HOW STRUCTURAL INEQUITIES, SOCIAL DETERMINANTS OF HEALTH, AND HEALTH EQUITY CONNECT

Health inequities are systematic differences in the opportunities groups have to achieve optimal health, leading to unfair and avoidable differences in health outcomes (Braveman, 2006; WHO, 2011). The dimensions of social identity and location that organize or “structure” differential access to opportunities for health include race and ethnicity, gender, employment and socioeconomic status, disability and immigration status, geography, and more. Structural inequities are the personal, interpersonal, institutional, and systemic drivers—such as, racism, sexism, classism, able-ism, xenophobia, and homophobia—that make those identities salient to the fair distribution of health opportunities and outcomes. Policies that foster inequities at all levels (from organization to community to county, state, and nation) are critical drivers of structural inequities. The social, environmental, economic, and cultural determinants of health are the terrain on which structural inequities produce health inequities. These multiple determinants are the conditions in which people live, including access to good food, water, and housing; the quality of schools, workplaces, and neighborhoods; and the composition of social networks and nature of social relations.

So, for example, the effect of interpersonal, institutional, and systemic biases in policies and practices (structural inequities) is the “sorting” of people into resource-rich or resource-poor neighborhoods and K–12 schools (education itself being a key determinant of health (Woolf et al., 2007) largely on the basis of race and socioeconomic status. Because the quality of neighborhoods and schools significantly shapes the life trajectory and the health of the adults and children, race- and class-differentiated access to clean, safe, resource-rich neighborhoods and schools is an important factor in producing health inequity. Such structural inequities give rise to large and preventable differences in health metrics such as life expectancy, with research indicating that one's zip code is more important to health than one's genetic code (RWJF, 2009).

The impact of structural inequities follows individuals “from womb to tomb.” For example, African American women are more likely to give birth to low-birthweight infants, and their newborns experience higher infant death rates that are not associated with any biological differences, even after accounting for socioeconomic factors (Braveman, 2008; Hamilton et al., 2016; Mathews et al., 2015). Although the science is still evolving, it is hypothesized that the chronic stress associated with being treated differently by society is responsible for these persistent differential birth outcomes (Christian, 2012; El-Sayed et al., 2015; Strutz et al., 2014; Witt et al., 2015). In elementary school there are persistent differences across racial and ethnic divisions in rates of discipline and levels of reading attainment, rates that are not associated with any differences in intelligence metrics (Howard, 2010; Losen et al., 2015; Reardon et al., 2012; Skiba et al., 2011; Smith and Harper, 2015). There also are race and class differences in adverse childhood experiences and chronic stress and trauma, which are known to affect learning ability and school performance, as well as structural inequities in environmental exposures, such as lead, which ultimately can lead to differences in intelligence quotient (IQ) (Aizer et al., 2015; Bethell et al., 2014; Jimenez et al., 2016; Levy et al., 2016). One of the strongest predictors of life expectancy is high school graduation, which varies dramatically along class and race and ethnicity divisions, as do the rates of college and vocational school participation—all of which shape employment, income, and individual and intergenerational wealth (Olshansky et al., 2012). Structural inequities affect hiring policies, with both implicit and explicit biases creating differential opportunities along racial, gender, and physical ability divisions. Lending policies continue to create differences in home ownership, small business development, and other asset development (Pager and Shepherd, 2008). Structural inequities create differences in the ability to participate and have a voice in policy and political decision making, and even to participate in the arguably most fundamental aspect of our democracy, voting (Blakely et al., 2001; Carter and Reardon, 2014). And implicit biases create differential health care service offerings and delivery and affect the effectiveness of care provided, including a lack of cultural competence (IOM and NRC, 2003; Sabin et al., 2009).

For many people, the challenges that structural inequities pose limit the scope of opportunities they have for reaching their full health potential. The health of communities is dependent on the determinants of health.

STRUCTURAL INEQUITIES

As described above, structural inequities refers to the systematic disadvantage of one social group compared to other groups with whom they coexist that are deeply embedded in the fabric of society. In Figure 3-1, the outermost circle and background indicate the context in which health inequities exist. Structural inequities encompass policy, law, governance, and culture and refer to race, ethnicity, gender or gender identity, class, sexual orientation, and other domains. These inequities produce systematic disadvantages, which lead to inequitable experiences of the social determinants of health (the next circle in the report model, which is discussed in detail later in this chapter) and ultimately shape health outcomes.

FIGURE 3-1

Report conceptual model for community solutions to promote health equity. NOTE: Structural inequities are highlighted to convey the focus of this section.

Racism

Though inequities may occur on the basis of socioeconomic status, gender, and other factors, we illustrate these points through the lens of racism, in part because disparities based on race and ethnicity remain the most persistent and difficult to address (Williams and Mohammed, 2009). Racial factors play an important role in structuring socioeconomic disparities (Farmer and Ferraro, 2005); therefore, addressing socioeconomic factors without addressing racism is unlikely to remedy these inequities (Kaufman et al., 1997).

Racism is an umbrella concept that encompasses specific mechanisms that operate at the intrapersonal, interpersonal, institutional, and systemic levels² of a socioecological framework (see Figure 3-2). Because it is not possible to enumerate all of the mechanisms here, several are described below to illustrate racism mechanisms at different socioecological levels. Stereotype threat, for example, is an intrapersonal mechanism. It “refers to the risk of confirming negative stereotypes about an individual's racial, ethnic, gender, or cultural group” (Glossary of Education Reform, 2013). Stereotype threat manifests as self-doubt that can lead the individual to perform worse than she or he might otherwise be expected to—in the context of test-taking, for example. Implicit biases—unconscious cognitive biases that shape both attitudes and behaviors—operate interpersonally (discussed in further detail below) (Staats et al., 2016). Racial profiling often operates at the institutional level, as with the well-documented institutionalization of stop-and-frisk practices on Hispanic and African American individuals by the New York City Police Department (Gelman et al., 2007).

FIGURE 3-2

Social ecological model with examples of racism constructs. NOTES: The mechanisms by which the social determinants of health operate differ with respect to the level. For the intrapersonal level, these mechanisms are individual knowledge, attitudes/beliefs, (more...)

Finally, systemic mechanisms, which may operate at the community level or higher (e.g., through policy), are those whose effects are interactive, rather than singular, in nature. For example, racial segregation of neighborhoods might well be due in part to personal preferences and behavior of landlords, renters, buyers, and sellers. However, historically, segregation was created by legislation, which was reinforced by the policies and practices of economic institutions and housing agencies (e.g., discriminatory banking practices and redlining), as well as enforced by the judicial system and legitimized by churches and other cultural institutions (Charles, 2003; Gee and Ford, 2011; Williams and Collins, 2001). In other words, segregation was, and remains, an interaction and cumulative “product,” one not easily located in any one actor or institution. Residential segregation remains a root cause of racial disparities in health today (Williams and Collins, 2001).

Racism is not an attribute of minority groups; rather, it is an aspect of the social context and is linked with the differential power relations among racial and ethnic groups (Guess, 2006). Consider the location of environmental hazards in or near minority communities. Placing a hazard in a minority community not only increases the risk of adverse exposures for the residents of that community, it also ensures the reduction of risk for residents of the nonminority community (Cushing et al., 2015; Taylor, 2014). Recognizing this, the two communities could work together toward an alternative that precludes having the hazard in the first place, an alternative that disadvantages neither group.

Most studies of racism are based on African American samples; however, other populations may be at risk for manifestations of racism that differ from the African American experience. Asians, Hispanics, and, more recently, Arabs and Muslims are subject to assumptions that they are not U.S. citizens and, therefore, lack the rights and social entitlements that other U.S. residents claim (Chou and Feagin, 2015; Cobas et al., 2009; Feldman, 2015; Gee et al., 2009; Johnson, 2002; Khan and Ecklund, 2013). The implications of this include threats or actual physical violence against members of these groups. For instance, researchers have found that in the months immediately following September 11, 2001, U.S. women with Arabic surnames who were residing in California experienced increases in both racial microaggressions (i.e., seemingly minor forms of “everyday racism”) and in poor birth outcomes compared to the 6 months preceding 9/11, while women of other U.S. ethnic groups did not (Kulwicki et al., 2008; Lauderdale, 2006). For Native Americans, because tribes are independent nations, the issues of racism need to be considered to intersect with those of sovereignty (Berger, 2009; Massie, 2016; Sundeen, 2016).

The evidence linking racism to health disparities is expanding rapidly. A variety of both general and disease-specific mechanisms have been identified; they link racism to outcomes in mental health, cardiovascular disease, birth defects, and other outcomes (Paradies, 2006a; Pascoe and Smart Richman, 2009; Shavers et al., 2012; Williams and Mohammed, 2009). Which racism mechanisms matter most depends in part on the disease and, to a lesser degree, the population. The vast majority of studies focus on the role of discrimination; that is racially disparate treatment from another individual or, in some cases, from an institution. Among the studies not focused on discrimination, the majority examine segregation. Generally, findings show that members of all groups, including whites, report experiencing racial discrimination, with levels typically, though not always, higher among African Americans and, to a lesser degree, Hispanics than among whites. Gender differences in some perceptions about and responses to racism have also been observed (Otiniano Verissimo et al., 2014). Three major mechanisms by which systemic racism influences health equity—discrimination (including implicit bias), segregation, and historical trauma—are discussed in more detail in the following paragraphs.

Discrimination

The mechanisms by which discrimination operates include overt, intentional treatment as well as inadvertent, subconscious treatment of individuals in ways that systematically differ so that minorities are treated worse than nonminorities. Recent meta-analyses suggest that racial discrimination has deleterious effects on the physical and mental health of individuals (Gee et al., 2009; Paradies, 2006a; Pascoe and Smart Richman, 2009; Priest et al., 2013; Williams and Mohammed, 2009). Significant percentages of members of racial and ethnic minority populations report experiencing discrimination in health care and non-health care settings (Mays et al., 2007). Greater proportions of African Americans than members of other groups report either experiencing discrimination personally or perceiving it as affecting African Americans in general, even if they have not experienced it personally. Hate crimes motivated by race or ethnicity bias disproportionately affect Hispanics and African Americans (UCR, 2015) (see the public safety section in this chapter for more on hate crimes).

Discrimination is generally associated with worse mental health (Berger and Sarnyai, 2015; Gee et al., 2009; Paradies, 2006b; Williams and Mohammed, 2009); greater engagement in risky behaviors (Gee et al., 2009; Paradies, 2006b; Williams and Mohammed, 2009); decreased neurological responses (Harrell et al., 2003; Mays et al., 2007) and other biomarkers signaling the dysregulation of allostatic load; hypertension-related outcomes (Sims et al., 2012), though some evidence suggests racism does not drive these outcomes (Roberts et al., 2008); reduced likelihood of some health protecting behaviors (Pascoe and Smart Richman, 2009); and poorer birth-related outcomes such as preterm delivery (Alhusen et al., 2016). Paradoxically, despite higher levels of exposure to discrimination, the mental health consequences may be less severe among African Americans than they are among members of other groups, especially Asian populations (Gee et al., 2009; Williams and Mohammed, 2009). Researchers have suggested that African Americans draw on reserves of resilience in ways that temper the effects of discrimination on mental health (Brown and Tylka, 2011).

