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Three Interventions That Reduce Childhood Obesity Are Projected To Save More Than They Cost To Implement Gortmaker, Steven L; Wang, Y Claire; Long, Michael W; Giles, Catherine M; Ward, Zachary J; Barrett,
Jessica L; Kenney, Erica L; Sonneville, Kendrin R; Afzal, Amna Sadaf; Resch, Stephen C; Cradock, Angie L
. Health Affairs ; Chevy Chase Vol. 34, Iss. 11, (Nov 2015): 1932-65A.
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ABSTRACT (ENGLISH) Policy makers seeking to reduce childhood obesity must prioritize investment in treatment and primary prevention.
We estimated the cost-effectiveness of seven interventions high on the obesity policy agenda: a sugar-sweetened
beverage excise tax; elimination of the tax subsidy for advertising unhealthy food to children; restaurant menu
calorie labeling; nutrition standards for school meals; nutrition standards for all other food and beverages sold in
schools; improved early care and education; and increased access to adolescent bariatric surgery. We used
systematic reviews and a microsimulation model of national implementation of the interventions over the period
2015-25 to estimate their impact on obesity prevalence and their cost-effectiveness for reducing the body mass
index of individuals. In our model, three of the seven interventions-excise tax, elimination of the tax deduction, and
nutrition standards for food and beverages sold in schools outside of meals-saved more in health care costs than
they cost to implement. Each of the three interventions prevented 129,000-576,000 cases of childhood obesity in
2025. Adolescent bariatric surgery had a negligible impact on obesity prevalence. Our results highlight the
importance of primary prevention for policy makers aiming to reduce childhood obesity. FULL TEXT
ABSTRACT Policy makers seeking to reduce childhood obesity must prioritize investment in treatment and primary
prevention. We estimated the cost-effectiveness of seven interventions high on the obesity policy agenda: a sugar-
sweetened beverage excise tax; elimination of the tax subsidy for advertising unhealthy food to children;
restaurant menu calorie labeling; nutrition standards for school meals; nutrition standards for all other food and
beverages sold in schools; improved early care and education; and increased access to adolescent bariatric
surgery. We used systematic reviews and a microsimulation model of national implementation of the interventions
over the period 2015-25 to estimate their impact on obesity prevalence and their cost-effectiveness for reducing
the body mass index of individuals. In our model, three of the seven interventions-excise tax, elimination of the tax
deduction, and nutrition standards for food and beverages sold in schools outside of meals-saved more in health
care costs than they cost to implement. Each of the three interventions prevented 129,000-576,000 cases of
childhood obesity in 2025. Adolescent bariatric surgery had a negligible impact on obesity prevalence. Our results
highlight the importance of primary prevention for policy makers aiming to reduce childhood obesity.
The childhood obesity epidemic in the United States affects all segments of society. There is a clear need for
action by governments, foundations, and other relevant institutions to address this public health problem.
Controlling childhood obesity is complex because many risk behaviors are involved, shaped by multiple
environments and requiring multiple intervention strategies.1-4 However, simply asking what works without
considering costs has led to the proliferation of obesity treatment and prevention initiatives with limited evaluative
information. Little serious discussion has taken place about relative costs or cost-effectiveness. When we
searched the PubMed database of the National Library of Medicine for articles published through 2014 containing
the term child obesity, we found more than 31,000, but only 89 of these also contained the term cost-effectiveness.
Communities and health agencies have limited resources to address high rates of childhood obesity and need to
know how best to invest those resources.
There are two main approaches to altering the population prevalence of obesity in children: treating obesity after
onset and preventing excess weight gain (primary prevention). Many studies have documented the effectiveness
of interventions using these two different ap- proaches. For example, a meta-analysis of ado-lescent bariatric
surgery studies indicates an average reduction in body mass index (BMI) of 13.5 kg/m2 following this procedure.5
Some nonsurgical interventions to treat childhood obesity are effective, but effect sizes are small relative to the
high BMIs (or BMI z-scores-that is, BMI scores that are standardized for age and sex) of the children before the
intervention,6 and treatments may reach too few children to have a substantial population-level impact. For
example, bariatric surgery is used with only about 1,000 adolescents per year.7
The promise of primary prevention strategies during childhood has been bolstered by recent findings generated by
mathematical models of the physiological development of excess weight in children, adolescents, and adults.8,9
Modeling indicates that excess weight accumulates slowly, and excess weight gain among young children is dueto
relatively small changes in energy balance.
