HEALTH DISPARITIES

For the purposes of this report, health disparities are differences that exist among specific population groups in the United States in the attainment of full health potential that can be measured by differences in incidence, prevalence, mortality, burden of disease, and other adverse health conditions (NIH, 2014). While the term disparities is often used or interpreted to reflect differences between racial or ethnic groups, disparities can exist across many other dimensions as well, such as gender, sexual orientation, age, disability status, socioeconomic status, and geographic location. According to Healthy People 2020, all of these factors, in addition to race and ethnicity, shape an individual's ability to achieve optimal health (Healthy People 2020, 2016). Indeed, the existing evidence on health disparities does reveal differential health outcomes across and within all of the aforementioned identity groups. Health disparities can stem from health inequities—systematic differences in the health of groups and communities occupying unequal positions in society that are avoidable and unjust (Graham, 2004). These are the type of disparities that are reflected in the committee's charge and that will be addressed for the remainder of this report. In this section, we describe health disparities affecting populations across multiple dimensions.

Racial and Ethnic Disparities

Race and ethnicity are socially constructed categories that have tangible effects on the lives of individuals who are defined by how one perceives one's self and how one is perceived by others. It is important to acknowledge the social construction (i.e., created from prevailing social perceptions, historical policies, and practices) of the concepts of race and ethnicity because it has implications for how measures of race have been used and changed over time. Furthermore, the concept of race is complex, with a rich history of scientific and philosophical debate as to the nature of race (James, 2016). Racial and ethnic disparities are arguably the most obstinate inequities in health over time, despite the many strides that have been made to improve health in the United States. Moreover, race and ethnicity are extremely salient factors when examining health inequity (Bell and Lee, 2011; Smedley et al., 2008; Williams et al., 2010). Therefore, solutions for health equity need to take into account the social, political, and historical context of race and ethnicity in this country.

The criteria people use to classify themselves and others racially and ethnically and the attitudes that people hold about race and ethnicity have been changing significantly in the early 21st century. According to the U.S. Census Bureau, 37.9 percent of the population was identified to be racial or ethnic minorities in 2014 (NCHS, 2016). “Minority” populations, which already constitute majorities in some cities and states (e.g., California), will become the majority nationwide within 30 years. By the year 2044, they will account for more than half of the total U.S. population, and by 2060, nearly one in five of the nation's total population will be foreign born (Colby and Ortman, 2014).

For racial and ethnic minorities in the United States, health disparities take on many forms, including higher rates of chronic disease and premature death compared to the rates among whites. It is important to note that this pattern is not universal. Some minority groups—most notably, Hispanic immigrants—have better health outcomes than whites (Lara et al., 2005). This “immigrant paradox” appears to diminish with time spent in the United States, however (Lara et al., 2005). For other indicators, disparities have shrunk, not because of improvements among minorities but because of declines in the health of majority groups. For example, white females have experienced increased death rates due to suicide and alcohol-related diseases. Research suggests that the recent drug overdose epidemic, along with the rise of suicide and alcohol-related diseases, has contributed to the first increase in the national death rate in decades and to the unusual recent decline in life expectancy for white females (Arias, 2016; Case and Deaton, 2015; NCHS, 2016).¹

Although significant progress has been made in narrowing the gap in health outcomes (NCHS, 2016), the elimination of disparities in health has yet to be achieved. Furthermore, this narrowing of health gaps does not hold true for a number of outcomes. Rather, despite overall improvements in health over time, some health disparities persist. This is true with many human immunodeficiency virus (HIV)-related outcomes. For instance, the magnitude of the African American–white disparity in acquired immunodeficiency syndrome (AIDS) diagnoses and mortality has actually grown substantially over time (Levine et al., 2001, 2007).

Infant gestational age, which is an important predictor of morbidity and infant mortality, differs among racial and ethnic groups. The National Center for Health Statistics (NCHS) reports that among the five racial and ethnic groups² measured in the National Vital Statistics Survey (NVSS) in 2014, African American women had the highest percentage of preterm singleton births at 11.1 percent, while Asian or Pacific Islander women had the lowest at 6.8 percent (NCHS, 2016). Within the Hispanic ethnic group, there is considerable variation in health outcomes based on country of origin. For example, the 2014 NVSS findings revealed that Puerto Rican mothers had the highest percentage of preterm singleton births at 9.1 percent, and Cuban mothers the lowest at 7.2 percent (NCHS, 2016).

