y )

m ea

su re

d a

s: H

av in

g s

o m

eo n

e to

w al

k w

it h

( y

es /

n o

)

A g

e Se

x E

d u

ca ti

o n

U se

d d

at a

fr o

m t

h e

19 96

A u

st ra

li an

A ct

iv it

y Su

rv ey

f o

r th

e st

at e

o f

N ew

So u

th W

al es

(t el

ep h

o n

e su

rv ey

)

L IS

R E

L (c

o n

- fi

rm at

o ry

m o

d el

— fo

r th

e 3

p er

ce iv

ed en

v ir

o n

m en

t v

ar ia

b le

sc o

re s)

at UNIV OF MARYLAND on December 16, 2009 http://jpl.sagepub.comDownloaded from

173

9 B

o o

th 20

00 A

d u

lt s

o ld

er th

an 6

0 y

ea rs

li v

in g

in co

m m

u n

it ie

s in

A u

st ra

li a

Sy st

em at

ic ra

n d

o m

iz ed

sa m

p le

o f

44 9

Y es

: S o

ci al

co g

n it

iv e

th eo

ry

P h

y si

ca l a

ct iv

it y

p ar

ti ci

p at

io n

m ea

- su

re d

a s

fr eq

u en

cy (c

o u

n ti

n g

w al

k in

g o

f 10

+ m

in u

te s

o n

ly )

an d

am o

u n

t o

f: 1.

V ig

o ro

u s

ac ti

v it

ie s

2. W

al k

in g

f o

r ex

er -

ci se

, le

is u

re , o

r re

c- re

at io

n 3.

M o

d er

at e-

in te

n si

ty ac

ti v

it ie

s su

ch a

s g

ar d

en in

g

E n

er g

y e

xp en

d it

u re

is ca

lc u

la te

d b

as ed

o n

th e

p re

v io

u s

ty p

es o

f ac

ti v

it ie

s, a

n d

f in

al o

u tc

o m

e v

ar ia

b le

s ar

e d

ic h

o to

m iz

ed b

as ed

o n

t o

ta l e

n er

g y

ex p

en d

it u

re o

f 80

0 k

ca l/

w ee

k (

su ff

i- ci

en tl

y a

ct iv

e v

s. in

su ff

ic ie

n tl

y a

ct iv

e)

E n

v ir

o n

m en

ta l i

n fl

u en

ce —

m ea

su re

d a

s p

re se

n ce

o f:

1. E

xe rc

is e

eq u

ip m

en t

at h

o m

e 2.

S af

et y

o r

d if

fi cu

lt y

o f

w al

k in

g in

t h

e n

ei g

h b

o rh

o o

d d

u ri

n g

th e

d ay

3. A

cc es

s to

f ac

il it

ie s

(e xe

rc is

e h

al l,

re cr

ea ti

o n

ce n

te r,

c y

cl e

p at

h , g

o lf

co u

rs e,

g y

m , p

ar k

, sw

im m

in g

p o

o l,

te n

n is

co u

rt , o

r b

o w

li n

g g

re en

) 4.

S o

ci al

e n

v ir

o n

m en

t (f

ri en

d a

n d

f am

il y

en co

u ra

g em

en t,

e tc

.)

O th

er n

o n

en v

ir o

n m

en ta

l v

ar ia

b le

s in

cl u

d ed

: 1.

S o

ci o

d em

o g

ra p

h ic

m ea

su re

s 2.

A tt

it u

d e

3. S

o ci

al r

ei n

fo rc

em en

t 4.

S o

ci al

m o

d el

in g

G en

d er

A g

e M

ar it

al s

ta tu

s C

o u

n tr

y o

f b

ir th

L iv

in g

si tu

at io

n (l

iv in

g a

lo n

e v

s. o

th er

) E

m p

lo y

m en

t st

at u

s

U se

d t

h e

P o

p u

la ti

o n

Su rv

ey M

o n

it o

r d

at a

(f ac

e- to

-f ac

e in

te rv

ie w

)

C h

i- sq

u ar

e an

al y

si s

L o

g is

ti c

re g

re ss

io n

10 B

ro w

n -

so n

20 00

A d

u lt

s li

v in

g in

t h

e 12

r u

ra l

co m

m u

n it

ie s

in M

is so

u ri

, U

n it

ed S

ta te

s

P o

p u

la ti

o n

- b

as ed

s am

p le

o f

1, 26

9

N o

: o n

ly m

en ti

o n

en v

ir o

n -

m en

ta l

an d

p o

li cy

ap p

ro ac

h

Tr ai

l u se

In cr

ea se

in w

al k

in g

si n

ce u

si n

g t

ra il

W al

k in

g f

o r

ex er

ci se

in t

h e

p as

t m

o n

th :

w al

k er

R eg

u la

r w

al k

in g

(5 +

t im

es /

w ee

k an

d 3

0+ m

in /

ti m

e) :

re g

u la

r w

al k

er

P re

se n

ce o

f w

al k

in g

t ra

il in

ar ea

D is

ta n

ce t

o t

ra il

Tr ai

l s u

rf ac

e Tr

ai l l

en g

th w

it h

in e

ac h

co m

m u

n it

y A

cc es

s to

in d

o o

r ex

er ci

se fa

ci li

ti es

A g

e Se

x R

ac e/

et h

n ic

g ro

u p

M ar

it al

s ta

tu s

E d

u ca

ti o

n H

o u

se h

o ld

in co

m e

P o

p u

la ti

o n

o f

th e

co m

m u

n it

y

Te le

p h

o n

e su

rv ey

o n

w al

k in

g b

eh av

io r,

k n

o w

le d

g e,

an d

a tt

it u

d e

(q u

es ti

o n

n ai

re in

cl u

d es

s ta

n -

d ar

d it

em s

fr o

m t

h e

M is

- so

u ri

B R

F SS

an d

a d

d it

io n

al it

em s)

P re

v al

en ce

o d

d s

ra ti

o

11 C

D C

19 99

A d

u lt

s ag

ed 18

+ y

ea rs

li v

in g

in t

h e

fi v

e se

le ct

ed st

at es

o f

th e

U n

it ed

S ta

te s

P o

p u

la ti

o n

- b

as ed

r an

d o

m sa

m p

le o

f 12

,7 67

N o

P h

y si

ca l i

n ac

ti v

it y

(r ep

o rt

in g

n o

a ct

iv it

y o

r ex

er ci

se d

u ri

n g

t h

e p

as t

m o

n th

)

R at

in g

s o

f p

er ce

iv ed

sa fe

ty f

ro m

c ri

m e

in t

h e

n ei

g h

b o

rh o

o d

R ac

e (w

h it

e, n

o n

w h

it e)

U se

d B

R F

SS L

o g

is ti

c re

g re

ss io

n C

o rr

el at

io n

an al

y si

s

(c on

ti n

u ed

)

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174

12 C

ra ig

20 02

A ll

c it

iz en

s o

f th

e U

n it

ed St

at es

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(2 0%

s am

p le

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lo n

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rm in

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, in

co m

e, a

n d

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al m

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e o

f tr

an sp

o rt

at io

n to

w o

rk )

N o

% w

al k

in g

t o

w o

rk E

n v

ir o

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en ta

l s co

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rh o

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u la

te d

b as

ed o

n t

h e

o b

se rv

er r

at in

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o f

en v

ir o

n m

en ta

l i te

m s

in cl

u d

in g

( ra

te d

): 1.

N u

m b

er o

f d

es ti

n at

io n

s 2.

V ar

ie ty

o f

d es

ti n

at io

n s

3. I

n cl

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v e

o f

p ed

es tr

ia n

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o ci

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am ic

s 5.

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k in

g r

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te s

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ee ts

p ed

es tr

ia n

’s n

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al k

in g

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8. T

ra n

sp o

rt at

io n

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st em

9. C

o m

p le

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st im

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s 10

. P o

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ti al

o v

er lo

ad o

f st

im u

lu s

11 . V

is u

al in

te re

st 12

. V is

u al

a es

th et

ic s

13 . T

im e

an d

e ff

o rt

r eq

u ir

ed to

w al

k 14

. T ra

ff ic

t h

re at

s 15

. O b

st ac

le s

16 . S

af et

y f

ro m

c ri

m e

17 . P

o te

n ti

al f

o r

cr im

e

D eg

re e

o f

u rb

an iz

at io

n In

co m

e U

n iv

er si

ty ed

u ca

ti o

n %

li v

in g

in p

o v

er ty

C en

su s

F ie

ld o

b se

rv at

io n

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ra rc

h ic

al li

n ea

r m

o d

el (3

le v

el s)

A P

P E

N D

IX (

co n

ti n

u ed

)

TA B

L E

A 3

(c o

n ti

n u

ed ) A

B C

D F

G H

I

C o

n fo

u n

d in

g 1s

t A

u th

o r

F ac

to rs

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a St

at is

ti ca

l So

u rc

e an

d Y

ea r

St u

d y

Sa m

p le

T h

eo re

ti ca

l D

ep en

d en

t Su

b je

ct iv

e C

o n

tr o

ll ed

/ C

o ll

ec ti

o n

A n

al y

si s

K ey

P u

b li

sh ed

P o

p u

la ti

o n

Ty p

e/ Si

ze F

ra m

ew o

rk V

ar ia

b le

s In

d ep

en d

en t

V ar

ia b

le s

C o

n si

d er

ed M

et h

o d

P er

fo rm

ed

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175

13 H

o v

el l

19 92

A d

u lt

s li

v in

g in

S an

D ie

g o

, C

al if

o rn

ia ,

U n

it ed

S ta

te s

R an

d o

m s

am p

le o

f 1,

73 9

Y es

: in

d ep

en -

d en

t v

ar ia

b le

s d

er iv

ed fr

o m

le ar

n in

g t

h e-

o ry

an d

s o

ci al

co g

n it

iv e

th eo

ry

C h

an g

e in

t o

ta l m

in u

te s

p er

w ee

k o

f w

al k

in g

fo r

ex er

ci se

b et

w ee

n b

as el

in e

an d

fo ll

o w

-u p

N ei

g h

b o

rh o

o d

s af

et y

E as

e o

f ex

er ci

si n

g in

t h

e n

ei g

h b

o rh

o o

d F

re q

u en

cy o

f se

ei n

g o

th er

s ex

er ci

se N

u m

b er

o f

ex er

ci se

f ac

il it

ie s

(a er

o b

ic d

an ce

s tu

d io

s, b

ik e

la n

es , r

u n

n in

g t

ra ck

s, e

tc .)

p er

ce iv

ed a

s co

n v

en ie

n t

So ci

o d

em o

g ra

p h

ic v

ar ia

b le

s d

ra w

n f

ro m

le ar

n in

g t

h eo

ry ar

e al

so in

cl u

d ed

A g

e Se

x E

d u

ca ti

o n

In co

m e

M ai

l s u

rv ey

B iv

ar ia

te co

rr el

at io

n H

ie ra

rc h

ic al

m u

lt ip

le re

g re

ss io

n A

N O

V A

14 K

in g

20 00

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o ri

ty w

o m

en 4

0 y

ea rs

o f

ag e

o r

o ld

er

M u

lt is

ta g

e cl

u st

er s

am p

le b

y z

ip ;

n at

io n

w id

e re

p re

se n

ta ti

v e

sa m

p le

o f

2, 91

2

Y es

: in

d ep

en -

d en

t v

ar ia

b le

s d

er iv

ed fr

o m

s o

ci al

co g

n it

iv e

th eo

ry

L ev

el o

f le

is u

re t

im e

an d

h o

u se

h o

ld -r

el at

ed p

h y

si ca

l a ct

iv it

y d

u ri

n g

t h

e p

as t

2 w

ee k

s

So ci

o d

em o

g ra

p h

ic v

ar ia

b le

s H

ea lt

h -r

el at

ed v

ar ia

b le

s P

sy ch

o so

ci al

v ar

ia b

le s

P ro

g ra

m -b

as ed

v ar

ia b

le s

E n

v ir

o n

m en

ta l v

ar ia

b le

s— m

ea su

re d

a s

p re

se n

ce o

f: 1.

S id

ew al

k 2.

H ea

v y

t ra

ff ic

3. H

il ls

4. S

tr ee

tl ig

h ts

5. U

n at

te n

d ed

d o

g s

6. E

n jo

y ab

le s

ce n

er y

7. F

re q

u en

t o

b se

rv at

io n

o f

o th

er s

ex er

ci si

n g

8. H

ig h

le v

el s

o f

cr im

e 9.

L ev

el o

f sa

fe ty

in w

al k

in g

/ jo

g g

in g

a lo

n e

Se as

o n

al v

ar ia

ti o

n in

p h

y si

ca l

ac ti

v it

y (b

y d

o in

g th

e su

rv ey

d u

ri n

g a

1- y

ea r

p er

io d

) So

ci o

d em

o -

g ra

p h

ic v

ar ia

b le

s

Te le

p h

o n

e su

rv ey

D es

cr ip

ti v

e st

at is

ti cs

P ea

rs o

n p

ro d

u ct

- m

o m

en t

co rr

el at

io n

s L

o g

is ti

c re

g re

ss io

n

15 R

u tt

en 20

01 A

d u

lt s

fr o

m th

e 6

E u

ro p

ea n

co u

n tr

ie s

R an

d o

m s

am p

le o

f 3,

34 3

N o

E n

g ag

em en

t in

p h

y si

ca l

ac ti

v it

y H

ea lt

h s

ta tu

s

O p

p o

rt u

n it

ie s

in t

h ei

r re

si -

d en

ti al

a re

a fo

r p

h y

si ca

l ac

ti v

it y

L o

ca l c

lu b

s an

d p

ro v

id er

s o

ff er

in g

p h

y si

ca l a

ct iv

it y

o p

p o

rt u

n it

ie s

C o

m m

u n

it y

a ct

io n

s to

s u

p -

p o

rt p

h y

si ca

l a ct

iv it

y

In co

m e

Te le

p h

o n

e su

rv ey

P ri

n ci

p al

co m

p o

n en

t an

al y

se s

(f o

r q

u es

- ti

o n

n ai

re te

st in

g )

D es

cr ip

ti v

e st

at is

ti cs

C o

rr el

at io

n an

al y

se s

A N

O V

A H

ie ra

rc h

ic al

re g

re ss

io n

(c on

ti n

u ed

)

at UNIV OF MARYLAND on December 16, 2009 http://jpl.sagepub.comDownloaded from

176

16 Sa

ll li

s 19

97 In

tr o

d u

ct o

ry p

sy ch

o lo

g y

st u

d en

ts fr

o m

S an

D ie

g o

S ta

te U

n iv

er si

ty ,

U n

it ed

S ta

te s

11 0

co ll

eg e

st u

d en

ts in

p sy

ch o

lo g

y

N o

: c o

n ce

p t

o f

b eh

av io

r se

tt in

g (m

en ti

o n

ec o

lo g

ic al

m o

d el

a n

d so

ci al

co g

n it

iv e

th eo

ry )

M in

u te

s o

f w

al k

in g

p er

w ee

k D

ay s

o f

v ig

o ro

u s

ex er

ci se

p er

w ee

k D

ay s

o f

st re

n g

th ex

er ci

se p

er w

ee k

H o

m e

E n

v ir

o n

m en

t Sc

al e

m ea

su re

d a

s av

ai la

b il

it y

o f

15 s

u p

p li

es o

r p

ie ce

s o

f eq

u ip

m en

t at

h o

m e

th at

ca n

b e

u se

d f

o r

p h

y si

ca l

ac ti

v it

y

N ei

g h

b o

rh o

o d

E n

v ir

o n

m en

t Sc

al e

in cl

u d

in g

: 1.

N ei

g h

b o

rh o

o d

f ea

tu re

s (s

id ew

al k

, h il

l, en

jo y

ab le

sc en

er y,

h ig

h c

ri m

e ra

te [a

n d

4 o

th er

v ar

ia b

le s]

) 2.

P er

ce iv

ed s

af et

y, m

ea su

re d

a s

sa fe

ty in

w al

k in

g in

t h

e n

ei g

h b

o rh

o o

d d

u ri

n g

th e

d ay

3. N

ei g

h b

o rh

o o

d p

er ce

p ti

o n

a s

re si

d en

ti al

, m

ix ed

, o r

co m

m er

ci al

C o

n v

en ie

n t

F ac

il it

ie s

Sc al

e, m

ea su

re d

a s

p re

se n

ce o

f 18

fa ci

li ti

es t

h at

c an

b e

u se

d fo

r p

h y

si ca

l a ct

iv it

y

A g

e Se

x E

th n

ic it

y

N o

t sp

ec if

ie d

P ea

rs o

n co

rr el

at io

n

A P

P E

N D

IX (

co n

ti n

u ed

)

TA B

L E

A 3

(c o

n ti

n u

ed ) A

B C

D F

G H

I

C o

n fo

u n

d in

g 1s

t A

u th

o r

F ac

to rs

D at

a St

at is

ti ca

l So

u rc

e an

d Y

ea r

St u

d y

Sa m

p le

T h

eo re

ti ca

l D

ep en

d en

t Su

b je

ct iv

e C

o n

tr o

ll ed

/ C

o ll

ec ti

o n

A n

al y

si s

K ey

P u

b li

sh ed

P o

p u

la ti

o n

Ty p

e/ Si

ze F

ra m

ew o

rk V

ar ia

b le

s In

d ep

en d

en t

V ar

ia b

le s

C o

n si

d er

ed M

et h

o d

P er

fo rm

ed

at UNIV OF MARYLAND on December 16, 2009 http://jpl.sagepub.comDownloaded from

177

17 W

il co

x 20

00 W

o m

en a

g ed

40 o

r o

ld er

li v

in g

in z

ip co

d e

ar ea

s w

it h

2 0+

% o

f et

h n

ic m

in o

ri ti

es an

d u

rb an

/ ru

ra l a

re a

o f

th e

U n

it ed

St at

es

M u

lt is

ta g

e cl

u st

er sa

m p

li n

g o

f 2,

91 2

N o

A m

o u

n t

o f

le is

u re

t im

e p

h y

si ca

l a ct

iv it

y in

th e

p as

t 2

w ee

k s

(i n

cl u

d in

g w

al k

in g

)— ca

te g

o ri

ze d

in to

ac ti

v e,

u n

d er

ac ti

v e,

an d

s ed

en ta

ry

E n

v ir

o n

m en

ta l

d et

er m

in an

ts m

ea su

re d

as p

er ce

iv ed

p re

se n

ce o

f: 1.

S id

ew al

k 2.

H ea

v y

t ra

ff ic

3. H

il ls

4. S

tr ee

t li

g h

ts 5.

U n

at te

n d

ed d

o g

s 6.

E n

jo y

ab le

s ce

n er

y 7.

F re

q u

en tl

y o

b se

rv e

o th

er ex er

ci se

8. H

ig h

le v

el o

f cr

im e

9. E

as y

a cc

es s

to w

al k

in g

tr ai

l, sw

im m

in g

p o

o ls

, re

cr ea

ti o

n c

en te

rs , o

r b

ic y

cl e

p at

h

So ci

o d

em o

g ra

p h

ic ,

p sy

ch o

so ci

al , a

n d

h ea

lt h

- re

la te

d v

ar ia

b le

s ar

e al

so in

cl u

d ed

R ac

e A

g e

E d

u ca

ti o

n G

eo g

ra p

h ic

re g

io n

(N o

rt h

ea st

, M

id w

es t,

So u

th , W

es t)

H ea

lt h

s ta

tu s

Te le

p h

o n

e su

rv ey

— m

o d

if ie

d v

er si

o n

o f

B R

F SS

D es

cr ip

ti v

e st

at is

ti cs

P ea

rs o

n co

rr el

at io

n s

L o

g is

ti c

re g

re ss

io n

at UNIV OF MARYLAND on December 16, 2009 http://jpl.sagepub.comDownloaded from

178

A P

P E

N D

IX (

co n

ti n

u ed

)

TA B

L E

A 4

O th

er E

xp lo

ra ti

v e

St u

d ie

s

A B

C D

E /

F G

H I

C o

n fo

u n

d in

g 1s

t A

u th

o r

F ac

to rs

D at

a St

at is

ti ca

l So

u rc

e an

d Y

ea r

St u

d y

Sa m

p le

T h

eo re

ti ca

l D

ep en

d en

t C

o n

tr o

ll ed

/ C

o ll

ec ti

o n

A n

al y

si s

K ey

P u

b li

sh ed

P o

p u

la ti

o n

Ty p

e/ Si

ze F

ra m

ew o

rk V

ar ia

b le

s K

ey R

es ea

rc h

Q u

es ti

o n

s C

o n

si d

er ed

M et

h o

d P

er fo

rm ed

18 C

o rt

i 19

97 A

d u

lt s

ag ed

b et

w ee

n 2

5 an

d 6

7

24 (

6- 8

p er

g ro

u p

) N

o : o

n ly

m en

ti o

n so

ci al

ec o

lo g

ic al

p er

sp ec

ti v

e

P h

y si

ca l A

ct iv

it y

U se

o f

lo ca

l p ar

k s

W al

k in

g a

ro u

n d

t h

ei r

lo ca

l n ei

g h

b o

rh o

o d

U se

o f

p ay

f ac

il it

y (g

y m

s, h

ea lt

h c

lu b

s, an

d r

ec re

at io

n ce

n te

rs )

N A

So ci

o ec

o n

o m

ic st

at u

s o

f th

e p

ar ti

ci p

an ts

st ra

ti fi

ed

4 F

o cu

s g

ro u

p s

R o

le -p

la y

N o

n e

19 E

y le

r 19

98 V

o lu

n te

er s

o ld

er t

h an

4 0,

an d

e it

h er

A si

an A

m er

ic an

/ P

ac if

ic Is

la n

d er

, B

la ck

, H

is p

an ic

, o r

A m

er ic

an In

d ia

n li

v in

g in

C al

if o

rn ia

o r

M is

so u

ri ,

U n

it ed

S ta

te s

Se lf

-s el

ec te

d g

ro u

p o

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NOTES

1. The programs are Active Community Environments by the Cen- ters for Disease Control and Prevention and Active Living Policy and Environmental Studies by the Robert Wood Johnson Foundation.

2. Generally, thirty minutes or more per day and five or more days per week of physical activity or an energy expenditure of 800 kcal or more per week are considered to be sufficient for health benefits.

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assignment 2/Lucas.pdf

Transport Policy ] (]]]]) ]]]–]]]

Contents lists available at SciVerse ScienceDirect

Transport Policy

0967-07

doi:10.1

E-m

Pleas j.tran

journal homepage: www.elsevier.com/locate/tranpol

Transport and social exclusion: Where are we now?