For example, among children ages 2-5, average excess weight gain is driven by an excess of about 33 extra
kilocalories per day.10 Changes needed to prevent excess weight gain and prevent obesity are thus quite small in
childhood. By adolescence, however, excess weight has accumulated for more than a decade, with an average
imbalance of almost 200 extra kcal/day.8,10 The typical adult with a BMI greater than 35 (about 14 percent of the
adult population) consumes 500 kcal/day more than is needed to maintain a healthy body weight.9 Improving
energy balance via improved diet and physical activity early in childhood thus requires much smaller changes than
those needed once obesity is established in adolescence and adulthood.
In addition, a large body of experimental evidence indicates that certain behavioral changes can reduce BMI and
obesity prevalence in children. For example, as documented in online Appendix A1,11 there is clear evidence of the
effectiveness of reducing the intake of sugarsweetened beverages on reducing BMI and obesity prevalence.
There is also strong evidence that reducing television viewing and other screen time leads to significant reductions
in BMI and obesity prevalence, mainly via dietary changes12 (also documented in Appendix A2).11 Despite
growing evidence that targeted interventions can improve diet and reduce BMI and obesity prevalence, there is
limited evidence concerning the cost-effectiveness of these approaches and the potential US population-level
impact of either treatment or preventive interventions.
In this article we present results of an evidence review and microsimulation modeling project concerning the cost-
effectiveness and population-level impact of seven interventions identified as potentially important strategies for
addressing childhood obesity. We conducted systematic evidence reviews of the interventions' effectiveness and
estimated costs and reach under specified implementation scenarios described in Appendices A1, A2, and A4-
A8.11 We developed a microsimulationmodel to assess key cost-effectiveness metrics of these interventions if
they were to be implemented nationally.
Study Data And Methods
We developed an evidence review process and microsimulation model to evaluate the costeffectiveness of
interventions for childhood obesity. Our modeling framework built on the Australian Assessing Cost-Effectiveness
approach13,14 in obesity15 and prevention studies.16 Our microsimulation model used US population, mortality,
and health care cost data. We focusedonoutcomes ofcostperBMIunitchange over two years following an
intervention and tenyear changes in obesity, health care costs, and net costs. We followed recommendations of
the US Panel on Cost-Effectiveness in Health and Medicine in reporting our results, including using a 3 percent
Our approach has distinct methodological components designed to improve both the strength of evidence and the
applicability of results to real-world decision making.We created a stakeholder group of thirty-two US policy
makers, researchers, and nutrition and physical activity experts to provide advice concerning the selection of
interventions, evaluation of data, analyses, and implementation and equity issues. This group advised us to look
broadly for interventions to evaluate across settings and sectors. The clinical subgroup selected adolescent
bariatric surgery as an important benchmark clinical intervention to evaluate, since many insurers pay for this
Interventions Our stakeholder group selected for the study seveninterventions that are high on the treatment and
prevention policy agenda (further details about the interventions are provided in the Appendices).11 The
interventions are as follows: an excise tax of one cent per ounce on sugar-sweetened beverages, applied nationally
and administered at the state level; the elimination of the tax deductibility of advertising costs for television ads
seen by children and adolescents for nutritionally poor foods and beverages; restaurant menu calorie labeling,
modeled on the federal menu regulations to be implemented under the Affordable Care Act; implementation of
nutrition standards for federally reimbursable school meals sold through the National School Lunch and School
Breakfast Programs, modeled on US Department of Agriculture (USDA) regulations implemented under the
Healthy, Hunger-Free Kids Act of 2010; implementation of nutrition standards for all foods and beverages sold in
schools outside of reimbursable school meals, modeled on USDA regulations implemented under the Healthy,
Hunger-Free Kids Act; improved early childhood educationpolicies and practices, including the national
dissemination of the Nutrition and Physical Activity SelfAssessment for Child Care (NAP SACC) program; and a
nationwide fourfold increase in the use of adolescent bariatric surgery.
Intervention Specifications, Implementation Scenarios, And Costs We specified a national implementation
scenario for each of the interventions using the best available data for population eligibility and costs at each level
of implementation, from recruitment to outcomes. Costing followed standard guidelines19,20 (for details of
models and costing, see Appendix A3).11 All costs were calculated in 2014 dollars and adjusted for inflation using
the Consumer Price Index for all nonmedical costs and the Medical Care Consumer Price Index for medical costs.
Evidence Reviews Of Intervention Effects We estimated the effects of each of the seven interventions using an
evidence review process consistent with the Grading of Recommendations Assessment, Development, and
Evaluation (GRADE) approach21 and guidelines from the Cochrane Collaboration.22 Details of the evidence
reviews for the interventions are provided in Appendices A1, A2, and A4-A8.11
Microsimulation Model We developed a microsimulation model to calculate the costs and effectiveness of the
interventions through their impact on BMI changes, obesity prevalence, and obesity-related health care costs over
ten years (2015-25). This is a stochastic, discrete-time, individual-level microsimulation model of the US population
designed to simulate the experience of the population from 2015 to 2025.
