Health Inequalities: Trends, Progress, and Policy

Health inequalities, which have been well documented for decades, have more recently become policy targets in developed countries. This review describes time trends in health inequalities (by sex, race/ethnicity, and socioeconomic status), commitments to reduce health inequalities, and progress made to eliminate health inequalities in the United States, United Kingdom, and other OECD countries. Time-trend data in the United States indicate a narrowing of the gap between the best- and worst-off groups in some health indicators, such as life expectancy, but a widening of the gap in others, such as diabetes prevalence. Similarly, time-trend data in the United Kingdom indicate a narrowing of the gap between the best- and worst-off groups in some indicators, such as hypertension prevalence, whereas the gap between social classes has increased for life expectancy. More research and better methods are needed to measure precisely the relationships between stated policy goals and observed trends in health inequalities.

INTRODUCTION

Over the past three decades, a sizable body of literature has documented pervasive and systematic inequalities in health (4, 40, 55, 79, 87). Health inequalities generally have been described in terms of disproportionate disease burden or behavioral risk factors experienced by subgroups of the population. In the United States, most research has focused on racial/ethnic health inequalities, whereas in other developed countries, most research has focused on health inequalities by socioeconomic status (SES) or class (3).

The definition of an inequality or disparity implies a difference in health status. These terms represent an inequality that is unfair, unjust, or avoidable (3, 45). Governments and researchers have defined the concept in a variety of ways (15). For instance, Carter-Pokras & Baquet (19) described 11 different definitions of health disparities used by different governmental entities. In the United States, the definition included in Healthy People 2010 (89) is often cited: “differences that occur by gender, race or ethnicity, education or income, disability, geographic location, or sexual orientation” (p. 11). In a European context, Whitehead (93) discusses the goal of health equity, which is “not to eliminate all health differences so that everyone has the same level and quality of health, but rather to reduce or eliminate those which result from factors which are considered to be both avoidable and unfair” (p. 220). In the preparation of Healthy People 2020, an advisory committee to the U.S. Department of Health and Human Services (DHHS) (90) put forth a goal to “achieve health equity, eliminate disparities, and improve the health of all groups” (p. 7). That committee (17) defined health disparities as “systematic, plausibly avoidable” differences in health that adversely affect socially disadvantaged groups and propose that health disparities be used as a metric for assessing health equity. In this context, health inequalities can be thought of as a manifestation of inequities.

In addition to disparities in health status, inequalities also exist in access to and quality of health care services. The Institute of Medicine’s (IOM) report, Unequal Treatment (71), defines health care disparities as “racial or ethnic differences that are not due to access-related factors or clinical needs, preferences, and appropriateness of intervention” (p. 32). In a wide-ranging literature review, the IOM (71) found that even when sociodemographic factors, insurance status, and clinical need were controlled for, racial and ethnic health care disparities remained. Remaining disparities were attributed to factors such as discrimination and the health care system and the regulatory climate in which it operates (71).

National governments and international organizations have made commitments to eliminate health inequalities, often through efforts to reduce the gaps between the best- and worst-off groups in society (53, 89). Such efforts include the World Health Organization’s (WHO) Commission on the Social Determinants of Health, which focused on health inequalities within and between countries (95), the U.S. program to eliminate health inequalities outlined in the Healthy People documents (88, 89, 91), and the U.K. (81) goal to reduce health inequalities in infant mortality and life expectancy.

Apart from the view that health inequalities represent a societal injustice (16, 93), inequalities are also harmful from an efficiency viewpoint. Accounting for both direct costs (i.e., medical spending) and indirect costs (i.e., lower productivity due to illness and premature death), a 2009 study conducted by our research group found that health inequalities cost the United States $1.24 trillion between 2003 and 2006 (46).

