HP_Ch. 9

Structural Interventions to Reduce and Eliminate Health Disparities

Health disparities research in the

United States over the past 2

decades has yielded considerable

progress and contributed to a

developing evidence base for in-

terventions that tackle disparities

in health status and access to

care. However, health disparity

interventions have focused primarily

on individual and interpersonal

factors, which are often limited

in their ability to yield sustained

improvements.

Health disparities emerge and

persist through complex mecha-

nisms that include socioeconomic,

environmental, and system-level

factors. To accelerate the reduction

of health disparities and yield en-

during health outcomes requires

broader approaches that intervene

upon these structural determinants.

Although an increasing number of

innovative programs and policies

have been deployed to address

structural determinants, few explic-

itly focused on their impact on mi-

nority health and health disparities.

Rigorously evaluated, evidence-

based structural interventions are

needed to address multilevel struc-

tural determinants that systemically

lead to and perpetuate social and

health inequities. This article high-

lights examples of structural in-

terventions that have yielded health

benefits, discusses challenges and

opportunities for accelerating im-

provements in minority health, and

proposes recommendations to fos-

ter the development of structural

interventions likely to advance

health disparities research. (Am J

Public Health. 2019;109:S72–S78.

doi:10.2105/AJPH.2018.304844)

Arleen F. Brown, MD, PhD, Grace X. Ma, PhD, Jeanne Miranda, PhD, Eugenia Eng, MPH, DrPH, Dorothy Castille, PhD, Teresa Brockie, RN, PhD, Patricia Jones, DrPH, MPH, Collins O. Airhihenbuwa, PhD, MPH, Tilda Farhat, PhD, Lin Zhu, PhD, and Chau Trinh-Shevrin, DrPH

Reducing health disparities toimprove health outcomes is a complex challenge that extends far beyond the reach of traditional health care settings. Increasingly, the structural conditions in which people are born, live, learn, work, worship, play, and age1,2 are recognized as critical determinants of health and health disparities. Minority populations often face multiple levels of mutually rein- forcing structural disadvantage that contribute to poor health.3,4

Although many promising health interventions have targeted indi- vidual-, interpersonal-, and, to some extent, community-level factors, the evidence on how enduring these interventions are in supporting sustained improve- ments in population health and reducing health disparities is limited. Inherent in the challenge to support individual behavioral change is the dynamic interplay of risk and protective factors that cut across social and environ- mental contexts that can help individuals and their communi- ties attain the highest level of health. Take, for example, the case of obesity disparities: in- terventions that improve nutri- tion and physical activity at the individual level are unlikely to succeed when the food and social environments (e.g., unsafe and limited recreational space, ready access to low-cost, calorie-dense food options) and high rates of poverty present severe barriers to maintaining healthy diets and active lifestyles.

Despite increasing national recognition of the relationship of structural determinants to health and health disparities, the majority of health disparities interventions have focused pri- marily on behavior change at individual and interpersonal levels, which have had limited impact on sustained improve- ments in health or reductions in health disparities.5 The vision for health disparities research is to promote intervention science that addresses the structural drivers of health disparities through multi- sectoral collaborations. This arti- cle highlights examples of major national efforts focused on struc- tural determinants that have yielded reductions in health dis- parities. These examples illumi- nate common themes inherent in

successful interventions that tackle structural drivers of health and challenges to deploying structural interventions that improve mi- nority health and health equity. We conclude with recommen- dations to advance the science of health disparities research.