The model used data from the Census Bureau, American Community Survey, Behavioral Risk Factor Surveillance
System, National Health and Nutrition Examination Surveys (NHANES), and National Survey of Children's Health. It
also used longitudinal data about weight and height from the National Longitudinal Survey of Youth, National
Longitudinal Study of Adolescent to Adult Health, Early Childhood Longitudinal Study-Kindergarten, Panel Survey
of Income Dynamics, and NHANES I Epidemiologic Followup Study.
We used smoking initiation and cessation rates from the National Health Interview Surveys and mortality rates by
smoking status and BMI from the NIH-AARP Diet and Health Study. Details of the data, analyses, and model are
provided in Appendix A3, and key model input parameters are listed in Appendix Exhibit A3.1.11
The estimated effects of the interventions on health care costs werebased on national analyses that
indicatedexcess health carecostsassociated with obesity among children and adults (see Appendix A3).11 We
assumed that each intervention took time-typically 18-36 months-to decrease the BMI of individuals who received
each intervention.8,9 Estimates of intervention costs included one-time start-up and ongoing costs, as well as
enforcement and compliance costs, but did not include costs of passing a policy. The annual costs for each
intervention are the average of its discounted total costs.
We used a "modified" societal perspective on costs. This means that we did not include several possible economic
impacts of the interventions, such as productivity losses associated with obesity or patient costs for items such
as transportation to clinic visits or the value of time spent seeking or receiving medical care. It was reasonable to
exclude these economic impacts because they are difficult to estimate systematically and likely to be small within
a ten-year period, relative to the intervention and health care costs.
We assumed that effects were sustained over the model's time frame-that is, eight years after two start-
upyears.For policy changes such asthe sugar-sweetened beverage excise tax, the elimination of the tax subsidy for
advertising unhealthy food to children, and restaurant menu calorie labeling, sustaining an effect for ten years is
reasonable, as the changed policy will continueoverthatperiod.For theinterventions that set nutrition standards for
school meals and other foods and beverages sold in schools, we can assume that most children will be exposed to
these for a substantial period of time-for example, from first through twelfth grades. For bariatric surgery, we can
also assume that the surgical change will persist over this time period.
Details of key input parameters for the interventions modeled where there is known variation from reviews of the
relevant literature, including the parameters' distributions and assumptions, are outlined in Appendices A1, A2, and
A4-A8.11 As explained above, all results are expressed in 2014 US dollars and discounted at 3 percent annually.
We calculated costs per BMI units reduced over two years (2015-17). We estimated health care costs, net costs,
and net costs saved per dollar spent over ten years (2015-25), since this is a time frame frequently used in policy
calculations.Weinflatedhealth carecoststo2014 dollars using the Medical Care Consumer Price Index. We
estimated obesity cases prevented and changes in childhood obesity prevalence in 2025, at the end of the period
Uncertainty And Sensitivity Analyses We calculated probabilistic sensitivity analyses by simultaneously sampling
all parameter values from predetermined distributions. We report 95 percent uncertainty intervals (around point
estimates) in Exhibits 1 and 2, taking 2.5 and 97.5 percentile values from simulated data.23 We calculated
uncertainty intervals using Monte Carlo simulations programmed in Java over one thousand iterations of the
model for a population of one million simulated individuals scaled to the national population size.
Consultation The stakeholder group assisted us in reviewing additional considerations, including quality of
evidence, equity, acceptability, feasibility, sustainability, side effects, and impacts on social and policy norms.
Limitations The study had several limitations. First, its results were based on a simulation model that incorporated
a broad range of data inputs. While we included the best available evidence on population characteristics, likely
trajectories of obesity prevalence, and obesity-related health care costs, our ability to forecast precise impacts of
all of the modeled interventionswas limited by the uncertainty around each of these inputs and by the
assumptions required to build the model (see Appendix A3).11
In previous publications we used a Markov cohort simulation model to estimate the impact of two of the
interventions modeled here, the sugar-sweetened beverage excise tax and the elimination of the tax subsidy for
advertising unhealthy food to children.24-26 The cohort model was limited in its ability to model heterogeneity of
individual differences, exposure to the intervention, and trajectories of BMI over the life course, and it could not
calculate population estimates for specific years. With the microsimulation model, we were able to estimate the
number of cases of obesity prevented. For both of these interventions, the estimated costs per BMI unit reduction
were similar under both modeling approaches, and both interventions were cost-saving.