Karen Lucas

Transport Studies Unit, University of Oxford, South Parks Road, Oxford, OX1 3QY, United Kingdom

a r t i c l e i n f o

Keywords:

Transport disadvantage

Social exclusion

Theory

Policy

Delivery

0X/$ - see front matter & 2012 Elsevier Ltd. A

016/j.tranpol.2012.01.013

ail address: [email protected]

e cite this article as: Lucas, K., Tra pol.2012.01.013

a b s t r a c t

The late 1990s and early 2000s witnessed a growing interest amongst UK academics and policy makers

in the issue of transport disadvantage and, more innovatively, how this might relate to growing

concerns about the social exclusion of low income groups and communities. Studies (predominantly in

the United Kingdom) began to make more explicit the links policy between poverty, transport

disadvantage, access to key services and economic and social exclusion (see for example Church and

Frost, 2000; TRaC, 2000; Lucas et al., 2001; Kenyon 2003; Kenyon et al., 2003; Hodgson and Turner,

2003; Raje, 2003).

By 2003, the UK Social Exclusion Unit had published and its now internationally recognised report

on this subject, which subsequently resulted in the development of a set of transport policy guidances

to local authorities in England to deliver what is now commonly referred to as accessibility planning as

part of their Local Transport Plans (Department for Transport, 2006). Since this time, researchers, policy

makers and practitioners in several other countries became interested in adopting a social exclusion

approach to transport planning, largely because of its utility in identifying the role of transport, land use

planning and service delivery decisions in creating and reinforcing poverty and social disadvantage.

Eight years on from the SEU report, we can begin to reflect on the extent to which a social exclusion

approach to the research of transport disadvantage has been successful in opening up new avenues of

research enquiry and/or identifying new theoretical perspectives and/or methodological approaches.

The paper begins by briefly revisiting the basic theories and core definitions which underpin and inform

a social exclusion perspective. It then considers how these have been translated and understood in

terms of transport. Secondly, it considers some of the emergent empirical research of transport-related

exclusion that has attempted to measure and model the interactions between transport and mobility

inequalities and relational negative social outcomes. Thirdly, it offers observations on progress in some

key areas of policy and practice, with specific reference to the UK and Australia. It concludes by

suggesting how further progress might be made on this issue and considers whether the social

exclusion agenda is still a relevant approach for achieving this.

& 2012 Elsevier Ltd. All rights reserved.

1. Introduction

The 2002–2003 Social Exclusion Unit (SEU) study of transport and social exclusion is widely recognised as having an important influence on this policy stance (Social Exclusion Unit, 2003). The most important contribution of the study is generally considered to be the way it has helped to identify the inter-relationships between transport disadvantage and key areas of social policy concern, such as unemployment, health inequalities, poor educational attainment and run-down neighbourhoods and estates. Since 2006, local trans- port authorities in the UK have been required to undertake strategic and local accessibility assessments as part of their statutory five yearly Local Transport Plans (Department for transport, 2006) and to work in partnership with other local public bodies to find solutions

ll rights reserved.

nsport and social exclusio

to the accessibility deficits these analyses identify. At the time of writing, it has been eight years since the UK Social Exclusion Unit (SEU) published its now widely acclaimed report on transport and social exclusion (Social Exclusion Unit, 2003). The intervening period has witnessed considerable academic interest in the subject not only in the UK but also in mainland Europe, Australasia, the Americas and South Africa.

I will be returning to a more detailed discussion of the contribu- tion these studies in later sections of the paper, but when taken in aggregate they have largely helped to establish the highly context and person specific nature of the phenomenon, as well as to develop some innovative methodologies for identifying and measuring it. Despite this mounting body of research, there is still a great deal of confusion surrounding the concepts and definitions of transport-related social exclusion, how these might be successfully measured and modelled and whether the research of transport disadvantage from this perspective constitutes a useful approach for policy makers

n: Where are we now? Transport Policy (2012), doi:10.1016/

K. Lucas / Transport Policy ] (]]]]) ]]]–]]]2

and practitioners. This paper considers and discusses these issues based on evidence of the available published and ‘grey’ literatures and my own experience of working in this field as an academic and policy advisor in various national and local contexts.

The scope of the paper is extremely limited, given the magnitude of this subject. It is intended to offer only an overview, rather than a comprehensive or complete review. It aims to make more explicit some of the fundamental underlying principles which underpin research enquiry in this area and to explore how far ‘transport-related exclusion’ can be accepted as a theoretical concept for describing the social consequences of transport. It then discusses some of the empirical research which has sought to identify and measure the incidences of transport- related exclusion in different local and national context. Finally, it draws on the evidence of two national case studies to assess progress in the development of policies and programmes to address the social exclusion effects of transport.

2. Understanding the concept of social exclusion

A great deal has already been written about social exclusion as a theoretical concept, mostly developed within the field of social policy research, and thus numerous definitions abound (Hills et al., 2002). There is no overarching consensual view about what precisely constitutes social exclusion, but there is wide agreement that it reaches beyond a description of poverty to provide a more multidimensional, multilayered and dynamic concept of depriva- tion. For example, Levitas et al. (2007) have identified social exclusion as involving:

‘y the lack or denial of resources, rights, goods and services, and the inability to participate in the normal relationships and activities, available to the majority of people in a society, whether in economic, social, cultural or political arenas. It affects both the quality of life of individuals and the equity and cohesion of society as a whole.’ (Levitas et al., 2007: 9)

The particular rationale for adopting a social exclusion approach to transport disadvantage is that it helps policy makers to recognise that: (a) the problem is multi-dimensional i.e. can be located with both the circumstances of the individual who is affected and processes, institutions and structures within wider society; (b) it is relational i.e. disadvantage is seen in direct comparison to the normal relationships and activities of the rest of the population; and (c) it is dynamic in nature (i.e. it changes over time and space, as well as during the lifetime of the person who is affected). In policy terms, the concept also forces a focus not only on the experience of disadvantage but also on the associated economic and social outcomes of this condition.

Crucially, for the study of transport-related exclusion, it is essential to recognise that the concept of social exclusion empha- sises the interactions between those causal factors which lie with the individual, such as age, disability, gender and race, factors which lie with the structure of the local area, such as a lack of available or inadequate public transport services, the failure of local services and factors that lie with the national and/or global economy, such as the re-structuring of the labour market, cultural influences, migration and legislative frameworks.

The concept is also useful from a transport policy perspective because it specifically relates these problems back to the values, processes and actions of key delivery agencies, which are seen to have systematically excluded certain individuals, groups or communities from the benefits of their policy decisions and practices. The implication of this conceptualisation, therefore, is that its resolution primarily rests with the social agencies that are responsible for policy

delivery, rather than the individuals that are affected. However, it is

Please cite this article as: Lucas, K., Transport and social exclusio j.tranpol.2012.01.013

also vital for policy makers to recognise that the abilities, skills, resources, capacities and past experiences of affected individuals also need to be considered in the design of policy solutions.

Furthermore, documenters of the phenomenon are less inter- ested in the fact that there is no transport available to people per se but rather the consequences of this in terms of their (in)ability to access key life-enhancing opportunities, such as employment, education, health and their supporting social networks. In this way, there is a move away from the traditional systems-based approach to transport provision, towards a more people-focused and needs-based social policy perspective. It asks questions about equality of opportunity to access key services and equity of outcome rather than outputs and also begins to raise the issue of redistributive justice, i.e. the extent to which policy should seek to redistribute transport wealth in the interests of ‘fairness’ or ‘justice’ (see Lucas, 2004 for more on this).

3. Transport/mobilty disadvantage

Transport and/or mobility inequality is not a new theme within the transportation literature. For example, as early as 1973 Wachs and Kumagai identified physical mobility as a major contributor to social and economic inequality in the US context (Wachs and Kumagai, 1973). Similarly, in the UK, Banister and Hall (1981) asserted that transport clearly had an important role to play in determining social outcomes for different sectors of modern society in terms of both the absence of adequate trans- port services and the impact of the transport system on indivi- duals and communities. There is also plenty of empirical evidence of this phenomenon.

However, it is important to establish, that transport disadvan- tage and transport-related social exclusion are not necessarily synonymous with each other, i.e. it is possible to be socially excluded but still have good access to transport or to be transport disadvantaged but highly socially included (Currie and Delabosc, 2010). Rather transport disadvantage and social disadvantage interact directly and indirectly to cause transport poverty. This in turn leads to inaccessibility to essential goods and services, as well as ‘lock-out’ from planning and decision-making processes, which can result in social exclusion outcomes and further social and transport inequalities will then ensue. Fig. 1 is an attempt to illustrate some of these key interactions.

Transport surveys demonstrate that it is most usually the poorest and most socially disadvantaged within society who also experience transport disadvantage. Almost every National Travel Survey (NTS) identifies significant inequalities in the travel patterns and access to transport of lower income populations in comparison to their higher income counterparts. For example, the 2006 UK NTS identifies that, whilst on average car ownership levels rest at around 85%, less than 50% of the lowest income quintile households own a car. Although 40% of individuals in the lowest income households report travelling by car at least once a week, they make only around one-tenth the car trips of members of one car households and they make far fewer trips in a week overall, using any mode of transport (Department for Transport, 2007). The annual journey distances of non-car owners is also roughly half that of car owners (ibid) with the consequence that many people on low incomes also experience social exclusion as a direct or partial result of these transport inequalities (Social Exclusion Unit, 2003).

Surprisingly, given the levels of car penetration in the US (approximately 92% of all households have access to a private vehicle), car ownership amongst the lowest income quintile is only slightly higher than it is in the UK (around 60%). Women are more likely to drive across all age categories in the USA than in

n: Where are we now? Transport Policy (2012), doi:10.1016/

Fig. 1. Diagram to illustrate the relationship between transport disadvantage, social disadvantage and social exclusion.

1 Coloured is still an official racial classification within the RSA NHTS

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the UK and there is less of a gender difference between licence holders and non-licence holders than in the UK. Black Americans are far less likely to own and drive a car than their white counterparts, with 20% of all Black households not having access to a car. American Indians, Hispanics, Pacific Islander, Asian and people of mixed race are also less likely to own cars than white Americans (Clifton and Lucas, 2004). There is con- siderable evidence to suggest that low income non-car owning households in the US also have less access to public transit (Garcia and Rubin, 2004) and, hence, experience considerable difficulties in accessing jobs (Cervero, 2004) and other key facilities (Morris, 2004).

In Australia, Currie et al. (2007) have identified that acute cases of transport tend to be found in suburban and regional areas, where distance is a major barrier to economic and social inclusion. Although, Australia has amongst the highest car ownership in the world, not everyone has a car or can drive. Young people (Johnson, 2011), low income households (Hurni, 2006) and aboriginal populations (Altman and Hinkson, 2007), in particular, are known to experience difficulties in accessing work, education, shops and leisure and cultural activities. Driving cessation is a major concern for older Australians, since economic and social life tends to revolve around the car and cessation has been associated with a decline in travel and social activity in later life (Browning et al., 2007).

In the Canadian context, Páez et al. (2009) (2009b) have been recording similar trends from their analysis of the Toronto and Montreal Household Travel Surveys finding that lower income households and particularly elderly and disabled Canadians travel considerably less and over shorter distances and have less access to key services than the average Canadian population.

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These transport inequalities can also be seen within the development context. For example, the 2003 South African National Household Travel Survey identified that identifies that the majority of poorer households also experience extremely poor access to private vehicles and public transport services. On average, only 26% of the lowest income quintile households had access to a car, more than 75% had no access to a train station and nearly 40% did not have access to a bus service. Whilst the majority of the white population (83%) hold a driving licence, only 10% of the black population, and 21% of coloureds1 and just over half of the Asian population (56%) do so (Republic of South Africa National Household Travel Survey, 2005). As a result, the majority of black South Africans state difficulties when trying to access work, education, healthcare, social welfare assistance and with visiting family members (Lucas, 2011a).

What is less clear from this statistical evidence is the extent to which this reduced mobility and access to services leads to the social exclusion of affected individuals and/or reduces their social capital, life chances and overall well-being. In my view, there have been three key areas of progress in terms of the research of transport and social exclusion which have emerged over the last eight years in this respect: (i) better conceptualisation of trans- port-related exclusion as a social phenomenon; (ii) improved identification and measurement of social disadvantage and its interaction with transport provision, in different geographical contexts, using new and innovative techniques and; (iii) greater policy recognition of these issues and practical responses to the problem. Given the epic proportions of the task, I only attempt to

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briefly describe progress in each of these areas within the context of this paper (a greater discussion of these issues can be found in Lucas 2011b, 2011 and Lucas and Currie, 2011).

4. Progress with theoretical conceptualisations

Kenyon et al. (2003: 210) offered the following, widely-cited definition of transport-related social exclusion, highlighting its accessibility and mobility dimensions:

‘[It is] The process by which people are prevented from participating in the economic, political and social life of the community because of reduced accessibility to opportunities, services and social networks, due in whole or part to insuffi- cient mobility in a society and environment built around the assumption of high mobility’

This definition is particularly cogent in the transport context because it identifies the relational nature of the problem, i.e. that it is the high and increasing levels of mobility within the population as a whole that is a key causal factor in the reduced, accessibility and, ultimately, exclusion of less mobile sectors of the population.

More specifically, Church et al. (2000: 198–200) denote seven specific features of the transport system that are contributing and/or related to the exclusion of certain population groups, which in line with social exclusion theory would appear to confirm the multidimensional nature of the problem. The identi- fied seven categories are:

i)

Ple j.t

physical exclusion: whereby physical barriers, such as vehicle design, lack of disabled facilities or lack of timetable informa- tion, inhibit the accessibility of transport services;

ii)

geographical exclusion: where a person lives can prevent them from accessing transport services, such as in rural areas or on peripheral urban estates;

iii)

exclusion from facilities: the distance of key facilities such as shops, schools, health care or leisure services from where a person lives prevents their access;

iv)

economic exclusion: the high monetary costs of travel can prevent or limit access to facilities or employment and thus impact on incomes;

v)

time-based exclusion: other demands on time, such as com- bined work, household and child-care duties, reduces the time available for travel (often referred to as time-poverty in the literature);

vi)

fear-based exclusion: where fears for personal safety preclude the use of public spaces and/or transport services;

vii)

space exclusion: where security or space management prevent certain groups access to public spaces, e.g. gated commu- nities or first class waiting rooms at stations.

Whilst this list maps the overall nature of the problem of transport-related exclusion, it does little to express at which level or layer of activity it occurs and, thereby, fails to identify where the policy attention should be directed, i.e. is it the individual which needs direct policy assistance, the social capital of the community that needs to be enhanced or better local services that are needed or the more strategic system of transport or land use planning that needs to be addressed?

4.1. Accessibility perspectives

To address this shortfall, Greico (2006) proposes three main dimensions for the analysis of transport-related social exclusion, namely: (i) place-based measures, including opportunities and

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services within the immediate area in which a person lives; (ii) social-category based measures, such as social stratification within as community to identify social need; and (iii) person- based measures, such as the individual public transport user’s profile of journey needs. However, it is also essential to recognise, the dynamic and relational nature of the exclusionary process where transport is concerned, however, i.e. the more mobile society becomes the more certain groups are excluded from and/or disproportionately impacted by the system (Kenyon, 2003). This suggests that to reduce transport-related social exclusion policy makers should not only be concentrating on the populations that are currently excluded or at risk of exclusion but also on reducing the escalating dynamic of hypermobility and its effects across society as a whole (Urry, 2000).

4.2. Social capital and capability perspectives

Urry (2000) builds on this theme of dynamic exclusion from the transport system within his new mobilities paradigm. His theories are concerned with macro (global), meso (national) and micro (local) changes in the physical and virtual movement of people, goods, services, images and information over time (Kaufmann, et al., 2004; Sheller and Urry, 2006; Urry, 2007). As Cass et al., 2005 identify, the new mobilities perspective is particularly important because it explores how different forms of mobility help to shape wider societal values and norms and to reinforce existing social stratification. Theorists from this perspec- tive identify motility (the potential and ability to move) consists of three main layers: (i) access—the range of all available mobilities according to time, place and other contextual constraints; (ii) competence—the skills and abilities that directly or indirectly relate to the appropriation of access; (iii) appropriation—how individuals, groups, networks or institutions act upon or interpret perceived or real access and competences (Kaufmann et al., 2004). Unequal mobilities are seen as arising from differences in the status, wealth, prestige, power and geographical distribution of people and activities (Urry, 2007).

Urry argues that unequal ‘network capital’ is distributed across traditional social stratifications leading to differential opportu- nities to access goods, services, social networks and life chances, which results in the social exclusion of both individuals and whole communities. One of the key issues that Urry and his colleagues bring to light within their thesis is the extent to which transport-related social exclusion can ever be properly addressed within a global system that prioritises hypermobility. Dennis and Urry (2009) predict it is not until After the Car that we will be able to establish the more equitable distribution of transport services. This implies that the problem of transport-related exclusion largely lies outside the influence of national or local policy makers.

4.3. Time geography perspectives

Time geographers have also opened up further challenges for the study of transport-related disadvantage, in particular their consideration of the issue from a time-space perspective,. Theor- ists here focus on the fundamental societal changes that have taken place over the last fifty years in spatial organisation of society (e.g. Miller 1999; Dijst et al., 2005; Neutens et al., 2009). These structural changes have created new inequalities in the opportunities that are available to different people within given timeframes, causing time-poverty based exclusion for certain social groups, particularly working women with children (Priya Uteng, 2009; Schwanen, 2011). The demands of tight scheduling, multi-tasking and multiple responsibilities are experienced dif- ferently by different population groups and by people living in

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different locations, particularly people living in rural areas and on peripheral urban estates (Lucas, 2004).

The particular insight time geography offers to the analysis of transport-related exclusion is that often it is people’s own preferences, needs and attitudes which determine the transport choices that are available to them. In this case, the transport disadvantages or time poverty that they experience may be the product of self-enforced, rather than externally imposed, physical isolation and exclusion (Currie and Delabosc, 2010). Barry (2002) refers to this form of self-imposed exclusion in his chapter entitled ‘Social Exclusion, Isolation and Income’, finding that:

‘The private car is the enemy of social solidarity in as much as public transport is its friend. The private car isolates people and puts them in competition with other road users’ (Barry, 2002: 26)

He suggests that the problem of higher income sectors of the population effectively ‘opting out’ from the use of public services is all part of the dynamic nature of the problem of social exclusion and also needs to be addressed by policy.

5. Progress with identification and measurement

As identified above, considerable progress has also been made with the development and application of innovative methods and techniques for the identification and measurement of transport- related social exclusion. These studies have taken place in different geographical and national context and have helped to establish that the phenomenon is universally experienced in both the developed and developing world. They also demonstrate its incidence to be highly correlated with social disadvantage and the level of transport provision that is available within households and neighbourhoods. There are also strong interactions with service delivery patterns, housing density and land uses, as well as the structure of the local economy and employment patterns.

It is not possible to revisit all of these studies in the context of this paper, but the examples which have been selected aim offer a flavour of the range of different methodological approaches which have been applied.

5.1. Accessibility studies in the uk

Since the publication of the SEU report in 2003 there have been numerous academic studies which have explored the various issues of mobility, accessibility and transport disadvan- tage in different geographical contexts in the UK. The main contribution of these studies has been to identify the highly context- and person-specific nature of transport-related exclu- sion, which clearly not only differs in terms of the experiences of low-income rural and urban populations (e.g. McDonagh, 2006; Farrington, 2007, Wright et al., 2009), but has also been demon- strated to vary for different socially excluded population groups within the same local contexts (e.g. Rajé, 2004; Preston and Raje, 2007; Mackett et al., 2006; Jones and Wixey, 2008). In most instances these studies have involved detailed local accessibility mapping of local travel survey data in combination with the transport system, using enhanced GIS-based tools.

For example, a Scottish study, Hine and Mitchell (2003) focused on three geographically defined case study areas to identify ways in which the transport system was creating transport disadvantage and to establish how this might be addressed through policy. The surveys identified that the residents who relied solely on public transport found it more difficult to access key activities in the local area and a small number of respondents in each of the three areas reported that transport considerations had prevented them from

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looking for work or accepting a job and/or accessing education. Respondents without a car also tended to go less frequently on shopping trips and to visit friends and family. Respondents also expressed a high degree of concern for their personal safety in relation to accessing and using public transport.

However, Preston and Raje (2007) identified that having transport (whether private or transit) available is not always a factor in social exclusion and that it is only where the price of transport exceeds its affordability that social exclusion occurs. On this basis, they recommend that policy maker can improve social inclusion by either; reducing the price of transport, and/or increasing social contact through virtual mobility, and/or increas- ing proximate facilities/contacts through land-use planning or pro-neighbourhood policies, and/or increasing incomes. Using a GIS-based mapping tool of the local walking environment and data collected through footfall surveys, Mackett et al. (2008) demonstrated the importance of micro level infrastructure for some disadvantaged groups.

5.2. Spatial and social network analysis in mainland Europe

Ohnmacht et al. (2009) identify three European studies to identify the interaction between people’s spatial networks and the social inequalities which can arise from an increasing demand for people to be more mobile. The first of these summarised the key findings of the GLOBALLIFE project, which was designed to perform a cross-national comparison empirical analysis of the effects of globalisation processes on the life-courses of men and women (Blossfeld et al., 2009). The study concludes that the spatial dynamics of the globalisation process have significantly affected the mobility of labour and labour capital. This has had the effect of reinforcing pre-existing social inequalities and class divides.

In the second case study, Frei et al. (2009) argue that an individual’s social networks are a particularly important area of study for social exclusion, in that they are generally seen to be the main way in which individuals and communities maintain their social capital. The stronger the social network, the greater the level of social capital and thereby access to life opportunities and resources. The study identified that car ownership (and the associated mobility that this offers) had a positive effect on the size and strength of the respondents’ social networks. Being less anchored to a physical location and also more professionally flexible also had a positive effect on the size of a person’s social network.

Furthering in this theme of social capital, the third case study considered the relationship between social capital and commut- ing in the Swiss cities of Zurich, Genoa and Basle (Viry et al., 2009). The authors found that having ‘a strong mobility capital’ allows individuals to maintain or widen their social capital. Conversely, for the disadvantaged populations in the samples (particularly for isolated women with children, migrants, less educated people and people with disabilities) having no car and living in a place isolated from the public transport system, effectively acts to weaken their social capital.

In a Norwegian study, Priya Uteng (2009) used a combination of quantitative and qualitative methods to understand the mobility patterns and transport-related exclusion of a specific sector of the Norwegian population, namely non-Western female immigrants, who have been identified as particularly isolated from mainstream economic and social participation in Norwegian society. Importantly, her study identifies the way in which ethnically divided space shapes a sense of both belonging and difference, including language, codes of behaviour, value systems and social networks, which have little or nothing to do with either transport or spatial planning. She argues that in this context, mobility (and ergo transport) becomes a highly

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internalised personal confine, which serves to act against integra- tion. From a methodological point of view, therefore, place-based measures of accessibility ignores these highly individualised (and internally imposed) experiences of social exclusion, which also predominantly lay outside of the transport policy makers’ jurisdiction to address.