From either an equity or efficiency perspective, there are important reasons why health inequalities will continue to pose a considerable challenge to policy makers. The U.S. Census Bureau (85) projects a significant increase in the diversity of the population’s racial/ethnic makeup, with large increases in the proportion of Hispanic and Asian residents and a simultaneous decline in white, non-Hispanic residents. In the United States and other developed countries, the birth rate for white populations has been declining, and nonwhite populations have had a consistently higher birth rate (23, 31). In addition, because birth rates in developed countries are declining (11, 76), immigrants will become an increasingly important proportion of the working-age population (84).

Previous reviews published in the Annual Review of Public Health have examined the definitions and measurement of health disparities (3, 15); the potential causes and mechanisms of health disparities (3); the social and behavioral contributors to health disparities (9); global commitments to reducing health inequalities (29); the need for comprehensive interventions to address disparities (77); and progress toward reaching the U.S. Healthy People 2010 goals, one of which is eliminating health disparities (72). This review adds to the literature by focusing on trends in health inequalities within and between population subgroups, and policy commitments made to eliminating those inequalities, in developed countries. This is a key area of focus from both a research and policy perspective given that literature focused on overall population averages may mask important differences among subgroups.

The term health disparity is predominantly used in the United States, whereas the term health inequality is commonly used in Europe. Although the two terms are sometimes used interchangeably, we refer to health inequalities throughout this review. Consistent with our goal of describing trends in health inequalities and related policy commitments, our primary focus is on health status inequalities, as opposed to inequalities in access, utilization, or quality of health care. We limit this review to the United States and other countries in the OECD (Organisation for Economic Cooperation and Development) that have made major policy commitments to reduce documented health inequalities and examine the progress made to eliminate such inequalities. We begin by describing trends in health inequalities with a primary focus on the United States and United Kingdom and a secondary focus on other OECD countries. We focus on health inequalities present in populations at the time of measurement rather than focusing on inequalities that occurred in childhood and had future ramifications. We next examine policies and commitments to reduce or eliminate health disparities. We then provide examples of evaluation strategies to assess strategies to address health inequalities. We subsequently provide a brief overview of research progress on improving our understanding of health inequalities. We conclude with a discussion of policy implications.

TRENDS IN HEALTH INEQUALITIES

Using a series of national-level data sets, we describe trends in health inequalities beginning in 1980 among adults aged 20 and older. We selected 1980 as the starting point because that was the year of the landmark Inequalities in Health: The Black Report and the Health Divide (79), which drew international attention to the issue of health inequalities. The Black Report was a major turning point in the United Kingdom, and its influence was felt in the United States as well.

The data are age-adjusted and stratified by gender, race/ethnicity, or SES, where population subgroup information is available. Race/ethnicity data are presented to the extent that data were collected with large enough sample sizes for analysis. In the United States, data for American Indians are not presented, despite documented health inequalities in that population compared with national averages. For the United States, SES is defined by educational attainment: those who have less than a high-school education, those with a highschool diploma, and those with some college education. For the United Kingdom, SES is defined by social class, based on the Office of National Statistics socio-economic classification (NS-SEC). Social class is hierarchically structured where class I is the highest social class and class VII is the lowest (83). It is important to note that SES in the United States is not completely analogous to social class in the United Kingdom. Krieger et al. (42) conceptualize social class as a measure of social relationships that is a precursor to SES, which is composed of “components of economic and social well-being” (p. 346).

We describe three broad categories of health indicators—mortality (i.e., infant mortality, allcause mortality, and life expectancy at birth), behavioral risk factors (i.e., smoking, drinking, physical activity, and fruit/vegetable consumption), and metabolic factors (e.g., obesity, hypertension, and diabetes)—for the United States, United Kingdom, and other OECD countries. U.S. data were obtained from the National Center for Health Statistics (mortality), National Health Interview Survey and Behavioral Risk Factor and Surveillance System (behavioral risk factors), and National Health and Examination Nutrition Survey (metabolic conditions). U.K. data were obtained from the Office of National Statistics (mortality) and the Health Survey for England (behavioral risk factors, metabolic conditions). Data for other OECD countries were obtained from the OECD Health Statistics database. A summary of the U.S. and U.K. individual-level data sets can be found in the Appendix.