While national infant mortality rates decreased overall by 14 percent from 2004 to 2014, disparities among racial and ethnic groups persisted (NCHS, 2016). For indigenous populations, infant mortality rates are staggering. Native Americans and Alaska Natives have an infant mortality rate that is 60 percent higher than the rate for their white counterparts (HHS, 2014). In 2013, infants born to African American mothers experienced the highest rates of infant mortality (11.11 infant deaths per 1,000 births), and infants born to Asian or Pacific Islander mothers experienced the lowest rates (3.90 infant deaths per 1,000 births) (NCHS, 2016). In 2015 the percentage of low-birthweight infants rose for the first time in 7 years. For white infants, the rate of low-birthweight infants was essentially unchanged, but for African American and Hispanic infants, the rate increased (Hamilton et al., 2016).

Obesity, a condition which has many associated chronic diseases and debilitating conditions, affects racial and ethnic minorities disproportionately as well. This has major implications for the quality of life and wellbeing for these population groups and their families. From 2011 to 2014, Hispanic children and adolescents ages 2 to 19 had the highest prevalence of obesity in the United States (21.9 percent), and Asians had the lowest (8.6 percent) (NCHS, 2016). Again, there is variation among Hispanics; Mexican Americans suffer disproportionately from diabetes (HHS, 2015).

Heart disease and cancer are the leading causes of death across race, ethnicity, and gender (see Table 2-1). African Americans were 30 percent more likely than whites to die prematurely from heart disease in 2010, and African American men are twice as likely as whites to die prematurely from stroke (HHS, 2016b,d). The U.S. Centers for Disease Control and Prevention (CDC) reports that nearly 44 percent of African American men and 48 percent of African American women have some form of cardiovascular disease (CDC, 2014a). Moreover, African American and American Indian/Alaska Native females have higher rates of stroke-related death than Hispanic and white women (Blackwell et al., 2014).

TABLE 2-1

Leading Causes of Death by Race, Ethnicity, and Gender, 2013.

Homicide-related deaths, another instance of health disparities, are highest for African American men (4.5 percent) and are at least 2 percent for American Indian/Alaska Native and Hispanic men. The rate of suicide is highest for male American Indians/Alaska Natives, who are also more likely than other racial and ethnic groups to die by unintentional injury (12.6 percent of all deaths) (CDC, 2013d).

It is important to be cautious with data on disparities in poverty, obesity, and diabetes for several reasons. First, surveillance and other data are adequate at capturing black–white disparities in part because of their large sample sizes. Other groups, however, are not studied in as much detail because their sample sizes can be small. Moreover, heterogeneous groups may be folded together—for example, Native Americans across tribes, rural and urban areas, or Pacific Islanders and Asians as one group—which may mask differences in poverty, obesity, and diabetes (Bauer and Plescia, 2014; Holland and Palaniappan, 2012). For Hispanics, an ethnic group among which there is substantial heterogeneity by country of origin, many data sources report health outcomes for the entire population, despite evidence for within-group variation on important outcomes such as HIV (Garcia et al., 2015). Relative to black–white disparities, the literature examining disparities across other racial and ethnic populations is extremely limited. Considering the significant growth of minority populations in the United States, the insufficient knowledge base to date about the health conditions of a number of these groups presents a serious challenge to understanding and addressing health disparities among specific populations.

ADDRESSING HEALTH INEQUITY IN UNIQUE POPULATIONS

In the sections that follow, the committee discusses in some detail health disparities that affect several populations unique for various reasons ranging from data challenges (e.g., one group is severely underrepresented in public health data collection) to mental health considerations (e.g., one group experiences posttraumatic stress disorder (PTSD) at a rate much higher than the average). Community-based solutions for these population groups—Native Americans; female gender; lesbian, gay, bisexual, transgender (LGBT) individuals; individuals with disabilities; and veterans—will require attention to unique needs and assets identified by members of those communities. For example, communities that are focusing on addressing health disparities among people with disabilities, could include such approaches as universal design (accessible to all) and maximizing the opportunities offered by technologic innovations, such as telemedicine.

Native American Health

Why Are Native Americans a Unique Population for Health Equity?

Native Americans, or American Indians and Alaska Natives, are a significant population for health equity considerations, especially at the community level. An extremely heterogeneous population, the 5.4 million Native Americans make up about 2 percent of the total population living in the United States, with 44 percent identifying as at least one other race (Norris et al., 2012). There are 567 federally recognized Native American tribes in the United States (GPO, 2016a) and many more that are not recognized by the government. U.S. Census estimates reveal that the majority of people who identify as Native American (78 percent) live outside of regions that are considered traditional Native American areas³ (Norris et al., 2012).