5.3. Structural and spatial modelling studies in Australia and Canada

Currie et al. (2009, 2010) undertook structural equation model- ling of data from the Victoria Household Travel Survey to empirically measure the links between transport disadvantage (on a number of different self-reported dimensions); social exclusion (using pre-determined indicators of income, unemployment, political engagement, participation and social support) and well-being (using an internationally recognised Satisfaction with Life Scale). Their modelled results showed the positive relationship between trans- port and disadvantage to be highly statistically significant (po.001). Interestingly, however, the authors found no significant relationship between realised trips and self-reported experiences of transport disadvantage, i.e. people who travelled a lot were just as likely to report difficulties with their transport as those who travelled little. It was identified that this was largely due to a time-poverty issue with the higher income, economically active respondents, which seems to support Barry’s thesis above (2002) that less disadvantaged people may also experience social exclusion from the physical isolation that a car based society allows. Currie and Stanley (2006) have also explored the role of public transport in promoting social capital in the Australian context, suggesting the links to be small but never- theless significant, particularly for older sectors of the population.

In Canada, Páez et al. (2009, 2010) also modelled the prevalence and extent of transport-related social exclusion in Toronto and Montreal using Household Travel Survey data, Census and Business Point Data. Their study focused on three vulnerable groups; seniors, low income people and single parent households within the urban areas of Hamilton, Toronto, and Montreal. Their analysis was based on a statistical and spatial modelling approach to identify person- and location-specific estimates of trip making frequency and distance travelled. They identified car ownership as highly important in influencing both trip generation and distance travelled, except in the case of single parent households. They concluded that, in general, the three identified vulnerable groups tend to make fewer or no trips, and have smaller activity spaces than the average population in both study areas. In terms of their three accessibility case studies, in Toronto, single parent households have relatively better accessi- bility to jobs near the central part of the city, but experience relative accessibility deprivation outside of this area. In Montreal, they found that low income individuals’ access to retail food tends to be relatively better than access to fast food in the central part of the region and the outer suburbs, but the opposite is true of a broad ring covering the outer part of the central city and the inner suburbs. Finally, in Hamilton, access to health care services for senior citizens was also relatively higher in the central part of the city but tends to decay very rapidly outside of this area, resulting in extremely low accessibility in most parts of the city.

There is clearly some way to go in terms of establishing systematic robust and effective ways to identify the extent and severity of transport-related social exclusion in different contexts and for different sectors of the population. Nevertheless, these studies demonstrate significant progress in this respect since 2003. The question remains as to how far these studies have had an impact on policy and service delivery in practice and is the focus of the next section of this paper.

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6. Progress in policy and with practical delivery

Despite its limited scope, the paper thus far has established that transport-related social exclusion is broadly accepted as a broad-brush theoretical concept for describing the social conse- quences of transport disadvantage within the academic literature. I next consider the extent to which this has influenced the transport policy agenda and/or been realised in the practical deliver of new transport projects at the local level. I draw specifically upon the two examples with which I am personally familiar: UK and Australia. Progress is not limited to these national contexts, however, and government websites reveal that policy makers in France, Spain, Canada, New Zealand, and South Africa are all currently responding to the transport and social exclusion agenda. Although often not specifically using the language of social exclusion, many other countries, such as the United States, Germany and the Netherlands, also offer policies to address the transport needs of socially disadvantaged population groups. This would suggest a break from transport policy tradi- tion, which has in the past tended towards a greater recognition of the economic and environmental outcomes of planning and decision-making.

6.1. The UK experience

The Social Exclusion Unit (SEU) study of transport and social exclusion is widely recognised as having an important influence on the UK policy approach (Social Exclusion Unit, 2003). Most impor- tantly it introduced a systematic process of accessibility planning within local transport, land use and service sector planning to identify and address the transport problems of socially excluded populations. Since 2006, there is a statutory requirement for local transport authorities to undertake strategic and local accessibility assessments as part of their five year Local Transport Plans. They must work in partnership with other local public bodies and key stakeholders to find solutions to the accessibility deficits these analyses identify (Department for Transport, 2006).

In 2009, the Department for Transport commissioned a three- year evaluation study to identify both the progress and impact of accessibility planning within local transport authorities. This has not yet officially reported and so, as yet, there are no formal evaluations of accessibility planning or of the interventions that have been put in place. An interim report (Centre for the Research of Social Policy (CRSP), 2009) identified major differences in approaches across the nine case studies it examined. It found that some authorities were targeting improved access at socially excluded groups and others introducing more universal measures for improved accessibility for all. Some plans were more transport-sector focused whilst other shared the responsibility for improvements with other key stake- holders such as health providers or social services. The research identified the important role of local champions as crucial to the delivery process; the authorities who had key personnel who understood both the value of the process and have the skills to develop multi-stakeholder agreement are making the biggest impact on the ground. Some local transport authorities have also achieved notable success with engaging other sectors in accessibility planning process. For example, both Merseytravel (Merseyside) and Centro (West Midlands) have secured significant partnership collaborations with their local employment services through the Workwise pro- gramme, which provides assistance with travel in the transition from welfare into work.

Other evaluation research has identified that public transport improvements in deprived areas have delivered significant improvements in bus patronage and travel uptake, as well as having knock-on benefits in terms of the take-up of new employ- ment, educational opportunities and healthcare visits (Lucas et al.,

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2008; Bristow et al., 2008). However, it has been virtually impossible to maintain the introduction of such initiatives with the advent of new economic austerity measures in the UK. Much of the subsidy funding for these new services has now run out and most are unable to continue to operate on a commercial (non- subsidy) basis. In addition, local transport authorities are review- ing their provision of socially necessary bus services more gen- erally in light of major cutbacks in central government funding streams.

The ‘new localism’ agenda which is currently being pro- pounded by the Coalition Government would suggest a tendency towards greater locally determined projects, with a potential danger that communities with the greatest political leverage will benefit whilst those with less capacity lose out. Meanwhile, both the Social Exclusion Unit and the Mobility and Inclusion Unit have been disbanded within central government and the focus of the social policy agenda for transport under the new administration remains opaque. These trends obviously have considerable impli- cations for the future of the transport and social exclusion policy at both the national and local level.

6.2. The Australian policy experience (State of Victoria)

Whilst the transport and social exclusion agenda appears to be on the wane in the UK, in the Australian context the reverse appears to be true, although it has followed quite a different policy trajectory here. In Australia, the federal government devolves most of the functions of transport governance to its States, which are responsible for autonomous policy development and delivery. This means that transport policy-making and plan- ning is much more regionally diverse and it is not possible to generalise the transport agenda across States. For this reason, I will focus on policy and delivery progress in the State of Victoria only. Since 2008, the Victoria Department of Transport (VICDOT) has been a lead player in the development of a transport and social exclusion agenda along similar lines to the SEU approach. Although other States have been developing their own social transport agendas, VICDOT is generally recognised as the front runner in this respect.

Transport disadvantage had long been recognised as a policy problem at the national level within Australia (e.g. Travers Morgan, 1992), but States were slow to adopt appropriate implementation strategies. For example, in the State of Victoria the process only began in 2004, when a group of transport academics and policy makers in the Melbourne region came together to discuss the issue of transport-related social exclusion in the Australian context, largely motivated by the SEU study. An edited publication resulted from the collaboration, which helped to establish an evidence base for transport-related social exclu- sion for certain population sectors and areas in Australia (Currie et al., 2007). A local organising committee was formed called the ‘Transport and Social Inclusion Committee’ (TASIC) which held a series of seminars and conferences to campaign for government action on policy to improve social inclusion outcomes from a transport perspective (Monash University, 2007).

The Victorian State Government had already campaigned on a platform that sought to address social disadvantage and studies have been undertaken by other independent agencies to compre- hensively identify key areas of deprivation across urban and rural Melbourne (e.g. Vinson, 2004). Its policy platform ‘A Fairer Victoria’ (Victoria Department of the Premier and Cabinet, 2005a, 2005b) focused on social sustainability and sought to improve access to services, reduce barriers to opportunity, strengthen assistance for disadvantaged groups and places and ensure that people get the help they need. Transport policies were briefly noted in this social policy document but were largely

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absent from the delivery plans of this and subsequent social policy documents.

Specific approaches to addressing transport disadvantage are described in various Department of Infrastructure documents (State of Victoria, 2008a, 2008b). Up to 2007 the main aim of the Victorian programme had been to reduce this transport disadvantaged through funded increases in public transport service levels with a focus on fringe urban and rural contexts (Loader and Stanley, 2009). In addition, the level of fares had been reduced for certain disadvantaged key groups (seniors over 60 years, young people under 18 years, people with disabilities and jobseekers) on a State wide basis. These measures directly targeted transport-related social exclusion related to transport and were part of what is termed ‘social transit’ within Victorian policy. This refers to transport services, including fixed route bus services, which cater for sections of the community that have limited or no transport options (Betts, 2007). It is separate from transport service catering for ‘mass transit’ i.e. volume not needs.

The Transport Connections Programme (TCP) has been another key feature of the Victorian approach (Victoria Department of Planning and Community Development website). This sought to build the capabilities of local government to find innovative solutions to transport disadvantage. It provided the financial support to employ local transport coordinators within commu- nities in order to build partnerships to deliver services between councils, local community transport providers and the resident community itself. A key theme is enduring outcomes and support for coordination of resources. An AU$4.19 m (approx. £2.9 m) ‘flexible fund’ supports the programme by providing funding for new projects. This programme is also seeking to find localised ways to bridge gaps due to ‘silo thinking’ between agencies and providers of transit. Since 2010, VICDOT has also established a Social Transit Unit to work closely across the department and its wider transport portfolio and with other government agencies and the community sector to identify issues that prevent people using the public transport system.

Loader and Stanley (2009) have identified that the Smartbus’ programme of improved ‘social transit’ services in Outer Melbourne that were supported through the ‘flexible transport fund’ has resulted in both patronage growth and social inclusion. Services have been upgraded to offer new minimum service levels, particu- larly extending the duration and frequency and operating hours of services and re-routing services to link with key employment, education and shopping destinations in the urban periphery. All five new routes have experienced significant patronage growth exceeding the relative growth that would have been expected from the introduction of traditionally routed peak services within central Melbourne. They have also opened up new employment and social opportunities and have increased social capital and inclusion, particularly for the youth and elderly population.

The federal government in Canberra is now also looking into the development of guidelines for addressing transport-related social exclusion at the national level.

7. Conclusions: where are we now?

This paper offers a flavour of the theoretical, empirical and policy progress that has been made in the field of transport and social exclusion since 2003, which has been identified as a pivotal point in this agenda. It has established that the concepts of social exclusion and its theories and methodologies emerged from the social policy discipline in the mid-1990s and were later pick-up on and explored as an area of related interest by transport researchers. One key question, therefore, is whether the concept has travelled well and

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whether it has been recognised and accepted as a discrete and robust subject area within the discipline.

It is clear from even the partial and limited coverage of the paper that since the relatively recent appearance of transport and social exclusion in the early 2000, progress has been considerable on three fronts. Firstly, the paper has established that the concept of transport-related social exclusion now has significant reso- nance with the transport research and policy community inter- nationally. Secondly, it has shown that the methodologies that have been developed and applied to identify and measure trans- port-related exclusion as a social phenomenon are highly varied, innovative and increasingly sophisticated in their overall design. Thirdly, the findings of the studies that have been undertaken add considerable weight to the claim that transport-related exclusion can be identified as a universal and operational concept, although it is differentially experienced within and between nations and by different social groups in different social and geographical contexts.

Despite this research progress and a promising early start in the UK, there appears to be relatively poor take-up of the transport and social exclusion agenda amongst local transport authorities. The VICDOT case is perhaps the exception to this rule, although even here the effort is meagre in comparison to the overall public transport spend for the region and it is still early days. Part of the problem has been with articulation and com- munication of the agenda to key delivery agencies, as well as a lack of available public subsidy for promoting new ‘social transit’ services more generally. There is a general consensus amongst those with an interest in seeing this agenda more widely promoted that better social evaluation and appraisal tools are needed at every level of governance. Metrics are needed to establish the minimum level and standards of public transport which are necessary for social inclusion given certain distances, densities, levels of services, etc. and local targets set to achieve these within given timeframes. To achieve this goal, social inclusion also has to be an explicitly stated outcome within service contracts with public transport operators.

Neither should the transport and social exclusion agenda be limited to a local or even national governance agenda, but should also be extended to high level funders of major infrastructure programmes such as the World Bank and other Development Banks. Indeed, it is arguably even more important to meet such basic standards of transport inclusion in the Global South, where the majority of the population is faced by woefully inadequate transport services and the social exclusion which results from a basic lack of access to employment, education, healthcare and other basic amenities.

What is clear from the case studies that are already available is that there is no panacea for addressing the problem of transport- related exclusion. One size definitely does not fit all and so many more examples are needed of what does and does not work in practice, within different geographical and social contexts and for different groups of people. If properly designed and delivered, public transport can provide a part of this solution, but it is most likely that other forms of more flexible (and often informal) transport services will be needed to complement these mainstream services. This does not come cheap and, as the UK experience demonstrates, if not properly supported and subsidised, these complementary measures will not deliver their desired outcomes.

Furthermore, transport and social exclusion can never survive as a solely transport-focused agenda. The accessibility planning (in its broadest sense) of public transport which is necessary to meet the travel needs of socially excluded people must be highly integrated with socially responsible land use, housing, health, education and welfare policies and programmes. Similarly, large transport infrastructure projects need to be more transparent in

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their ex ante analyses to consider their long-term social equity effects on local populations and communities.

It is my belief that much progress has already been made within the transport sector to recognise and begin to address the issues raised by this paper, but as yet we still have a long way to go in convincing other key sectors of the value of recognising the importance of this agenda. This will only happen if we are willing and able to raise the profile of our research within other relevant policy sectors such as health, social policy, development studies and housing and planning. We need to convince our colleagues in these other policy areas that transport really matters to them and their own policy goals.

Finally, we need to recognise that the social research agenda itself is moving forward. In light of the current global economic crisis, many researchers in geography, urban studies and else- where are now fundamentally questioning the neo-liberal agenda and the theories and concepts which have supported it. Issues of social, spatial and environmental justice are brought to the fore within their emerging research debates, which suggest that wholly new, radical and transformative research programmes are needed in order to overthrow the redundant social develop- ment paradigms of a bygone era. To meet this challenge we need to develop new interdisciplinary theories and innovative metho- dological approaches so that policymakers can move beyond the ineffective ‘trickle-down’ models they are currently applying and towards the development of ‘just cities’ for all. Transport and access has a fundamental role to play in this transition and so understanding the processes, actions and decisions which lead to transport-related exclusion should be one of the key foci of our future transport policy research.

Acknowledgements

In the words of one of my reviewer’s this paper has been ‘epic’ in its scope and would not have been possible without the significant contributions of numerous people including my col- leagues Tim Schwanen and Julia Markovich at the Transport Studies Unit, Emily Simatos at VICDOT, Nigel Dotchin and Lee Smith at the DfT, workshop participants in the Social Impacts and Equity Issues in Transport project http://www.tsu.ox.ac.uk/ research/uktrcse/ and the helpful comments of the reviewers who encouraged me to go the extra distance in this final version.

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n: Where are we now? Transport Policy (2012), doi:10.1016/

  • Transport and social exclusion: Where are we now?
    • Introduction
    • Understanding the concept of social exclusion
    • Transport/mobilty disadvantage
    • Progress with theoretical conceptualisations
      • Accessibility perspectives
      • Social capital and capability perspectives
      • Time geography perspectives
    • Progress with identification and measurement
      • Accessibility studies in the uk
      • Spatial and social network analysis in mainland Europe
      • Structural and spatial modelling studies in Australia and Canada
    • Progress in policy and with practical delivery
      • The UK experience
      • The Australian policy experience (State of Victoria)
    • Conclusions: where are we now?
    • Acknowledgements
    • References

assignment 2/MacDonald.pdf

Problem, research strategy, and fi ndings: Increasing walking and bicycling to school has been a national policy goal since Congress created the Safe Routes to School (SRTS) program. While previous research has suggested positive program impacts, there have been no large-scale studies with strong research designs. Here we study 801 schools in the District of Columbia, Florida, Oregon, and Texas to assess how the proportion of students walking and bicycling to school changed after the introduction of SRTS programs. By including schools with and without SRTS programs and analyzing data collected over time (2007–2012), we are able to distinguish SRTS impacts from secular trends. We fi nd increases in walking and bicycling after schools implemented SRTS programs. Engineering improvements are associated with an 18% relative increase in walking and bicycling, and the effects of education and encouragement programs are cumulative. Over the course of fi ve years, these education and encouragement programs could lead to a 25% relative increase in walking and bicycling. Takeaway for practice: Planners should work to prioritize capital improvements that improve non-motorized access to school and revise comprehensive plans and subdivision regulations to ensure that new development supports access to school. Keywords: walk, bicycle, children, Safe Routes to School About the authors: Noreen C. McDonald ([email protected]) is an associate professor of city and regional planning at the University of North Carolina at Chapel Hill. Ruth L. Steiner ([email protected] .edu) is a professor

Impact of the Safe Routes to School Program on Walking and Bicycling

Noreen C. McDonald, Ruth L. Steiner, Chanam Lee, Tori Rhoulac Smith, Xuemei Zhu, and Yizhao Yang

I ncreasing active transportation to school has been a national policy goal since Congress included the Safe Routes to School (SRTS) program in the 2005 federal transportation bill. Policy attention to this topic refl ects the

health benefi ts associated with regular physical activity, environmental benefi ts from decreased driving, and safety benefi ts from decreasing injuries and fatali- ties related to school travel (Davison, Werder, & Lawson, 2008; DiMaggio & Li, 2013; Janssen & LeBlanc, 2010; Woodcock et al., 2009; Younger, Morrow- Almeida, Vindigni, & Dannenberg, 2008). The role that planners have in infrastructure investment and the skills planners have in coordinating initia- tives with developers, schools, and local law enforcement place them at the center of efforts to encourage walking and bicycling to school.

Between 2005 and 2012, Congress appropriated $1.2 billion for the SRTS program to provide education, encouragement, and enforcement programs as well as engineering improvements at almost 14,000 elementary and middle schools (McDonald, Barth, & Steiner, 2013; National Center for Safe Routes to School, 2013a). Existing evaluations of the SRTS program fi nd increases in walking and bicycling to school (Boarnet, Day, Anderson, McMillan, & Alfonzo, 2005; Mendoza et al., 2011; Stewart, Moudon, & Claybrooke, 2014) and decreases in injuries near SRTS improvements (DiMaggio & Li, 2013; Ragland, Pande, Bigham, & Cooper, 2014). However, many of the studies focus on small geographic areas, such as an individual school or school district, limiting the generalizability of fi ndings (Buckley, Lowry, Brown, & Barton, 2013; McDonald, Yang, Abbott, & Bullock, 2013; Mendoza et al., 2011). Larger-scale studies are characterized by research designs that make it diffi cult

of urban and regional planning at the University of Florida. Chanam Lee (clee@ arch.tamu.edu) is a professor of landscape architecture and urban planning at Texas A&M. Tori Rhoulac Smith (trhoulac@ howard.edu) is an adjunct assistant professor and director of undergraduate studies in the College of Engineering, Architecture, and Computer Sciences at Howard University. Xuemei Zhu ( [email protected]) is an

associate professor of architecture at Texas A&M. Yizhao Yang ([email protected]) is an associate professor of planning, public policy, and management at the University of Oregon.

Journal of the American Planning Association,

Vol. 80, No. 2, Spring 2014

DOI 10.1080/01944363.2014.956654

© American Planning Association, Chicago, IL.

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154 Journal of the American Planning Association, Spring 2014, Vol. 80, No. 2

to discern SRTS impacts from secular trends (Staunton, Hubsmith, & Kallins, 2003).

This study addresses both of these concerns by evalu- ating the SRTS program in the District of Columbia (DC) and three states—Florida, Oregon, and Texas— using a strong research design with case and control schools, which allows identifi cation of the independent impacts of the SRTS program. Using data from 801 schools, we fi nd a positive impact of the SRTS program on walking and bicycling. Engineering improvements are associated with an 18% relative increase in walking and bicycling. The effects of education and encouragement programs are cumulative, with each additional year of program participation associated with an absolute in- crease of 1% in the proportion of students walking and bicycling to school. Over the course of fi ve years, these education and encouragement programs could lead to a 25% relative increase in walking and bicycling. These results provide planners with the evidence required to make provision of safe walk and bicycle routes to school a standard part of planning practice using tools such as the comprehensive plan, subdivision regulations, and capital budgeting and planning.

Background

SRTS Program Overview The 2005 federal transportation bill, the Safe,

Accountable, Flexible, Effi cient Transportation Equity Act: A Legacy for Users (SAFETEA-LU), authorized SRTS as a new program that would provide full federal funding to enable and encourage children, including those with disabilities, to walk and bicycle to school; to make walking and bicycling to school safe and more appealing; and to facilitate the planning, development, and implementation of projects that improve safety and reduce traffi c, fuel consumption, and air pollution in the vicinity of schools (Federal Highway Administration, 2007).

The SRTS program provided grants to assist commu- nities across the country in creating safer and more sup- portive environments for children to walk or bicycle to school. The program contributed to multiple policy objec- tives, including the U.S. Department of Transportation’s livability goals and the Department of Health and Human Services’ efforts to increase physical activity and reduce obesity in children and adolescents. These efforts sought to reverse sharp declines in walking and bicycling to school from about 48% in 1969 to less than 13% in 2009 ( McDonald, Brown, Marchetti, & Pedroso, 2011).

The program allocated funding to state departments of transportation (DOTs) based on the number of school- aged children. Each state was required to set aside 10% to 30% of the funds for non-infrastructure-related activities such as public awareness campaigns and outreach to the community, traffi c education, bicycle and pedestrian safety programs for children, and training for SRTS volunteers and managers. The infrastructure investments could in- clude the planning, design, and construction of sidewalk improvements; traffi c calming and speed reduction im- provements; pedestrian and bicycle crossing improvements; on-street bicycle facilities; off-street bicycle and pedestrian facilities; secure bicycle parking; and traffi c diversion improvements in the vicinity of schools (within 2 miles) that would substantially improve the ability of students to walk and bicycle to school. Each state was also required to fund a full-time coordinator for the state’s SRTS program. In 2012, the SRTS program was merged with other non- motorized funding programs into the Transportation Alternatives Program (Federal Highway Administration, 2013a).

SRTS Evaluation Studies Many studies evaluate aspects of the SRTS program.

Several of those studies are primarily descriptive, aimed at explaining the program history, trends, or funding mechanism and expenditures (Cradock, Fields, Barrett, & Melly, 2012; McDonald, Barth, et al., 2013; National Center for Safe Routes to School, 2013b). The remainder focuses on the impacts of SRTS programs on active transportation and injuries. Most attention has been given to the program’s impacts on the modes of travel children use to go to and from school; the results generally show increased walking and bicycling. The study designs of these evaluations have been a major challenge. Studies with strong research designs tend to have a limited geographic scope and range of SRTS interventions, and therefore limited generalizability. For example, Mendoza et al. (2011) test the impacts of researcher-led walking school bus programs using a randomized controlled trial in eight low-income Houston schools, fi nding these programs led to more walking to school. However, it is unclear what the impact of the intervention would be in other areas or with “walking school buses” organized by volunteers or school staff.