Though people may experience overt forms of racism (e.g., being unfairly fired on the basis of race), the adverse health effects of racism appear to stem primarily from the stress of chronic exposure to seemingly minor forms of “everyday racism” (i.e., racial microaggressions), such as being treated with less respect by others, being stopped by police for no apparent reason, or being monitored by salespeople while shopping (APA, 2016; Sue et al., 2007; Williams et al., 2003). The chronic exposure contributes to stress-related physiological effects. Thus, discrimination appears to exert its greatest effects not because of exposure to a single life traumatic incident but because people must mentally and physically contend with or be prepared to contend with seemingly minor insults and assaults on a near continual basis (APA, 2016). The implications appear to be greatest for stress-related conditions such as those tied to hypertension, mental health outcomes, substance abuse behaviors, and birth-related outcomes (e.g., low birth weight and premature birth) than for other outcomes (Williams and Mohammed, 2009).

Higher socioeconomic status (SES) does not protect racial and ethnic minorities from discriminatory exposures. In fact, it may increase opportunities for exposure to discrimination. The concept of “John Henryism” is used to describe an intensely active way of tackling racial and other life challenges (James, 1994). Though the evidence is mixed, John Henryism may contribute to worse cardiovascular outcomes among African American males who respond to racism by working even harder to disprove racial stereotypes (Flaskerud, 2012; Subramanyam et al., 2013).

Implicit bias John Dovidio defines implicit bias—a mechanism of unconscious discrimination—as a form of racial or other bias that operates beneath the level of consciousness (Dovidio et al., 2002). Research conducted over more than four decades finds that individuals hold racial biases of which they are not aware and, importantly, that discriminatory behaviors can be predicted based on this construct (Staats et al., 2016). The effects are greatest in situations marked by ambiguity, stress, and time constraints (Bertrand et al., 2005; Dovidio and Gaertner, 2000). Implicit bias is not an arbitrary personal preference that individuals hold; for example, “I just happen to prefer pears over apples.” Rather, the nature and direction of individuals' biases are structured by the racial stratification and norms of society. As a result, they are predictable.

Much of the public health literature has focused on the implicit biases of health care providers, who with little time to devote to each patient can provide care that is systematically worse for African American patients than for white patients even though the health care provider never intended to do so (IOM and NRC, 2003; van Ryn and Burke, 2000). The evidence is clear that unconscious racialized perceptions contribute to differences in how various individual actors, including health care providers, perceive others and treat them. Based on psychology lab experiments, functional magnetic resonance imaging (fMRI) pictures of the brain, and other tools, researchers find that white providers hold implicit biases against African Americans and that, to a lesser degree, some minority providers may also hold these biases (Hall et al., 2015). Although not limited to health care professionals, the biases lead providers to link negative characteristics (e.g., bad) and emotions (e.g., fear) with people or images they perceive as being African American (Zestcott et al., 2016). As a result of such implicit biases, physicians treat patients differently depending on the patient's race, ethnicity, gender, or other assumed or actual characteristics (IOM and NRC, 2003; Zestcott et al., 2016).

Given the importance of implicit bias, researchers have considered the role of health care provider–patient racial and ethnic concordance. Even if patients have similar clinical profiles, their care may differ systematically based on their race or ethnicity and that of their health care provider (Betancourt et al., 2014; van Ryn and Fu, 2003; Zestcott et al., 2016). The evidence on whether and how patient–provider concordance contributes to health disparities is mixed (van Ryn and Fu, 2003). Qualitative and quantitative findings suggest that patients do not necessarily prefer providers of the same race or ethnicity; they prefer a provider who treats them with respect (Dale et al., 2010; Ibrahim et al., 2004; Schnittker and Liang, 2006; Volandes et al., 2008). Providers appear to evaluate African American patients more negatively than they do similar white patients; seem to perceive them as more likely to participate in risky health behaviors; and may be less willing to prescribe them pain medications and narcotics medications (van Ryn and Fu, 2003). In a video-based study conducted among primary care providers, the odds ratio of providers referring simulated African American patients to otherwise identical white patients for cardiac catheterization was 0.6 (Schulman et al., 1999). Some evidence suggests minority providers deliver more equitable care to their diverse patients than white providers. For instance, a longitudinal study among African American and white HIV-positive patients enrolled in HIV care found that white doctors took longer to prescribe protease inhibitors (an effective HIV medication) for their African American patients than for their clinically similar white patients. Providers prescribed them on average 162 days earlier for white patients than for comparable African American patients (King et al., 2004). Among African American providers, there was no difference between African American and white patients in how long before providers prescribed the medications.

Racial and ethnic minority providers play an important role in addressing disparities because they help bridge cultural gulfs (Butler et al., 2014; Cooper et al., 2003; Lehman et al., 2012), and greater proportions of them serve minority and socially disadvantaged communities (Cooper and Powe, 2004); however, these providers are underrepresented in the health professions, and they face challenges that may constrain their professional development and the quality of care they are able to provide (Landrine and Corral, 2009). Specifically, they are more likely to serve patients in resource-poorer areas and lack professional privileges associated with academic and other resource-rich institutions. The structural inequities have implications not only for individual clinicians but also for the patients and communities they serve. Pipeline programs that grow the numbers of minority providers may help to address underrepresentation in the health professions. The available data suggest that pipeline participants are more likely to care for poor or underserved patients when they join the workforce (McDougle et al., 2015). Supporting the professional development of and expanding the resources and tools available to providers working in resource-poor communities seems to be one option for improving access to and quality of care; however, the literature does not clearly elucidate the relationship between health care workforce pipeline programs (e.g., to grow the numbers of minority providers) and their impact on the social determinants of health for poor and underserved communities (Brown et al., 2005; Smith et al., 2009). A commitment to equity is not enough to remedy the discriminatory treatment that results from implicit biases because the inadvertent discriminatory behavior co-occurs alongside deeply held personal commitments to equity. Identifying implicit biases and acknowledging them is one of the most effective steps that can be taken to address their effects (Zestcott et al., 2016). Trainings can help health care providers identify their implicit biases. Well-planned allocations of resources, including time, may afford them sufficient opportunity to account for it while serving diverse persons/patients.

Segregation

Residential segregation—that is, the degree to which groups live separately from one another (Massey and Denton, 1988)—can exacerbate the rates of disease among minorities, and social isolation can reduce the public's sense of urgency about the need to intervene (Acevedo-Garcia, 2000; Wallace and Wallace, 1997). The effects of racial segregation differ from those of socioeconomic segregation. Lower SES whites are more likely to live in areas with a range of SES levels, which affords even the poorest residents of these communities access to shared resources (e.g., parks, schools) that buffer against the effects of poverty (APA Task Force on Socioeconomic Status, 2007; North Carolina Institute of Medicine Task Force on Prevention, 2009). By contrast, racial and ethnic minorities are more likely to live in areas of concentrated poverty (Bishaw, 2011). Indeed, if shared resources are of poor quality, they may compound the low SES challenges an individual faces. Racial segregation contributes to disparities in a variety of ways. It limits the socioeconomic resources available to residents of minority neighborhoods as employers and higher SES individuals leave the neighborhoods; it reduces health care provider density in predominately African American communities, which affects access to health care (Gaskin et al., 2012); it constrains opportunities to engage in recommended health behaviors such as walking; it may be associated with greater density of alcohol outlets, tobacco advertisements, and fast food outlets in African American and other minority neighborhoods (Berke et al., 2010; Hackbarth et al., 1995; Kwate, 2008; LaVeist and Wallace, 2000); it increases the risk for exposure to environmental hazards (Brulle and Pellow, 2006); and it contributes to the mental and physical consequences of prevalent violence, including gun violence and aggressive policing (Landrine and Corral, 2009; Massey and Denton, 1989; Polednak, 1996).

Historical Trauma

Historical trauma, “a collective complex trauma inflicted on a group of people who share a specific group identity or affiliation” (Evans-Campbell, 2008, p. 320), manifests from the past treatment of certain racial and ethnic groups, especially Native Americans. This is another form of structural (i.e., systemic) racism that continues to shape the opportunities, risks, and health outcomes of these populations today (Gee and Ford, 2011; Gee and Payne-Sturges, 2004; Heart et al., 2011). The past consignment of Native Americans to reservations with limited resources continues to constrain physical and mental health in these communities; however, the methods to support research on this topic have not yet been fully developed (Heart et al., 2011). Additional details on the health of Native Americans are presented in Chapter 2 and Appendix A.

Interventions

The literature includes a small number of tested interventions. Interventions to address the health consequences of racism need not target racism in order to address the disparities it helps to produce. Furthermore, despite the deeply rooted nature of racism, communities are taking action to address the issue. (See Box 3-2 for a brief example of a community targeting structural racism and Box 3-3 for guidance on how to start a conversation about race.) Policy interventions and multi-sectoral efforts may be necessary to address structural factors such as segregation.

BOX 3-2

Addressing Structural Racism in Everett, Massachusetts, Through Improving Community–Police Interactions.

BOX 3-3

How to Start a Conversation on Race and Health (Excerpted from Culture of Health Prize Winner, Everett, Massachusetts).

Examples of interventions that target racism include the following:

• Dismantling racism by addressing factors in organizational settings and environments that “directly and indirectly contribute to racial health care disparities” (Griffith et al., 2010, p. 370); see work by Derek Griffith (Griffith et al., 2007, 2010).
• The Undoing Racism project (Yonas et al., 2006), which integrates community-based participatory research with the “undoing racism” process, which is built around community organizing.
• The Praxis Project,³ a national organization whose mission is to build healthy communities by transforming the power relationships and structures that affect lives. The organization's comprehensive strategy for change includes policy advocacy, local organizing, strategic communications, and community research.

Although there is not a robust evidence base from which to draw solutions for implicit bias and its effects, there are promising strategies. For example, there is emerging evidence that mindfulness-based interventions have the potential to reduce implicit bias (Kang et al., 2014; Levesque and Brown, 2007; Lueke and Gibson, 2014). One promising avenue of research involves models of self-regulation and executive control on interracial interaction (Richeson and Shelton, 2003). Mindfulness has been shown to work on the cognitive brain function attentional processes involved in executive function, which is involved in decision making (Lueke and Gibson, 2014; Malinowski, 2013). A key component of mindfulness is paying attention with intention and without judgment.

There is also existing literature that points to the need for community-based interventions to mitigate implicit bias within the context of criminal justice and community safety (Correll et al., 2002, 2007; La Vigne et al., 2014; Richardson and Goff, 2013). According to the National Initiative for Building Community Trust and Justice, implicit bias can shape the outcomes of interactions between police and residents, which in turn result in pervasive practices that focus suspicion on specific populations (National Initiative for Building Community Trust and Justice, 2015). As discussed later in this chapter, the criminal justice system is a key actor and setting in shaping health inequity (see also Chapters 6 and 7 for more on criminal justice system as policy context and as a partner, respectively). Law enforcement agencies in communities around the country have employed strategies such as “principled policing” and policy changes and trainings to strengthen police–community relations (Gilbert et al., 2016; Jones, 2016).