United States

Table 1 displays time trends in age-adjusted mortality indicators by sex, race/ethnicity, and education from 1980 to 2007 (or for years in which data are available) for the United States. Among males, the infant mortality rate is lowest among Hispanic males, followed by white males—who have slightly higher infant mortality—and highest among black males. In 1980, the infant mortality rate for black males was approximately twice that of white males (24 per 1,000 compared with 12 per 1,000). By 2007, the gap between infant mortality of white and black males increased slightly, despite an absolute reduction in infant mortality among black males. This pattern of inequalities is mirrored among females; Hispanic females experienced the lowest infant mortality over time, followed by white females and black females. Among different household education levels, infant mortality declined among the most highly educated and least-well educated strata, the gap in infant mortality between the most- and least-educated groups declined slightly from 1995 to 2005, and the middle education stratum experienced an increase in infant mortality. Time trends in all-cause mortality rates among race/ethnicity groups are similar to infant mortality, with declines seen in all subpopulations. Hispanic males and females experienced the lowest all-cause mortality rates, followed by white populations; whereas black populations had the highest all-cause mortality. The white-black gap between all-cause mortality rates among males increased over time, but the gap between white and black females in all-cause mortality rates declined. All groups experienced gains in life expectancy at birth. Notable patterns included a decline in the black-white difference in life expectancy among males (6.9-year gap versus 5.9-year gap) and females (5.6-year gap versus 4.0-year gap) over the period.

Table 1

Time trends in age-adjusted mortality overall and by sex and race/ethnicity, United States a , b

a Sources: Data from Reference 98. Infant mortality data also obtained from United States Department of Health and Human Services (U.S. DHHS), Centers of Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), Office of Analysis and Epidemiology (OAE), Division of Vital Statistics (DVS), Linked Birth/Infant Death Records on CDC WONDER Online Database (http://wonder.cdc.gov/lbd-icd9.html).

b Notes: Data is reported in five-year increments beginning in 1980 up until 2005. After 2005, we include the most recent year of data which is 2007.

Table 2 displays differences in major behavioral risk factors by race/ethnicity and education. Over time, smoking prevalence is highest among those with less than a high-school education and lowest among those with more than a high-school education. Both the lowest- and highest-education strata experienced a decrease in smoking prevalence, and the difference in smoking prevalence narrowed over time between these groups. Those in the middle stratum (a high-school education) experienced a decline in smoking prevalence from 1990 to 2004 but had an increase in smoking prevalence from 2006 to 2009. Physical activity generally increased among all groups over time; however, a gap still remains between education groups; those with the most education reported the highest amount of physical activity and those with less than a high-school education reported the lowest amount of physical activity. Fruit and vegetable consumption appeared similar across race/ethnicity groups and over time, although those with more than a high-school education had a higher fruit/vegetable intake compared with those with either a high-school education or less than a high-school education.

Table 2

Time trends in age-adjusted behavioral risk factors overall and by race/ethnicity and education,%. United States a , b , c

a Source: National Health Interview Survey (smoking, drinking, physical activity) Behavioral Risk Factor Surveillance System (fruit/vegetable intake).

b Data is reported for 1990 or earliest year and biannually beginning in 2000 up until 2008. After 2008, we include the most recent year of data which is 2009. Includes adults aged 20 and older.

c Survey questions. Current smoking: ever smoked 100 cigarettes and currently smoke (every day or some days). Current drinking: ever had 12 drinks in lifetime and had at least 12 drinks in the last year. Physical activity: participate in vigorous activity for 20+ min for 3+ times per week. Fruit/vegetable consumption: number of fruit and vegetables servings per day including potatoes.

d Fruit/vegetable consumption data are not available in 1990, 2006, or 2008; we report data for 1996, 2005, and 2007.