Another set of recent studies investigates a wider range of environments using comparisons of active travel before and after SRTS interventions or between areas with and without SRTS interventions. For example, Stewart et al. (2014) use data from 53 schools in four states and fi nd walking and bicycling increased from

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McDonald et al.: Impact of the Safe Routes to School Program on Walking and Bicycling 155

12.8% to 19.8% after completion of SRTS projects. Ragland et al. (2014) study eight California schools, and fi nd students living near SRTS improvements were more likely to walk to school than students living equally close to school but not near a SRTS improvement. The limita- tion of these studies is that, due to the research designs, it is unclear whether the observed increases in active travel are due to the SRTS program or alternate explanations such as preexisting conditions or an exogenous, time- dependent shift such as a change in gas prices or employment levels.

A small number of studies that include control schools in their research design also fi nd that SRTS programs have positive impacts. Buckley et al. (2013) study encourage- ment events at two Moscow (ID) elementary schools and fi nd sustained increases in walking and bicycling after the program compared with a nearby school that did not participate in the program. McDonald, Yang, et al. (2013) fi nd absolute increases of 5 to 20 percentage points in walking and bicycling due to the SRTS programs at Eugene (OR) schools, using data from nine schools with SRTS projects and fi ve schools without such projects. While these studies use an improved research design, they represent a very small number of schools, and are therefore unlikely to be generalizable to a wider range of environments.

Two recent, high-quality studies fi nd reductions in pedestrian injuries and crashes around SRTS interventions. DiMaggio and Li (2013) fi nd that the rate of pedestrian injury decreased by 44% for youth aged 5 to 19 years in New York City census tracts with SRTS treatments, while rates were unchanged for census tracts without SRTS projects. Ragland et al. (2014) analyze the impacts of SRTS infrastructure at 47 schools in California and fi nd signifi - cant decreases in total collisions within 250 feet of SRTS infrastructure interventions; a decrease in child-involved collisions is also observed, but the effect is not statistically signifi cant.

Approach and Methods

Our analysis focuses on DC and three states—Florida, Oregon, and Texas. These areas were selected because they include a wide range of environments and the research team had access to extensive data on their SRTS programs. As Table 1 shows, Florida and Texas are large states where active SRTS programs funded interventions at nearly 1,000 schools in each state. Oregon is a mid-sized state with cities that have received national attention for their SRTS pro- grams, such as Portland and Eugene. DC represents a highly urbanized region with schools serving students from diverse socioeconomic backgrounds. As Table 1 shows, available SRTS funding on a per-student basis was much higher in DC due to the structure of the program, which set a funding fl oor irrespective of student population. The remainder of this section describes the data and analytic methods used to identify the impacts of the SRTS program on walking and bicycling to or from school.

Data: School Travel Mode The outcome of interest in this study is the proportion

of students walking and bicycling for school trips. Informa- tion on children’s mode to and from school is compiled from surveys of students and parents obtained from the National Center for SRTS, the federally funded clearing- house for information related to SRTS. The National Center developed a freely available survey instrument to collect information on school travel mode from parents and students and also provided schools with free data entry and data storage. Student reports of travel mode were collected at the classroom level, with students raising their hands to report how they traveled to and from school on the survey day. Parent reports were collected through individual surveys sent from the school to parents. An evaluation of the National Center surveys fi nds that they provide reliable reports of travel mode (McDonald, Dwelley, Combs, Evenson, & Winters, 2011). While there

Table 1. Characteristics of state Safe Routes to School programs.

District of Columbia Florida Oregon Texas Total

Appropriated SRTS funding (FY 2005–2012) (thousands)a $8,140 $58,239 $13,017 $90,067 $169,463

Number of K–8 students (fall 2010) (thousands)b 53.5 1,858.5 392.6 3,586.6 5,891.3

SRTS funding per student $152 $31 $33 $25 $29

Schools with announced SRTS fundingc 31 1,085 152 853 2,121

Notes: FY = fi scal year; SRTS = Safe Routes to School. a. Federal Highway Administration, 2013b. b. National Center for Education Statistics, 2012. c. National Center for Safe Routes to School, 2013a.

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156 Journal of the American Planning Association, Spring 2014, Vol. 80, No. 2

is no federal requirement that schools collect mode data, many states require applicants and recipients of SRTS funding to provide travel mode data.

The National Center’s travel mode database covers the period from the program’s start through the current period. We selected the years 2007–2012 for our study because there were few travel mode reports in the program’s early years (2005–2006), and our study began in 2013. We supplemented the National Center data with mode data from previous research studies on school travel to increase the sample of schools included in this analysis; the supple- mental surveys used phrasing consistent with the National Center surveys (see the Technical Appendix for further details). Our analysis focuses on public and public charter schools because states awarded few grants to private schools, and information on school characteristics was not available for all private schools (McDonald, Barth, et al., 2013).

School travel mode and information on SRTS programming was available for an initial sample of 810 schools in DC, Florida, Oregon, and Texas. Data cleaning,

described in the Technical Appendix, reduced the sample to 801 schools. As Table 2 shows, the fi nal sample refl ects travel mode reports from approximately 65,000 students and 16,000 parents annually. As Table 3 indicates, of the 801 schools in the fi nal sample, 378 (47%) schools had an SRTS program between 2007 and 2012, and 423 (53%) schools had no program during the study period. For many schools in the sample, travel mode was surveyed at mul- tiple time points. For example, 110 (14%) schools reported mode data four or more times, 85 (10%) schools reported data at three time points, 193 (24%) schools reported at two time points, and 413 (52%) schools provided data for one time point.

For each school and survey date, we calculate the proportion of students that walked or bicycled to and from the school in the morning and afternoon. The Technical Appendix describes the process of calculation for the student and parent data. Mode surveys at the 801 study schools generated 4,090 observations of the proportion of students walking and bicycling to or from school. The number of observations was larger

Table 2. Parent and child respondents by year and state.

2007 2008 2009 2010 2011 2012 Annual average

Student report

District of Columbia 0 1,489 1,003 476 252 2,623 974

Florida 3,263 54,634 51,154 27,682 35,181 30,204 33,686

Oregon 19,880 22,871 24,785 25,787 32,009 26,237 25,261

Texas 445 0 18,509 6,308 2,740 4,202 5,367

Total 23,588 78,994 95,451 60,253 70,182 63,265 65,289

Parent report

District of Columbia 0 780 135 240 588 139 314

Florida 72 10567 13486 10049 6177 6295 7,774

Oregon 67 6517 5664 12267 8338 2403 5,876

Texas 2504 3370 2252 4193 760 1176 2,376

Total 2,643 21,234 21,537 26,749 15,863 10,013 16,340

Table 3. Number of intervention and control schools by state.

District of Columbia Florida Oregon Texas Total

Total study schools 24 282 222 273 801

Control schools 7 123 59 234 423

Control: none or unknown SRTS application 0 35 15 41 91

Control: applied for SRTS funding 7 88 44 193 332

Schools with SRTS interventions 17 159 163 39 378

Note: SRTS = Safe Routes to School.

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McDonald et al.: Impact of the Safe Routes to School Program on Walking and Bicycling 157

than the number of schools because each survey gener- ated at least two observations of school travel mode, such as morning and afternoon, because some schools surveyed students and parents on the same survey date, and because nearly half of schools were surveyed mul- tiple times. Despite the inclusion of multiple observa- tions from the same school and survey date, we are not “double counting” because we used appropriate statisti- cal methods to adjust for the presence of multiple observations from the same school and survey date. We also conducted several additional analyses that validated our strategy (described in detail in the Technical Appendix).

Data: SRTS Interventions For all schools with available travel mode data, we

attempted to identify the type and timing of SRTS interventions. State SRTS coordinators provided lists of schools with SRTS funding and, in some states, detailed information about the nature of the projects. In cases where the state DOT lacked information on when SRTS interventions were implemented or the nature of the interventions, members of the research team interviewed local SRTS program managers, school and municipal staff, and state and local health depart- ments. In some cases, staff turnover made it impossible to obtain this information; in these cases, schools were dropped from the analysis. For schools that did not receive any SRTS interventions (i.e., control schools), we also used state DOT records and interviews with school officials, state health departments, and other providers of SRTS programs to help identify those that

had applied for SRTS funding but had been unsuccess- ful in their application.

We categorize reported SRTS activities based upon the “4 E’s”: engineering, enforcement, education, and encouragement. As Table 4 indicates, education and encouragement programs are the most common non- infrastructure programs in our sample. Education programs include classroom safety instruction as well as skills workshops outside of the classroom where students practice crossing the street by foot and bicycle. Encour- agement efforts focus on creating excitement around walking or bicycling by offering small rewards such as pencils and stickers, or using organized efforts, such as walking school buses, to encourage children to walk. We fi nd that education and encouragement initiatives were undertaken at the same time; thus, we combine these categories in our analysis. Enforcement efforts ranged from collaborations with local police departments to assign offi cers to monitor and enforce school zone speed regulations to more passive initiatives such as placing portable speed signs in the school zone to provide drivers with real-time speed information. Almost all schools with enforcement interventions also had education and encouragement programs.

Engineering improvements were designed to improve the safety of walking and bicycling through the provision or improvement of sidewalks, crosswalks, paths, and bicycle lanes. Engineering projects also funded bicycle parking at schools, signage, and traffi c calming near the school. In this sample, many schools reported sidewalk and crosswalk improvements but relatively few investments in bicycle lanes or off-street paths.

Table 4. Types of Safe Routes to School interventions at study schools by state.

District of Columbia Florida Oregon Texas Total

Schools with Safe Routes to School interventions 17 159 163 39 378

Non-infrastructure interventions 17 126 135 11 289

Education and encouragement 17 126 134 11 288

Enforcement 2 3 34 11 50

Infrastructure interventions 11 54 116 29 210

Sidewalk 9 50 38 28 125

Crosswalks 4 0 38 27 69

On-street bicycle 1 2 7 2 12

Off-street bicycle and pedestrian 0 0 14 2 16

Traffi c calming 3 0 26 4 33

Bicycle parking 1 2 24 8 35

Signage 3 2 56 0 61

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158 Journal of the American Planning Association, Spring 2014, Vol. 80, No. 2

Data: Contextual School, Neighborhood, and Survey Information

Previous research has shown that walking and bicycling to school varies based on demographic and spatial charac- teristics (Davison, Werder, & Lawson, 2008; McDonald, Brown, et al., 2011). To control for this systematic varia- tion, we incorporated information about school character- istics from the National Center for Education Statistics (NCES) and information about neighborhood characteris- tics from the American Community Survey (ACS). The NCES database contains annual information on enroll- ment, racial and ethnic composition, free and reduced- price lunch program eligibility, and school location for American public schools.1 We obtained neighborhood socio-demographic information from the 2007–2011 ACS using the block group where the school was located.2 Most neighborhood-level sociodemographic variables (e.g., racial and ethnic composition of residents) were not signifi cant in preliminary models and are not included in the fi nal models due to the lack of signifi cance and the presence of school-level measures of racial and ethnic composition. We retain median household income in the fi nal model despite a lack of statistical signifi cance because previous research has highlighted meaningful economic differences in walk- ing and bicycling to school and we wanted to control for

neighborhood-level income variation in addition to school- level variation (McDonald, 2008).

The school’s location is also used to assess the local built environment through street network and destination proximity metrics. Final models include Walk Score as a primary environmental metric, a commercially available index (0–100) that correlates with access to walkable desti- nations and residential population density (Carr, Dunsiger, & Marcus, 2011; Duncan, Aldstadt, Whalen, Melly, & Gortmaker, 2011).3 We tested metrics of street connectivity, such as intersection density and average block length, in the models, but they were not statistically signifi cant.

Sample Summary Schools with SRTS programs differ on some but not

all characteristics. For example, as Table 5 shows, schools with SRTS programs had a lower percentage of Hispanic students and a higher proportion of African-American students than schools without a SRTS program. Schools with SRTS programs had a smaller number of enrolled students. Economic characteristics were similar across the two groups; there are no signifi cant differences in the proportion of students receiving free or reduced-price lunch or the block group median household income. Schools receiving SRTS interventions were located in

Table 5. Comparison of schools with and without Safe Routes to School interventions.

All schools (n = 801)

Schools with SRTS interventions

(n = 378)

Control schools (n = 423)

Difference: intervention

control p value of difference

School characteristics (2010–2011)a

Elementary school (%) 83 86 79 7 0.008

Enrollment 607 579 632 –53.26 0.004

Free or reduced-price lunch (%) 61 61 61 1 0.718

Black (%) 14 17 11 6 <0.001

Hispanic (%) 42 31 51 –20 <0.001

Two races (%) 3 4 2 1 <0.001

White (%) 38 43 33 10 <0.001

Neighborhood characteristics (2007–2011)b

Walk Score 44 47 41 7 <0.001

Median household income ($) 51,741 53,074 50,550 2,524 0.200

Population density per square mile 4,172 4,957 3,471 1,486 <0.001

Proportion walking and bicycling

To school (%) 18 20 13 7 <0.001

From school (%) 22 23 17 6 <0.001

Notes: SRTS = Safe Routes to School. a. Keaton, 2012. b. U.S. Census Bureau, 2013.

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McDonald et al.: Impact of the Safe Routes to School Program on Walking and Bicycling 159

neighborhoods with a higher population density and better access to destinations as measured by Walk Score.

Active travel was more common at schools that received an SRTS intervention during the study period than at control schools. Rates of walking and bicycling to school averaged 18% to school and 22% from school, but with considerable variation across schools. For example, the bottom quarter of schools had active travel rates of less than 8%, while the top quarter of schools had rates higher than 26% in the morning. These reports are higher than recent national estimates of walking and bicycling (13%) (McDonald, Brown, et al., 2011).

Analysis By using schools with and without SRTS programs in

a wide range of contexts, we are able to identify the impacts of SRTS programs and ensure these impacts are not confounded with secular trends or demographics. We model the proportion of students that walked or bicycled to school as a function of two factors: SRTS interventions and contextual variables related to school, neighborhood, and survey characteristics. The focus of our interest is the SRTS interventions in place at the school at the time of the survey. For each observation of school travel mode, we use our database of SRTS interventions to determine if the SRTS program was in place at the school and, if so, the number of years the program had been in place. This structure allows researchers to test how the presence and length of participation in the SRTS program affected walking and bicycling.

We developed two models to test the impacts of the SRTS program. The fi rst focuses on the presence or absence of any SRTS program elements without regard to the exact nature of the efforts. This model provides the broadest test of whether the SRTS program has affected children’s travel behavior. The second model assesses the impacts of different categories of SRTS interventions, such as education and encouragement, engineering, and enforcement, and is included to provide practitioners with a better understanding of the impacts of each type of SRTS intervention. We did not develop models to analyze the impacts of specifi c SRTS projects, such as crosswalk improvements, because we believe the choice of specifi c intervention is controlled by idiosyncratic local conditions that are diffi cult to model.

Models include contextual variables related to school, neighborhood, and survey characteristics to control for systematic variation in rates of walking and bicycling to school unrelated to the SRTS interventions. For example, the prevalence of walking and bicycling is higher in denser areas. We systematically controlled for the time of day

because previous research shows that walking is higher in the afternoon. We also controlled for who reported the travel mode because we know that parents tend to report higher walking and bicycling rates than do students themselves (McDonald, Brown, et al., 2011).

We use a fractional logit model, as described in the Technical Appendix, because it best fi ts our needs and the data. To account for dependence across observations from the same school, we use robust standard errors that adjust for potential correlation across schools in the fi nal models. We also conducted several tests (described in the Technical Appendix) to ensure that potential correlation across observations from the same school and survey date did not unduly infl uence the fi nal results. All these additional tests confi rm the model results presented in this study.

We calculate the impacts of the SRTS program on school travel mode by estimating the marginal effect of the presence and number of years of SRTS interventions on walking and bicycling. The reported marginal effects represent how the proportion of students walking and bicycling to school would change if the SRTS program were implemented or if it were in place for one additional year. Further details on the calculation of marginal effects are available in the Technical Appendix.

SRTS and Children’s Travel to School

As Figure 1 shows, rates of walking and bicycling to school increased with each year of participation in the SRTS program. At schools with SRTS programs, 18% of students walked or bicycled prior to the start of the pro- gram. Schools with one year of SRTS program participa- tion had average rates of walking and bicycling of 20%. Schools with four or more years of SRTS participation had active travel rates greater than 30%. These simple averages showed an absolute increase of 13 percentage points, or a relative change of 71%, in the proportion of students walking and bicycling after fi ve years of participating in the SRTS program. These results suggest that SRTS programs may strongly affect walking and bicycling. Moreover, there may be a “dose-response” relationship where each addi- tional year (or “dose”) of SRTS participation leads to more walking and bicycling.

However, the simple averages are not a defi nitive evaluation of the SRTS program because of the possibility of selection bias. Schools with long-lived and successful SRTS program may simply be located in environments where walking is more likely or may have been surveyed in a year when exogenous factors increased walking, such as increases in gas prices. To address these issues, as described

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160 Journal of the American Planning Association, Spring 2014, Vol. 80, No. 2

above, we use multivariate regression models that introduce statistical controls for school and neighborhood character- istics, as well as time period, to assess active travel at schools with and without SRTS programs.

After controlling for these other factors, we continue to fi nd that the SRTS program increased walking and bicycling to school. Specifi cally, walking and bicycling rose by 1.1 percentage points (p = .002) with each year of participation in the SRTS program. These fi ndings suggest a linear “dose-response” relationship: Each additional year of SRTS participation led, on average, to more walking and bicycling. For example, if active travel rates were 18% prior to the start of an SRTS program, our model predicts that 23.5% of students, on average, would walk and bicycle after fi ve years of program participation. This represents an absolute increase of 5.5 percentage points and a relative increase of 31% after fi ve years of SRTS participation. After one year of SRTS participation, the expected absolute increase would be 1.1 percentage points or a relative change of 6%. For reference, the Technical Appendix contains the full model results.

In our second model, we compare the differential impacts of engineering, education and encouragement, and enforcement programs (the full model is available in the Technical Appendix). The presence of an engineering improvement was associated with a 3.3 percentage point increase in walking and bicycling (p = .031); this impact did not depend on how long the improvement had been in place. For comparison, this would mean that schools with 18% of students walking and bicycling might expect to see

rates rise to 21.3%, on average, after completing an engi- neering project. This represents a relative increase of 18%.

Education and encouragement interventions also had signifi cant positive impacts on walking and bicycling, with each year of participation in an education and encourage- ment program associated with a 0.9 percentage point increase in walking and bicycling (p = .025). In other words, schools that started with 18% of students walking and bicycling would be expected to increase the rate of active transportation by 0.9 percentage point per year to 22.5% after fi ve years on average, an absolute change of 4.5 percentage points and a relative change of 25%. Enforcement initiatives did not have a signifi cant associa- tion with walking and bicycling, though in our sample many schools implemented education, encouragement, and enforcement at the same time.

Other variables beyond simply adopting an SRTS program also infl uence rates of walking and bicycling to school in ways consistent with previous research. For example, walking and bicycling were higher in areas with greater population density. Walk Score, a proxy for access to commercial and recreation amenities, had no signifi cant association, perhaps because the indicator only refl ects access and not the quality of the walking environment (Talen & Koschinsky, 2013). Other factors also matter. Rates of walking and bicycling were 3 percentage points higher in the afternoon, results consistent with other studies (National Center for Safe Routes to School, 2013b; Zhu & Lee, 2009). Reported walking and bicycling rates were also higher when reported by parents than by students because parents

Figure 1. Average rates of walking and bicycling to school by length of participation in Safe Routes to School program.

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McDonald et al.: Impact of the Safe Routes to School Program on Walking and Bicycling 161

reported the students’ usual travel mode as opposed to their actual travel mode (McDonald, Dwelley, et al., 2011).

School characteristics generally did not signifi cantly affect walking and bicycling to or from school. However, a 10 percentage point increase in the proportion of students receiving free or reduced-price lunch was associated with a 0.5 percentage point increase in walking and bicycling. We did include a dummy variable indicating whether the school ever received a SRTS treatment to account for any remaining differences between schools that participated in the SRTS program and those that did not. The dummy variable was not signifi cant in either model, suggesting that observed characteristics do an adequate job of adjusting for differences between treatment and control schools.

Impacts of the SRTS Program

Our analysis shows that SRTS interventions are associ- ated with increased walking and bicycling in DC, Florida, Oregon, and Texas. We fi nd that engineering improve- ments are associated with an absolute increase of 3 percent- age points in active travel, which represents a relative increase of 18%. Education and encouragement programs exhibit a dose-response relationship with walking and bicycling, where each additional year of program participa- tion is associated with a 1 percentage point increase in walking and bicycling. Over a fi ve-year period, these edu- cation and encouragement programs would be expected to lead to a relative increase in active travel of 25%. These results hold when comparing funded schools only with those that applied for the SRTS program and after control- ling for other factors that infl uence walking to school such as population density. These fi ndings accord with the results of previous studies, which also fi nd positive impacts of the SRTS program (Boarnet, Anderson, Day, McMillan, & Alfonzo, 2005; McDonald, Yang, et al., 2013; Mendoza et al., 2011; Staunton et al., 2003; Stewart et al., 2014). However, our study represents a substantial extension of the literature because it uses a stronger research design with a large study area, thereby increasing confi dence in the generalizability of the results.

While this analysis demonstrates the effectiveness of the SRTS program in meeting the goal of increasing walking and bicycling to school, recent changes in federal transportation policy may result in less federal funds being available for such investments. The SRTS program was created in the 2005 federal transportation bill, and approximately $1.2 billion was appropriated for the pro- gram (McDonald, Barth, et al., 2013). However, the 2012 transportation bill, Moving Ahead for Progress in the 21st

Century (MAP-21), dismantled the standalone SRTS program and instead made SRTS projects eligible to com- pete for funding with other non-motorized improvements. In addition, MAP-21 decreased the total funding available for non-motorized programs and allowed states increased fl exibility to move non-motorized funds to other programs. It is not yet clear how these changes will affect state fund- ing for the SRTS program, but it is possible that some states will decrease funding for SRTS or non-motorized programs more generally.

What do these results mean for planning practitioners? This study provides strong evidence that children will walk and bicycle to school if communities invest in supportive infrastructure and programs. Given the uncertainty and limitations of federal funding for non-motorized modes, communities should develop strategies to mainstream SRTS programs through tools available to local planners. First, planners can articulate support for providing access by foot and bicycle to schools through the comprehensive plan and any linked small-area or neighborhood plans. The goal would be to create an environment where planning for non-motorized school access is a normal part of neighbor- hood and transportation planning. Second, planners can amend subdivision regulations to require or encourage the provision of pedestrian and bicycle access to schools for new construction or redevelopment. Third, planners can consider access to school in the capital improvements planning process. For example, a multiyear sidewalk com- pletion program could prioritize investments that are near a school or route to school. Fourth, local planners can work more closely with school facility planners to encour- age construction of schools that can be reached by foot or bicycle and to identify routes to school (McDonald, 2010). The development of an ongoing, collaborative relationship between school and local planners could ensure that students effectively use infrastructure investments made by local communities. Finally, planners could pursue federal and state funding for non-motorized infrastructure for projects that will improve school travel. Such projects could be designed to benefi t many users, such as a multiuse path that connects a school to several neighborhoods and other community amenities.