The Perception Institute,⁴ an organization committed to generating evidence-based solutions for bias in education, health care, media, workplace, law enforcement, and civil justice, published a report authored by Godsil et al. (2014) in which promising interventions for implicit bias are highlighted (Godsil et al., 2014). Among these interventions was a multipronged approach to reducing implicit bias that Devine and colleagues (2012) found to be successful and the “first evidence that a controlled, randomized intervention can produce enduring reductions in implicit bias” (Devine et al., 2012, p. 1271). The multiple strategies of the intervention tested included stereotype replacement, counter-stereotype imaging, individuation, perspective taking, and increasing opportunities for contact. As discussed above, there is an emerging body of literature that is beginning to highlight promising solutions for implicit bias; however, that research base needs to be expanded further.

Recommendation 3-1: The committee recommends that research funders⁵ support research on (a) health disparities that examines the multiple effects of structural racism (e.g., segregation) and implicit and explicit bias across different categories of marginalized status on health and health care delivery; and (b) effective strategies to reduce and mitigate the effects of explicit and implicit bias.

This could include implicit and explicit bias across race, ethnicity, gender identity, disability status, age, sexual orientation, and other marginalized groups.

There have been promising developments in the search for interventions to address implicit bias, but more research is needed, and engaging community members in this and other aspects of research on health disparities is important for ethical and practical reasons (Minkler et al., 2010; Mosavel et al., 2011; Salway et al., 2015). In the context of implicit bias in workplaces and business settings, including individuals with relevant expertise in informing and conducting the research could also be helpful. Therefore, teams could be composed of such nontraditional participants as community members and local business leaders, in addition to academic researchers.

Conclusion 3-1: To reduce the adverse effects and the level of implicit bias among stakeholders in the community (such as health care workers, social service workers, employers, police officers, and educators), the committee concludes, based on its judgment, that community-based programs are best suited to mitigate the adverse effects of implicit bias. Successful community programs would be tailored to the needs of the community. However, proven strategies and efficacious interventions to reduce the effects of or mitigate effects of implicit bias are lacking. Therefore:

Recommendation 3-2: The committee recommends that research funders support and academic institutions convene multidisciplinary research teams that include nonacademics to (a) understand the cognitive and affective processes of implicit bias and (b) test interventions that disrupt and change these processes toward sustainable solutions.

SOCIAL DETERMINANTS OF HEALTH

As described earlier, structural inequities are produced on the basis of social identity (e.g., race, gender, and sexual orientation), and the social determinants of health are the “terrain” on which the effects play out. Traditionally, the most well-known and cited of the factors that shape health outcomes are the individual-level behavioral factors (e.g., smoking, physical activity, nutrition habits, and alcohol and drug use) that the evidence shows are proximally associated with individual health status and outcomes. As stated in Chapter 1, understanding the social determinants of health requires a shift toward a more upstream perspective (i.e., the conditions that provide the context within which an individual's behaviors are shaped). Again, consider the metaphor of a fish, and the role of the conditions of the fishbowl in influencing the fish's well-being, and the analogy to human beings and conditions in which people live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks. These environments and settings (e.g., school, workplace, neighborhood, and church) have been referred to as “place.” In addition to the more material attributes of “place,” the patterns of social engagement, social capital, social cohesion, and sense of security and well-being are also affected by where people live (Braveman and Gottlieb, 2014; Healthy People 2020, 2016). Although the term “social determinants of health” is widely used in the literature, the term may incorrectly suggest that such factors are immutable. It is important to note that the factors included among the social determinants of health are indeed modifiable and that they can be influenced by social, economic, and political processes and policies. In fact, there are communities throughout the United States that have prioritized addressing the social determinants of health and are demonstrating how specific upstream strategies lead to improved community conditions and health-related outcomes. (See Chapter 5 for an in depth examination of nine community examples.) Although it might be more accurate to refer to social “contributing factors” for health, the committee continues to use the widely accepted word “determinants” in this report.

For the purposes of this report, the committee has identified nine social determinants of health (see report conceptual model, Figure 3-3) that the literature shows fundamentally influence health outcomes at the community level. These determinants are education, income and wealth, employment, health systems and services, housing, the physical environment, transporation, the social environment, and public safety (Table 3-1 provides a brief definition of each).

FIGURE 3-3

Report framework for community solutions to promote health equity. NOTE: The social (and other) determinants of health are highlighted to convey the focus of this section.

TABLE 3-1

The Social (and Other) Determinants of Health.

There is a vast and growing body of literature on the social, economic, and environmental determinants of health and their impacts on health outcomes (Braveman and Gottlieb, 2014; Braveman et al., 2011; CSDH, 2008; Marmot et al., 2010). Often, the evidence is in the form of cross-sectional analyses, and the pathways to health outcomes are not always clearly delineated, in part due to the complexity of the mechanisms and the long time periods it takes to observe outcomes (Braveman and Gottlieb, 2014). Therefore, the literature is not sufficient to establish a causal relationship between each of these determinants and health, but the determinants certainly are correlated with and contribute to health outcomes. While this report focuses on the community level, it should be made clear that the social determinants of health operate at multiple levels throughout the life course (IOM, 2006). This includes the individual level (knowledge, attitudes/beliefs, skills), family and community level (friends and social networks), institutional level (relationships among organizations), and systemic level (national, state, and local policies, laws, and regulations) (see Figure 3-2, the social ecological model adapted from McLeroy et al. [1988]). Furthermore, the various levels of influence that the social determinants of health have can occur simultaneously and interact with one another (IOM, 2006). In addition to the multiple levels of influence, there is a diversity of actors, sectors, settings, and stakeholders that interact with and shape the social determinants of health. This adds an additional layer of complexity to the factors that shape health disparities.

The following sections describe each of these nine determinants and how they shape health outcomes, as well as the disparities within these social determinants of health that contribute to health inequity. To highlight the ongoing work of communities that seek to address the conditions in which members live, learn, work, and play, this section will feature brief examples of communities for each determinant of health.

Education

Education, as it pertains to health, can be conceptualized as a process and as an outcome. The process of educational attainment takes place in many settings and levels (e.g., the home/family, school, and community), while the outcome can be described as a sum of knowledge, skills, and capacities that can influence the other social determinants of health, or health, more directly (Davis et al., 2016). Within the current social determinants of health literature, the primary focus on education is on educational attainment as an outcome (i.e., years of schooling, high school completion, and number of degrees obtained) and how it relates to health outcomes.

There is an extensive body of research that consistently demonstrates a positive correlation between educational attainment and health status indicators, such as life expectancy, obesity, morbidity from acute and chronic diseases, health behaviors (e.g., smoking status, heavy drinking physical activity, preventive services or screening behavior, automobile and home safety) and more (Baum et al., 2013; Cutler and Lleras-Muney, 2006, 2010; Feinstein et al., 2006; Krueger et al., 2015; Rostron et al., 2010). Educational attainment also has an intergenerational effect, in which the education of the parents, particularly maternal education, is linked to their children's health and well-being (Cutler and Lleras-Muney, 2006). For example, research suggests that babies born to mothers who have not completed high school are twice as likely to die before their first birthday as babies who are born to college graduates (Egerter et al., 2011b; Mathews and MacDorman, 2007). Death rates are declining among the most-educated Americans, accompanied by steady or increasing death rates among the least educated (Jemal et al., 2008). The findings on the association between education and health are consistent with population health literature within the international context as well (Baker et al., 2011; Furnee et al., 2008; Marmot et al., 2010).

Even more noteworthy about the education and health relationship is the graded association that is observed across populations with varying education levels, commonly referred to as the “education gradient.” In the United States the gradient in health outcomes by educational attainment has steepened over the last four decades in all regions of the United States (Goldman and Smith, 2011; Montez and Berkman, 2014; Olshansky et al., 2012), producing a larger gap in health status between Americans with high and low education. Specifically, trends in data suggest that, over time, the disparities in mortality and life expectancy by education level have been increasing (Meara et al., 2008; Olshansky et al., 2012). Meara et al. found that approximately 20 percent of this trend was attributable to differential trends in smoking-related diseases in the 1980s and 1990s, despite the overall population increases in life expectancy during these two decades (Meara et al., 2008). Economic trends and shifting patterns of employment, in which skilled jobs linked to educational attainment are associated with increased income, also have implications for health (NRC, 2012). This makes the connection between education and health, mediated by employment opportunities, even more important and worth exploring.

Data from the Behavioral Risk Factor Surveillance System reveal that across all racial groups, adults with higher levels of educational attainment are less likely to rate their own health as less than very good (Egerter et al., 2011b). While the education gradient is present across racial and ethnic groups, it is important to keep in mind that the rates of educational attainment vary across different racial and ethnic groups. For the 2013–2014 academic year, the high school graduation rate for white students was 87.2 percent as compared with 76.3 percent among Hispanics, 72.5 percent among African Americans, and 70 percent among Native Americans (Kena et al., 2016). These rates are consistent with high school diploma and bachelor degree achievement gaps that have persisted since the late 1990s (see Figures 3-4 and 3-5).

FIGURE 3-4

Percentage of 25- to 29-year-olds who completed at least a high school diploma or its equivalent, by race and ethnicity: Selected years, 1995–2015. NOTE: Race categories exclude persons of Hispanic ethnicity. Prior to 2005, separate data on persons (more...)

FIGURE 3-5

Percentage of U.S.-born population ages 25 years and older with a bachelor's degree or higher by race and Hispanic origin, 1988–2015. SOURCE: Ryan and Bauman, 2016.

Although the literature linking education and health is robust, there is still some debate as to whether or not this relationship is a causal one (Baker et al., 2011; Fujiwara and Kawachi, 2009; Grossman, 2015). Issues that have been raised in the course of this debate include the role of reverse causation and the potential influence of any unobserved third variables (Grossman, 2015). The association between education and health is clearly bidirectional. Education outcomes are substantially affected by health (Cutler and Lleras-Muney, 2006). Students living in community conditions that contribute to hunger, chronic stress, or lack of attention to visual or hearing needs are likely to have problems concentrating in class (Evans and Schamberg, 2009). Unmanaged health conditions (e.g., asthma, dental pain, acute illnesses, mental health issues, etc.) give rise to chronic absenteeism, which in turn is highly correlated with underachievement (Ginsburg et al., 2014). In short, health issues are much more than minor distractions in the lives of students, especially students living in low-income communities.

Disparities in Education

Educational attainment, common measures of which include high school diploma or bachelor's degree, has increased for all race groups and Hispanics since 1988, according to U.S. Census estimates (Ryan and Bauman, 2016). Despite this overall progress, the gaps between these groups have remained the same for some and increased for others. For example, in 1988 African Americans and Hispanics attained bachelor's degrees at very similar rates; however, by 2015 the percentage gap between African Americans and Hispanics had reached 7 percent, with rates of completion at 22 percent and 15 percent, respectively (Ryan and Bauman, 2016). Furthermore, there has been little to no progress in closing the gap of achievement between whites and African Americans (Ryan and Bauman, 2016).