DEFINITION AND CONCEPTUAL FRAMEWORK

Structural interventions at- tempt to change the social, physical, economic, or political environments that may shape or constrain health behaviors and outcomes, altering the larger social context by which health disparities emerge and persist. They target factors such as

ABOUT THE AUTHORS Arleen F. Brown is with General Internal Medicine and Health Services Research, University of California Los Angeles (UCLA) and Olive View-UCLA Medical Center, Los Angeles, CA. Grace X. Ma is with Center for Asian Health, Fox Chase Cancer Center, Lewis Katz School of Medicine, Temple University, Philadelphia, PA. Jeanne Miranda is with the Department of Psychiatry and Biobehavioral Sciences, Jonathan and Karin Fielding School of Public Health, UCLA. Eugenia Eng is with the Gillings School of Global Public Health, University of North Carolina at Chapel Hill. Dorothy Castille is with the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD. Teresa Brockie is with Community Public Health Nursing, Johns Hopkins School of Nursing, Johns Hopkins Bloomberg Center for American Indian Health, Baltimore, MD. Patricia Jones is with Division of Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health. Collins O. Airhihenbuwa is with Health Policy and Behavioral Sciences, Global Research Against Noncommunicable Diseases, Georgia State School of Public Health, Atlanta, GA. Tilda Farhat is with the Office of Science Policy, Planning, Analysis, Reporting and Data; National Institute on Minority Health and Health Disparities. Lin Zhu is with the Center for Asian Health, Lewis Katz School of Medicine, Temple University. Chau Trinh-Shevrin is with the Department of Population Health, New York University School of Medicine, New York, NY. Tilda Farhat is also a Guest Editor for this supplement issue.

Correspondence should be sent to Arleen Brown, UCLA GIM and HSR, 1100 Glendon Avenue, Suite 850, Los Angeles, CA 90024 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph.org by clicking the “Reprints” link.

This article was accepted October 13, 2018. doi: 10.2105/AJPH.2018.304844

S72 Analytic Essay Peer Reviewed Brown et al. AJPH Supplement 1, 2019, Vol 109, No. S1

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economic instability, limited educational and employment opportunity, societal racism, systemic discrimination, and lack of resources, which limit neigh- borhoods’ access to healthy food, clean water, physical activity spaces, transportation, and health care. It has long been argued that to effect population-level change and reduce health disparities, multilevel structural interventions are needed.6

The National Institute on Minority Health and Health Disparities (NIMHD) Minority Health and Health Disparity Research Framework can guide structural interventions by em- phasizing multiple domains of conceptual constructs that may be relevant to the development of structural interventions such as physical and built environments, sociocultural determinants, and multiple levels of influences in addressing health disparities.7

Furthermore, the most promising interventions should involve di- verse stakeholders from multiple sectors, such as criminal justice, education, transportation, hous- ing, business, and other social services, in addition to the health care system.8 For more in- formation on designing, con- ducting, and analyzing multilevel structural interventions, see the multilevel intervention analytic essay by Agurs-Collins et al. (p. S86) in this special issue.

EVIDENCE-BASED STRUCTURAL INTERVENTIONS

A few promising interven- tions have addressed structural determinants of health disparities, intervening at the intersection of behavioral, sociocultural, physi- cal and built environment, and policy domains.9 However, there

is a dearth of evidence on effec- tive structural interventions focused explicitly on health dis- parity outcomes. This is not a systematic review article, but an analytic essay to share themes common to nationally recog- nized structural interventions that reduce health disparities, describe challenges in designing and implementing these programs, and discuss lessons learned to- ward advancing the science of making meaningful and sustain- able improvements in minority health and reductions in health disparities.

We identified common themes that provide key insights for researchers interested in ad- vancing the science of health disparities research. These ex- amples also illustrate the need for more such programs, common frameworks, and measures to fill the knowledge gap.

Context Understanding the various

contexts that influence individ- ual- and community-level risk for health disparities is central to identifying points of intervention and the mechanisms by which risk and protective factors interact and are mutually reinforcing. These contexts vary at multi- ple levels (e.g., individual, in- terpersonal, community, and societal) and domains of influ- ence (e.g., biological, physical and built environment, socio- cultural, and health care). Struc- tural interventions by definition should tackle 1 or more contexts across domains and levels of in- fluence to reinforce environ- ments and social norms that support positive behavior change. For example, reduction of obesity disparities may require interventions that tackle struc- tural drivers across sectors related to access to fresh fruits and

vegetables and safe recreational spaces among low-income school- aged children and their families in poor neighborhoods,10,11 family- based interventions that improve education, and collective efficacy to reinforce social and built en- vironments to sustain healthy lifestyles.12