This analysis has several limitations. First, we were unable to use panel data methods to address concerns about self-selection bias or other potential confounding factors due to our use of fractional logit models and our unbalanced data set. However, we address self-selection bias by including contextual variables and estimating models on portions of our data set and fi nd results are consistent with overall models. Second, the format of our data set includes multiple observations of each school at

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162 Journal of the American Planning Association, Spring 2014, Vol. 80, No. 2

each survey date (e.g., walking in the morning and the afternoon). We address concerns about the impacts of dependence across these observations by using robust standard errors and estimating additional models on a subset of data with only one observation per time point. Again, submodels showed similar results to the overall models. Third, we evaluate the impact of broad interven- tions: engineering, education and encouragement, and enforcement. This approach refl ects our goal of testing whether SRTS interventions had positive impacts on walking and bicycling and recognition that the selection of particular engineering or education programs depends heavily on local conditions that may be diffi cult to model. We recommend that future research provide more detailed case studies of how communities selected specifi c interven- tions and what their impacts were locally. These case studies would not be generalizable, but would provide important information to practitioners.

Conclusion

The SRTS program has demonstrated signifi cant increases in walking and bicycling. Analysis of data from 801 schools in DC, Florida, Oregon, and Texas indicates an absolute increase of 5.5 percentage points or a relative change of 31% in the proportion of students walking and bicycling to school after fi ve years of participating in a SRTS program. This study supports the effi cacy of SRTS programs as a mechanism for increasing active travel in elementary and middle schools. The fi ndings represent a benefi cial extension of the existing literature using a strong research design and a large study area, which has not been done before, and thereby increasing confi dence in the transferability of results. These results provide planners with strong evidence to support strategies that make the provision of safe walk and bicycle routes to school a normal part of the planning process. Planners have many tools to accomplish this goal, including comprehensive plans, subdivision regulations, and capital improvement planning and budgeting.

Acknowledgments We are very grateful for the assistance of the Safe Routes to School coordi- nators in each of the study areas, as well as Seth LaJeunnesse (National Center for Safe Routes to School) and Margo Pedroso (Safe Routes to School National Partnership). We would also like to thank the anonymous reviewers for their excellent suggestions for improving the manuscript.

Research Support This project was funded by the Active Living Research program of the Robert Wood Johnson Foundation.

Notes 1. For the small number of study schools with missing data in the NCES, we obtained comparable information from the school district or state education department’s website. 2. We used the block group as a proxy for the school’s neighborhood because we believe it is most likely to correlate with the school’s attend- ance zone without including areas outside the zone. It was not possible to report demographics for the school’s attendance zone because many schools do not have geographically defi ned attendance areas and because we were unable to systematically collect attendance zone maps for districts that do use them. 3. No bicycle-specifi c environmental measure was included because Bike Score data were not universally available for all schools in the study. However, the vast majority of reported active school travel was walking, not bicycling, and therefore we do not believe the lack of bicycle-specifi c environmental metrics is problematic.

References Boarnet, M., Anderson, C., Day, K., McMillan, T., & Alfonzo, M. (2005). Evaluation of the California safe routes to school legislation: Urban form changes and children’s active transportation to school. American Journal of Preventive Medicine, 28(2, Suppl. 2), 134–140. doi:10.1016/j.amepre.2004.10.026 Boarnet, M., Day, K., Anderson, C., McMillan, T., & Alfonzo, M. (2005). California’s safe routes to school program: Impacts on walking, bicycling and pedestrian safety. Journal of the American Planning Association, 71(3), 301–317. doi:10.1080/01944360508976700 Buckley, A., Lowry, M. B., Brown, H., & Barton, B. (2013). Evaluating Safe Routes to School events that designate days for walking and bicycling. Transport Policy, 30, 294–300. doi:10.1016/j.tranpol.2013. 09.021 Carr, L. J., Dunsiger, S. I., & Marcus, B. H. (2011). Validation of Walk Score for estimating access to walkable amenities. British Journal of Sports Medicine, 45(14), 1144–1148. doi:10.1136/bjsm.2009.069609 Cradock, A. L., Fields, B., Barrett, J. L., & Melly, S. (2012). Program practices and demographic factors associated with federal funding for the Safe Routes to School program in the United States. Health & Place, 18(1), 16–23. doi:10.1016/j.healthplace.2011.08.015 Davison, K. K., Werder, J. L., & Lawson, C. T. (2008). Peer reviewed: Children’s active commuting to school: Current knowledge and future directions. Preventing Chronic Disease, 5(3), A100. Retrieved from http://www.cdc.gov/pcd/issues/2008/jul/07_0075.htm DiMaggio, C., & Li, G. (2013). Effectiveness of a Safe Routes to School program in preventing school-aged pedestrian injury. Pediatrics, 131(2), 290–296. doi:10.1542/peds.2012-2182 Duncan, D. T., Aldstadt, J., Whalen, J., Melly, S. J., & Gortmaker, S. L. (2011). Validation of Walk Score® for estimating neighborhood walkability: An analysis of four U.S. metropolitan areas. International Journal of Environmental Research and Public Health, 8(11), 4160–4179. doi:10.3390/ijerph8114160 Federal Highway Administration. (2007). Fact sheets on highway provisions: Safe routes to school program. Retrieved from http://www.fhwa.dot.gov/ safetealu/factsheets/saferoutes.htm Federal Highway Administration. (2013a). MAP-21 fact sheet: Trans- portation alternatives program. Retrieved from http://www.fhwa.dot.gov/ map21/factsheets/tap.cfm Federal Highway Administration. (2013b). Safe Routes to School: Funding. Retrieved from http://www.fhwa.dot.gov/environment/safe_ routes_to_school/funding/

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Janssen, I., & LeBlanc, A. G. (2010). Review: Systematic review of the health benefi ts of physical activity and fi tness in school-aged children and youth. International Journal of Behavioral Nutrition and Physical Activity, 7, 40. doi:10.1186/1479-5868-7-40 Keaton, P. (2012). Documentation to the NCES Common Core of Data Public Elementary/Secondary School Universe Survey: School Year 2010–11 (NCES 2012-338rev). Washington, DC: National Center for Education Statistics, U.S. Department of Education. Retrieved from http://nces. ed.gov/pubsearch/pubsinfo.asp?pubid=2012338rev McDonald, N. C. (2008). Critical factors for active transportation to school among low-income and minority students: Evidence from the 2001 National Household Travel Survey. American Journal of Preventive Medicine, 34(4), 341–344. doi:10.1016/j.amepre.2008.01.004 McDonald, N. C. (2010). School siting: Contested visions of the community school. Journal of the American Planning Association, 76(2), 1–15. doi:10.1080/01944360903595991 McDonald, N. C., Barth, P. H., & Steiner, R. L. (2013). Assessing the distribution of Safe Routes to School program funds, 2005–2012. American Journal of Preventive Medicine, 45(4), 401–406. doi:10.1016/j. amepre.2013.04.024 McDonald, N. C., Brown, A. L., Marchetti, L. M., & Pedroso, M. S. (2011). U.S. school travel 2009: An assessment of trends. American Journal of Preventive Medicine, 41(2), 146–151. doi:10.1016/j. amepre.2011.04.006 McDonald, N. C., Dwelley, A. E., Combs, T. S., Evenson, K. R., & Winters, R. H. (2011). Reliability and validity of the Safe Routes to School parent and student surveys. International Journal of Behavioral Nutrition and Physical Activity, 8, 56. doi:10.1186/1479-5868-8-56 McDonald, N. C., Yang, Y., Abbott, S. M., & Bullock, A. N. (2013). Impact of the Safe Routes to School program on walking and biking: Eugene, Oregon study. Transport Policy, 29, 243–248. doi:10.1016/j. tranpol.2013.06.007 Mendoza, J. A., Watson, K., Baranowski, T., Nicklas, T. A., Uscanga, D. K., & Hanfl ing, M. J. (2011). The walking school bus and children’s physical activity: A pilot cluster randomized controlled trial. Pediatrics, 128(3), e537–e544. doi:10.1542/peds.2010-3486d National Center for Education Statistics. (2012). Table 37: Enrollment in public elementary and secondary schools: Fall 2010. Retrieved from http://nces.ed.gov/programs/digest/d12/tables/dt12_037.asp National Center for Safe Routes to School. (2013a). Program tracking reports: Winter 2012. Retrieved from http://www.saferoutesinfo.org/ data-central/national-progress/program-tracking-reports National Center for Safe Routes to School. (2013b). Trends in walking and bicycling to school from 2007 to 2012. Chapel Hill, NC: National Center for Safe Routes to School. Retrieved from http://www.saferoutesinfo.org/ sites/default/fi les/Trends_in_Walking_and_Bicycling_to_School_ from_2007_to_2012_FINAL.pdf Ragland, D. R., Pande, S., Bigham, J., & Cooper, J. F. (2014, January). Ten years later: Examining the long-term impact of the California safe routes to school program. Paper presented at the Transportation Research Board 93rd Annual Meeting, Washington, DC. Retrieved from http://docs.trb.org/prp/14-4226.pdf Staunton, C. E., Hubsmith, D., & Kallins, W. (2003). Promoting safe walking and biking to school: The Marin County success story. American Journal of Public Health, 93(9), 1431–1434. doi: 10.2105/ajph.93.9.1431 Stewart, O., Moudon, A. V., & Claybrooke, C. (2014). Multistate evaluation of safe routes to school programs. American Journal of Health Promotion, 28(Suppl. 3), S89–S96. doi:10.4278/ajhp.130430- quan-210

Talen, E., & Koschinsky, J. (2013). The walkable neighborhood: A literature review. International Journal of Sustainable Land Use and Urban Planning, 1(1), 42–63. Retrieved from https://www.sciencetarget.com/Journal/index. php/IJSLUP/article/view/211/89 U.S. Census Bureau. (2013). “Summary File,” 2007–2011 American Community Survey. Washington DC: Author. Woodcock, J., Edwards, P., Tonne, C., Armstrong, B. G., Ashiru, O., Banister, D.,…Roberts, I. (2009). Public health benefi ts of strategies to reduce greenhouse-gas emissions: Urban land transport. The Lancet, 374(9705), 1930–1943. doi:10.1016/s0140-6736(09)61714-1 Younger, M., Morrow-Almeida, H. R., Vindigni, S. M., & Dannen- berg, A. L. (2008). The built environment, climate change, and health: Opportunities for co-benefi ts. American Journal of Preventive Medicine, 35(5), 517–526. doi:10.1016/j.amepre.2008.08.017 Zhu, X., & Lee, C. (2009). Correlates of walking to school and implica- tions for public policies: Survey results from parents of elementary school children in Austin, Texas. Journal of Public Health Policy, 30(Suppl. 1), S177–S202. doi:10.1057/jphp.2008.51

Technical Appendix

This appendix provides additional detail on the study data, model structure, estimation of marginal effects, model results, and tests of model robustness.

Study Data Student reports of school travel were collected at the

classroom level. Many schools conducted this survey for multiple days; these daily counts were averaged to produce a weekly count by mode for the trip to and from school by classroom. The classroom estimates were then aggregated to estimate the proportion of students walking and bicy- cling by grade. School-level estimates of walking and bicycling in the morning and afternoon were constructed by averaging the grade-level estimates. This approach standardized the reported rates of walking and bicycling by grade, which means that differential response rates by grade over time did not affect our results. Parent reports of the child’s usual travel mode were available from a validated instrument that reported travel mode to and from school as well as the child’s grade and school (McDonald, Dwelley, Combs, Evenson, & Winters, 2011). These individual-level reports were aggregated in the same manner as the student reports so that the proportion of students walking and bicycling to school was calculated by school, survey date, and time of day. No attempt was made to identify unique parent–child dyads because the data sets provide no way to link the two data sets.

Beyond data from the National Center for Safe Routes to School, we also included information from previous research. In Florida, mode data on an additional 40 schools that did not receive SRTS interventions were available in four counties from previous research by Steiner et al.

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164 Journal of the American Planning Association, Spring 2014, Vol. 80, No. 2

cluded statistical controls for the time period, Dt; neigh- borhood characteristics, Zi; and school characteristics, Xit, to adjust for any systematic variation in active travel based on location, demographics, or time period (Equation 1). The fractional logit model required, by construction, that the outcome variable be between 0 and 1. The advantage of the fractional logit model over other approaches to dealing with dependent variables with limited outcomes is that the use of a fractional logit model allowed recovery of the marginal effects of interest; other approaches such as taking logarithms do not allow this (Papke & Wooldridge, 1996). We analyzed the data as a pooled cross-section because panel methods for fractional logit models with unbalanced data have not yet been developed (Papke & Wooldridge, 2008).

y SRTS D X Z

SRTS D X Z exp( )

1 exp( )it it t it i

it t it i

α β ω γ η α β ω γ η[ ]= + + + +

+ + + + + (1)

Estimation of Marginal Effects We estimated the impacts of the SRTS program by

focusing on the marginal effects. The effect of the pres- ence of a SRTS intervention was estimated as a discrete effect, ΔE(y|x)/ΔDsrts (Equation 2). These discrete effects provided an estimate of the absolute percentage point increase in walking and bicycling associated with SRTS interventions and were computed by calculating the discrete effect for each observation and then averaging over the sample (Equation 2). Models also included an indicator of the number of years since the SRTS interven- tion was implemented. The reported marginal effect provides an estimate of how walking and bicycling changes for a one-year increase in SRTS program partici- pation. The reported marginal and discrete effect of SRTS participation was calculated for each observation and then averaged over the sample.

Presence of SRTS Program:

E y x SRTS N E y x SRTSn

E y x SRTS

( | ) 1 ( ( , 1)

( , 0). it

it

it

Δ Δ = =∑

− = (2)

Model Results Table A-1 shows the full model results with coeffi cients

as well as marginal effects.

Tests of Model Robustness As noted in the study, there were two potential

methodological concerns with our approach to estimat- ing the effects of the SRTS program. First, there were

(2011). In Oregon, supplementary data were obtained from the City of Portland, which developed their own survey instrument to collect annual mode data, and from a study of the SRTS program in Eugene (OR; McDonald, Yang, Abbott, & Bullock, 2013). In Texas, mode data were obtained from multiple resources, including the SRTS application data submitted to the Texas Department of Transportation and researchers’ previous research projects (Abiodun et al., 2014; Lee, Zhu, Yoon, & Varni, 2013; Zhu & Lee, 2009; Zhu, Lee, Kwok, & Varni, 2011).

This approach yielded an initial sample of 810 schools with suffi cient data on school travel mode and SRTS interventions. For these schools, there were 4,504 unique observations of school travel mode by school, survey date, time of day, and data source (parent vs. student). To ensure data quality, we dropped a number of cases. First, we eliminated records if the reported walk and bicycle share was 100% and information for other modes was missing (n = 6). These surveys were dropped from the analysis because of the likelihood of survey administration problems (i.e., survey administrators collected data on walkers and bicyclists only instead of all students). Second, observations were dropped if the reported proportion of students walking was missing (n = 6). Third, we also dropped observations where the survey response rates were less than 25% (approximately the 10th percentile) and sample sizes were less than 25 (approximately the 10th percentile; n = 402) because they may indicate nonrandom sampling. Survey response rates were estimated as the ratio of the number of survey respondents divided by the school enrollment. This approach underestimated the response rate for students slightly since it does not adjust for absences; it might also have signifi cantly underestimated parent response rates since many parents have multiple children at the same school, yet the survey instructed them to answer only for one child. Response rates were quite high for student reports of travel mode with a median response rate of 73% and an interquartile range (IQR) of 39% to 90%. Response rates for parent surveys were lower, with a median response rate for parent surveys of 14% (IQR, 5% to 26%). The fi nal sample included 801 schools with 4,090 observations of school travel mode.

Model Structure As described in the study, we used a fractional logit

model to estimate the impacts of the Safe Routes to School (STRS) program (Equation 1). We modeled the propor- tion of students at school i and time t that walked or bicycled, yit, as a function of the presence and number of years of SRTS interventions, SRTSit. The model also in-

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Table A-1. Coeffi cients and marginal effects for models of walking and bicycling for school travel.

Model 1: Presence/absence of SRTS Model 2: Type of SRTS intervention

Coeffi cient Marginal effect Coeffi cient Marginal effect

SRTS interventions

SRTS: Presence 0.059 0.009

SRTS: No. years 0.072** 0.011**

Engineering: presence 0.204* 0.032*

Engineering: no. years –0.063 –0.010

Educ. & Enc.: presence 0.057 0.009

Educ. & Enc.: no. years 0.059* 0.009*

Enforcement: presence 0.078 0.012

Enforcement: no. years 0.078 0.012

Infra & non-infra presence –0.085 –0.013

School characteristics

School ever had SRTS program 0.080 0.012 0.084 0.013

Elementary –0.031 –0.005 –0.046 –0.007

Enrollment ×100 –0.023 –0.003 –0.022 –0.003

Percent White ×10 –0.082 –0.012 –0.056 –0.009

Percent Black ×10 0.024 0.004 0.049 0.008

Percent Hispanic ×10 –0.076 –0.012 –0.049 –0.007

Percent FRL ×10 0.038* 0.006* 0.035* 0.005* Neighborhood characteristics

Walk Score ×10 0.032 0.005 0.030 0.005

Median HH income ×10,000 –0.004 –0.001 –0.003 0.000

Pop. density per sq. mile ×10,000 0.331** 0.051** 0.324** 0.049** State

DC (reference)

Florida 0.151 0.019 0.141 0.018

Oregon 0.653 0.094* 0.639 0.093*

Texas 0.532 0.074 0.494 0.069

Survey characteristics

Afterschool 0.195*** 0.030*** 0.195*** 0.030***

Parent report 0.121*** 0.019*** 0.099** 0.015**

Survey year

2007 0.316** 0.314** 0.051** 0.051**

2008 –0.029 –0.046 –0.004 –0.007

2009 0.045 0.024 0.007 0.004

2010 0.124 0.113 0.019 0.017

2011 0.098 0.111 0.015 0.017

2012 (reference)

Survey month

January 0.071 0.011 0.075 0.012

February –0.078 –0.012 –0.076 –0.012

March 0.055 –0.009 –0.046 –0.007

April –0.042 –0.007 –0.038 –0.006

May –0.152* –0.023* –0.118 –0.018

(continued)

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166 Journal of the American Planning Association, Spring 2014, Vol. 80, No. 2

multiple observations from the same school and survey date (e.g., morning and afternoon reports of travel mode). Such observations are not independent. We adjusted for potential correlation by using robust standard errors adjusted for clustering across schools. However, we also wanted to test whether our fi ndings changed if we limited observations to one observation for each school and survey date, a situation that elimi- nates potential correlation by school and survey date. After limiting the data set to one observation by school and survey date (selected randomly), we found our results unchanged (Table A-2). This suggests that correlation across observations from the same school and survey date is not problematic.

The second methodological concern was self- selection bias. Program evaluation is diffi cult, particularly when

assignment to treatment—in this case receiving an SRTS intervention—is not exogenous. Schools and communities made their own decision about whether or not to apply for SRTS funding, and states selected schools that would receive the grants. It is not unreason- able to expect that schools that applied to the SRTS program were different from schools that did not apply. For example, schools that sought funding might have an identifi ed safety problem, have a strong champion of walking and bicycling, or be places where communities valued walking and bicycling. The type of places that applied for the SRTS program might be places where the program was more likely to be effective. This self- selection bias creates diffi culties for modeling program impacts. In the study, we address self-selection bias by including statistical controls for school and neighbor- hood characteristics. Here, we conduct an additional analysis that compares schools receiving the SRTS program with schools that applied for but did not re- ceive funding. Schools that applied for the SRTS pro- gram, but did not receive funding, should be more similar to funded schools on unobservable characteris- tics such as attitudes favorable to walking and bicycling than schools that never applied for SRTS funding. As shown in Table A-3, we fi nd our results unchanged when only including the 708 schools that applied for SRTS funding. Our fi nal check included only the 378 schools that had a SRTS program during the study period. In effect, this used observations on schools prior

Table A-1. (Continued)

Model 1: Presence/absence of SRTS Model 2: Type of SRTS intervention

Coeffi cient Marginal effect Coeffi cient Marginal effect

June –0.073 –0.011 –0.030 –0.005

July –1.625*** –0.158*** –1.604*** –0.156***

August –0.084 –0.013 –0.074 –0.011

September –0.011 –0.002 0.008 0.001

October (reference)

November 0.217 0.036 0.219 0.037

December –0.136 –0.021 –0.112 –0.017

Unknown –0.224 –0.034 –0.215 –0.032

No. observations 4,090 4,090

No. schools 801 801

LL –1404.04 –1402.41

AIC –2878.1 –2884.8

Notes: Coeffi cients from month of survey administration and constant terms are not shown. AIC = Akaike information criterion; Educ. & Enc. = education and encouragement; HH = household; FRL = free or reduced-price lunch; LL = log likelihood; SRTS = Safe Routes to School. *p < .05; **p < .01; ***p < .001.

Table A-2. Marginal effects of Safe Routes to School interventions with one observation per school and survey date.

Marginal effect p value

SRTS intervention

Presence 0.005 0.700

Length (years) 0.013 0.001

No. schools 801

No. observations 1649

LL –568.0

Note: Models include all variables included in Model 1 from Table A-1.

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McDonald et al.: Impact of the Safe Routes to School Program on Walking and Bicycling 167

to receiving SRTS interventions as the control group. Again, we fi nd the overall pattern of impact and signifi - cance unchanged. We continue to observe a statistically signifi cant impact of the number of years of SRTS participation (Table A-3).

References Lee, C., Zhu, X., Yoon, J., & Varni, J. W. (2013). Beyond distance: Children’s school travel mode choice. Annals of Behavioral Medicine, 45(1), 55–67. doi:10.1007/s12160-012-9432-z McDonald, N. C., Dwelley, A. E., Combs, T. S., Evenson, K. R., & Winters, R. H. (2011). Reliability and validity of the Safe Routes to School parent and student surveys. International Journal of Behavioral Nutrition and Physical Activity, 8, 56. doi:10.1186/1479-5868-8-56 McDonald, N. C., Yang, Y., Abbott, S. M., & Bullock, A. N. (2013). Impact of the Safe Routes to School program on walking and biking: Eugene, Oregon study. Transport Policy, 29, 243–248. doi:10.1016/j. tranpol.2013.06.007 Oluyomi, A. O., Lee, C., Nehme, E. K., Dowdy, D., Ory, M., & Hoelscher, D. M. (2014). Parental safety concerns and active school commute: Correlates across multiple domains in the home-to-school journey. International Journal of Behavioral Nutrition and Physical Activity, 11, 32. doi:10.1186/1479-5868-11-32

Papke, L. E., & Wooldridge, J. M. (1996). Econometric methods for fractional response variables with an application to 401(k) plan participation rates. Journal of Applied Econometrics, 11(6), 619–632. doi: 10.1002/ (SICI)1099-1255(199611)11:6<619::AID-JAE418>3.0.CO;2-1 Papke, L. E., & Wooldridge, J. M. (2008). Panel data methods for fractional response variables with an application to test pass rates. Journal of Econometrics, 145(1–2), 121–133. doi:10.1016/j. jeconom.2008.05.009 Steiner, R. L., Bejleri, I., Wheelock, J. H., Perez, B. O., Provost, R. E., Fischman, A., . . . Cahill, M. (2011). How policy drives mode choice in children’s transportation to school: An analysis of four Florida school districts. In R. Miles, M. Wyckoff, & A. Adelaja (Eds.), School siting and healthy communities: Why where we invest in school facilities matters (pp. 147–164). East Lansing: Michigan State University Press. Zhu, X., & Lee, C. (2009). Correlates of walking to school and implica- tions for public policies: Survey results from parents of elementary school children in Austin, Texas. Journal of Public Health Policy, 30(Suppl. 1), S177–S202. doi:10.1057/jphp.2008.51 Zhu, X., Lee, C., Kwok, O. M., & Varni, J. W. (2011). Context-specifi c correlates of walking behaviors to and from school: Do they vary across neighborhoods and populations? Journal of Physical Activity & Health, 8(Suppl. 1), S59–S71. Retrieved from http://journals.humankinetics. com/jpah-supplements-special-issues/jpah-volume-8-supplement-janu- ary/context-specifi c-correlates-of-walking-behaviors-to-and-from-school- do-they-vary-across-neighborhoods-and-populations

Table A-3. Marginal effects of Safe Routes to School interventions for schools after controlling for self-selection.