Native Americans have a unique historical and legal background in the United States (see Appendix A for more detail on the historical and legal context), which provides the basis for the federal government's trust obligation to Native American tribes. Unlike other racial and ethnic minority groups in this country, Native Americans possess legal rights to federal health care services. Despite these legal rights, the current state of health among this population is starkly worse than its counterparts in large part due to historical and legal contexts and the subsequent conditions of Native American communities. Furthermore, the body of literature on Native Americans has not been sufficient for a number of reasons, including small sample sizes, the heterogeneity of the population, and racial misclassification on disease registries and death certificates (Jim et al., 2014).

Health Disparities Among Native Americans

Although the creation of the Indian Health Service (IHS) and a trend toward self-determination have contributed to improvement of Native American health across many areas, including infectious disease prevention and sanitation (Rhoades and Rhoades, 2014), racial and ethnic health disparities have persisted for this population. The National Interview Health Survey revealed that 13.2 percent of Native Americans report being in fair or poor health, compared to only 9.8 percent of the total population (Adams and Benson, 2015).

Mortality Overall, mortality rates for Native Americans are almost 50 percent higher than that of their white counterparts (Bauer and Plescia, 2014). Additionally, Native Americans have an infant mortality rate that is 1.5 times the rate of whites (Mathews et al., 2015). While research shows that whites experienced a significant decline in all-cause mortality rates from 1990 to 2009, Native Americans did not (Espey et al., 2014).

Burden of diseases The health and overall well-being of Native Americans reflect a higher risk and higher rates of chronic diseases when compared to other racial and ethnic groups. For example, Native Americans are twice as likely to have diabetes as whites (HHS, 2016c). This is especially true for specific subgroups of Native Americans, such as the Pima Indians, who have historically been identified as having the world's highest recorded prevalence and incidence of type 2 diabetes (HHS, 2016c; Schulz et al., 2006). While overall population rates of diabetes as an underlying cause of death have been decreasing over time, the rates of diabetes as an underlying cause of death and a multiple cause of death have remained 2.5 to 3.5 times higher for Native Americans than for whites of all ages 20 and older, for every IHS region except Alaska (Cho et al., 2014).

A 10-year analysis revealed that Native Americans were 1.21 times as likely to die from heart disease as an underlying cause of death than were whites (Veazie et al., 2014). In 2012 the tuberculosis rate for Native Americans was 6.3 percent, as compared with 0.8 percent for the white population (HHS, 2016c). This disparity is especially striking when examined against the backdrop of successful infectious disease prevention efforts that have almost eliminated the burden of tuberculosis in other racial and ethnic populations.

While overall rates of cancer are lower for Native Americans than for other racial and ethnic groups, there are specific cancers for which this population is at high risk. These include stomach, liver, cervix, kidney, gallbladder, and colorectal cancer (Espey et al., 2014; White et al., 2014). Research suggests that the burden of disease from these types of cancer is in large part attributable to the high rates of alcohol consumption among Native Americans (Landen et al., 2014). From 1990 to 2009, overall cancer death rates increased significantly for Native Americans, whereas these rates declined for white men during the entire period, and for white women during most of the 19-year period (White et al., 2014).

Mental health Native Americans have had a complex and tumultuous history in the United States. The resulting historical trauma is an important context for the discourse on mental health issues that are faced by Native American communities today. Although research on mental health is limited because of the size and heterogeneity of this population, there is literature that suggests that Native Americans disproportionately suffer from mental health disorders and related conditions. These include, but are not limited to, increased prevalence and risk factors for depression, suicide, drug and alcohol abuse, and PTSD (Berman, 2014; Herne et al., 2014; HHS, 2016c; Landen et al., 2014). When compared to the general U.S. population, Native Americans experience PTSD more than twice as often and experience psychological distress 1.5 times more often (APA, 2010). These experiences have major implications for suicide rates in Native American communities. A 10-year analysis of death certificate data linked with IHS health data found that death rates from suicide were approximately 50 percent higher among Native Americans than among whites (Herne et al., 2014). Recently, suicide has replaced homicide as the second leading cause of death among U.S. teenagers, and the highest rates are among Native American youth (VanOrman and Jarosz, 2016).