The importance of integrating the geographic context in health is exemplified by the Moving to Opportunity study, a random- ized housing mobility trial that offered housing vouchers to low-income families who resided in public housing in high- poverty communities to en- courage them to move to lower-poverty neighborhoods. After 10 to 15 years of follow-up, the intervention group had improvements in physical and mental health, in- cluding reductions in rates of extreme obesity, diabetes, psy- chological distress, and major depression.13–15

Authentic Engagement Authentic community and

stakeholder engagement is criti- cal to the development, imple- mentation, and sustainability of interventions to tackle struc- tural drivers of health disparities. Community-based participatory research manages power imbal- ances, ensures transparent access to resources, and fosters shared decision-making16,17 to support genuine and lasting partnerships across sectors, researchers, com- munity members, and policy- makers. Successful structural interventions demonstrate that in populations affected by dispar- ities, community stakeholders can be active equal partners in designing and evaluating struc- tural interventions and in the advocacy and policy translation processes needed to sustain and scale these efforts.

As an example, between 2002 and 2009, the Delaware Co- lorectal Cancer Coalition galva- nized diverse policy, health care, and community stakeholders to sharply reduce or eliminate Af- rican American–Whitedisparities in colorectal cancer screening, incidence, and mortality.18 In 2 Los Angeles County, California, programs—Community Partners in Care and the Health Neigh- borhoods Initiative—the for- mation of multistakeholder coalitions to address mental health disparities resulted in a broadened definition of mental health “treatment” to include structural factors that can be in- tervened upon (e.g., homeless- ness, unemployment, safety, school dropout, incarceration) to improve mental wellness, in- crease housing stability, and re- duce hospitalizations for adults with depression.19,20

Disease-Agnostic Interventions

Structural interventions that successfully address health dis- parities and improve minority health are disease-agnostic in their approach, enabling them to tackle common risk factors that lead to multiple health disparities, thereby altering the context(s) that yield social inequalities. Among these are policies and practices that focus on changing the mechanisms and trajectory of risk factors that lead to health disparities. For example, Parent- Corps, which was designed to tackle gaps in academic achievement and mental health status among impoverished children in New York City, had a significant effect on reducing childhood obesity, anxiety, and depression in minority and low-income communities.12,21

The Earned Income Tax Credit, which aimed to increase

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individual wealth among low- income working families, had cascading effects that included higher rates of prenatal care among pregnant women, re- ductions in low birth weight rates, particularly among low- income African American mothers, and enhanced child nutrition.22–25 Thus, inter- ventions focused on education and fiscal policy resulted in long-term impact on minority health outcomes and health dis- parities reduction.

Timing and Location A crucial challenge is opti-

mizing the timing and location of structural interventions to have the largest impact on reducing disparities. The Moving to Op- portunity housing mobility ex- periment found that children from low-income and minority families who relocated to low- poverty areas had better long- term outcomes if the move occurred beforeage 13 years. Both Moving to Opportunity and the Earned Income Tax Credit dem- onstrated the profound effect of prenatal and childhood in- terventions on life course social, economic, and health trajectories. Similarly, identifying geographic risks associated with residential neighborhood factors can inform local-area capacity building and propel cross-sectoral interventions that directly or indirectly reduce health disparities and improve health outcomes.26

Unintended Consequences

The complex nature of structural interventions makes it important to examine their intended and unintended con- sequences—positive and nega- tive—on health disparities and how to measure and interpret them. This concern is particularly

important when one is evaluating how such programs and policies affect disparities. If population- wide health improvements dis- proportionately benefit the most advantaged members of society, disparities may widen among vulnerable underserved pop- ulations, as in the case of tobacco control in the United States,27–30

which has been of less benefit to some minority communities compared with the general population. Longitudinal ana- lyses of Moving to Opportunity actually uncovered potential harms for some subgroups asso- ciated with this intervention, including social stressors that many low-income and minority families face regardless of neigh- borhood, the impact of multi- generational poverty and racism, and disrupted social ties engen- dered by the move to a new neighborhood.13,31