A recent study of school trends conducted by the U.S. Government Accountability Office (GAO) found that there has been a large increase in schools that are distinguished by the poverty and race of their student bodies (GAO, 2016). The percent of K–12 schools with students who are poor and are mostly African American or Hispanic grew from 9 percent to 16 percent from 2000 to 2013. These schools were the most racially and economically concentrated among all schools, with 75 to 100 percent of the students African American or Hispanic and eligible for free or reduced-price lunch—a commonly used indicator of poverty. Moreover, compared with other schools, these schools offered disproportionately fewer math, science, and college preparatory courses and had disproportionately higher rates of students who were held back in 9th grade, suspended, or expelled (GAO, 2016).

One gap in educational achievement that has successfully been narrowed over the past five decades is the gender disparity in bachelor's degree attainment, in which men historically had higher achievement rates (Crissey et al., 2007). In 2015 the percentage of men ages 25 or older with a bachelor's degree or higher was not statistically different from that of women, with women leading by one percentage point (Ryan and Bauman, 2016).

The evidence suggests that disparities in education are apparent early in the life course, which reflects broader societal inequities (Garcia, 2015). In education, these early disparities are evidenced by wide gaps in vocabulary between children from low-income and those from middle- or upper-income families. Children from low-income families may have 600 fewer words in their vocabulary by age 3, a gap that grows to as many as 4,000 words by age 7 (Christ and Wang, 2010). These word gaps directly affect literacy levels and reading achievement (Marulis and Neuman, 2010). There is substantial evidence that children who do not read at grade level by 7 or 8 years of age are much more likely to struggle academically (Chall et al., 1990). Both high school graduation rates and participation in postsecondary education opportunities are correlated with early literacy levels. Hence, attention to and investments in early childhood education are generally viewed as an important way to reduce disparities in education (Barnett, 2013).

Mechanisms

Although the association between education and health is clear, the mechanisms by which educational attainment might improve health are not so clearly understood. A keen understanding of the mechanisms could help to inform the most cost-effective and targeted policies or solutions that seek to improve health and, ultimately, promote health equity (Picker, 2007). Egerter et al. (2011b) identified multiple interrelated pathways through which education can affect health, based on the literature (see Figure 3-6). The three major pathways are the following:

FIGURE 3-6

Pathways through which education can affect health. SOURCE: Egerter et al., 2011b. Used with permission from the Robert Wood Johnson Foundation.

• Education increases health knowledge, literacy, coping, and problem solving, thereby influencing health behaviors;
• Educational attainment shapes employment opportunities and related benefits, such as income, working conditions, and other resources; and
  • Research indicates that each additional year of education leads to almost 11 percent more income annually (Rouse and Barrow, 2006), which can secure safer working environments and benefits such as health insurance and sick leave.
• Education affects social and psychological factors that influence health (e.g., self-efficacy, social status, and social networks) (Egerter et al., 2011b).
  • Education has also been linked to human capital, a systematic way of thinking that benefits every decision, which could positively affect health decisions (Cutler and Lleras-Muney, 2006; Lundborg et al., 2012, 2016).

In this framework, note that educational attainment is a predictor of health and can either improve or hinder health outcomes depending on educational attainment. This suggests that policies and practices proven to increase academic performance and reduce education disparities are important to reducing health disparities. (See Box 3-4 for an example of a community school working to improve educational outcomes.) Intervening early is generally considered a high-impact strategy (Barnett, 2013). However, interventions that support academic achievement in high schools and in postsecondary settings are also important to increasing educational attainment (Balfanz et al., 2007; Carnahan, 1994; Kirst and Venezia, 2004; Louie, 2007). One of the key factors in both high school and college completion rates has to do with how well students transition from one level of the education system to another (Rosenbaum and Person, 2003).

BOX 3-4

Reagan High School: A Community School.

Income and Wealth

Income can be defined broadly as the amount of money earned in a single year from employment, government assistance, retirement and pension payments, and interest or dividends from investments or other assets (Davis et al., 2016). Income can fluctuate greatly from year to year depending on life stage and employment status. Wealth, or economic assets accumulated over time, is calculated by subtracting outstanding debts and liabilities from the cash value of currently owned assets—such as houses, land, cars, savings accounts, pension plans, stocks and other financial investments, and businesses. Wealth measured at a single time period may provide a more complete picture than income of a person's economic resources. Moreover, wealth has an intergenerational component, which can have implications for who has access to wealth and who does not (De Nardi, 2002).

Access to financial resources, be it income or wealth, affects health by buffering individuals against the financial threat of large medical bills while also facilitating access to health-promoting resources such as access to healthy neighborhoods, homes, land uses, and parks (Davis et al., 2016). Income can predict a number of health outcomes and indicators, such as life expectancy, infant mortality, asthma, heart conditions, obesity, and many others (Woolf et al., 2015).

Income Inequality and Concentration of Poverty

Income inequality is rising in the United States at a rate that is among the highest in the economically developed countries in the north (OECD, 2015). The past few decades have seen dramatic rises in income inequality. In 1970, 17 percent of families lived in upper-income areas, 65 percent in middle-income areas, and 19 percent in lowest-income areas; in 2012, 30 percent of families lived in upper-income areas, 41 percent in middle-income areas, and 30 percent in lowest-income areas (Reardon and Bischoff, 2016). In 2013, the top 10 percent of workers earned an average income 19 times that of the average income earned by the bottom 10 percent of workers; in the 1990s and 1980s, this ratio was 12.5 to 1 and 11 to 1, respectively (OECD, 2015). Furthermore, households earning in the bottom 10 percent have not benefited from overall increases in household income over the past few decades; the average inflation-adjusted income for this population was 3.3 percent lower in 2012 than in 1985 (OECD, 2015). Disparities in life expectancy gains have also increased alongside the rise in income inequality. From 2001 to 2014, life expectancy for the top 5 percent of income earners rose by about 3 years while life expectancy for the bottom 5 percent of income earners saw no increase (Chetty et al., 2016).

Not only are income and wealth determinants of health, but the concentration of poverty in certain neighborhoods is important to recognize as a factor that shapes the conditions in which people live. Concentrated poverty, measured by the proportion of people in a given geographic area living in poverty, can be used to describe areas (e.g., census tracts) where a high proportion of residents are poor (Shapiro et al., 2015). Concentrated poverty disproportionately affects racial and ethnic minorities across all of the social determinants of health. For example, National Equity Atlas data reveal that in about half of the largest 100 cities in the United States, most African American and Hispanic students attend schools where at least 75 percent of all students qualify as poor or low-income under federal guidelines (Boschma, 2016). Given that concentrated poverty is tightly correlated with gaps in educational achievement, this has implications for educational outcomes and health (Boschma and Brownstein, 2016).

Disparities Related to Income Inequality

In 2012, of the 12 million full-time low-income workers between the ages of 25 and 64, 56 percent were racial and ethnic minorities (Ross, 2016b). Regional percentages varied from 23 percent in Honolulu, Hawaii, to 65 percent in Brownsville, Texas (Ross, 2016a). Figure 3-7 shows the proportion of low-income workers of racial and ethnic minority groups across different regions of the United States. The burden faced by low-income people suggests that efforts to advance health equity through income and wealth will need to take into consideration rising income inequality as well as significant geographic variation.

FIGURE 3-7

The share of people of color below 200 percent of poverty ranges. SOURCE: Woolf et al., 2015. Used with permission from PolicyLink, figure from article by Angel Ross, New Data Highlights Vast and Persistent Racial Inequities in Who Experiences Poverty (more...)

Chetty and colleagues published the largest study of its kind, using 1.4 billion income tax and Social Security records to report the association between income level and life expectancy from 1999 through 2014 (Chetty et al., 2016). Consistent with previous findings (NASEM, 2015; Waldron, 2007; Woolf et al., 2015), they found that higher income is related to higher life expectancy and that lower income is related to lower life expectancy. The gap in life expectancy for the richest and poorest 1 percent of individuals was 14.6 years for men and 10.1 years for women. A novel contribution of the study is its examination of the income–longevity relationship across time and local areas. In certain local areas, the effect of being at the bottom of the income gradient is more pronounced than in others, with four- to five-fold differences. This strong local component reinforces the notion suggested by the literature that place matters. Trends in life expectancy also varied geographically, with some areas experiencing improvements and others declines. Others have commented on the limitations of the study (Deaton, 2016; McGinnis, 2016; Woolf and Purnell, 2016).

Zonderman et al. take the findings of this study a step further by considering the role of race and gender differences in the relationship between poverty and mortality. They found that while African American men below poverty status had 2.66 times higher risk of mortality than African American men living above poverty status, white men below poverty status had approximately the same risk as white men living above poverty status (Zonderman et al., 2016). Both African American women and white women living below poverty status were at an increased mortality risk relative to those living above poverty status (Zonderman et al., 2016).

Infant mortality rates in the United States rank among the highest for developed nations (NRC and IOM, 2013), and mortality rates for infants born to low-income mothers are even higher. Studies have shown an inverse correlation between family income and infant mortality (Singh and Yu, 1995) as well as a positive correlation between income inequality (measured with the Gini coefficient) and infant mortality (Olson et al., 2010). Infants born to low-income mothers have the highest rates of low birth weight (Blumenshine et al., 2010; Dubay et al., 2001).

Chronic diseases are more prevalent among low-income people than among the overall U.S. population. Low-income adults have higher rates of heart disease, diabetes, stroke, and other diseases and conditions relative to adults earning higher levels of income (Woolf et al., 2015).

Mechanisms

Researchers have offered various hypotheses about the multiple mechanisms by which income can affect health. Woolf et al. suggest that among others, these mechanisms include more income providing the opportunity to afford health care services and health insurance; greater resources affording a healthy lifestyle and access to place-based benefits known as the social determinants of health; and economic disadvantage and hardship leading to stress and harmful physiological effects on the body (Woolf et al., 2015). Evans and Kim identify “multiple risk exposure” as a potential mechanism for the socioeconomic status and health gradient. This is the convergence among populations with low socioeconomic status of multiple physical and psychosocial risk factors such as poor housing and neighborhood quality, pollutants and toxins, crowding and congestion, noise exposure, and adverse interpersonal relationships (Evans and Kim, 2010).

Wealth affects health through mechanisms that are not necessarily monetary, such as power and prestige, attitudes and behavior, and social capital (Pollack et al., 2013). Even in the absence of income, wealth can provide resources and a safety net that is not available to those without it. (See Box 3-5 for an example of an initiative seeking to build income and wealth in communities around the country.)

BOX 3-5

Family Independence Initiative: The Power of Information and Investment in Families Who Take Initiative.