A Shift in the Narrative

Despite the barriers to achieving health and well-being that Native Americans face, there have been positive advancements by communities and community partners toward improving the health of this population. For example, the emergence of tribal health research infrastructures has been supported by National Institutes of Health funding of the Native American Research Centers for Health, which started in 2001 (Jernigan et al., 2015; Kelley et al., 2013). Furthermore, resilient Native American communities have followed the trend toward self-governance and have taken the initiative to create community-driven solutions to address the severe health conditions discussed in this section. Box 2-1 briefly introduces one of these communities and its path to health (see Chapter 4 for a more in-depth discussion of another Native American community that is taking action on health inequity).

BOX 2-1

Menominee Nation's Path to Health.

Gender Disparities

When discussing health disparities across gender groups, it is important to acknowledge that while the basis of some disparities is biological (e.g., rates of ovarian and prostate cancers), the majority of the disparities discussed in this section are not based in biological mechanisms unless otherwise stated. Nonbiological health disparities stem from socioeconomic conditions that can shape gender differences in health outcomes such as mortality rates, alcohol and substance abuse, mental health disorders, and violence victimization.

In 2014 life expectancy at birth was 81.2 years for women and 76.4 years for men (NCHS, 2016). From 2004 to 2014, the gap in life expectancy between men and women decreased from 5.1 years to 4.8 years (NCHS, 2016). While the narrowing of the life expectancy gap could be considered a positive trend, it is in fact a troubling trend because it stems from a rise in mortality rates among women over the past two decades in many areas (Arias, 2016). Kindig and Cheng found that from 1992 to 2006, as mortality decreased in most U.S. counties, female mortality rates increased in 42.8 percent of counties. During this same period, only 3.4 percent of counties saw an increase in male mortality rates (Kindig and Cheng, 2013).

More specifically, recent evidence reveals an unprecedented increase in the death rates among white women and a decline in life expectancy, changes that white men did not experience (Arias, 2016). Findings on the causes of death among white women point to accidental poisoning (related to the rise in prescription opioid use), suicide, obesity, and smoking-related diseases (Astone et al., 2015). Figure 2-1 shows that across multiple racial groups, women—particularly white women—have been more affected than men by the increasing rates of drug poisonings (NASEM, 2016a).

FIGURE 2-1

Percentage increase in drug poisonings between 1994 and 2010. SOURCE: NASEM, 2016a.

In terms of alcohol and illicit drug use, men ages 12 and older report higher usage rates than women (SAMHSA, 2015a,b). While women have lower rates of alcohol and substance use, they are more likely to have a serious mental illness than men (SAMHSA, 2015a). Research shows that women are more likely to be diagnosed with anxiety or depression (including post-partum depression) and men are more likely to have substance abuse or antisocial disorders (Eaton, 2012). In fact, depression is the number one cause of women's disability in the United States (NASEM, 2016a).

Gender disparities are present across all social determinants of health, with some more prominent than others. In education, the historical gender gap has narrowed over the past 50 years, with the percentage of men and women older than 25 years with bachelor's degrees roughly equal now (32 percent and 33 percent, respectively), and the percentage of women ages 25–29 with a bachelor's degree exceeds that of men. However, men still outnumber women in the attainment of degrees beyond a bachelor's degree (Ryan and Bauman, 2016). The gender pay gap, a widely reported disparity in income, has implications for health inequities because income is closely tied to health. A report by the National Academies of Sciences, Engineering, and Medicine examined gains in life expectancy across different income groups over time and found that while men in the top 60 percent of the income distribution were making gains in life expectancy at age 50, women were experiencing losses in expected life expectancy at age 50 in the bottom two income quintiles and no progress in the third or fourth quintiles (NASEM, 2015).

Access to routine, quality health care is essential for both men and women. The uninsured rate is higher for men, even after the passage of the Patient Protection and Affordable Care Act (ACA), in part because men have not historically qualified for Medicaid (NASEM, 2016a). Reproductive and sexual health services are an especially important consideration for women because of their ability to bear children. Unintended pregnancy can have an impact on the overall health and well-being of women. From 2007 to 2010 teenage pregnancy rates in the United States declined 17 percent (Hamilton and Ventura, 2012).