Discordance between in- terventions and local community cultures, norms, or other entrenched structures can also contribute to unintended con- sequences.32–35 If changes pro- moted in structural interventions conflict with existing social, cultural, religious, or other structures of the local commu- nity, the intervention may be less efficacious or generate adverse effects. Structural interventions must be developed and evaluated with sensitivity and appropriate- ness to existing local sociocultural structures, should be planned and tailored in collaboration with the communities directly impacted by the intervention, and should integrate the cultural, historical, and psychological factors that influence targeted behaviors.36–39

Finally, it is critical that these programs undergo rigorous, long-term evaluations to un- derstand their intended and unintended impact on health disparities.

CHALLENGES We identified several chal-

lenges to developing and deploying structural interventions that have the potential to reduce disparities. To fill knowledge gaps, new research and policies are needed in several domains, including theoretical frame- works, measurement, study de- sign, funding, evaluation, and dissemination.

Common Framework and Research on Mechanisms

The task of identifying the distinct social-ecological factors that contribute to health risks and disparities and targeting these multiple contexts and levels of influence can be complex and pose several challenges to developing, implementing, and evaluating structural in- terventions.40 The domains and levels of influence are often dy- namic, juxtaposed, and interact with one another, resulting in synergistic intervention effects. These interacting factors com- plicate the measurement of in- dividual and collective impacts, particularly over short time- frames, and potentially hinder the ability to prioritize meaningful solutions. Standard epidemio- logic methods may not ade- quately measure the outcomes and the impact on disparities. For naturally occurring social exper- iments, such as universal pre-K in poor neighborhoods, tax credits, and food environment inter- ventions, this challenge of attri- bution remains salient despite the emerging science in this area. Better understanding of the mechanisms through which structural interventions succeed or fall short in improving mi- nority health and reducing disparities is critical to inform- ing and advancing the devel- opment, scalability, and

sustainability of these programs and policies.

Improved Measurement and Methods

Measurement and methodo- logical issues are critical to nar- rowing the evidence gap and elucidating the role of structural interventions in reducing and eliminating health disparities. The literature reviewed for this article revealed that interventions targeting social and, specifically, structural determinants represent a broad class of strategies and approaches that cut across mul- tiple sectors and domains of in- fluence. As described in the previous section, these in- terventions target a range of issues, from early childhood ed- ucation, fiscal and tax policies, housing access, and neighbor- hood environments, to structural racism. Although individual in- terventions may have positive effects, the lack of standardized definitions of structural factors and consistent criteria for classi- fying different sets of relevant interventions and the limited inclusion of process and outcome measures related to health in many of these interventions im- pede opportunities to compare and evaluate their impact on a range of health disparities.

Despite opportunities for an- alyzing and linking existing data across systems, such as electronic health records, registry data, and non–health sector data, there are limitations in utilizing these data for evaluating structural interventions. Investigators and evaluators may not have contributed to intervention de- sign, implementation, or evalua- tion; therefore, the measures needed to determine causal in- ferences are lacking or unavail- able. Consistent and valid measurement across different

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sectors is also a concern if, for example, important variables such as race or ethnicity are inadequately measured or specified.

Rigorous Study Designs There is limited capacity and

technical expertise for linking large data sets across multiple sectors to evaluate the impact of structural interventions. Related to this issue is the need for greater interoperability and harmoniza- tion across different data systems and for a common set of minority health and disparities-related data elements that can be captured across health and nonhealth sec- tors. In this era of big data, a number of challenges continue to impede the culling of disparate data sets to meaningfully analyze community-wide and system- level interventions.