Employment

Employment is the level or absence of adequate participation in a job or workforce, including the range of occupation, unemployment, and underemployment. Work influences health not only by exposing employees to certain physical environments but also by providing a setting where healthy activities and behaviors can be promoted (An et al., 2011). For most adults, employment is the main source of income, thus providing access to homes, neighborhoods, and other conditions or services that promote health. The features of a worksite, the nature of the work, the amount of earnings or income, and how the work is organized can affect worker mental and physical health (An et al., 2011; Clougherty et al., 2010). Many Americans also obtain health insurance through their workplace, accounting for another potential impact on health and wellbeing. While the correlation between employment and health has been well established, there appears to be a bidirectional relationship between employment and health, as health also affects one's ability to participate in and maintain stable employment (Davis et al., 2016; Goodman, 2015). Not only that, but a healthy workforce is a prerequisite for economic success in any industry (Doyle et al., 2005).

The existing literature on the social determinants of health makes it clear that there is a positive correlation between SES and health (Adler and Stewart, 2010a; Braveman et al., 2005; Conti et al., 2010; Dow and Rehkopf, 2010; Pampel et al., 2010; Williams et al., 2010). Occupational status, a composite of the power, income, and educational requirements associated with various positions in the occupational structure, is a core component of a person's SES (Burgard and Stewart, 2003; Clougherty et al., 2010). Occupational status can be indicative of the types of tangible benefits, hazards, income, fringe benefits, degree of control over work, and level of exposure to harmful physical environments associated with a job (Clougherty et al., 2010). While the mechanisms by which occupational status influences health have not clearly been delineated, there is evidence that the type of job does affect such health outcomes as hypertension risk and obesity (An et al., 2011; Clougherty et al., 2010).

On the other end of the spectrum, unemployment is associated with poor psychological well-being (McKee-Ryan et al., 2005; Paul and Moser, 2009). Zhang and Bhavsar (2013) examined the literature to illuminate the causality, effect size, and moderating factors of the relationship between unemployment as a risk factor and mental illness as an outcome. The authors reported that unemployment does precede mental illness, but more research is required to determine the effect size (Zhang and Bhavsar, 2013). There is also evidence to suggest that emerging adults who are unemployed are three times as likely to suffer from depression as their employed counterparts (McGee and Thompson, 2015). Burgard and colleagues found that even after controlling for significant social background factors (e.g., gender, race, education, maternal education, income, and more), involuntary job loss was associated with poorer overall self-rated health and more depressive symptoms (Burgard et al., 2007).

Disparities in Employment

Employment data show disparities in unemployment rates across various racial and ethnic groups and geographic regions, despite the overall progress that has been made in reducing unemployment nationally (Wilson, 2016). During the fourth quarter of 2015, the highest state-level unemployment rate was 13.1 percent for African Americans (Illinois), 11.9 percent for Hispanics (Massachusetts), 6.7 percent for whites (West Virginia), and 4.3 percent for Asians (New York) (Wilson, 2016). Figure 3-8 shows how disparities in unemployment by race and ethnicity have persisted for more than 40 years, with the exception of whites and Asians. Disparities in employment between African Americans and whites persist even when level of education, a major predictor of employment, is held equal between the two groups (Buffie, 2015).

FIGURE 3-8

Unemployment rates by race and Hispanic or Latino ethnicity, 1973–2013 annual averages. NOTE: People whose ethnicity is identified as Hispanic or Latino may be of any race. Data for Asians are only available since 2000. SOURCE: BLS, 2014.

Among the employed, there are systematic differences in wages and earnings by race, ethnicity, and gender. According to the U.S. Bureau of Labor Statistics, in 2013 the median usual weekly earnings⁶ were $578 for Hispanics, $629 for African Americans, $802 for whites, and $942 for Asians (BLS, 2014). These disparities are consistent across almost all occupational groups. The widest gap in median usual weekly earnings was found between Hispanic women and Asian men, who made $541 and $1,059, respectively (BLS, 2014).

As with income, the distribution of occupations tends to differ across racial and ethnic groups (see Figure 3-9). Whereas half of Asians worked in management, professional, and related occupations in 2013, only 29 and 20 percent of African Americans and Hispanics, respectively, worked in those professions (BLS, 2014).

FIGURE 3-9

Employed people by occupation, race, and Hispanic or Latino ethnicity, 2013 annual averages. NOTE: People whose ethnicity is identified as Hispanic or Latino may be of any race. Data may not sum to 100 percent due to rounding. SOURCE: BLS, 2014.

Mechanisms

The literature suggests that there are three potential mechanisms through which employment affects health:

1.

Physical aspects of work and the workplace

2.

Psychosocial aspects of work and how work is organized

3.

Work-related resources and opportunities (An et al., 2011; Clougherty et al., 2010)

The nature of work and the conditions of a workplace can increase the risk of injury or illness depending on the type of job. For employees in specific sectors (e.g., air transportation, nursing facilities, using motorized vehicles and equipment, trucking services, hospitals, grocery stores, department stores, food services), the risk of occupational injury is higher (An et al., 2011). This is especially true for operators, laborers, fabricators, and laborers (An et al., 2011). Occupational health can also be shaped by the physical nature of the tasks involved in a given work setting. For example, the health impact of a job that requires intense, laborious physical activity will be different than of a job in which the tasks are primarily sedentary. There is also emerging evidence suggesting that women working hourly jobs bear a larger burden due to hazardous conditions in the workplace than their male counterparts on outcomes such as hypertension, the risk of injury, injury severity, rates of absenteeism, and the time to return to work after illness (Clougherty et al., 2010; Hill et al., 2008).

The psychosocial aspects and organization of one's job can influence both mental and physical health. The factors that make up this pathway can include work schedules, commute to work, degree of control in work, the balance between effort and rewards, organizational justice, social support at work, and gender and racial discrimination (An et al., 2011). Longer commute times specifically affect low-income populations, as the cost burden of commuting for the working poor is much higher than for other workers and makes up a larger portion of their household budgets (Roberto, 2008).

The resources and opportunities associated with work can have lasting implications for health. Higher-paying jobs are more likely than lower-paying jobs to provide workers with safe work environments and offer benefits such as health insurance, workplace health promotion programs, and sick leave (An et al., 2011). Box 3-6 briefly describes a program that aims to increase “green” employment opportunities for underserved individuals in a community.

BOX 3-6

Green Jobs Central Oklahoma.

Health Systems and Services

Health care is arguably the most well-known determinant of health, and it is traditionally the area where efforts to improve health have been focused (Heiman and Artiga, 2015). Over the past few decades there has been a paradigm shift that reflects “health” care over “sick” care. The idea is to promote access to effective and affordable care that is also culturally and linguistically appropriate. Health care spans a wide range of services, including preventative care, chronic disease management, emergency services, mental health services, dental care, and, more recently, the promotion of community services and conditions that promote health over the lifespan.

Although screening, disease management, and clinical care play an integral role in health outcomes, social and economic factors contribute to health outcomes almost twice as much as clinical care does (Heiman and Artiga, 2015; Hood et al., 2016; McGinnis et al., 2002; Schroeder, 2007). For example, by some estimates, social and environmental factors proportionally contribute to the risk of premature death twice as much as health care does (Heiman and Artiga, 2015; McGinnis et al., 2002; Schroeder, 2007). That being said, in March 2002, the Institute of Medicine released a report that demonstrated that even in the face of equal access to health care, minority groups suffer differences in quality of health. The noted differences were lumped into the categories of patient preferences and clinical appropriateness, the ecology of health systems and discrimination, bias, and stereotyping (IOM and NRC, 2003). Our health systems are working to better understand and address these differences and appreciate the importance of moving beyond individualized care to care that affects families, communities, and populations (Derose et al., 2011). This new focus on improving the health of populations has been accompanied by a welcome shift from siloed care to a health care structure that is interprofessional, multisectoral and considers social, economic, structural and other barriers to health (NASEM, 2016).

Arriving at the place of shared understanding concerning the health care needs of individuals, families, and communities has required taking a broader look at health. The triple aim, a framework that aims to optimize health system performance, has helped conceptualize this look, bringing to the forefront the elements that matter most, considering per capita cost, improving the health care experience for patients, and focusing on population health (Stiefel and Nolan, 2012). In addition to helping create new health care opportunities, the Patient Protection and Affordable Care Act (ACA) has helped mitigate the challenge of access to care. According to the U.S. Centers for Disease Control and Prevention (CDC), the proportion of people in 2015 without health insurance had dropped below 10 percent (Cohen et al., 2016c).

Continuing the momentum of improving access to culturally competent and linguistically appropriate care will be a crucial step to improving the health of populations. Culturally and linguistically appropriate care includes high-quality care and clear communication regardless of socioeconomic or cultural background (Betancourt and Green, 2010). There is limited research studying whether there is a link between culturally appropriate care and health outcomes, but data do exist that indicate that behavioral and attitudinal elements of cultural competence facilitate higher-quality relationships between physicians and patients (Paez et al., 2009). Making cultural competency training a part of the all types of providers' (e.g., physicians, nurses, medical assistants, dentists, pharmacists, social workers, psychologists) education experience, as well as making it a requirement for licensure for providers (Like, 2011), may have the potential to link quality and safety. Continued work is needed to figure out how to translate increased access to care into improved health outcomes and increased health equity.

In light of the ACA's emphasis on access to improving quality, health outcomes, and population health, it makes sense to look at the environments in which patients live.⁷ If the social determinants of health are not addressed in a multi-sectoral approach by educational systems, health systems, communities and others, the country will fall short of the triple aim. The Robert Wood Johnson Foundation's Culture of Health Action Framework has identified action areas meant to work together to address issues of equity, well-being, and improved population health (RWJF, 2015b). Social determinants of health are woven through these action areas. In fact, research shows that social determinants of health play a larger role in health outcomes than do medical advances (Hood et al., 2016; Woolf et al., 2007).

Disparities

While some disparities in access to care have been narrowing, gaps persist among certain groups of the population. For example, the gaps in insurance that existed between poor and nonpoor households and between African Americans and whites or Hispanics and whites decreased between 2010 and 2015 (AHRQ, 2016). However, systematic differences in access to care still exist and negatively affect poor households and racial and ethnic minority groups, including Hispanics and African Americans (NCHS, 2016) (see Figure 3-10). In fact, in 2013 people living below the federal poverty level had worse access to care than people in high-income households across all access measures⁸ (NCHS, 2016). People living in low-income households are at an elevated risk of poor health, and access to care is vital for this vulnerable population. The ACA authorized states to expand Medicaid coverage to adults with low incomes up to 138 percent of the poverty level. From 2013 to 2014, the percent of adults who were uninsured declined in all states, with the decline in the number of uninsured being greater in the states that opted to expand their Medicaid programs (NCHS, 2016).

FIGURE 3-10

Percent of adults ages 18–64 with no health insurance coverage by race and Hispanic origin: United States, 1999–June 2015. SOURCE: NCHS, 2016.

Racial and ethnic disparities in mental health services exist as well. Members of racial and ethnic minority groups are less likely than whites to receive necessary mental health care and more likely to receive poor-quality care when treated. Specifically, minority patients are less likely than whites to receive the best available treatments for depression and anxiety (McGuire and Miranda, 2008). Among the barriers to access to care, the lack of culturally competent care can be a barrier for specific racial and ethnic groups who face stigma due to cultural norms (Wahowiak, 2015).