Schools that applied for SRTS funding Schools with SRTS program during study period

Marginal effect p value Marginal effect p value

SRTS intervention

Presence 0.010 0.360 0.013 0.228

Length (years) 0.011 0.003 0.011 0.005

No. schools 710 378

No. observations 3778 2985

LL –1318.4 –1076.3

Note: Models include all variables included in Model 1 from Table A-1. LL = log likelihood; SRTS = Safe Routes to School.

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assignment 2/Rosenbloom.pdf

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Copyright © 2009 American Society on Aging; all rights reserved. This article may not be duplicated, reprinted or distributed in any form without written permission from the publisher: American Society on Aging, 71 Stevenson St., Suite 1450, San Francisco,CA 94105-2934; e-mail: [email protected].

In the face of continued and ever growing “automobility” and suburbanization, there is little evidence that the United States is prepared to meet the mobility challenge facing older Americans. Policy makers and even advocates may have fooled themselves about the magni- tude and cost of the policy options available. Many assume that older people who face mobility problems or must cease driving will be served by public transit and by special demand- responsive transportation services. Yet all indications are that neither traditional public transit services nor special demand services will come anywhere near meeting the mobility needs of the country’s aging population. Moreover, there is far too little policy focus on enhancing the travel modes that do serve most older people: cars and pedestrian facilities. What are the options for making transportation in our com- munities more aging-friendly?

Travel Modes Available to Elders Many analysts assume that older people will

come to rely on conventional public transit services and, to a lesser extent, on special demand-responsive services as they age. Are these assumptions a valid basis for planning?

Traditional public transit The assumption that older people will rely

on traditional public transit services may be

based on historical patterns showing that older people have used public transit more than younger people have. Unfortunately, those patterns represent a cohort effect; in the past many people reaching 65, particularly women, had never driven and had long relied on public transit for some of their trips. There is no evidence that older people suddenly begin to use public transit upon retirement. In fact, there is far more evidence that older adults are even less likely to use public transit when they retire than when they are in the labor force. Most public transit services are best at meeting the needs of those traveling to work, and not those making other kinds of trips (Transit Cooperative Re- search Program [TCRP] and National Coopera- tive Highway Research Program [NCHRP], 2006; Rosenbloom and Stähl, 2003).

Even more important, the overwhelming number of people now 65-plus probably never used public transit when in the workforce—pub- lic transit use has been dropping for decades among workers (TCRP and NCHRP, 2006). As new cohorts of car-oriented citizens reach traditional retirement age, even fewer use public transit. Today only 1.3 percent of all trips taken by people over age 65 are made using any form of public transit. In fact, the use of public transit by this age group is lower than that of younger people. In 2001, for example, older people who drove—the majority of that age group—took less

By Sandra Rosenbloom

Meeting Transportation Needs in an Aging-Friendly Community

Surprisingly, the most promising focus may be on keeping older people driving longer.

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than 1 percent of all trips using any type of public transit (U.S. Bureau of Transportation Statistics [U.S. BTS], 2003a). Even nondrivers over age 65 took only 8 percent of all trips by public transit but took 66 percent of all their trips in a private car. When they did not drive or ride as a passenger, older drivers and nondrivers alike were many times more likely to walk than to take public transit (U.S. BTS, 2003a, 2008b).

Traditional public transit services as cur- rently funded and delivered are not responsive to the needs of most older travelers, particu- larly those no longer in the labor force. Studies consistently show that older travelers have a variety of safety, personal security, flexibility, reliability, and comfort concerns about public transit, even if it is physi- cally accessible. Moreover, they often do not find the actual routes and hours of service to match their desired travel patterns (TCRP, 1998c, 1999c, 2002a; U.K. Department for Transportation [U.K. DfT], 2003; Herbel et al., 2005).

ADA paratransit services The 1990 Americans with Disabilities Act

(ADA) requires public transit operators receiv- ing federal financial assistance to provide special demand-responsive services to people with serious disabilities to complement bus services. Many people assume that these ADA comple- mentary paratransit services will meet the needs of their aging relatives who do not or cannot drive and are unable to use conventional public transit. But these assumptions are easily chal- lenged. To begin, ADA complementary paratran- sit was designed to be a temporary alternative for most people with disabilities, until all buses were fully accessible (National Council on Disability [NCD], 2005). As more transit ve- hicles, transit stops, and the pathways to them become accessible, operators will be allowed to substantially decrease the amount of special services that they provide—even as the popula- tion of older adults grows.

Second, eligibility for ADA complementary paratransit services is based on disability and not age—and that disability must be severe enough to significantly interfere with the use of traditional public transit. While disabilities do increase with age, the majority of older adults are not disabled (U.S. Census Bureau, 2005). Today roughly 58 percent of older people simply do not qualify for ADA complementary paratransit services, where they exist, because they do not have serious physi-

cal or mental impairments. A substantial number of the 42 percent of

older people with at least one disability will also be ineligible for these services because their functional impairments do not rise to the level of ADA eligibility.

Indeed, the vast number of older people in the United States do not and probably will not live in or travel in neighborhoods with ADA paratransit service, and, even if they do live or travel in such corridors, they are unlikely to qualify for those services for most of their lives after they reach age 65. National data show that fewer than 8 percent of older people with disabilities report ever using these services (U.S. BTS, 2004). In fact, most ADA paratransit systems provide a small number of active users with a fairly large number of trips each (TCRP, 1998a).

Community transit services Most U.S. communities also host many other

special demand-responsive (“paratransit”) services provided by nontransportation govern- mental agencies, nonprofit organizations, faith-based groups, and advocates for older adults. The U.S. General Accounting Office (GAO) (2003, 2004) identified more than seventy federal programs alone that finance such organizations to provide a range of transporta- tion services to a variety of users, including, but not limited to, older people. Ultimately, however,

Policy makers may have fooled themselves about the magnitude and cost of the options available.

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we have no good data on who is provided rides, how often, and how much these transportation services cost.

We do know that many such community transportation systems limit their services to a small number of agency clients or affiliated riders rather than providing for the general public or older people (GAO, 2003; Rosenbloom, 2004). Even to these selected riders, these systems often provide limited services and restrict travel to trips they consider “important,” such as to agency activities or medical appoint- ments. But older people don’t make more than 5 percent of their trips for any kind of medical purpose. So even people who are served by such systems usually have a number of other unmet trip needs—from social and recreational activi- ties to grocery shopping. Overall, less than 3 percent of older people with disabilities report ever using the services of community transporta- tion providers (less than half the number reporting the use of ADA services) (U.S. BTS, 2003b, 2004).

Realistic Travel Options Perhaps surprising to some, the auto-based

system and walking emerge as the most realistic travel options currently available for many older adults.

The auto-based system In 2007, the overwhelming percentage of

people over age 65 had a driver’s license. As a result, those over 65 accounted for more than one in seven drivers on U.S. roadways (computed from Table DL-20, U.S. Federal Highway Admin- istration [U.S. FHWA], 2008). By 2030, older drivers will account for as many as one of four U.S. drivers and substantially more in many rural and retirement communities (Herbel et al., 2005). Older people have become more and more reliant on the car as their licensing rates have increased.

Today those ages 65 to 84 take roughly 90 percent of all their trips by car, most often as

the driver. Even those 85 and older take 80 percent of their trips by car, driving half the time. In fact, in 2001, older people actually made a greater percentage of their trips as drivers than did people between ages 25 and 64 (Rosenbloom and Herbel, 2009; Herbel et al., 2005; Rosenbloom, 2005).

The car is also a significant mode for those who do not drive; in 2001, nondrivers over 65 made almost as high a percentage of their total trips in a car as did drivers that age. Clearly, older people who do not drive are very depen- dent on others for rides, often on other older drivers. While nondrivers take the majority of their trips by car, they do not make as many trips nor are their trips as long as those of drivers. In 2001, drivers ages 65 to 69 made 87 percent more trips by car than did nondrivers of the same age. Even at age 85, drivers made more than twice as many trips as those who did not drive (Rosenbloom, 2005; Herbel et al., 2005).

Pedestrian facilities National data show that the second most

important travel mode for older people, behind car travel, is walking. Walking is necessary for all other modes of travel, and it can provide a healthful physical activity geared to older people’s needs. About 9 percent of all trips taken by those over age 65 are walking trips; among older adults who don’t drive (almost all of whom are women), walking accounts for almost one out of every four trips, and its importance increases with age (U.S. BTS, 2004). But walking is far from an easy task for many older people.

In several national studies older people with and without disabilities reported significant problems in the pedestrian environment, including the lack of sidewalks or the lack of a system of connected sidewalks. Other commonly reported problems were unsafe intersection crossings, crowded sidewalks, cyclists on the sidewalk, cars parked on or obstructing side- walks, broken or uneven pavements, and the failure to remove leaves, ice, snow, weeds, and

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other obstructions that can cause falls. Fear of personal security is also an issue for older pedestrians (U.S. BTS, 2003a; U.S. FHWA, 2001; U.K. DfT, 2003).

A 1994 national study found that among older respondents who reported problems in “getting around outside home,” over 75 percent said that their major issue was difficulty in walking. Among the small number of those who reported difficulty in using public transit because of their disability (as opposed to other reasons for not using public transit), the single most frequently cited problem was difficulty in walking. Overall, reported barriers in the pedestrian environment far outnumbered reported problems with transit or paratransit modes (U.S. National Center for Health Statistics, n.d.).

The lack of appropriate pedestrian facilities has safety as well as mobility implications (U.S. FHWA, 2001). Older people have more pedes- trian crashes than anyone except children, and they are far more likely to be seriously injured or die in those crashes (Rosenbloom and Herbel, 2009). In fact, older people are far more at risk as pedestrians than as car passengers or drivers. Some experts believe that older people are at least 15 times more likely to be injured or killed as pedestrians than as car drivers, on an expo- sure basis (Rosenbloom, forthcoming).

Implications for Future Mobility This section highlights possible ways

to increase both the safety and mobility of older people in each of the travel modes discussed above.

Public transit Simply providing a greater number of

traditional public transit services would un- doubtedly serve the needs of some older travel- ers. But major studies have suggested that these services must be improved in a number of ways to meet the needs of an aging population (TCRP, 1997a, 1997b, 1998b, 1998c, 1999a, 2002a, 2002b; Rosenbloom, 2004). Most studies stress that to

do so requires increasing safety and security in all parts of the system, providing better informa- tion both before and during travel, expanding the hours of service and providing additional routes, making service more reliable, and enhancing driver training (TCRP, 1994, 1998b).

But even increasing and improving tradition- al public transit services is unlikely to meet the needs of most older people unable to drive. Research suggests that transit operators have to provide more customized services, more directly linking residential concentrations of older people to the destinations to which they want to travel and at the hours they need to travel, often outside the traditional peak period, and some- times at night (TCRP, 2002b, 2004a). Those services must be provided in fully accessible and preferably smaller vehicles and must offer service attributes not commonly found in traditional transit services, such as a higher level of driver assistance, some route deviation, and allowing travelers to disembark anywhere along the route as opposed to only at designated stops (TCRP, 1997a, 1998a, 1999b, 2002b).

It will, of course, cost a great deal to provide a greater number of traditional transit services, and the costs of providing more customized services are likely to be even higher. But in total, the costs of providing both will be substantially less than the costs of providing a large number of older people with special demand-responsive services would be. In Phoenix, for example, in 2006, the average operating cost for an ordinary bus trip was $2.37, but the comparable operating cost for a paratransit trip was over $35. Expand- ing public transit options when and where they can meet the needs of older travelers makes more sense than limiting older travelers to expensive paratransit services.

Special and demand-responsive services No matter how much public transit services

are modified and improved, some older people will not be able to use them (TCRP, 1997a, 1997b). To respond, society could expand all

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types of special transportation services and relax eligibility requirements so that older people unable to drive qualify for service. Unfortunately, these services are extremely expensive; in 2007, the average one-way ADA paratransit trip for the fifty largest transit systems cost almost $36. That is, taking one eligible person to and from a medical appoint- ment cost over $75 (FTA, 2008).

So, over the past decade, many transit systems, rather than expanding service and making older people eligible for services, have moved in exactly the opposite direction—re- stricting service and carefully limiting eligibility (Thole and Harvey, 2005; NCD, 2005; Griffin and Priddy, 2005).

The high costs seen in U.S. paratransit systems are inherent in the nature of the service. It is hard to generate substantial economies of scale transporting people with significant disabilities within a large, low-density service area—while being forbidden by law to signifi- cantly delay their trips to pick up or drop off other passengers. While it is possible that the productivity of such systems could be improved, these services will still remain very expensive both absolutely and in comparison to the cost of a regular transit trip. Most transit systems are unlikely to expand these services unless they receive substantial additional funding.

In addition to the ADA services provided by public transit operators, there are a wide variety of community transport providers (Easter Seals, 2008). Some operate large systems that resemble ADA paratransit services. A number of well- known and award-winning community transport systems, such as Ride Connections (Portland, Oregon) and Portland, Maine’s ITN, have trip costs that are only two-thirds of those of public

transit operators, in spite of using substantial volunteer resources (Rosenbloom, 2007).

At the other end of the spectrum are commu- nity transport providers who do not operate systems but find ways to match volunteer drivers to older (and other) travelers with mobility needs. Their costs tend to be substantially less than more formal systems. However, given their administrative costs (which sometimes include

providing additional insurance to volun- teers), their unit costs are still higher than that of an ordinary transit trip (Beverly

Foundation and AAA Foundation for Traffic Safety, 2001).

There are important ways to support, expand, and improve all these services, although substantially more funding would be needed.

In addition to coordination, state or other governmental units could help increase the productivity and lower the costs of more formal- ized community transport systems by developing ways to improve dispatching services, increase driver and dispatcher training, and the like (TCRP, 2004b, 2004c). But given the large and growing demand for these kinds of services, initial savings resulting from coordination or better operational practices will soon be swamped by the costs of providing new services to the growing number of older people who need mobility options.

There are also ways to improve and support community transport programs that match volunteer drivers to older people needing transportation—and perhaps encourage the development of more such systems. To do so, the state or other governmental units could dissemi- nate information on how to establish and maintain such programs, provide insurance or lower insurance costs, and develop ways for volunteer drivers to receive auto maintenance at reduced rates. Another promising approach is the use of a voucher system which repays drivers

Neither traditional public transit services nor special demand services will come anywhere near meeting mobility needs of the country’s aging population.

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for their gas and auto costs; eligible travelers are given vouchers which they can then offer to drivers whom they ask for a ride (Beverly Foundation and AAA Foundation for Traffic Safety, 2001).

All of these kinds of providers have an impor- tant role to play in a family of mobility services for older people (Easter Seals, 2008). But federal, state, and local governments will have to commit substantially more money to such systems to allow them to serve more than the small number of older people they currently transport today. Given their (generally) high cost per trip, they should be reserved for those older people who need that level of service and cannot use other transportation options.

Improving the highway system Since so many older people are and will be

drivers until very late in their lives, the most promising mobility option is to modify all the components of the auto-based infrastructure so that older people can drive safely longer (Stap- lin, 2004), beginning with the driver. There is a need to develop effective in-car driver education programs targeted specifically at the needs and skills of older drivers (Stutts and Wilkins, 2003). The federal government could fund the development, testing, and evaluation of various in-car training strategies. Either the public or private sector could use this research to structure effective train- ing courses to which older drivers could be referred or volunteer to attend.

In addition, programs could assist safe older drivers who have financial difficulties to con- tinue driving in two different ways. A commu- nity can develop programs which provide assistance for maintenance or fuel, or even purchase of a car. This approach has been adopted by the U.K. to assist older drivers and those with disabilities. Another way to imple- ment this strategy is to develop a car-sharing program for older people. Independent living centers, retirement communities, or naturally

occurring retirement neighborhoods could contract with an existing car-share operator such as Zipcar. Or they could cooperatively buy and operate a small fleet of vehicles, allowing individual residents to reserve and drive them on an hourly or daily basis.

The next component of the system that needs to be addressed is the highway network. High- ways can be made safer for older drivers by improved street lighting, additional signage, new lane-marking and sign systems responsive to diminishing eyesight and contrast sensitivity, enhanced intersection signalization, reserved lanes and signal priority for left turns, and greater separation between motorists and cyclists and pedestrians (U.S. FHWA, 2001; Staplin, 2004; Consdorf, 2004; NCHRP, 2004, 2005; Oxley and Whelan, 2008). In fact, the U.S. FHWA has developed a series of design stan- dards in all these areas to reflect the aging of the driver pool (U.S. FHWA, 2001, 2003).

The highway network can also be made safer for older drivers using technological solutions— in the road, on the vehicle, or in some effective combination. Older drivers can better manage the driving task if their cars warned them that they were following another vehicle too closely,

drifting into another lane, or likely to hit center dividers or other highway infrastructure. Technology that facilitated left turns, for exam- ple, by warning drivers when it was safe to make the turn, might reduce crash rates, since older drivers are now substantially overrepresented in crashes turning left at intersections (U.S. NHTSA, 2007; Braitman et al., 2007).

A third element to be addressed is the vehicle itself; if cars were both more comfortable and easier to drive, older people would find the driving task less challenging. The public and

As new cohorts of car-oriented citizens reach traditional retirement age, even fewer use public transit.

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private sectors are conducting research on ways to redesign vehicles to compensate for dimin- ished driving skills, make the driving task more pleasant and less stressful, reduce crashes, and improve crash outcomes (Boufous et al., 2008). Some vehicle improvements thought to be useful to older drivers have slowly been making their way into higher-end private cars. However, it may be some time before many cars include improved designs or technology (and older people are more likely to own older cars which will lack the newest improvements).

The full cost of all these policies and pro- grams is unknown. Moreover, it may be decades before all of the design and technological options just described are incorporated into the highway and auto network. Yet, given the very large number of older drivers, the cost per traveler or per trip may be substantially lower than any of the transit or paratransit options discussed in the previous section. It is important to note that long after they can no longer walk far or use public transit, older people can drive (European Conference of Ministers of Transport, 1999; Rosenbloom, 2004, 2005). Keeping older people driving as long as safely possible may well be the most feasible and cost-effective mobility option for an aging society.

Pedestrian Facilities Given its importance for older people, many

studies have suggested measures that alone or together can facilitate walking both as a mode itself and to gain access to public transit (U.S. FHWA, 2001; NCD, 2005; U.K. DfT, 2003). Most of these measures can be used to retrofit existing neighborhoods where baby boomers are aging in place; they can also be incorporated into new suburban developments or formal or informal retirement communities through new or modi- fied subdivision and zoning regulations and impact or development fees. They can also be added to existing urban neighborhoods or incorporated into new developments in the core of central cities.

Suggested pedestrian improvements include raised pavement markings, median islands, improved user-activated signal crossing devices, enhanced signals, and improved pedestrian crossings. Other possibilities include adopting traffic-calming devices such as narrowing streets, lowering speed limits, and using traffic circles to slow traffic. Finally, it is important to improve access to public transit by creating accessible paths to accessible transit stops, following ADA standards (French, 2003; Kochera and Bright, 2006).

And in addition to physical changes, it is important to actively enforce traffic laws and maintain pedestrian facilities (Huang and Cynecki, 2000). A recent Swedish study found that pedestrian crashes went up 27 percent after speed limits were reduced at marked crosswalks throughout the country in 2000 because pedestrians assumed that drivers would reduce speed and acted accordingly—but

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drivers did not slow down because there was no effective enforcement (Leden, Garder, and Johansson, 2006).

Land use People need to travel because of the way their

communities are structured spatially; because so many older people live in low-density neighbor- hoods, they are very dependent on the car to meet their mobility needs. (See Rosenthal and other articles in this issue for a full discussion of land use.) There has been substantial discussion of (1) older people moving (back) to denser urban areas to address their mobility needs (Evans, 1999; Spain, 1999) and (2) creating neighborhoods where it is possible for people of all ages to access a range of needed services within walking or transit distance from their home (AARP, 2005, 2008; Rosenbloom and Stähl, 2003).

While land use options have promise, it does not seem likely that many older people will move to more walkable or transit-useful communities. Even if some older people do move if offered such options, the majority will undoubtedly continue to age in place in their communities.

If so, more attention should be focused on retrofitting those neighborhoods where most older people will age in place. This can be done by increasing the safety and accessibility of the pedestrian and public transit network, offering more appropriate housing options in those neighborhoods (so people can move into smaller homes but in the same neighborhood), finding ways to deliver more on-site or mobile services, and encouraging commercial as well as residential infill.

Summary and Conclusions By 2030 there will be over 72 million people

in the U.S. at least 65 years old and 11.5 million age 85 and older (U.S. Census Bureau, 2008). Most of those older adults will have passed their sixty-fifth birthday as drivers, and most

will stay drivers for decades after that birthday. Their lifestyles and the contributions they make to their communities will depend on the flexibility and convenience offered by the private car. Very few will have the interest or ability to move from their suburban or rural homes to places where they may be able to find reasonable alternatives to driving when they can or should no longer drive.

A variety of transportation alternatives, from public transit to community transportation systems, can be part of a family of services for older people who can no longer drive. But these

alternatives, while providing lifesaving services to the small number of older people who use them, as currently funded and

delivered are unlikely to replace anywhere near the mobility lost by millions of older people unable to drive.

To address these needs, we must do the following: adopt policies that provide substan- tially more funding for transit operators to develop meaningful transit services and increase ADA-type paratransit services for older people without serious disabilities, provide better support and financial resources for the wide variety of community transporta- tion providers, develop programs and policies to keep older people driving safely as long as possible, enhance and maintain the pedestrian network, and ensure that traffic regulations are enforced. All of these actions must be combined with the major focus on retrofitting the neigh- borhoods in which the majority of older people are aging in place.