Limited Funding for Structural Interventions

Tackling structural deter- minants, such as a lack of af- fordable housing, poverty, and limited educational attainment, requires substantial investment from the national to the local community level across health and nonhealth sectors. However, funding is often siloed within sectors and allocated in tightly restricted ways that limit

innovation and collaboration, even when organizations recog- nize the value of working col- lectively around shared goals and strategies.

Changing Priorities and Longer-Term Investment

Structural interventions often evolve in response to emerging policy, funding, or political priorities, and thus may be implemented in an iterative, discontinuous manner. Another challenge is the long follow-up periods required to observe and measure health outcomes, and especially to document decreases in health disparities, thus ne- cessitating prolonged, multilevel evaluations that extend far be- yond typical funding cycles. Structural interventions may require years, sometimes de- cades, of follow up before im- provements in health outcomes can be observed.14,15,18 Most research grants are between 3 and 5 years, a timeline too short to assess long-term impact on reducing health disparities. The examples of ParentCorps and the Earned Income Tax Credit il- lustrate the need in disparities research for long-term in- terventions to understand downstream effects of these structural interventions on minority health and health disparities.

Dissemination and Implementation Gaps

Although the evidence base for structural interventions to address health disparities is growing, evaluation data are still lacking on sustainability, scalability, and replicability of successful inter- ventions.41,42 Furthermore, the growth of evidence-based strate- gies has not been matched by data that inform understanding of the processes that lead to adoption and implementation in different geo- political contexts and resource environments. The costs of structural interventions pose ad- ditional challenges as communities determine which interventions may offer the best return on in- vestment in population health improvement and reduction in health disparities. There is a lack of clarity of the trade-offs for choosing one set of interventions versus another and how much those strategies cost per person in different communities.

FUTURE DIRECTIONS Structural interventions

are fundamentally rooted in un- derstanding, and often altering, the contexts through which health disparities emerge and persist. They tackle complex combina- tions of structural determinants of health, including culture, social

position, racism, environmental settings, and policies. Their com- mon features that have successfully mitigated or eliminated disparities include accounting for the social and physical contexts that produce or perpetuate disparities, authentic engagement and integration of community and other stakeholders in all phases of the research process, and taking a disease-agnostic ap- proach to promote disparities re- duction across different conditions and at multiple levels. Further- more, effective implementation and evaluation require close attention to the timing and location of the intervention and both intended and un- intended outcomes. However, significant gaps remain in our knowledge. The following sec- tions and the box on this page present recommendations for reducing these knowledge gaps and advancing the science of health disparities research.

Promote Community and Stakeholder Engagement

A key element of successful structural interventions is the critical role of community and stakeholder engagement in iden- tifying the needs of disparity populations and communities, developing shared goals, and supporting meaningful, sustain- able, and scalable interventions.

KEY RECOMMENDATIONS FOR STRUCTURAL INTERVENTIONS TO REDUCE HEALTH DISPARITIES

d Promote the science of community and stakeholder engagement in assessing structural determinants of health and designing meaningful relevant interventions to reduce health disparities.

d Strengthen scientific frameworks to evaluate long-term impact of structural interventions on health disparities.

d Develop robust methods and measures to evaluate structural intervention impact in reducing disparities.

d Support dissemination and implementation science research for structural interventions on health disparities to enhance understanding of what strategies work

across different populations, disease conditions, and geographic settings.

d Harness innovative and evidence-based approaches to addressing disparities.

d Support multilevel and multisectoral interventions that tackle structural determinants with rigorous evaluation methods and population-level data infrastructure

building to assess changes over time in reducing health disparities.

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The development, implementa- tion, evaluation, translation, and dissemination of structural in- terventions require early and continuous input by the com- munities who bear the dispro- portionate burden of disease and by the stakeholders who are in- strumental in efforts to sustain and scale successful practices. Community-engaged approaches result in the development of strategies that have direct rele- vance and practical benefits to local communities, leading to better integration of science, practice, and policy. Stakeholder engagement also informs the de- velopment of strategic partner- ships across a range of sectors (such as housing, food systems, trans- portation, criminal justice, and health care) to address domains that contribute to health dispar- ities at each level of influence.