The health care system has an important role to play in addressing the social determinants of health. At the community level, it can partner with community-based organizations and explore locally based interventions (Heiman and Artiga, 2015), creating payment models that take into account social determinants and implementing service delivery models that lend themselves to more community engagement and intervention. Health care systems can center equity by involving the community in decision making, allocating resources to act on the determinants of health in mind, and increasing community-based spending (Baum et al., 2009). Communities can be viewed as places of change for health systems, allowing for work both at micro and macro levels. (See Box 3-7 for an example of a community-based health system.) Cost-effective interventions to reduce health disparities and promote health equity should be recognized and explored, including attention to the structural barriers that affect access to health services.

BOX 3-7

Kokua Kalihi Valley Comprehensive Family Services.

Housing

Housing, as a social determinant of health, refers to the availability or lack of availability of high-quality, safe, and affordable housing for residents at varying income levels. Housing also encompasses the density within a housing unit and within a geographic area, as well as the overall level of segregation and diversity in an area based on racial and ethnic classifications or SES. Housing affects health because of the physical conditions within homes (e.g., lead, particulates, allergens), the conditions in a multi-residence structure (an apartment building or town home), the neighborhoods surrounding homes, and housing affordability, which affects financial stability and the overall ability of families to make healthy choices (Krieger and Higgins, 2002). The Center for Housing Policy has outlined 10 hypotheses on how affordable housing can support health improvement (Maqbool et al., 2015). These range from affordable housing freeing up resources for better nutrition and health care spending to stable housing reducing stress and the likelihood of poor health outcomes (e.g., for mental health or the management of chronic disease).

There is substantive evidence that the physical conditions in homes are important contributors to health outcomes (Cox et al., 2011; WHO, 2006). The World Health Organization (WHO) assessed the evidence in 2005 and found that sufficient evidence was available to estimate the burden of disease for physical factors, such as temperature extremes; chemical factors, such as environmental tobacco smoke and lead; biological factors, such as mold and dust mites; and building factors associated with injuries and accidents. Since 2005 research has added to the areas where the WHO found some, but not sufficient, evidence to estimate the burden of disease, including more clarity on the relationship between rodent allergens and asthma (Ahluwalia et al., 2013; American College of Allergy Asthma and Immunology, 2014; Sedaghat et al., 2016). Data from the National Health and Nutrition Examination Survey show a decrease in blood lead levels between 1976 and 2002, with a steep drop between 1978 and 1988, probably due to lead being phased out of gasoline, and later a more gradual decrease, perhaps due to a reduction in the use of lead-based paint in housing (Jacobs et al., 2009). Conditions in multiunit residential buildings, including whether indoor smoking is permitted, are another dimension of housing that can affect health outcomes. Box 3-8 introduces the revitalization efforts of one multiunit apartment complex in a community in Minnesota.

BOX 3-8

Renovating the Rolling Hills Apartment Complex, St. Paul, Minnesota.

Neighborhoods matter for a number of reasons, including their influence on physical safety and access to opportunity. The U.S. Department of Housing and Urban Development's (HUD's) Moving to Opportunity program was a 10-year demonstration program, which provided grants to public housing authorities in Baltimore, Boston, Chicago, Los Angeles, and New York City to implement an experimental study—a randomized controlled trial of a housing intervention. Housing authorities

randomly selected experimental groups of households with children [to] receive housing counseling and vouchers that must be used in areas with less than 10 percent poverty. Families chosen for the experimental group receive tenant-based Section 8 rental assistance that helps pay their rent, as well as housing counseling to help them find and successfully use housing in low-poverty areas. Two control groups are included to test the effects of the program: one group already receiving Section 8 assistance and another just coming into the Section 8 program. (HUD, n.d.)

Homeless Populations

For homeless people, a lack of stable housing contributes to disparities in the social determinants. In addition to having direct ties with lack of employment and income, a lack of housing is also associated with greater barriers to education, lower levels of food security, and reduced public safety. Compared to the overall population, homeless people have shorter life expectancies, which are attributable to higher rates of substance abuse, infectious disease, and violence (Baggett et al., 2013). Infectious diseases—including HIV, tuberculosis, and heart disease—have all been linked to shorter life expectancies among homeless people (Fazel et al., 2014). Other studies have found drug overdose, cancer, and heart disease to be the greatest causes of death among the homeless, with greater barriers to and lower rates of screening, diagnosis, and treatment as contributing factors (Baggett et al., 2013).

The Changing American City

Neighborhoods generally change slowly, but urban neighborhoods are seeing dramatic shifts in demographics and property value and over time are becoming more segregated by income (Zuk et al., 2015). Gentrification—the process of renewal and rebuilding, which precedes the influx of new, more affluent residents—is a trend that is being observed in urban centers around the country (McKinnish et al., 2010; Phillips et al., 2014; Sturtevant, 2014). While the literature linking the process of gentrification to health outcomes is not definitive, there is substantial evidence that connects displacement and health outcomes (Zuk et al., 2015). Displacement can occur as a direct result of a policy or program (Freeman and Braconi, 2002), because of recent development and property value increases in an area, or as a result of exclusion from a property for various reasons (Levy et al., 2006).

Displacement has major implications for housing, other social determinants, and the health of communities. According to the CDC, displacement exacerbates health disparities by limiting access to healthy housing, healthy food options, transportation, quality schools, bicycle and walk paths, exercise facilities, and social networks (CDC, 2013). Displacement leads to poor housing conditions, including overcrowding and exposure to substandard housing with hazardous conditions (e.g., lead, mold, pests) (Phillips et al., 2014). Displacement can result in financial hardship, reducing disposable income for essential goods and services. This can have a negative impact on the health of the displaced population, with income being a significant determinant of health (CDC, 2013).

Physical Environment

The physical environment reflects the place, including the human-made physical components, design, permitted use of space, and the natural environment. Specific features of the physical or built environment include, but are not limited to, parks and open space, what is sold and how it is promoted, how a place looks and feels, air, water, soil, and arts and cultural expression (Davis et al., 2016). All of these physical factors shape the safety, accessibility, and livability of any locale, thus providing the context in which people live, learn, work, and play. This has direct implications for health. The physical environment contributes to 10 percent of health outcomes (Remington et al., 2015). Additionally, 40 percent of health outcomes depend on social and economic factors, which are intricately tied to the features of the physical environment (Remington et al., 2015). Inequities observed between the different physical environments of states, towns, and neighborhoods contribute to disparate health outcomes among their populations.

Exposure to a harmful physical environment is a well-documented threat to community health. Such threats include environmental exposures such as lead, particulate matter, proximity to toxic sites, water contamination, air pollution, and more—all of which are known to increase the incidence of respiratory diseases, various types of cancer, and negative birth outcomes and to decrease life expectancy (Wigle et al., 2007). Low-income communities and communities of color have an elevated risk of exposure to environmental hazards (Evans and Kantrowitz, 2002). In response to these inequities, the field of environmental justice seeks to achieve the “fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income, with respect to the development, implementation, and enforcement of environmental laws, regulations, and policies” (EPA, 2016). Emerging considerations for low-income communities include the resulting gentrification and potential displacement of families when neighborhoods undergo revitalization that is driven by environmental clean-up efforts (Anguelovski, 2016).

Built Environment: Parks and Green Space

Access to green space has been demonstrated to positively affect health in many contexts. Such green space includes both parks and observable greenery. Living in the presence of more green space is associated with a reduced risk of mortality (Villeneuve et al., 2012). Nature has been shown to relieve stress and refocus the mind. Spending time in parks has been shown to improve mental health (Cohen et al., 2016a; Sturm and Cohen, 2014).

Beyond their benefits to mental health and reductions in stress, parks provide opportunities for increased physical activity. Local parks departments manage more than 108,000 outdoor public park facilities across the nation, many of them containing open space, jogging paths, and exercise equipment (Cohen et al., 2016b). According to Cohen et al., the average neighborhood park of 8.8 acres averaged 1,533 hours of active use per week (Cohen et al., 2016b). Individuals who are not as physically active face a greater risk of heart disease, diabetes, and cancer (James et al., 2016). In fact, about 9 percent of premature deaths in the United States are attributable to inactivity (Lee et al., 2012).

The usage of neighborhood parks and the associated health benefits are not equally distributed across communities. Research shows that recreational facilities are much less common in low-income and minority communities, though parks are more evenly distributed (Diez Roux et al., 2007). Moreover, the size and quality of park facilities vary based on race and income (Abercrombie et al., 2008). Accordingly, in low-income communities, residents are less likely to use parks (Cohen et al., 2016a). Beyond race and income, other disparities exist in park use. While seniors represent 20 percent of the population, they account for only 4 percent of park users (Cohen et al., 2016a). Proximity to park facilities also matters, as evidenced by a decrease in physical activity by more than half when distance between one's home and the park doubles (Giles-Corti and Donovan, 2002).

Food Environment

The food environment refers to the availability of food venues such as supermarkets, grocery stores, corner stores, and farmer's markets, including food quality and affordability. In communities described as food deserts, there is limited access to affordable and quality food. When there are fewer supermarkets, fruit and vegetable intake is lower, and prices are higher (Powell et al., 2007). This makes achieving a healthy diet difficult for local residents. Research indicates that a poor diet is associated with the development of cancer, diabetes, hypertension, birth defects, and heart disease (Willett et al., 2006).

The distribution of supermarkets is not equitable in the United States. Neighborhoods housing residents of lower socioeconomic status often have fewer supermarkets. Discrepancies also exist between racial and ethnic groups (Powell et al., 2007). Underserved communities turn to small grocery or corner stores to serve their food needs, but these businesses rarely provide the healthy selection offered by larger supermarkets. Moreover, food is most often higher priced in such stores.

Access to and the density of alcohol outlets are also associated with health outcomes in communities. In local areas where liquor store density is higher, alcohol consumption rates in the community are also higher (Pereiram et al., 2013). Alcoholism has been linked to diseases such as cancer, anemia, and mental illnesses. Moreover, alcohol outlets can serve as nuisance businesses, with their clientele bothering others in the neighborhood, decreasing the sense of security, and detracting from social cohesion. There is also evidence that links high-density alcohol outlet areas with higher rates of crime and substance use. In urban environments, a higher concentration of liquor stores is found in low-income, African American, and Hispanic communities, contributing to an elevated risk of alcohol-associated disorders in these neighborhoods (Berke et al., 2010).

A Changing Climate

Climate change has become a public health concern (Wang and Horton, 2015). There is a growing recognition that the physical environment is undergoing changes caused by human activity, such as through the production of greenhouse gases (IPCC, 2014). Human health is intricately linked to the places where we live, learn, work, and play. The air we breathe, the surrounding temperature, the availability of food, and whether there is access to clean water are all important ingredients to a healthy life, and the changing climate will affect all of these areas (Luber et al., 2014).