Sandra Rosenbloom, Ph.D., is professor, Graduate Program in Planning, School of Landscape Architec- ture and Planning, College of Architecture, University of Arizona, Tucson.

Older people are far more at risk as pedestrians.

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Rosenbloom, S. 2007. “The Transportation Patterns and Needs of People with Disabilities.” In M. J. Field and A. Jette, eds., The Future of Disability in America, pp. 519–560. Washington, D.C.: Institute of Medicine of the National Academies, National Academies Press.

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assignment 2/Rosso.pdf

SAGE-Hindawi Access to Research Journal of Aging Research Volume 2011, Article ID 816106, 10 pages doi:10.4061/2011/816106

Review Article

The Urban Built Environment and Mobility in Older Adults: A Comprehensive Review

Andrea L. Rosso, Amy H. Auchincloss, and Yvonne L. Michael

Department of Epidemiology and Biostatistics, Drexel University School of Public Health, 1505 Race Street, Mail Stop 1033, Bellet 6th Floor, Philadelphia, PA 19102, USA

Correspondence should be addressed to Andrea L. Rosso, [email protected]

Received 16 December 2010; Accepted 3 May 2011

Academic Editor: Thomas R. Prohaska

Copyright © 2011 Andrea L. Rosso et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Mobility restrictions in older adults are common and increase the likelihood of negative health outcomes and premature mortality. The effect of built environment on mobility in older populations, among whom environmental effects may be strongest, is the focus of a growing body of the literature. We reviewed recent research (1990–2010) that examined associations of objective measures of the built environment with mobility and disability in adults aged 60 years or older. Seventeen empirical articles were identified. The existing literature suggests that mobility is associated with higher street connectivity leading to shorter pedestrian distances, street and traffic conditions such as safety measures, and proximity to destinations such as retail establishments, parks, and green spaces. Existing research is limited by differences in exposure and outcome assessments and use of cross-sectional study designs. This research could lead to policy interventions that allow older adults to live more healthy and active lives in their communities.

1. Introduction

Mobility limitations are defined by impairment or depen- dence in movement and affect between one third and one half of adults aged 65 or older [1]. Mobility limitations can affect an individual’s health through a number of pathways. Lack of physical activity in older individuals can lead to loss of muscle mass (sarcopenia), loss of bone density (osteoporosis), and an increase in fat mass (obesity) [2, 3]. Isolation and loss of social ties resulting from reduced mobility can lead to depression and other adverse mental health outcomes [4]. A lack of access to resources such as fresh foods and medical care which can result from limited mobility can also have negative impacts on health [5]. Individuals with mobility limitations are also at higher risk of health service utilization [6–8] and institutionalization [6, 9, 10]. Ultimately, further frailty and disability and an increased risk of premature mortality can result from restricted mobility [1, 11].

Methods of assessing mobility limitations vary [1]. In assessment of mobility, it is important to distinguish between capacity to function—what an individual could do—and

enacted function—what an individual does do [12]. In this way, assessments of an individual’s walking behavior represent an enacted form of mobility while questions that assess an individual’s perception of their ability represent functional capacity. Both may be relevant measures of mobility.

Mobility restrictions are not typically the result of a single cause, but arise from an interaction of risk factors in various domains, both individual and environmental [1]. Traditionally, disability research had been based on the medical model in which the focus is on the individual and pathology [13]. More recently, following on the work of Lawton [14, 15], Verbrugge and Jette [16], and the World Health Organization’s International Classification of Functioning, Disability, and Health (ICF) [17], disability models have focused on the interaction of the individual with their environment. Lawton stressed the importance of the environment in determining the well-being of older adults where an individual’s competence to deal with their environment combines with the stresses, or press, that the environment places on that individual [14]. Thus, Lawton’s model adds the possibility that mobility may be enhanced

2 Journal of Aging Research

through environmental buoys as compared to the medical model that assumes decline [5]. Both the ICF and Verbrugge stress the importance and bidirectionality of environmental as well as personal factors on individual health [16, 17]. Environmental characteristics are hypothesized to limit or promote an individual’s ability to complete purposeful actions and fulfill role expectations, affecting physical func- tioning and disability (see Figure 1).

Older adults may be more vulnerable to influence of their residential environment as they tend to travel outside their own neighborhoods less often than do younger adults and children who travel for work and school and tend to have a longer duration of exposure to neighborhood influences than younger individuals [5]. Declining physical and mental health, shrinking social networks, loss of social support, and increased fragility may also reduce the ability of older individuals to cope with environmental demands [5, 19, 20]. Therefore, neighborhood environment likely has a greater impact on the elderly than on those in other age groups and evidence suggests that supportive environments improve quality of life in older adults [21]. Lawton proposed several dimensions of environment that are important for older adults: personal environment (family, friends), suprapersonal environment (i.e., neighborhood racial or age composition), social environment (norms or values related to society or culture), and physical environment (e.g., built environment) [14]. The built environment is defined as the human-made or human-altered space in which individuals live out their daily lives [22] and is the focus of this paper.

Much of the existing research regarding neighborhoods and health has been conducted in younger or middle-aged adults and has focused on aspects of the environment other than the physical or built environment [19, 20, 23]. The built environment’s effect on health has been conceptualized into three domains: transportation systems which include street networks and transit systems, land use patterns which includes density and land-use mix, and urban design which includes safety, attractiveness, and site design [18]. Transportation systems are defined as the network of physical infrastructure, such as its street network, transit systems, and trails (e.g., for jogging or biking,). Transportation systems influence how easy it is to travel through a neighborhood and get to places a person wants to go. Land use patterns reflect where and how residential, commercial, and industrial uses are distributed in a neighborhood. Density of land use represents an increased compactness of neighborhoods with easier access to pedestrian destinations. Urban design characteristics—such as number and width of traffic lanes, size and extensiveness of sidewalks, traffic calming devices— influence safety and attractiveness and ultimately decisions about whether or not to walk. Pleasant pedestrian environ- ments that promote feelings of belonging to a neighborhood and trust in ones neighbors can be created through positive urban design [18]. In contrast, evidence of decay, such as vandalism and poorly maintained vacant lots, can reduce mobility by creating feelings of discomfort in one’s neigh- borhood. All three of these domains can potentially impact mobility in the elderly (see Figure 1).

Use of self-reported measures of the environment is common in the existing literature but relies on participant’s perception of problems rather than actual presence of barriers. Evidence consistently shows differences between objective and perceived measures of the local environment [19, 24]. The two measurement types are likely capturing dif- ferent constructs both of which are important in determining mobility of older adults. We focus on objective measures here in an attempt to summarize the direct effects of built environment factors as these can be ideal targets for public policy interventions.

The goal of this paper is to summarize the recent published literature on objective measures of the built environment and mobility or disability in older adults and provide a critical analysis of the limitations.

2. Methods

Searches of Medline and Web of Science were conducted for English-only articles published between 1 January, 1990 and 7 December, 2010 with the following keyword search terms: neighborhood, built environment, or physical environment and elderly, older adults, aging, mobility, disability, walking, or physical function. Additional articles were identified through consultation with experts and review of reference lists of included articles. Inclusion criteria were (1) the study population consisted of community-dwelling adults aged 60 years or older or if no range was provided, the average age was ≥65 years, (2) built environment was objectively measured either through use of administrative datasets or research rater assessments, (3) outcomes included measures of mobility or disability and physical functioning as described in Verbrugge’s disablement model [16]. Articles were excluded if they were a review or commentary or if they provided qualitative data only.

3. Results

We reviewed 31,596 abstracts for relevancy to this paper. Of these, 28 articles were reviewed for inclusion criteria, with seventeen articles meeting our criteria. Details of these studies are provided in Table 1. Four studies were longitudinal [25–28]; the remainder assessed cross-sectional associations. One study used nationally representative data from the USA [25] and one was conducted outside the USA [29]. Seven of the studies (41%) were conducted in the Pacific Northwest [28, 30–35]. Enacted function, or walking in some form, was the most commonly assessed outcome, though there was little overlap in the way in which walking was assessed. Walking has been measured as specifically for exercise [35], for utilitarian purposes [30, 36], by frequency of neighborhood walking on a Likert scale [32–34], by whether individuals met physical activity recommendations for walking (>150 hours/week) [27, 29, 37], and by other measures of walking frequency [3, 28, 31]. One study used accelerometers to directly measure the number of steps taken by participants in a day [38]. There were also a wide range of definitions for neighborhood, including specified

Journal of Aging Research 3

Pathology DisabilityImpairments

Land use patterns

Urban design Transportation

systems

Built environment

Individual factors

Functional limitations

(including mobility)

Built environment Transportation systems: street network, transit systems Land use patterns: density, land-use mix Urban design: safety, attractiveness, site design

Disablement pathway Pathology: disease or injury Impairments: dysfunction in body systems Functional limitations: restrictions in purposeful actions including mobility and enacted forms of walking Disability: difficulty performing expected activities and roles

Individual factors: gender, age, health conditions, financial resources, etc.

Figure 1: The role of the built environment in the disablement process (adapted from Verbrugge and Jette, 1994 [16] and Frank et al., 2003 [18]).

distances from an individual’s home (i.e., quarter-mile radius), census tracts, and other administratively defined neighborhoods. Subgroup analyses were completed in only 5 studies, including gender [35], lower body functional status [37, 39], age [25], and neighborhood socioeconomic status [28]. Fewer than half of the studies explicitly stated the theoretical framework or causal model that guided their research in the article [26, 28, 30, 34, 37–39]. Effect sizes tended to be small: approximately three-quarters of the statistically significant estimates had relative risks or odds ratios below 2.0 (range was 1.08 to 4.12).

3.1. Transportation Systems. Traffic-related street charac- teristics have been assessed in relation to mobility, with high-traffic volume positively associated with walking [31]. However, presence of through routes, representing high- traffic volume, was not associated with disability [40]. A high percentage of car commuters, indicating a greater reliance on driving rather than walking for transportation, was positively associated with increased walking difficulty among those aged 75 and older, but not among younger age groups [25]. Living within a specified area of Bogotá, Columbia in which streets are closed to vehicular traffic on Sundays and holidays, creating a pedestrian corridor, was positively associated with walking among older residents [29]. Proximity to walking paths and trails was associated with amount of daily walking [38] but not with frequency of neighborhood walking [32]. Finally, presence of nearby transit stops, providing access to areas outside the immediate neighborhood via public

transit, was not associated with walking in two studies [29, 31]. Street connectivity, indicating shorter blocks with more intersections and resulting in easier pedestrian links between two points, have been studied in relation to walking in older adults with mixed results. Nagel and colleagues and Satariano and colleagues found no association [31, 37], Li and colleagues found a positive association [33], and Gomez and colleagues found an unexpected negative association [29]. Differences in study site, neighborhood definitions, and operationalization of walking likely accounted for some differences in results for street connectivity. Neighborhoods were specified differently in the four studies: those studies finding no association, Nagel et al. [31] and Satariano et al. [37], used a specified distance from homes, Li et al. [33] used city-defined neighborhoods, and Gomez et al. [29] used neighborhoods defined by socioeconomic status. Two discordant studies were conducted in the same city (Nagel et al. [31] and Li et al. [33]) and another two discordant studies both assessed walking as meeting physical activity recommendations (Satariano et al. [37] and Gomez et al. [29]).

3.2. Land Use Patterns. Housing density was associated with greater levels of walking [33] and with less disability among those with lower body functional limitations [39]. However, population density was not associated with increased walking difficulty over 15 years [25]. Mix of land use, representing proximity to a variety of destinations such as places of em- ployment and retail establishments, has been assessed in

4 Journal of Aging Research

T a

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Journal of Aging Research 5

T a

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6 Journal of Aging Research

T a

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Journal of Aging Research 7

several studies with inconsistent results. More mixed land use was negatively associated with walking in one study [37], negatively associated with disability among those with lower body limitations in another [25], and unassociated with disability in a third [40].

Proximity to particular destinations has been widely assessed as a promoter of mobility among older adults. Presence of destinations may increase mobility by providing locations for recreational walking or by providing access to needed services such as grocery stores. No associations have been found between walking and presence of recreational facilities [28, 38], gyms [38], or schools [38]. In contrast, shopping malls and overall retail destinations have been associated with walking [31, 32]. More general measures of destinations have been used, including a measure of total places of employment which was positively associated with walking [33] and two separate measures of select destinations, including places such as retail businesses and parks, neither of which was associated with walking [36, 37].

3.3. Urban Design. Front entrance characteristics that pro- mote social interactions, such as presence of a stoop and a shallow housing setback, were positively associated with physical functioning among older adults in a Hispanic neighborhood [26]. Neighborhood decay, represented by presence of graffiti or vandalism, was not associated with disability [40]. Graffiti or vandalism was associated with less walking in one study [36] but not associated in an- other [32]. Differences in results for the two walking studies cannot be attributed to size of the studies or to assess- ment of neighborhood as these were similar for both studies. However, the study finding no association evaluated walking as frequency of any neighborhood walking and the one reporting a positive association measured walking for errands only. Neither presence nor condition of sidewalks was associated with walking in several studies [31, 32, 36] but presence of safety measures for pedestrians against traffic was associated with walking [36]. Presence of parks has been positively associated with walking in two studies [33, 34], but no association was found in three others [29, 31, 38]. These inconsistencies may be a result of different localities, differences in neighborhood definitions, or differences in outcomes assessments as these all differed between those with positive findings and those with findings of no association. Michael and colleagues demonstrated a positive association between proximity to parks or paths and increases in walking over a 3–6-year period among men living in neighborhoods classified as having high socioeconomic status but not among those living in low socioeconomic status neighborhoods [28].

3.4. Composite Scores. For some study questions, a theoreti- cal framework was used to guide the development of a built environment summary score. If the items in the summary score are similarly correlated with mobility, it may provide a more robust exposure than a single measure. Urban sprawl represents density of land use with more sprawling areas often having poorer accessibility and greater reliance on

automobiles for transportation. Urban sprawl measured by census data was negatively associated with walking in cross- sectional analysis, but no association was found between movement to an area classified as more or less sprawling and change in walking behavior [27]. Neighborhood walkability scores have included land use mix, residential density, street connectivity, park and trail presence, and vehicular traffic information. Frank and colleagues demonstrated a positive association between their walkability score and walking [3], whereas Berke and colleagues found a positive asso- ciation only among women [35]. Patterson and Chapman developed a scale that combines elements of urban sprawl and walkability and found it was positively associated with walking among older adults in their study [30]. Another study reported negative street characteristics, defined as low density of intersections, few shade trees and few transit stops, were associated with greater disability [40].

4. Conclusions

The evidence provides empirical support for an association between aspects of the built environment and mobility in older adults. This paper suggests that built environment characteristics from three domains (transportation systems, land use patterns, and urban design) can impact both functional limitations and disability in positive and negative directions. However, it is still unclear if these associations represent direct influences on the disablement process. The most promising evidence points to high density of intersections, street and traffic conditions, and proximity to select destinations and green space as the most likely factors to impact mobility, though results have been incon- sistent. These inconsistencies are likely due to differences in methodology. There are many differences between studies regarding neighborhood definition, exposure measurements, and outcome assessment.

Theoretical and methodological limitations are present in much of the existing literature on this topic. A num- ber of papers lacked an explicit theoretical framework to guide determination of which neighborhood factors may impact mobility, at what spatial resolution effects should be assessed, and which individual and neighborhood level factors should be considered as confounders or mediators [19, 23, 41]. A majority of the existing literature is cross- sectional, making causal inferences impossible [19, 20, 22, 24]. It is unknown whether individuals adapt their mobility based on environmental presses and buoys or whether they choose neighborhoods with fewer environmental demands as their potential mobility decreases. However, there is some evidence that an effect of built environment on walking persists even after accounting for selection factors [42].

It is unlikely that built environment characteristics affect all neighborhood residents in the same manner [19, 24]. Assessing subpopulations among older adults may prove important as the socially disadvantaged among them— women, minorities, and those with low income—may be more vulnerable to environmental factors and have a higher propensity to live in disadvantaged neighborhoods [5, 20].

8 Journal of Aging Research

In addition, results should be replicated in different localities as the existing research has been limited in its geographic scope and it is unclear if differences may be due to unique characteristics of a locality. Greater use of nationally repre- sentative data may help to confirm results and assess effect modification by location, although these studies may suffer from less detailed measures of the built environment.

Finally, this research field would benefit from use of broader measures of enacted mobility. This paper has iden- tified walking measures as the primary measure of mobility; however, general mobility may be more important than walking, specifically. Use of assistive devices, public trans- portation, and personal automobiles allow for increased mobility and access to services such as healthcare and health- y foods [1]. General mobility assessments are available, such as the University of Alabama Birmingham Life-Space Assessment [43, 44]. Life-space is defined as the spatial area traveled by an individual in their daily life over a specified period of time. The Life-Space Assessment assesses extent of movement in the past month, how frequently that movement occurred, and whether assistance was used [43]. New technologies are also allowing objective measures of mobility through use of individual global positioning system (GPS) monitors [45]. GPS monitors do not rely on individual recall, allow assessment of individual trips into the community, and can provide information on specific location and speed of movement [45].

The current review is limited in that it addresses only objective measures of the built environment. While objective characteristics are more relevant to policy interventions [19], perceived measures capture important information about an individual’s relationship with their environment. Perceived environmental measures can more easily assess quality and access to resources within the built environment that are often not apparent from objective data (e.g., residents underreport neighborhood parks because they are not safe to use). However, perceptions bundle psychosocial and behavioral factors with objective features of the environment [46]. Studies using perceived measures face a number of methodological challenges and bias issues that complicate their interpretation [47]. Perceived and objective measures are known to capture different conceptual aspects of many environmental factors [24]. Only five articles included in this review assessed perceived as well as objective measures, though only two included comparable variables [29, 32, 34, 37, 38]. More research is needed that allows direct comparison of the two types of measures and allows eval- uation of independent and combined effects on mobility. An additional limitation was the use of broad search terms resulting in a large number of abstracts. The lack of dual review may have resulted in missed articles, but the use of reference lists as an additional review should have at least partially addressed this.

For this field to advance, research must have a strong theoretical framework, identify associations of the built envi- ronment with incident mobility restrictions, assess how changes in the built environment affect mobility, and char- acterize subpopulations among which these associations are strongest, areas that have not been adequately addressed

in previous research. In general, effect sizes of associations between built environment characteristics and functioning in older adults are small to moderate. However, a large per- centage of the population is exposed to these conditions, indicating that the potential public health impact of policy interventions could be great [48]. The advantage of popula- tion level interventions over those that target only high-risk individuals has been demonstrated [49, 50]. In general, older adults wish to age in place, remaining in their homes rather than moving to potentially more accommodating locations [51]. In order to facilitate aging in place and maintaining quality of life as people age, it is important to understand the role of the built environment on mobility limitations and disability while addressing the limitations of the current body of evidence.

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[11] L. P. Fried and J. M. Guralnik, “Disability in older adults: evi- dence regarding significance, etiology, and risk,” Journal of the American Geriatrics Society, vol. 45, no. 1, pp. 92–100, 1997.

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[18] L. D. Frank, P. O. Engelke, and T. L. Schmid, Health and Community Design: The Impact of the Built Environment on Physical Activity, Island Press, Washington, DC, USA, 2003.

[19] I. H. Yen, Y. L. Michael, and L. Perdue, “Neighborhood envi- ronment in studies of health of older adults: a systematic review,” American Journal of Preventive Medicine, vol. 37, no. 5, pp. 455–463, 2009.

[20] P. Clarke and E. R. Nieuwenhuijsen, “Environments for healthy ageing: a critical review,” Maturitas, vol. 64, no. 1, pp. 14–19, 2009.

[21] T. Sugiyama and C. W. Thompson, “Outdoor environments, activity and the well-being of older people: conceptualising environmental support,” Environment and Planning, vol. 39, no. 8, pp. 1943–1960, 2007.

[22] A. Renalds, T. H. Smith, and P. J. Hale, “A systematic review of built environment and health,” Family and Community Health, vol. 33, no. 1, pp. 68–78, 2010.

[23] S. Macintyre, A. Ellaway, and S. Cummins, “Place effects on health: how can we conceptualise, operationalise and measure them?” Social Science and Medicine, vol. 55, no. 1, pp. 125–139, 2002.

[24] I. Kawachi and L. F. Berkman, Neighborhoods and Health, Oxford University Press, New York, NY, USA, 2003.

[25] P. Clarke, J. A. Ailshire, and P. Lantz, “Urban built environ- ments and trajectories of mobility disability: findings from a national sample of community-dwelling American adults (1986–2001),” Social Science and Medicine, vol. 69, no. 6, pp. 964–970, 2009.

[26] S. C. Brown, C. A. Mason, T. Perrino et al., “Built environment and physical functioning in hispanic elders: the role of ‘eyes on the street’,” Environmental Health Perspectives, vol. 116, no. 10, pp. 1300–1307, 2008.

[27] I. M. Lee, R. Ewing, and H. D. Sesso, “The built environment and physical activity levels. The Harvard alumni health study,” American Journal of Preventive Medicine, vol. 37, no. 4, pp. 293–298, 2009.

[28] Y. L. Michael, L. A. Perdue, E. S. Orwoll, M. L. Stefanick, and L. M. Marshall, “Physical activity resources and changes in walking in a cohort of older men,” American Journal of Public Health, vol. 100, no. 4, pp. 654–660, 2010.

[29] L. F. Gomez, D. C. Parra, D. Buchner et al., “Built environment attributes and walking patterns among the elderly population in Bogota,” American Journal of Preventive Medicine, vol. 38, no. 6, pp. 592–599, 2010.

[30] P. K. Patterson and N. J. Chapman, “Urban form and older residents’ service use, walking, driving, quality of life, and neighborhood satisfaction,” American Journal of Health Pro- motion, vol. 19, no. 1, pp. 45–52, 2004.

[31] C. L. Nagel, N. E. Carlson, M. Bosworth, and Y. L. Michael, “The relation between neighborhood built environment and walking activity among older adults,” American Journal of Epidemiology, vol. 168, no. 4, pp. 461–468, 2008.

[32] Y. Michael, T. Beard, D. Choi, S. Farquhar, and N. Carlson, “Measuring the influence of built neighborhood environ- ments on walking in older adults,” Journal of Aging and Physical Activity, vol. 14, no. 3, pp. 302–312, 2006.

[33] F. Li, K. J. Fisher, R. C. Brownson, and M. Bosworth, “Multilevel modelling of built environment characteristics related to neighbourhood walking activity in older adults,” Journal of Epidemiology and Community Health, vol. 59, no. 7, pp. 558–564, 2005.

[34] K. J. Fisher, F. Li, Y. Michael, and M. Cleveland, “Neighbor- hood-level influences on physical activity among older adults: a multilevel analysis,” Journal of Aging and Physical Activity, vol. 12, no. 1, pp. 45–63, 2004.

[35] E. M. Berke, T. D. Koepsell, A. V. Moudon, R. E. Hoskins, and E. B. Larson, “Association of the built environment with phys- ical activity and obesity in older persons,” American Journal of Public Health, vol. 97, no. 3, pp. 486–492, 2007.