Strengthen Scientific Frameworks

As noted earlier, few in- terventions aimed at structural determinants are guided by sci- entific frameworks. The effec- tiveness of these real-world efforts may be influenced by intersecting political, legal, eco- nomic, cultural, and biomedical factors that should be considered and accounted for in their design and evaluation. A critical step in addressing the inherent com- plexity of structural interventions is developing and adopting a scientifically credible conceptual framework or theory of change that incorporates these diverse factors and the roles they are anticipated to play in health disparities.

Develop Robust Methods and Measures

Robust evaluation designs and measures—derived from a broad range of disciplines and capable of

harnessing big data across sectors —are needed to address the ev- idence gap in our understanding of the impact and reproducibility of structural interventions de- veloped to reduce health dis- parities. Big data science is rapidly evolving and should engage health disparities researchers who have expertise in social and structural determinants of health. Addressing measurement and data collection challenges re- quires broad-based strategies, among them, mixed-method evaluation, stakeholder in- volvement in designing the intervention and evaluation, multisector agreement on common nomenclature and measurement, standardized measurement systems, effective methods to harmonize disparate data, and novel modeling strategies43

Some structural interventions may not be suited to traditional research designs because of cost and time constraints, ethical considerations, an inability to randomize sites or individuals, or the continually evolving nature of the intervention. Robust and validated approaches, such as stepped-wedge or staggered in- terventions, interrupted time-series, quasi-experimental designs, and cluster or group-randomized trials can facilitate rigorous eval- uation at the individual, in- terpersonal, community, and societal levels.44

Construct and Analyze Connected Data Sets

Optimally, studies should be prospective and should include data from multiple sectors that allow examination of the impact of structural interventions on population health and health disparities. Historical data from various sectors may provide important insights into the

development and evaluation of long-term impact of structural interventions by identifying si- multaneous changes in social and health indicators over time that are associated with health dis- parities. Predictive analytics and other robust methods can inform decision-making on the nature and scope of various structural interventions and strategies to optimize health impact and dis- parities reduction.

Support Research Understanding how structural

interventions that were success- fully developed in one commu- nity might be adapted, scaled up, and transferred to another setting is of critical importance. Prom- ising and evidence-based struc- tural interventions do not easily translate into improved health and reduced health disparities because it takes time, resources, and multidisciplinary teams to improve the relevance, uptake, and implementation of evidence-based interventions in real-world settings. Dissemina- tion and implementation re- search training has great potential to improve the reach and impact of structural interventions on minority health and health disparities.

Harness Innovation Advances in several disciplines

are rapidly changing the ability to design, implement, and evaluate structural interventions. Tech- nological advances, including big data science, can be mobilized to explain and address dispar- ities. Many health system in- terventions have made innovative use of electronic health records as tools to char- acterize social and structural characteristics of populations, identify targets for intervening, and deploy interventions.

Geographic information system platforms can link individuals to social and structural risks and resources. Similarly, advances in fields such as personalized med- icine, personalized public and population health, systems sci- ence, and computational biology may result in powerful predictive tools to identify those at highest risk for disparities and link them to appropriate structural interventions.

Fund Cross-Sector Interventions

To conduct well-designed structural interventions and ro- bust evaluations, resources are needed to promote interactions among stakeholders from dispa- rate sectors to plan and develop large-scale meaningful structural interventions that can effectively reduce health disparities in pop- ulations and communities. Trans–federal agency collabora- tions and public–private part- nerships may be promising approaches to intervening on health disparities. Standardizing approaches for motivating mul- tistakeholder collaborations is a critical need in disparities re- search. Future efforts should fo- cus on building partnerships among sectors in the earliest phases of intervention design by providing resources to support multisector partners. These early partnerships can plan effectively by using a collective impact framework and group facilitation to support consensus building that effectively translates evi- dence into practice. In addition, these collaborations should have an explicit emphasis on inform- ing the collection of shared metrics and facilitating opportu- nities to support interoperable data systems to access large classes of epidemiological, environ- mental, social, and biological data