Not only do polluting emissions make air quality worse in the short term, but climate change itself will worsen air quality. Poor air quality exacerbates previous health conditions such as asthma and chronic obstructive pulmonary disease, and air pollution is associated with cardiovascular disease and many other illnesses. The changing climate is also causing a shift in seasons, which can affect pollen production and therefore seasonal allergies. Overall, with the changing climate there will be more extreme weather events such as increasing drought, vulnerability to wildfires, floods, hurricanes, and winter storms—all with subsequent health impacts from displacement, stress, or primary physical harm. The changing temperature is even having an impact on infectious diseases. New infectious diseases that spread via a vector, such as a tick or mosquito, have the potential to emerge in previously non-affected areas. There is also a risk for an increase in food-related and waterborne illness caused by the changing temperatures and the survival of various infectious agents. Food insecurity, which is already a challenge in many locations, is at risk of worsening due to higher food prices, poorer nutritional content, and new challenges with distribution.

Although climate change will affect everyone, certain communities and groups will be more vulnerable to these effects. People with preexisting medical conditions, children, elderly populations, and low-income groups are at increased risk for poor outcomes. Existing health disparities that are due to social, economic, and environmental factors have the potential to be even more affected by climate change.

However, climate change also presents a significant opportunity. Given the existential threat to humanity, there is now a great deal of momentum to mitigate and adapt to climate change. Companies are pursuing new business opportunities, governments are forming international agreements, and policies are being implemented at the national, sub-national, state, regional, and local levels to affect change. Many of these policies to adapt to and mitigate climate change are also the key components in creating healthier, more equitable, and resilient communities. There are many co-benefits, and the policies, if implemented correctly, have the potential to significantly improve health outcomes and reduce health disparities (Rudolph et al., 2015). Examples of climate change mitigation and adaptation policies with co-benefits to build healthier, more equitable places include

• Improving access to public transit;
• Promoting flexible workplace transit;
• Creating more complete streets for better pedestrian and bicycle use;
• Implementing urban greening programs;
• Reducing urban heat islands through green space, cool roofs, and cool pavements;
• Promoting sustainable food systems and improved access;
• Building more walkable, dense, affordable housing and amenities;
• Reducing greenhouse gases;
• Promoting weatherizing homes, energy efficiency, and green buildings; and
• Greening fleets and reducing emissions.

Climate change will affect the physical environment in unprecedented ways. To mitigate and adapt to climate change will require multi-sector collaboration and approaches to effect systems change. Many of the same multi-sector partners required to address the social determinants of health also are already partnering on related climate change work in their communities, creating a substantial opportunity for change (see Box 3-9 for an example of a community engaged in climate change–related work).

BOX 3-9

A Community Addressing Climate Change, Food Insecurity, and Improving Health Equity—Achieving Co-Benefits.

Transportation

In the social determinants of health literature, transportation is typically discussed as a feature of the physical (or built) environment (TRB and IOM, 2005). This report highlights transportation as a separate determinant of health because of its multifaceted nature: pollution and greenhouse gas production; motor vehicle–related deaths and injuries; mobility and access to employment and vital goods and services; and active transportation. Transportation consists of the network, services, and infrastructure necessary to provide residents with the means to get from one place to another (Davis et al., 2016), and it is also vital to accessing goods, services (including health and social services), social networks, and employment. If designed and maintained properly, transportation facilitates safe mobility and is accessible to all residents, regardless of geographic location, age, or disability status. However, current research suggests that transportation costs are a barrier to mobility for households in poverty, which are disproportionately represented by African Americans and Hispanics (FHWA, 2014). Long commute times and high transportation costs are significant barriers to employment and financial stability (Roberto, 2008). Brookings researchers have concluded, based on analyses of census data, that the suburbanization of poverty is disproportionately affecting proximity to jobs for poor and minority populations as compared with their nonpoor and white peers (Kneebone and Holmes, 2015; Zimmerman et al., 2015).

Transportation presents unevenly distributed negative externalities, including air pollution, noise, and motor vehicle–related injuries and deaths that are more prevalent in low-income and minority communities with poor infrastructure (Bell and Cohen, 2014; US DOT, 2015). Low-income and minority populations are more likely to live near environmental hazards, including transportation-related sources of pollution and toxic emissions such as roadways, bus depots, and ports (McConville, 2013; NEJAC, 2009; Perez et al., 2012). See, for example, Shepard (2005/2006) on the high concentration of bus depots in West Harlem, which also has one of the highest rates of asthma in the nation. The Regional Asthma Management and Prevention collaborative, in Oakland, California, and the California Environmental Protection Agency's Air Resources Board, among others, have described the evidence on the relationship between asthma and exposures to diesel and other air pollution (California EPA, 2016; RAMP, 2009).

Active transportation—the promotion of walking and cycling for transportation complemented by public transportation or any other active mode—is a form of transportation that reduces environmental barriers to physical activity and can improve health outcomes (Besser and Dannenberg, 2005; Dannenberg et al., 2011). Since the mid-20th century, road design and transportation planning have centered on the automobile, with multiple and interconnected consequences for health and equity (IOM, 2014).

The relationship between physical activity and health is well established and was summarized by the U.S. Surgeon General's 1996 report Physical Activity and Health (HHS, 1996) and the U.S. Task Force on Community Preventive Services (U.S. Task Force on Community Preventive Services, 2001). The evidence on the relationship among active transportation, physical activity, and health has been accumulating more recently. In a 2005 report from the Transportation Research Board and the Institute of Medicine, the authoring committee stated that “[r]esearch has not yet identified causal relationships to a point that would enable the committee to provide guidance about cost beneficial investments or state unequivocally that certain changes to the built environment would lead to more physical activity or be the most efficient ways of increasing such activity” (TRB and IOM, 2005, p. 10). Since then, Pucher et al. (2010) found “statistically significant negative relationships” between active travel (walking and cycling) and self-reported obesity as well as between active travel and diabetes (Pucher et al., 2010).

McCormack and Shiell conducted a systematic review of 20 cross-sectional studies and 13 quasi-experimental studies and concluded that most associations “between the built environment and physical activity were in the expected direction or null” (McCormack and Shiell, 2011). They also found that physical activity was considerably influenced by “land use mix, connectivity and population density and overall neighborhood design” and that “the built environment was more likely to be associated with transportation walking compared with other types of physical activity including recreational walking” (McCormack and Shiell, 2011).

CDC has developed a set of transportation recommendations that address all of the facets described above and has also developed a Transportation Health Impact Assessment Toolkit.⁹ The CDC and the U.S. Department of Transportation (DOT) have also developed a Transportation and Health Tool to share indicator data on transportation and health.¹⁰

There have been multiple national initiatives in the past two to three decades aiming to improve livability and sustainability in places across the United States, and transportation equity is a mainstay of much of this work. (See Box 3-10 for an example of a regional transportation planning agency that seeks to improve access to transportation.) Initiatives have ranged from the federal Sustainable Communities Partnership,¹¹ launched by the DOT, HUD, and the U.S. Environmental Protection Agency in 2009 to help U.S. communities “improve access to affordable housing, increase transportation options, and lower transportation costs while protecting the environment,” to Safe Routes to School, which aims to improve children's safety while walking and riding bicycles.¹²

BOX 3-10

The Nashville Metropolitan Planning Organization.

Social Environment

How the social environment is conceptualized varies depending on the source (Barnett and Casper, 2001; Healthy People 2020, 2016). However, there are common elements identified by the literature that collectively shape a community's social environment as a determinant of health. For the purposes of this report, the social environment can be thought of as reflecting the individuals, families, businesses, and organizations within a community; the interactions among them; and norms and culture. It can include social networks, capital, cohesion, trust, participation, and willingness to act for the common good in relation to health. Social cohesion refers to the extent of connectedness and solidarity among groups in a community, while social capital is defined as the features of social structures (e.g., interpersonal trust, norms of reciprocity, and mutual aid) that serve as resources for individuals and facilitate collective action (Kawachi and Berkman, 2000).

A 2008 systematic review found associations between trust as an indicator of social cohesion and better physical health, especially with respect to self-rated health. Furthermore, it revealed a pattern in which the association between social capital and better health outcomes was especially salient in inegalitarian countries (i.e., countries with a high degree of economic inequity), such as the United States, as opposed to more egalitarian societies (Kim et al., 2008).

The social environment in a community is often measured as it relates to mental health outcomes. For example, social connections between neighbors (i.e., greater social cohesion, social capital, and reciprocal exchanges between neighbors) are protective against depression (Diez Roux and Mair, 2010). Factors such as exposure to violence, hazardous conditions, and residential instability are all associated with depression and depressive symptoms (Diez Roux and Mair, 2010).

It is important to note that high levels of social capital and a strong presence of social networks are not necessarily guarantors of a healthy community. In fact, they can be sources of strain as well as support (Pearce and Smith, 2003). Some studies explore the potential drawbacks of social capital, such as the contagion of high-risk behaviors (e.g., suicidal ideation, injection drug use, alcohol and drug use among adolescents, smoking, and obesity) (Bearman and Moody, 2004; Christakis and Fowler, 2007; Friedman and Aral, 2001; Valente et al., 2004).

Mechanisms

McNeill et al. (2006) postulate that the following are mechanisms by which features of the social environment influence health behaviors:

• Social support and social networks enable or constrain the adoption of health-promoting behaviors; provide access to resources and material goods; provide individual and coping responses; buffer negative health outcomes; and restrict contact to infectious diseases.
• Social cohesion and social capital shape the ability to enforce and reinforce group or social norms for positive health behaviors and the provision of tangible support (e.g., transportation).

The social environment interacts with features of the physical environment at the neighborhood level to shape health behaviors, stress, and, ultimately, health outcomes (Diez Roux and Mair, 2010). For example, a built environment that is poor in quality (i.e., low walkability, fewer parks or open space, unsafe transportation) can contribute to a lack of structural opportunities for social interactions, resulting in limited social networks in a community (Suglia et al., 2016). Other research points to the role of physical activity as a potential pathway by which the social environment affects health outcomes such as obesity (Suglia et al., 2016).

At the community level, an important element of the social environment that can mediate health outcomes is the presence of neighborhood stressors. While the occurrence of stress is a daily facet of life that all people experience, chronic or toxic stress, in which the burden of stress accumulates, is a factor in the expression of disease (McEwen, 2012). Stressful experiences are particularly critical during early stages of life, as evidenced by the adverse childhood experiences study (Felitti et al., 1998), and are associated with abnormal brain development (IOM, 2000; Shonkoff and Garner, 2012). For low-income communities, stressors are salient because of the lack of resources, the presence of environmental hazards, unemployment, and exposure to violence, among other factors (McEwen, 2012; Steptoe and Feldman, 2001). (See Box 3-11 for an example of a community working to combat these stressors.) This applies as well to children in low-income households, who are more likely to experience multiple stressors that can harm health and development (Evans and Kim, 2010), mediated by chronic stress (Evans et al., 2011).

BOX 3-11

Cowlitz Community Network.

Chronic stress due to adverse neighborhood and family conditions has been linked to the academic achievement gap, in which children living in poverty fall behind those in better-resourced neighborhoods (Evans et al., 2011; Zimmerman and Woolf, 2014). Furthermore, stress and poor health in childhood are associated with decreased cognitive development, increased tobacco and drug use, and a higher risk of cardiovascular disease, diabetes, depression, and other conditions (County Health Rankings, 2016).