For women, experiencing violence is a strong predictor of health, and violence against women is primarily in the form of intimate partner violence (IOM, 2010; Tjaden and Thoennes, 2000). Living in low-income neighborhoods is associated with an increased risk of intimate partner violence for African American and white women (Cunradi et al., 2000). Women are more likely than men to sustain injuries from an assault (Tjaden and Thoennes, 2000). In addition to injury, research suggests that women's health can be greatly affected over time after experiencing violence. For example, women who experience violence are at increased risk of arthritis, asthma, heart disease, gynecological problems, and risk factors for HIV or sexually transmitted diseases (STDs) than those who do not experience violence (Campbell and Boyd, 2000; IOM, 2010). For men, community violence is likely to affect their health, and this is particularly true for men of color, who experience disproportionate amounts of violence (Prevention Institute, 2011). Men are also much more likely to commit suicide than women, regardless of age, race, or ethnicity, with overall rates at almost four times those of women (CDC, 2013a).

Disability Status and Health Disparities

Disabilities,⁵ whether present or acquired at birth or developed later in the life course, can manifest as physical, cognitive, or mental health-related impairments, which can affect health outcomes. People with disabilities represent about 18.7 percent of the U.S. population (Brault, 2012). Although there is ample evidence to suggest that people with disabilities are at increased relative risk for poor well-being (see Figure 2-2), until recently this population has been overlooked in population health data collection, analyses, and reports (Krahn et al., 2015). One of the major challenges in data collection has been the lack of consensus on a clear and specific definition of disability (Oreskovich and Zimmerman, 2012). There has been an emerging effort to document and address health disparities among people with disabilities (CDC, 2013a; HHS, 2016a; NASEM, 2016b), in addition to the ACA requirement to improve data collection and reporting on disability, among other factors.

FIGURE 2-2

Factors affecting the health of people with disabilities and without disabilities. SOURCE: CDC, 2015.

Adults with disabilities are four times as likely as adults with no disabilities to report having fair or poor health (40.3 percent versus 9.9 percent) (Krahn et al., 2015). People with disabilities also report higher rates of obesity, lack of physical activity, smoking, and three to four times the rate of cardiovascular disease versus people without disabilities (CDC, 2014b, 2016c; Reichard and Stolzle, 2011; Reichard et al., 2011). For specific subgroups of this population, factors such as race and ethnicity, age, language, sex or gender, poverty, and low education can compound the effects of having a disability (Krahn et al., 2015). Furthermore, living with a disability shapes one's experiences of the social, economic, and environmental determinants of health. For instance, having a disability is associated with an increased likelihood of not having a high school education, less likelihood of employment, less access to the Internet, an increased likelihood of having an annual income less than $15,000, and inadequate access to transportation (Krahn et al., 2015).

Living with a disability can present barriers to accessing health care services and navigating the health care system (WHO, 2016). People with disabilities, including those with health insurance and those without, were more than twice as likely as people without disabilities to not receive medical care because of cost in 2009 (CDC, 2010b). While they experience higher rates of chronic disease than the general population, people with disabilities are significantly less likely to receive preventive care (Krahn et al., 2015). Additional barriers include common misconceptions, stigma, and attitudes among providers (CDC, 2016b).

Disability types vary in prevalence and in how they are associated with health disparities. In the United States, disabilities in mobility and cognition are the most commonly reported types (Courtney-Long et al., 2015). People with cognitive limitations are up to five times more likely to have diabetes than the general population (Reichard and Stolzle, 2011). Disability severity also has implications for the economic factors that shape health. According to U.S. Census data, in 2010 approximately 28.6 percent of people ages 15 to 64 with severe disabilities were in poverty, compared with 17.9 percent of adults with non-severe disabilities and only 14.3 percent of adults with no disability (Brault, 2012).

Veterans Health

As a vulnerable and growing population, military veterans are an important focus of many ongoing efforts to promote health equity. Many veterans experience lasting trauma from their military service as well as socioeconomic disadvantages post-deployment that can significantly influence their physical and mental well-being. These conditions have resulted in health and health care disparities both relative to the general population and among certain veteran subpopulations. For the purposes of this report, veterans are defined as those “who served in the active military, naval, or air service, and who [were] discharged or released therefrom under conditions other than dishonorable,”⁶ who receive health care from the Veterans Health Administration (VHA) as well as those who are not enrolled.