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to determine the impact on ad- vancing health equity and im- proving population health.45

Develop Decision-Making Tools

Many local communities recognize the role of structural determinants on health and social outcomes but face the challenge of identifying the interventions most likely to influence their populations’ social and health outcomes. An emerging solution is the collation of evidence-based interventions in registries and reports, among them the Na- tional Registry of Evidence- Based Programs and Practices, the What Works Clearinghouse, and the Community Guide, along with an increasing number of databases that aim to help local communities examine health and social indicators at the state, county, and local level, such as the 500 Cities: New Data for Better Health and County Rankings Projects and The Op- portunity Atlas. NIMHD is currently developing an In- tervention Portal to serve as a repository for interventions that have successfully improved mi- nority health or reduced health disparities. This portal is part of HDPulse (https://hdpulse. nimhd.nih.gov), an ecosystem that provides access to data and resources to design, implement, and evaluate evidence-based in- terventions to improve minority health and reduce health dispar- ities. There is potential to harness expertise in predictive modeling and analytics to help local com- munities and states determine which structural interventions may yield the most meaningful reductions in health disparities.

Systems science—in particu- lar, agent-based modeling—may aid in evaluating the influence of structural factors on health

behaviors, outcomes, and costs, both independently and as they interact with other factors within the social-ecological frame- work.46 When paired with community-based data tailored to local settings, simulation modeling may facilitate prioriti- zation of programs and in- terventions in communities, particularly resource-constrained environments.47

CONCLUSIONS Health and health disparities

are the result of more than individual, interpersonal, or biological factors. Social, eco- nomic, environmental, and pol- icy drivers also determine the health status of individuals and populations. Structural de- terminants play a vital role in health outcomes and the ability to seek preventive and treatment services or support for quality of care. Structural interventions should seek to change the social and environmental contexts that yield and perpetuate social and health inequalities. They can advance health equity by changing the conditions in which people live, work, learn, and play, and the community norms that influence and derive from these conditions. To tackle health disadvantage and gradients in populations, researchers must build the scientific base for multisector stakeholder engage- ment; extend beyond individual outcomes to community and system-level outcomes; expand methods for implementing, evaluating, and disseminating multilayered, multifaceted in- terventions; support the data science and infrastructure for more robust evaluations of social and health indicators; and prior- itize funding for well-designed

structural interventions and rig- orous evaluations.

CONTRIBUTORS All authors have participated in the con- ceptualization, writing, and editing of the submitted article and have given their final approval.

ACKNOWLEDGMENTS This work was supported in part by the following institutes of the National In- stitutesofHealth(NIH):NationalInstitute on Minority Health and Health Disparities (NIMHD) and National Center for Ad- vancing Translational Science (NCATS). A. F. Brown was supported by National Institute of Neurologic Disorders and Stroke under award U54NS081764 and NCATS award UL1TR001881. G. X. Ma was supported by National Cancer Institute award U54 CA153513 and Centers for Disease Control and Pre- vention (CDC) award U58DP005828. C. Trinh-Shevrin was supported by NIMHD award U54 MD000538 and CDC award U48 DP005008.

The authorswishto acknowledge Rina Das, PhD, program director of the Divi- sion of Extramural Scientific Programs at NIMHD, for her significant contributions to the conceptualization, development, and editorial comments on the article.

Note. This trans-NIH work resulted from an NIMHD-led workshop, in- cluding external experts, to address In- tervention Science for Health Disparities Research. The final content of the analytic essay is the responsibility of authors and does not necessarily represent the per- spective of the US government.

CONFLICTS OF INTEREST Theauthorsdeclarenoconflictsofinterest.

HUMAN PARTICIPANT PROTECTION Human participant protection was not required because this work did not involve human participants.

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