Public Safety

Public safety and violence are significant, intertwined social determinants of health, but they are also each significant indicators of health and community well-being in their own right. Public safety refers to the safety and protection of the public, and it is often characterized as the absence of violence in public settings (Davis et al., 2016). Since the late 1960s, homicide and suicide (another form of violence) have consistently ranked among the top leading causes of death in the United States (Dahlberg and Mercy, 2009).

Violent victimization affects health by causing psychological and physical injury, which can lead to disability and, in some cases, premature death. Beyond the risk of injury and death, violent victimization also has far-reaching health consequences for individuals, families, and neighborhoods. Furthermore, research shows that simply being exposed to violence can have detrimental effects on physical and psychological well-being (Felitti et al., 1998; Pinderhughes et al., 2015). Violent victimization and exposure to violence have been linked to poor health outcomes, including chronic diseases (e.g., ischemic heart disease, cancer, stroke, chronic obstructive lung disease, diabetes, and hepatitis), asthma-related symptoms, obesity, posttraumatic stress disorder, depression, and substance abuse (Prevention Institute, 2011). For youth in schools, the data suggest that there is a cumulative effect of exposure to violence, with multiple exposures to violence being associated with higher rates of youth reporting their health as “fair” or “poor” (Egerter et al., 2011a). There is also research that indicates a link between neighborhood crime rates and adverse birth outcomes such as preterm birth and low birth weight (Egerter et al., 2011a).

Violence and the fear of violence can negatively affect other social determinants that further undermine community health. Violence rates can lead to population loss, decreased property values and investments in the built environment, increased health care costs, and the disruption of the provision of social services (Massetti and Vivolo, 2010; Velez et al., 2012). In addition, violence in communities is associated with reduced engagement in behaviors that are known to promote health, such as physical activity and park use (Cohen et al., 2010).

The perception of safety is a key indicator of violence in a community that is associated with health. For example, people who describe their neighborhoods as not safe are almost three times more likely to be physically inactive than those who describe their neighborhood as extremely safe (Prevention Institute, 2011). The perception of safety is also important for mental health. There is research that suggests that perceived danger and the fear of violence can influence stress, substance use, anger, anxiety, and feelings of insecurity—all of which compromise the psychological well-being of a community (Moiduddin and Massey, 2008; Perkins and Taylor, 1996). At the community level, fear of crime and violence can undermine social organization, social cohesion, and civic participation—all key elements in a social environment that is conducive to optimal health (Perkins and Taylor, 1996). Low perception of safety can also undermine the efforts of a community to improve the built environment through the availability of parks and open space to promote physical activity (Cohen et al., 2016a; Weiss et al., 2011).

Violence is not a phenomenon that affects all communities equally, nor is it distributed randomly. The widespread disparity in the occurrence of violence is a major facet of health inequity in the United States. Low-income communities are disproportionately affected by violence and by the many effects that it can have on physical and mental well-being. The conditions of low-income communities (concentrated poverty, low housing values, and high schools with low graduation rates among others), foster violence and put residents at an increased risk of death from homicide (Prevention Institute, 2011). This holds true for other types of violence as well. Living in poor U.S. neighborhoods puts African American and white women at an increased risk for intimate partner violence compared with women who reside in areas that are not impoverished (Prevention Institute, 2011).

Criminologists attribute the disparities in neighborhood violence not to the kinds of people living in certain neighborhoods but to the vast differences in social and economic conditions that characterize communities in the United States. Some refer to these differences as “divergent social worlds” and the “racial–spatial divide” (Peterson and Krivo, 2010). This is because there are specific racial and ethnic groups, such as African Americans, Hispanics, and Native Americans, who are vastly overrepresented in communities that are at risk for violence because of the social and economic conditions. Residential segregation, which has been perpetuated by discriminatory housing and mortgage market practices, affects the quality of neighborhoods by increasing poverty, poor housing conditions, and social disorder and by limiting economic opportunity for residents (Prevention Institute, 2011).

As a result of the racial–spatial divide in community conditions, the violent crime rate in majority nonwhite neighborhoods is two to five times higher than in majority white neighborhoods. This is especially true for youth of color, particularly males. Overall homicide rates among 10- to 24-year-old African American males (60.7 per 100,000) and Hispanic males (20.6 per 100,000) exceed that of white males in the same age group (3.5 per 100,000) (Prevention Institute, 2011). African American males 15 to 19 years old are six times as likely to be homicide victims as their white peers (Prevention Institute, 2011). More specifically, African American males ages 15 to 19 are almost four times as likely to be victims of firearm-related homicides as white males (Prevention Institute, 2011). In terms of exposure to violence, African American and Hispanic youth are more likely to be exposed to shootings, riots, domestic violence, and murder than their white counterparts (Prevention Institute, 2011). This has major implications for trauma in communities that are predominantly African American or Hispanic. Native American communities also suffer from a disproportionately high violent crime rate that is two to three times higher than the national average (Prevention Institute, 2011). Box 3-12 briefly describes a public health–oriented model to address violence in communities.

BOX 3-12

The Cure Violence Health Model.

Child Abuse and Neglect

Child abuse and neglect are two important measures of community violence that can affect physical and mental health. The Institute of Medicine and the National Research Council published a report (2014) that cited abuse and neglect during childhood as a contributor to the following health-related outcomes: problems with growth and motor development, lower self-reported health, gastrointestinal symptoms, obesity, delinquency and violence, and alcohol abuse (IOM and NRC, 2014).

In 1998, Felitti and colleagues published a pivotal study which demonstrated a link between adverse childhood experiences and the leading causes of death in adults at the time. The authors found a strong, graded association between the amount of exposure to abuse or household dysfunction and multiple risk factors (e.g., smoking, severe obesity, physical inactivity, depressed mood, and suicide attempts) for several leading causes of death (Felitti et al., 1998). Child abuse and neglect not only affect health directly, they also affect outcomes within the other social determinants of health, such as education, work, and social relationships (IOM and NRC, 2014). While the overall rates of child maltreatment have been declining since 2002, rates are still much higher for African American (14.3 per 1,000), Native American (11.4 per 1,000), multiracial (10.1 per 1,000), and Hispanic (8.6 per 1,000) children than for white children (7.9 per 1,000) (IOM and NRC, 2014; Prevention Institute, 2011). Child abuse and neglect are often accompanied by family stressors and other forms of family violence (IOM and NRC, 2014). As discussed above, the conditions of concentrated poverty in a neighborhood are associated with violence incidence. According to the Prevention Institute, the higher the percentage of families living below the federal poverty level in a neighborhood, the higher the rate of child maltreatment (Prevention Institute, 2011).

Hate Crimes

Hate crimes, which may or may not involve physical violence, are often motivated by some bias against a perceived characteristic.¹³ An FBI analysis of single-bias hate crime incidents revealed that in 2014, 48.3 percent of victims were targeted because of the offender's bias against race, and 62.7 percent of those victims were targeted because of anti-African American bias (UCR, 2015). Among hate crimes motivated by bias toward a particular ethnicity in 2014, almost 48 percent of the victims were targeted because of anti-Hispanic bias (UCR, 2015).

As is the case with other types of violence, exposure to hate crime violence can have pernicious effects on health. For lesbian, gay, bisexual, and transgender (LGBT) persons specifically, exposure to hate crimes at the community level has been linked to increased rates of suicide among youth, marijuana use, and all-cause mortality (Duncan and Hatzenbuehler, 2014; Duncan et al., 2014; Hatzenbuehler et al., 2014). Discrimination in general, which by definition is the driving factor behind the perpetration of hate crimes, has been shown to affect the health of individuals and communities. Whether it be perceived discrimination in everyday encounters or systemic discrimination in housing policies, this type of unequal treatment has been associated with major depression, psychological distress, stress, increased pregnancy risk, mortality, hypertension, and more health-related outcomes (Dolezsar et al., 2014; Galea et al., 2011; Kessler et al., 1999; Padela and Heisler, 2010; Sims et al., 2012).

Criminal Justice System

The criminal justice system is a key actor, setting, and driver of public safety as it relates to health equity. Specifically, the criminal justice system's role in the mass incarceration of racial and ethnic minorities is an important factor when examining the social determinants of health (NRC, 2014). The past 40–50 years have seen a large-scale expansion of incarceration, which has had lasting effects on families and communities (Cloud, 2014; Drake, 2013). This expansion has affected racial and ethnic minority groups, and particularly men (Drake, 2013). Research suggests that disproportionately more Hispanics and African Americans are confined in jails and prisons than would be predicted by their arrest rates and that Hispanic and African American juveniles are more likely than white juveniles to be referred to adult court rather than juvenile court (Harris, 2009).

When those who were formerly incarcerated are released back into their communities, successful reentry is hindered by a number of obstacles, such as stigma, limited employment and housing opportunities, and the lack of a cohesive social network (Lyons and Pettit, 2011). All of these factors are vital to achieving optimal health, and for communities with high rates of incarceration, the absence of these opportunities can lead to a diminished capacity to combat crime and mobilize for resources (Clear, 2008). It is important to examine the patterns and effects of mass incarceration because it not only affects the health of incarcerated populations but also has a detrimental effect on multiple determinants of health in communities. Mass incarceration has contributed to the breakdown of educational opportunities, family structures, economic mobility, housing options, and neighborhood cohesion, especially in low-income communities of color (Cloud, 2014). Neal and Rick examined U.S. Census data from 1960 to 2010 and found that although great progress was made in closing the black–white education and employment gap up until the 1980s, that progress then came to a halt in large part due to rising incarceration rates (Neal and Rick, 2014). In addition, communities with high levels of incarceration have higher rates of lifetime major depressive disorder and generalized anxiety disorder (Hatzenbuehler et al., 2015).

Wildeman estimated the effects of incarceration on population-level infant mortality rates, and his findings suggest that if incarceration rates remained the same as they were in 1973, the infant mortality rate in 2003 would have been 7.8 percent lower and the absolute African American–white disparity in infant mortality would have been 14.8 percent lower (Wildeman, 2012). A keen understanding of the precise mechanisms by which incarceration affects the health of specific populations and contributes to health inequity is needed to reduce disparities in key health outcomes such as infant mortality.

CONCLUDING OBSERVATIONS

The root causes of health inequity begin with historical and contemporary inequities that have been shaped by institutional and societal structures, policies, and norms in the United States. As discussed in this chapter, these deeply rooted inequities have shaped inequitable experiences of the social and other determinants of health: education, income and wealth, employment, health systems and services, housing, the physical environment, transportation, the social environment, and public safety.

Conclusion 3-2: Based on its review of the evidence, the committee concludes that health inequities are the result of more than individual choice or random occurrence. They are the result of the historic and ongoing interplay of inequitable structures, policies, and norms that shape lives.

These structures, policies, and norms—such as segregation, redlining and foreclosure, and implicit bias—play out on the terrain of the social, economic, environmental, and cultural determinants of health.

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