Many conditions and factors contribute to premature mortality among veterans, including higher rates of suicide risk, homelessness, and mental health issues. The risk of suicide in the veteran population is higher than in the general population and has become an increasingly serious problem among younger veterans. A study of 1.3 million veterans who served in Iraq and Afghanistan between 2001 and 2007 found that non-deployed and deployed veterans had 61 and 41 percent higher risks of suicide, respectively, than members of the general population (Kang et al., 2015). The U.S. Department of Veterans Affairs (VA) recently examined suicide rates among VA-enrolled veterans from all states and found that in 2014, VA-enrolled veterans accounted for 17.9 percent of suicide deaths among U.S. adults and had a 21 percent higher risk of suicide relative to the general adult population (VA, 2016). The higher risk of suicide among younger veterans has also drawn significant attention. Specifically, between 2006 and 2011, the suicide rate among young California veterans (a yearly average of 27 suicides per 100,000 veterans) was 57 percent higher than the rate among active duty military personnel (Zarembo, 2013).

Mental illness and related psychopathological problems, including PTSD, depression, substance abuse, and sexual trauma, are significantly more prevalent among the veteran population. Despite the high burden, calculated prevalence rates have varied significantly because of substantial variations in many components of study design. The prevalence of these disorders among veterans who receive care from the VA and among those who do not can be even more difficult to discern. The prevalence of PTSD in veterans who were deployed to Afghanistan and Iraq is two to three times greater than in the overall population, with many studies estimating that the prevalence among this veteran cohort ranges from 13 to 20 percent (IOM, 2012). PTSD is closely linked to military sexual trauma (MST), which federal law defines as “psychological trauma, which in the judgment of a mental health professional employed by the VA, resulted from a physical assault of a sexual nature, battery of a sexual nature, or sexual harassment which occurred while the veteran was serving on active duty, active duty for training, or inactive duty training.”⁷ Sexual trauma is far more prevalent among veterans and military personnel than in the general population and is likely to be considerably underreported. Recently, data from the National Health and Resilience in Veterans Study collected in 2013 revealed a prevalence rate of 7.6 percent, with 32.4 percent of female veterans and 4.8 percent of male veterans reporting MST (Klingensmith et al., 2014). MST disproportionately affects female veterans but is also a pervasive problem among male veterans, and it detrimentally affects both mental and physical health. It has been linked to suicidal ideation, substance abuse, PTSD, depression, anxiety, eating disorders, and impaired mental and cognitive functioning (Klingensmith et al., 2014; Mondragon et al., 2015; O'Brien and Sher, 2013). It has also been linked to greater symptoms of physical pain (Mondragon et al., 2015; O'Brien and Sher, 2013). Sexual trauma suffered during military service may also affect the social well-being of veterans after they are deployed, as MST has been negatively correlated with emotional and social support post-deployment (Mondragon et al., 2015).

Disparities related to access to and use of health care as well as higher prevalence of certain chronic diseases are also present in the veteran population. A review of studies examining racial and ethnic health care disparities in the VA found that relative to white veterans, African American veterans experience lower levels of arthritis and cardiovascular disease management, lower levels of participation in surgery related to cancer and cardiovascular disease, and a lower quality of diabetes care (Saha et al., 2007). Prevalence rates for certain chronic diseases are also disproportionately high in the veteran population. Among African American male veterans born between 1945 and 1965, the prevalence of hepatitis C virus was 17.7 percent, a fivefold greater rate than the 3.5 percent prevalence found in the same birth cohort of the general population between 2001 and 2010 (Backus et al., 2014).

Veteran homelessness is one of the most staggering and urgent issues affecting veteran health; although the number of homeless veterans has decreased in recent years, veterans remain at significantly higher risk than members of the general population for becoming homeless (Tsai and Rosenheck, 2015). Point-in-time counts by the U.S. Department of Housing and Urban Development across all states estimated 47,725 homeless veterans in 2015 and 39,471 homeless veterans in 2016, a decrease of 17.3 percent between the 2 years⁸ (HUD, 2016). Studies with more geographically focused sampling also illustrate the continuing pervasiveness of veteran homelessness. In a study of homeless veterans 65 years and older in Los Angeles between 2003 and 2005, 56 percent were found to be chronically homeless, with African American veterans accounting for 42 percent of this number (van den Berk-Clark and McGuire, 2013). Additionally, female veterans are at higher risk of homelessness than both male veterans and females in the civilian population and account for an increasing proportion of homeless veterans, as the number of female veterans increases (Balshem et al., 2011; Byrne et al., 2013). Box 2-2 briefly describes a community-based program that was designed to address a few of the barriers that veterans face.

BOX 2-2

Veterans Sustainable Agricultural Training Program.