[36] D. King, “Neighborhood and individual factors in activity in older adults: results from the neighborhood and senior health study,” Journal of Aging and Physical Activity, vol. 16, no. 2, pp. 144–170, 2008.

[37] W. A. Satariano, S. L. Ivey, E. Kurtovich et al., “Lower-body function, neighborhoods, and walking in an older popula- tion,” American Journal of Preventive Medicine, vol. 38, no. 4, pp. 419–428, 2010.

[38] K. S. Hall and E. McAuley, “Individual, social environmental and physical environmental barriers to achieving 10 000 steps per day among older women,” Health Education Research, vol. 25, no. 3, pp. 478–488, 2010.

[39] P. Clarke and L. K. George, “The role of the built environment in the disablement process,” American Journal of Public Health, vol. 95, no. 11, pp. 1933–1939, 2005.

[40] J. R. Beard, S. Blaney, M. Cerda et al., “Neighborhood characteristics and disability in older adults,” The Journals of Gerontology. Series B, vol. 64, no. 2, pp. 252–257, 2009.

[41] G. O. Cunningham and Y. L. Michael, “Concepts guiding the study of the impact of the built environment on physical activity for older adults: a review of the literature,” American Journal of Health Promotion, vol. 18, no. 6, pp. 435–443, 2004.

[42] S. Handy, X. Y. Cao, and P. L. Mokhtarian, “Self-selection in the relationship between the built environment and walking: empirical evidence from Northern California,” Journal of the American Planning Association, vol. 72, no. 1, pp. 55–74, 2006.

[43] P. S. Baker, E. V. Bodner, and R. M. Allman, “Measuring life- space mobility in community-dwelling older adults,” Journal of the American Geriatrics Society, vol. 51, no. 11, pp. 1610– 1614, 2003.

[44] C. Peel, P. S. Baker, D. L. Roth, C. J. Brown, E. V. Bodner, and R. M. Allman, “Assessing mobility in older adults: the UAB sudy of aging life-space assessment,” Physical Therapy, vol. 85, no. 10, pp. 1008–1019, 2005.

[45] S. C. Webber and M. M. Porter, “Monitoring mobility in older adults using global positioning system (GPS) watches and accelerometers: a feasibility study,” Journal of Aging and Physical Activity, vol. 17, no. 4, pp. 455–467, 2009.

10 Journal of Aging Research

[46] A. Bowling and M. Stafford, “How do objective and subjective assessments of neighbourhood influence social and physical functioning in older age? Findings from a British survey of ageing,” Social Science and Medicine, vol. 64, no. 12, pp. 2533– 2549, 2007.

[47] S. W. Raudenbush and R. J. Sampson, “Ecometrics: toward a science of assessing ecological settings, with application to the systematic social observation of neighborhoods,” Sociological Methodology, vol. 29, no. 1, pp. 1–41, 1999.

[48] K. E. Pickett and M. Pearl, “Multilevel analyses of neighbour- hood socioeconomic context and health outcomes: a critical review,” Journal of Epidemiology and Community Health, vol. 55, no. 2, pp. 111–122, 2001.

[49] J. B. McKinlay, “The promotion of health through planned sociopolitical change: challenges for research and policy,” Social Science and Medicine, vol. 36, no. 2, pp. 109–117, 1993.

[50] G. Rose, “Sick individuals and sick populations,” International Journal of Epidemiology, vol. 14, no. 1, pp. 32–38, 1985.

[51] A. E. Scharlach, “Creating aging-friendly communities,” Gen- erations, vol. 33, no. 2, pp. 5–11, 2009.

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assignment 2/Shephard.pdf

Sports Med 2008; 38 (9): 751-758REVIEW ARTICLE 0112-1642/08/0009-0751/$48.00/0 © 2008 Adis Data Information BV. All rights reserved.

Is Active Commuting the Answer to Population Health? Roy J. Shephard

Faculty of Physical Education & Health and Department of Public Health Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada

Contents Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 751 1. Walking or Cycling? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 752 2. Historic Trends in Active Transportation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 753 3. Potential to Modify Walking and Cycling Behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 754 4. Impact of Active Commuting on Health Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 755

4.1 Theoretical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 755 4.2 Empirical Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 756

5. Areas Needing Further Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 756 6. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 756

This brief review examines whether active commuting is an effective methodAbstract of controlling the current obesity epidemic and enhancing the cardiovascular health of the population. Of the many potential methods of active commuting, walking and cycling are the usual choices. Children and adolescents prefer cycling, but for adults issues of safety, cycle storage and company dress codes make walking the preferred option, particularly in North American cities, where urban design and weather conditions often do not favour cycling. Active transpor- tation is more frequent in some European countries with dedicated cycle and pedestrian paths, but in most developed societies, active transportation has declined in recent years.

Attempts to increase walking behaviour in the sedentary population have had only limited success to date. A weekly gross energy expenditure of at least 4 MJ is recommended to reduce all-cause and cardiovascular mortality. This can be achieved by walking 1.9 km in 22 minutes twice per day, 5 days per week, or by cycling at 16 km/h for 11 minutes twice per day, 5 days per week. When engaged in level walking, the intensity of effort may be adequate for cardiovascular benefit in older adults, but in fit young workers, it is necessary to either increase the pace or choose a hilly route in order to induce cardio-respiratory benefit; in contrast, cycling is likely to provide an adequate cardiovascular stimulus even for young adults.

Empirical data to date have yielded mixed results: a reduced all-cause and cardiovascular mortality has been observed more frequently in cyclists than in walkers, and more frequently in women and older men than in young active

752 Shephard

commuters. More information is needed concerning the typical weekly dose of activity provided by active commuting, and the impact of such commuting on overall attitudes towards physical activity. It is also necessary to find better methods of involving the sedentary population, through both counselling and changes in urban design.

Expert groups, focusing primarily on the out- tation. One recent analysis estimated that in Canada, come of all-cause mortality, have concluded that the the 7.8% of Canadian workers who currently engage minimum physical activity recommendation for the in active commuting save the national economy adult population is 30 minutes of moderately vigor- some $Can2 billion per year by not using cars or ous physical activity on most days of the week.[1] public transport for this purpose.[9]

However, some groups have argued that adults need This article makes a brief assessment of active 60 or even 90 minutes per day if the current epidem- commuting as a means of maintaining and enhanc- ic of obesity is to be contained.[2-4] Minimum re- ing population health. It looks at the choice between quirements for cardiovascular health are also much walking and cycling, examines secular trends in greater in children and youths.[5,6] For those individ- both these modes of transportation, evaluates our uals who have appropriate motor skills and enjoy ability to increase the proportion of the population competition, the necessary physical activity can be who engage in active commuting, assesses the likely obtained by participating in team or individual impact of such commuting on population health, and sports. However, a few simple calculations show indicates some areas for further research. that this is not an appropriate solution for an entire national population,[7] whether one considers the 1. Walking or Cycling? demands on limited reserves of land (e.g. for soccer pitches) or the huge capital costs involved in provid- In theory, there are many forms of active trans- ing multiple facilities such as skating rinks and port, including canoes, rowing boats and skate- tennis courts. Governments have therefore shifted boards, but in reality, the choice for most people lies their emphasis to the advocacy of ‘active living’, the between walking and cycling. Their decision will be incorporation of the needed physical activity into based in part on the distance to be covered. The size normal daily life (see, for example, the Canadian of many cities is such that walking to work would be Coalition for Active Living [www.activeliving.ca] practicable only if one decided to walk one or two and the Leadership for Healthy Communities pro- subway stops, or a section of a bus route. Age is also gram of the Robert Wood Johnson Foundation [ww- a factor. Children and adolescents commonly prefer w.activelivingleadership.org/]). cycling rather than walking, but for many adults

who work in the business centre of a city, there areOne possible component of such an active living issues of traffic safety and cycle storage. Further-initiative would be to encourage physically active more, unless a company opts to provide showers andcommuting to and from the place of work or school- changing facilities, the commuting cyclist may haveing, either by bicycle or on foot. There are two difficulty in meeting office dress codes. In citiesimmediate advantages to such a suggestion: it is with continental climates, concerns also arise fromdifficult to ‘forget’ work or schooling (in contrast to the icing of streets and cycle paths during the winterthe ease of missing attendance at a scheduled exer- months.cise class), and the replacement of cars by bicycles

and pedestrians could be a big help in meeting the In the Netherlands, Denmark, Sweden, parts of reduction of carbon dioxide emissions mandated by Finland, and many less developed countries, cycling the Kyoto Accord.[8] There may be many other to work remains commonplace, but in most North economic dividends from a shift to active transpor- American cities, a major issue is the danger to the

© 2008 Adis Data Information BV. All rights reserved. Sports Med 2008; 38 (9)

Is Active Commuting the Answer to Population Health? 753

cyclist from fast-moving motor traffic. Substantial There are many advantages to adopting active transportation as a major source of daily physicalchanges in the ‘built environment’ are needed if activity. Participants have little need to purchasecycling is to become a widely accepted option;[10,11]

expensive equipment or clothing, and with a littlefor example, the provision of cycle lanes on major forethought, the walk or leisurely cycle trip to workroads, the use of traffic calming devices, the intro- can be combined with other pleasant activities, suchduction of specific traffic signals for cycles and the as conversation with a friend or colleague, or reflec-construction of dedicated cycle paths.[12-14] Compa- tion on issues that have arisen during the workingnies could also encourage cycling by allocating day. Nevertheless, there are sometimes practicalsome of the savings realized through a reduction in problems associated with active transportation thatemployer-paid car parking[15] to the construction of may need imaginative solutions; for example, thecycle storage and changing facilities for active com- occasional need to transport heavy articles, or themuters. need to combine personal commuting with the trans-

Walking is the most popular form of physical portation of children to school or childcare. From

activity cited by most North American adults.[16] the health standpoint, critical issues are historic de-

When the average patient is asked what they do for creases in walking and cycling, the extent to which

exercise, the most common response is “walking”; it weekly walking can be augmented by a public

has been argued that this offers a ‘near perfect’ form health promotional campaign, and the impact of any

of exercise.[17] In the US, encouragement of walking resulting change in behaviour upon various indices

was found to be the most effective tactic for the of population health.

promotion of physical activity in the sedentary pop- ulation.[18] Walking certainly has many attractions

2. Historic Trends in for the older worker. However, it also has disadvan-

Active Transportation tages, the main danger being from fast-moving traf- fic. Injuries from vehicles have become less fre- What proportion of the population are currently quent in recent years, although part of this decline active commuters? Much depends on the national could reflect a decrease in the number of walkers, culture. A study in Copenhagen found that about 10 rather than a true improvement in vehicle safety.[17] years ago, 20–30% of adults cycled to work, spend- In addition to collisions with motor vehicles, con- ing 3 hours per week on their bicycles; the propor- cerns include local exposure to carbon monoxide[19] tion of cyclists dropped from 28% in the least edu- and an increased inhalation of oxidant smog,[20] cated to 20% in the best educated.[24] In Denmark as although the exposure for walkers is likely to be less a whole, 46% of 25-year-old men and women used a than for cyclists because of smaller respiratory min- bicycle to travel to work every day throughout the ute volumes and less immediate contact with vehi- year, and the percentage rose to about 70% during cles. Incidents of tripping on kerbs and broken pave- the summer months.[25] In the Netherlands, 19% of ment, slipping on ice or wet leaves, and collisions workers walked and 27% cycled to work, and in with roadside furniture such as lamp standards are Sweden the corresponding figures were 39% and also not unknown.[21,22] Despite these hazards, walk- 10%.[9] However, in other developed countries, the ing to work can be commended as a very safe form percentage of adults who are presently cycling is of physical activity throughout a person’s working very small. Two decades ago, only 7% of adult career. Moreover, the intensity of such effort can Londoners cycled to work,[26] and more recently, readily be adapted to the individual’s immediate adult Canadians who had adopted active modes of physical condition by choosing an appropriate pace. transportation accounted for only 7.8% of the work- In young children, the issue of safety can be ad- ing population, 6.6% of the total being walkers and dressed by simple expedients such as an organized 1.2% cyclists.[9] Weather conditions may be an im- neighbourhood walk or cycle trip to school.[23] portant determinant of behaviour, particularly in

© 2008 Adis Data Information BV. All rights reserved. Sports Med 2008; 38 (9)

754 Shephard

central Canada, since in the more temperate climate tant studies of walking were conducted prior to that of Victoria (BC), one survey found 10.4% of walk- date. Furthermore, as in so many meta-analyses, ers and 4.8% of cyclists.[9] A recent report from after a quick scan, only 441 texts from an initial list small-town Japan showed that in those aged 65–74 of 53 491 were studied in any detail. The primary years, the energy expended on active transportation criterion for inclusion in the final analysis was self- averaged 10.8 MET-hours (metabolic equivalent reported or objective data on walking behaviour task-hours) per week (about 3 hours of moderately before and after the intervention. Ultimately, the paced walking), although the figure was lower in study was restricted to 19 randomized controlled older age groups.[27] trials and 29 non-randomized controlled trials. In the

Short walks were still quite popular among Brit- most promising studies, the immediate response to ish adults in 1992–4, with 81% making journeys the intervention was a 30- to 60-minute increase per under 1.6 km on foot. However, walking accounted week in the time allocated to walking. However, for only 24% of journeys over distances between 1.6 studies provided no information on long-term adher- and 3.2 km. Moreover, tolerance of 1.6–3.2 km ence, possible compensating reductions in other for- walks dropped from 32% of the adult population in ms of voluntary activity, or adverse consequences of 1985–6 to 24% in 1992–4.[28] A more recent report regular walking (such as injuries). Relatively few of has confirmed these disturbing trends.[29] the interventions were in the context of active com-

As cars have become widely available, and the muting, and in such studies the increases in walking perceived hazards of urban walking and cycling were generally smaller (15–30 minutes per week) have increased, most developed nations have seen a than in other types of walking programme. Investi- progressive decrease in active commuting by school gations having a commuter focus were in general children. One report from the UK estimated that targeted to those already considering such an initia- there had been a 20% decrease in the number of tive, and there was personal tailoring of the interven- children walking to school between 1970 and tion (for example, in children, safe routes were 1991.[30] A second report found a 28% reduction in mapped for active commuting to school).[35] In- the total distance walked by children in 1975–6 and creases in walking were seen when interventions 1992–4.[28] By 1993, half of British primary school were addressed to individuals, households or children were being driven distances of less than 1.6 groups, but evidence of gains from workplace, km (1 mile) to their place of schooling.[31] In the US, school or community-wide initiatives was less con- likewise, personal chauffeuring led to a 37% de- vincing. crease in children’s trips by bicycle or on foot be-

The average impact on commuters (15–30 min- tween 1977 and 1995.[32,33]

utes’ increase in walking per week) is disappointing relative to current recommendations that adults en-

3. Potential to Modify Walking and hance their cardiovascular health by taking 30–60 Cycling Behaviour minutes of moderate physical activity per day.

Moreover, it is possible the response would haveMost studies of adults have examined responses been even smaller if the intervention had been ap-to the encouragement of walking rather than cy- plied on a population-wide basis, rather thancling. One recent meta-analysis focused on the abili- targeted at interested individuals.ty of various interventions to augment walking be-

A cross-sectional study among primary schoolhaviour.[34] An exhaustive search was made of 25 children looked at active commuting in relation todatabases, 12 websites, prior systematic reviews and overall physical activity. In boys, the overall physi-the input of an international panel of experts; this cal activity was greater in those either walking oryielded a total of 53 491 papers. Despite this large cycling to school, but in girls, only walking waslist, the literature search was limited to the period

1990–2006, and unfortunately a number of impor- associated with a greater overall weekly physical

© 2008 Adis Data Information BV. All rights reserved. Sports Med 2008; 38 (9)

Is Active Commuting the Answer to Population Health? 755

activity.[36] One potential issue in this study was the speed of walking may benefit a very unfit young use of accelerometers to measure overall physical adult, and in a 65-year-old, where the maximal activity; such devices would have detected little of oxygen intake has dropped to 25 mL/[kg • min], the the energy expended in cycling. same speed of walking would demand around 50%

of aerobic power, at the bottom end of the aerobic 4. Impact of Active Commuting on training zone. In older seniors, the impact would be Health Outcomes even greater.

If the commuter is relatively fit, several simpleThe likely impact of active commuting upon health can be examined both in theoretical terms tactics can be recommended to bring the intensity of (based on the likely amount and intensity of physical walking to a level where a wide spectrum of health activity that will be achieved) and empirically (by benefits are likely to accrue. The most obvious is to looking at selected markers of health status either in increase the pace of walking; at a speed of 6.4 km/h, cross-section, or preferably, before and after the the gross oxygen cost rises to about 16.2 mL/ introduction of various walking programmes). [kg • min], with some saving of time and no de-

crease in the total energy cost over a fixed-distance 4.1 Theoretical Analysis journey. Further increments of intensity can be in-

troduced by the choice of a more hilly route. TheIn theoretical terms, the likely health impact of energy cost of climbing a 5% (1 in 20) incline isactive commuting can be estimated from the extent about 50% higher than that of walking at the sameof any increase in the commuter’s overall energy pace on the level.[39,41] Roughness of the terrain isexpenditure. A number of epidemiological studies another important variable, and after a heavy snow-on sedentary middle class US adults have demon- fall there can be a 2- to 3-fold increase in the energystrated a favourable association between a cumula- cost of a given commute.[39] The individual’s per-tive gross energy expenditure of 4 MJ per week and ception of moderate effort or the ability to continue ahealth outcomes such as overall and cardiovascular conversation provide subjective guides to an appro-mortalities.[37,38] The walking pace of a commuter is priate intensity of effort in the face of these severallikely to be around 5 km/h, although in the inner

city, the impact of such walking may be reduced by variables. prolonged halts at busy intersections. Depending on Energy expenditures are more difficult to predict an individual’s body mass, the gross energy cost of for the cyclist. Much depends on the design of the walking at 5 km/h over a smooth and level surface bicycle, the speed of riding, the terrain and any would be about 18 kJ/min.[39] Thus, a total energy head-winds that are encountered. On urban streets, a expenditure of 4 MJ per week would require no speed of 16 km/h might be anticipated, with a cost of more than a 1.9 km walk for 22 minutes in each

about 7 METs (24.5 mL/[kg • min] or approaching direction, 5 days per week. In terms of both the

36 kJ/min).[42] A cumulative energy expenditure of distance to be walked and the time taken, this seems

4 MJ per week would then be reached with a daily a reasonable expectation for a middle-aged commut-

journey of only 11 minutes in each direction. The er;[40] indeed, if a bus service is infrequent, this

intensity of effort would also reach the cardio- amount of walking may take little longer than riding

vascular training zone even for a younger worker, the bus. In terms of cardiovascular health, the inten-

and many older individuals would probably need tosity of effort is a more important issue. Even without slow their speed in order to remain within the com-enforced rests at traffic lights, the gross oxygen cost fort zone.of the commuter is some 12.5 mL/[kg • min]. In a

Theoretical considerations therefore suggest thatmoderately fit young man, this amounts to only from the viewpoint of health impact, cycling is the30–35% of maximal oxygen intake, insufficient to preferred option for younger commuters, whereasinduce any aerobic training effect. However, this

© 2008 Adis Data Information BV. All rights reserved. Sports Med 2008; 38 (9)

756 Shephard

for those who are older, the answer lies in walking only half of that in the general population,[26] and in all or part of the way to work. Shanghai, all-cause mortality was inversely correlat-

ed with cycling to work after adjustment of data for other forms of physical activity.[48] Such observa-4.2 Empirical Data tions cannot establish cause and effect; there is

Controlled studies examining the health impact always the possibility that those who choose to cycle of walking have shown little agreement, in part to work have a better initial health or a better life- because few observers have considered the critical style than the comparison group. Nevertheless, the influence of age on the relative intensity of the apparent benefits of cycling are in line with the activity. A recent meta-analysis concluded that there theoretical calculations of energy expenditures, not- were no significant differences in health outcomes ed in section 4.1 of this article. between those who were persuaded to increase their

5. Areas Needing Further Researchwalking by 30–60 minutes per week and appropriate control groups.[34] However, other investigators

Much more information is needed before we can have questioned whether the criteria of this particu-

make a categorical assessment of the impact of lar meta-analysis excluded studies where a signif-

active commuting on population health. We need a icant response had been shown.[43,44] Trials showing

more detailed picture of the typical dose of exercise benefit have generally involved older individuals

arising from such activity (the typical duration and who were walking substantial daily distances with-

intensity of bouts, and number of times performed out compensatory reductions in their other activities,

per week), together with a clearer assessment as to and who were exercising at a substantial fraction of

how far active commuting may discourage an indi- their heart rate reserve.[45-47] A recent study from

vidual from engaging in other forms of physical China found that among active commuters, all-cause

activity. In the case of young people, there is also a mortality was less strongly associated with walking

need for attitudinal studies; does active commuting than with cycling.[48] A report from Finland[40] noted

instil a love of walking or cycling that will persist that spending ≥15 minutes per day in walking or

into adulthood, or will it push adolescents into use of cycling to work was associated with reduced all-

a car once a driving licence has been obtained? How cause and cardiovascular mortality in women, but

far is the likelihood of active commuting persisting not in men. All of these observations seem in keep-

into adult life influenced by the prevailing culture ing with theoretical concerns about the relative in-

(for example, how large are differences between tensity of walking in younger and fitter individuals,

North America and some bicycle-friendly European as noted above.

countries)? More objective information is also A number of cross-sectional studies of both chil-

needed on how to persuade the general population to dren and adults have found that cardiovascular

engage in active commuting; this should involve health was substantially better in those who cycled

studies not only of counselling, but also of the built to school or to work. In Odense, Denmark, children

environment; how could simple and more complex and adolescents who cycled to school were substan-

modifications of the urban landscape encourage ac- tially more fit than those who walked or were driven

tive transportation?[10-14] to school.[49] Likewise, a prospective study of adults followed more than 30 000 men and women living 6. Conclusions in Copenhagen for an average of 14.5 years. Over this period, all-cause mortality was 40% lower in the Active commuting has the potential to generate cyclists than in other commuters, even after adjust- the 4 MJ weekly volume of physical activity com- ment of the data for reported leisure-time activi- monly associated with enhanced health. In the case ties.[12] In the UK, the incidence of myocardial in- of cycling, the intensity also appears to fall into the farction among those cycling to work was said to be cardio-respiratory training zone. The usual intensity

© 2008 Adis Data Information BV. All rights reserved. Sports Med 2008; 38 (9)

Is Active Commuting the Answer to Population Health? 757

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environmental factors correlated with walking near home:Currently, relatively few people in the developed using SPACES. Med Sci Sports Exerc 2006; 38: 708-14 world use walking as a regular means of transport, 15. Shoup D. Evaluating the effects of cashing out employer-paid

parking: eight case studies. Transport Policy 1997; 4: 201-16and there are even fewer cyclists. The challenge thus 16. Canada Fitness Survey. Fitness and lifestyle in Canada. Ottawa

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23: 306-32substantial fraction of the general population to en- 18. Hillsdon M, Thorogood M. A systematic review of physical

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