Second, we modeled each of the interventions separately, which limited our ability to estimate their cumulative
effects. Future obesity prevention simulation modeling should begin to evaluate the impact of simultaneous
implementation of multiple interventions.
Third, there is limited evidence that directly links the interventions we evaluated to change in population-level
obesity prevalence. However, as detailed in Appendices A1, A2, and A4-A8,11 six of the interventions were
supported by randomized trials or natural or quasi-experimental evaluations27 that linked the intervention or
behavioral mechanism targeted by the intervention directly to reductions in BMI for recipients of each intervention.
We incorporated uncertainty for all of the underlying model inputs into the probabilistic uncertainty analyses (see
Fourth, because we focused on obesity, we did not incorporate additional health improvements and health care
cost reductions due to improvements in diet and physical activity that were independent of reductions in BMI (for
example, reductions in diabetes and heart disease).28
There were large differences in the projected populationreach of the interventions(Exhibit 1). The reach of bariatric
surgery, the smallest, was very limited, even assuming a fourfold increase in the number of adolescents who
receive the procedure. The most recent national data indicate that in 2012, among adolescents classified as
having grade 3 obesity (a BMI of roughly 40 or above), fewer than two in a thousand received the procedure
(Appendix A8).11 The largest population reaches occurred with interventions that would affect the whole
population, such as the sugar-sweetened beverage excise tax and restaurant menu calorie labeling-both of which
would reach 307 million people.
The annual costs of the interventions were driven by both the cost per person and the population reach and varied
greatly (Exhibit 1).
Differences across interventions in cost per BMI unit reduction varied more than 2,000-fold. Eliminating the tax
deduction for advertising nutritionally poor food to children would reduce a BMI unit for $0.66 per person, while
increasing access to bariatric surgery would reduce a BMI unit for $1,611.
Three of the interventions studied were found to be cost-saving across the range of modeled uncertainty: the
sugar-sweetened beverage excise tax, eliminating the tax subsidy for advertising unhealthy food to children, and
setting nutrition standards for food and beverages sold in schools outside of school meals (Exhibit 2). In other
words, these interventions were projected to save more in reduced health costs over the period studied than the
interventions would cost to implement. Perhaps more important, the interventions were projected to prevent
576,000, 129,100, and 345,000 cases of childhood obesity, respectively, in 2025. The net savings to society foreach
dollarspentwereprojectedtobe$30.78, $32.53, and $4.56, respectively.
Restaurant menu calorie labeling was also projected to be cost-saving (Exhibit 2), although on average the
uncertainty intervals were wide because of the wideuncertaintyintervalaround the estimated per meal reduction in
calories ordered or purchased as a result of the intervention (see Appendix A4).11 This uncertainty highlights the
need for ongoing monitoring of this policy when it is implemented nationwide in 2016. Of note, a study of
restaurant menu calorie labeling in King County, Washington, found that eighteen months after implementation of
menu calorie labeling regulations, restaurants had reduced their calorie content by 41 kilocalories per entrée,29 a
much larger effect than the reduction of 8 kilocalories per meal estimated in this study.
Setting nutrition standards for school meals would reach a very large population of children and have a substantial
impact: An estimated 1,816,000 cases of childhood obesity would be prevented, at a cost of $53 per BMI unit
change (Exhibits 1 and 2). Improved early care and educationpolicies and practices would reach a much smaller
segment of the population (1.18 million), preventing 38,400 childhood obesity cases if implemented nationally, at a
cost of $613 per BMI unit change.
The modeled preventive interventions could significantly reduce the overall prevalence of childhood obesity in the
United States. Currently, the prevalence of obesity among children and youth is about 17 percent.30 Based on our
model, the largest reduction in childhood obesity prevalence compared to no intervention would occur with the
implementation of nutrition standards for school meals (a reduction of 2.6 percent; data not shown), followed by
the sugar-sweetened beverage excise tax (0.8 percent). Adding in the two other cost-saving interventions
(elimination of the tax subsidy for advertising unhealthy food to children and setting nutrition standards for other
foods and beverages sold in schools) would reduce prevalence by an additional 0.7 percent.
These interventions would have a modest impact on obesity prevalence. Even if all were implemented and the
effects were additive, the overall impact would be a reduction of 4.1 percent, or 2.9 million cases of childhood
obesity prevented for the population in 2025.
Tax Revenue In addition to their effects on obesity, we estimated that both the sugar-sweetened beverage excise
tax and the elimination of the tax subsidy for advertising unhealthy food to children would lead to substantial
yearly tax revenues ($12.5 billion and $80 million, respectively). These revenues were not included in our
calculations of net costs.