PLACE MATTERS

In the following section, the committee discusses the relationship between people and place and implications for health disparities. One of the most consistent findings in the health disparities literature is that place matters. Research shows that there are systematic disparities in morbidity, mortality, and other measures of well-being across different areas of the country, even across small areas that lie relatively close together. At a larger level of analysis, life expectancy varies between states by up to 7.0 years for males and 6.7 years for females (NRC and IOM, 2013). Historically, many analyses compared health and life expectancy rates across wide areas, such as regions or states. Thus, it can be stated that obesity—a condition associated with chronic disease, mortality, and decreased overall well-being—is concentrated in the South and Midwest (Levi et al., 2015b). Likewise, people living in the South are more likely to be diagnosed with HIV over the course of their lifetime than other Americans, with the highest risk in Washington, DC (1 in 13), Maryland (1 in 49), Georgia (1 in 51), Florida (1 in 54), and Louisiana (1 in 56) (CDC, 2016d).

However, the availability of more granular data has allowed for the observation of even larger disparities across smaller geographic regions such as zip codes, counties, and census tracts (see Figures 2-3 and 2-4) (Kulkarni et al., 2011; UWPHI, 2016; Zimmerman and Woolf, 2014). In some cities, for example, life expectancy can differ by as much as 25 years from one neighborhood to the next (Figure 2-4 illustrates this disparity between New Orleans neighborhoods) (Evans et al., 2012; Zimmerman and Woolf, 2014). Life expectancy is but one measure of these disparities. Similar gaps in health-related outcomes across geographic areas can be found for infant mortality, obesity, violence, and chronic diseases (UWPHI, 2016). There is also research suggesting that African Americans and whites living in similar neighborhood conditions do not experience the racial disparities in health that national data reflect (LaVeist et al., 2011).

FIGURE 2-3

Map of life expectancy disparities in Kansas City, Missouri. NOTE: The average life expectancy gap for babies born to mothers in Kansas City can reach up to 14 years. SOURCE: RWJF, 2013a. Used with permission from the Robert Wood Johnson Foundation.

FIGURE 2-4

Map of life expectancy disparities in New Orleans, Louisiana. NOTE: The average life expectancy gap for babies born to mothers in New Orleans can reach up to 25 years. SOURCE: RWJF, 2013b. Used with permission from the Robert Wood Johnson Foundation.

EVIDENCE GAPS

Since the publication of Heckler's 1985 Report of the Secretary's Task Force on Black & Minority Health (the Heckler Report) and even the IOM's 2003 Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care report, significant progress has been made in the science of health inequities. Scientific progress is evident in the development of conceptual models of the multilevel factors that shape health inequities, a greater standardization and collection of data on race and ethnicity, more sophisticated data analytic tools and methods, and the exponential growth of published studies on health inequities. Adler and colleagues provided a review of progress to date in the field of health inequities and note in detail the scientific advances, challenges, and future directions for research (Adler and Stewart, 2010).

Yet, compared to other fields of health research, health inequities is still a relatively new field. It faces significant research and practical application challenges that need to be addressed in order to offer knowledge that can strategically and accurately inform interventions aimed at reducing or eliminating health inequities.

First, the collection and use of data on race, ethnicity, and language are key parts of the process of identifying health and health care needs and eliminating disparities. Yet, work remains to be done in ensuring that our current data systems capture the appropriate categories and that these are consistently collected across studies and data systems. Toward this aim, in 2009, the IOM report Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement proposed templates of granular ethnicity and language categories for national adoption so that entities wishing to collect detailed data can do so in systematic, uniform ways. The Office of Management and Budget (OMB) is currently undertaking a review of the current classifications for race and ethnicity and has issued a call for comments, including on the salience of the terminology used for race and ethnicity classifications and other language in the standard (GPO, 2016b).

Beyond the collection of data on race and ethnicity, a significant challenge has been the lack of sufficiently large samples of some racial and ethnic groups and their subgroups in population-level epidemiological studies such as the National Health and Nutrition Examination Survey and the National Survey on Drug Use and Health. Insufficiently large samples of some groups (e.g., Native Americans/American Indians, Hispanics and subgroups, and Asian and Pacific Islanders and subgroups) result in unreliable estimates of health indicators and resulting limitations on studies to investigate the factors that contribute to disparities within and across groups. Oversampling of these groups in national epidemiological studies is needed to yield appropriate estimates of health conditions.

Reliable estimates of health indicators can sometimes be derived by collapsing data across years, but this also poses some limitations on tracking health changes over time and providing up-to-date estimates. For smaller and geographically concentrated racial and ethnic groups (which are not well represented in national studies), specialized ongoing periodic studies are needed to track health conditions and the progress in reducing health inequities. For example, the National Latino and Asian American Study, while limited to one administration, provided previously unavailable but highly valuable data on Hispanic and Asian populations (Burnham and Flanigan, 2016).

Beyond race and ethnicity, the 2011 IOM report, The Health of Lesbian, Gay, Bisexual, and Transgender People: Building a Foundation for Better Understanding made recommendations regarding data collection about sexual orientation and gender identity in federal surveys and in electronic health records; implementation of the recommendations will provide essential data to document and monitor progress on LGBT health. For example, questions on sexual orientation and gender identity are included in recent versions of the Behavioral Risk Factor Surveillance Survey (CDC, 2016a).

Second, one of the important areas of knowledge advancement in health disparities research has been the integration of neighborhood-level factors that contribute to or are associated with health inequities. For example, measures of neighborhood-level segregation (e.g., the Diversity Index [National Equity Atlas, 2016], public school segregation [JSRI, 2016], and community diversity and distances between communities with different racial or ethnic profiles [VDH, 2016]); income inequality (National Equity Atlas, 2016; RWJF, 2016a; United Health Foundation, 2016), health equity (e.g., National Equity Atlas: Economic Vitality, Readiness, Connectedness, Economic Growth [National Equity Atlas, 2016]), social cohesion and social capital (e.g., group membership, volunteerism [Opportunity Index, 2016], linguistic isolation [Brandeis University, 2016]), gentrification (e.g., change in median income [United Health Foundation, 2016]), and housing affordability (Brandeis University, 2016) have been developed and used to document the associations and effects of these features of neighborhoods on health and health equity. The integration of these and other neighborhood-level features, if added to existing epidemiological health studies, could facilitate researchers' use of these measures in studies of health equity.

An additional challenge is that most studies of the features of the neighborhood environment and their impacts on health and health equity have been cross-sectional and are thus limited in establishing causal relationships (Diez Roux and Mair, 2010). As noted by Diez-Roux and Mair, the field needs longitudinal studies of neighborhood features and their relationships to health outcomes that use statistical controls for baseline differences and longitudinal analyses relating changes in outcomes to changes in predictors. While such studies are still observational, they can employ a number of statistical approaches that are preferable to cross-sectional analyses as they build a case for experimental studies and for rigorous intervention evaluations. Similarly, longitudinal studies of life-course processes on the impacts of neighborhood level factors on health and health equity are needed. For example, in considering residential mobility, Diez Roux and Mair note the limited work on characterizing neighborhood environments across the life course and the need to develop strategies to link cohort data to historical neighborhood data (Diez Roux and Mair, 2010).

Third, health disparity research has developed from a description of associations (e.g., socioeconomic status and health) to mechanisms linking socioeconomic status and health and multilevel influences to more recent work on the interactions among factors (Adler and Stewart, 2010). Yet, epidemiological studies on the factors that contribute to health and health inequities have not yet consistently provided clear answers regarding the most powerful and promising candidate levers to be targeted in community interventions. Although we cannot wait for the science to develop to the point of being able to provide exact answers, pilot interventions need to be based on the best available evidence and to be carefully evaluated with the most rigorous methods possible. However, in order to have a more definitive scientific basis for intervention approaches in this complex arena—with the myriad factors and ways that neighborhood and other factors affect health—a combination of research strategies, including rigorous observation studies, natural experiences or feasible experiments, and simulation studies, is needed (Diez Roux and Mair, 2010). Based on the data presented in this chapter and the current gaps in the evidence, the committee concludes the following:

Conclusion 2-1: To enable researchers to fully document and understand health inequities, to provide the foundation for solution development, and to measure solution outcomes longitudinally, the following are needed:

• An expansion of current health disparity indicators and indices to include other groups beyond African Americans and whites, such as Hispanics and their major subgroups, Native Americans, Asians, Pacific Islanders, and mixed race, in addition to LGBT individuals, people with disabilities, and military veterans.
  • Including consideration of methods to generate stable estimates of disparities through oversampling certain populations where necessary.
• An expansion of metrics and indicators capturing the broader definition of health, including health equity and the social determinants of health.
• Longer-term studies, as many health outcomes take years (or decades) to see quantifiable changes in health outcomes related to the social determinants of health.
• Studies examining the ways in which a single structural factor may influence multiple health outcomes.
• Increased funding opportunities dedicated to developing and testing relevant theory, measures, and scientific methods, with the goal of enhancing the rigor with which investigators examine structural inequities such as structural racism and health disparities.

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