These results indicate that primary prevention of childhood obesity should be the remedy of choice. Four of the
interventions studied here have the potential for cost savings-that is, the interventions would cost less to
implement than they would save over the next ten years in health care costs-and would result in substantial
numbers of childhood obesity cases prevented.
The sugar-sweetened beverage excise tax- and, to a lesser extent, removing the tax deduction for advertising
unhealthy food to children- would also generate substantial revenue that could be used to fund other obesity
prevention interventions. The excise tax has been the focus of recent policy discussion,25,31 and the recent
enactment of an excise tax of one cent per ounce in Berkeley, California, and the national implementation of an
excise tax in Mexico indicate the growing political feasibility of this approach.
The improvements in meal standards in the National School Lunch and School Breakfast Programs as well as
implementation of the first meaningful national standards for all other foods and beverages sold in schools make
the Healthy, Hunger-Free Kids Act one of the most important national obesity prevention policy achievements in
recent decades. Although improving nutrition standards for school meals was not intended primarily as an obesity
reduction strategy, we estimated that this intervention-which includes improving the quality of school meals and
setting limits on portion sizes-would have the largest impact on reducing childhood obesity of any of the
interventions evaluated in this study.
The individual benefits of bariatric surgery and other intensive clinical interventions to treat obesity can be life
changing.32 Another promising new obesity treatment strategy employs lowcost technological approaches-
computerized clinical decision support-to effectively reduce excess childhood weight.33 Our study should in no
way discourage ongoing investment in advancing the quality, reach, and cost-effectiveness of clinical obesity
treatment. However, our results indicate that with current clinical practice, the United States will not be able to
treat its way out of the obesity epidemic. Instead, policy makers will need to expand investment in primary
prevention, focusing on interventions with broad population reach, proven individual effectiveness, and low cost of
We modeled each intervention in this study separately to help policy makers prioritize investment in obesity
prevention. However, as the results show, none of the interventions by itself would be sufficient to reverse the
obesity epidemic. Instead, policy makers need todevelop a multifaceted prevention strategy that spans settings
and reaches individuals across the life course.
Because the energy gap that drives excess weight gain among young children is small, and adult obesity is difficult
to reverse, interventions early in the life course have the best chance of having a meaningful impact on long-term
obesity prevalence and related mortality and health care costs. However, early intervention will not
besufficientifyoungchildrenat ahealthyweight are subsequently introduced into environments that promote excess
weight gain later in childhood and in adulthood.
Increased access to adolescent bariatric surgery had the smallest reach and the highest cost per BMI unit
reduction. Of the other six interventions that we analyzed, improving early care and education using the NAP SACC
model both had the smallest reach, because of the intervention's relatively small age range and voluntary
implementation strategy, and was the most costly per BMI unit reduction. Nonetheless, this intervention might still
be a good investment, considering that even small changes among very young children can be important for
setting a healthier weight trajectory in childhood.
Additionally, the intervention focuses on improvements in nutrition, physical activity, and screen time for all
children and thus could have benefits for child development beyond reducing unhealthy weight gain. In contrast to
the tax policies we evaluated, which have been met with opposition from industry, the NAP SACC program is well
liked and has been widely adopted.
While policy makers should consider the longterm effectiveness of interventions that target young children,
substantially reducing health care expenditures due to obesity in the near term will require implementation of
strategies that target both children and adults. We estimated that over the decade 2015-25, the beverage excise
tax would save $14.2 billion in net costs, primarily due to reductions in adult health care costs. Interventions that
can achieve nearterm health cost savings among adults and reduce childhood obesity offer policy makers an
opportunity to make long-term investments in children's health while generating short-term returns. These results
are consistent with previous research that estimated the potential health cost savings and health gains from
reducing childhood obesity, much of which resulted from preventing obesity during adulthood.34
Reversing the tide of the childhood obesity epidemic will require sustained effort across all levels of government
and civil society for the foreseeable future. To make these efforts effective and sustainable during a period of
constrained public health resources, policy makers need to integrate the best available evidence on the potential
effectiveness, reach, and cost of proposed obesity strategies to prioritize the highest-value interventions.
We found that a number of preventive interventions would have substantial population-level impacts and would be
cost-saving. An important question for policy makers is, why are they not actively pursuing cost-effective policies
that can prevent childhood obesity and that cost less to implement than they would save for society?
Our results also highlight the critical impact that existing investments in improvements to the school food
environment would have on future obesity prevalence and indicate the importance of sustaining these preventive
strategies. Furthermore, while many of the preventive interventions inchildhood do not providesubstantial health
care cost savings (because most obesity-related health care costs occur …