Table 3 displays the prevalence of obesity, hypertension, and diabetes by race/ethnicity and education. Among all metabolic conditions, blacks had the highest prevalence at each point in time compared with whites and Mexican Americans (who had the lowest prevalence). All education strata had increased prevalence of obesity, hypertension, and diabetes over time; the highest-education stratum experienced the lowest prevalence, and the lower-education strata experienced a higher prevalence of metabolic conditions.

Table 3

Time trends in age-adjusted metabolic factors overall and by race/ethnicity and education,%. United States a , b

d Systolic blood pressure ≥140, diastolic blood pressure ≥90 (measured) or currently taking antihypertensive medications (self-reported).

e Diabetic defined as reporting a doctor told them they had diabetes, taking diabetic medications, or having a fasting plasma glucose level ≥126 mg/dl.

United Kingdom

Table 4 displays time trends in age-adjusted mortality indicators by social class and sex in England and Wales. Although infant mortality rates are generally higher among lower social classes—class VII experienced the highest infant mortality (5.6 per 1,000) as compared with class I (4.1 per 1,000)—there is not a consistent gradient. For instance, households in class V experienced an infant mortality rate almost identical to that of class II (3.2 per 1,000 versus 3.3 per 1,000). With respect to all-cause mortality, there is a clear social-class gradient among both males and females where the mortality rate experienced by the lowest social class was at least twice that of the highest social class. Similarly, for life expectancy, there is a social gradient among both males and females. From 1982 to 2006, the gap in life expectancy between the highest and lowest social classes increased for males (from a 4.9-year gap to a5.8-year gap) and females (from a 3.8-year gap to a 4.2-year gap). All groups experienced an increase in life expectancy over the period.

Table 4

Time trends in age-adjusted mortality by sex and socio-economic classification. England and Wales a , b , c

b Data are missing for years where stratified analyses by social class were not available from the Office of National Statistics.

c Infant mortality estimates are for babies born to married individuals. They do not differ substantially from estimates for babies born to nonmarried/jointly registered individuals. Social class is based on the Office of National Statistics socioeconomic classification (NS-SEC) and is hierarchically structured where class I is considered the highest and class VII is the lowest.

Table 5 displays trends in major behavioral risk factors by race/ethnicity and social class in England. White, South Asian, and Asian populations all experienced a decline in smoking prevalence from 2001 to 2009; however, blacks had an increase in smoking prevalence from 2007 to 2009. In 2009, smoking prevalence was highest among the lowest social class (40.5%) and lowest among the highest social class (11.6%). Most social classes experienced a consistent decline in smoking prevalence over time. White populations had consistently higher levels of physical activity compared with other race groups, and no clear trend was seen among social classes. Asians and South Asians had the highest fruit and vegetable consumption, with white and black populations, respectively, lower.

Table 5

Time trends in age-adjusted behavioral risk factors by race/ethnicity and socioeconomic classification,%. England a , b , c , d

b In 2001, the measure of socioeconomic position used in official statistics, known as the Registrar General’s social class, was replaced by the NS-SEC (socioeconomic classification). Both measures are based on occupation, but they are difficult to compare. Therefore, we report only data from 2001 and onward. Social class is based on the Office of National Statistics socioeconomic classification (NS-SEC) and is hierarchically structured where class I is considered the highest and class VII the lowest.

c South Asian included Indian, Pakistani, Bangladeshi, and Sri Lankan. Asian included Chinese, Japanese, Philippino, and Vietnamese.

d Survey questions. Current smoking: currently smoke cigarettes. Current drinking: drank once or twice a month during the past 12 months. Physical activity: participated in vigorous sports at least 1 time in the past 4 weeks for 20 min. Fruit/vegetable consumption: portions of fruits and teaspoons of vegetables eaten in the prior day not including potatoes. Includes adults aged 20–65.

e Physical activity data are not available for 2001, 2005, 2007, or 2009; we report 2002, 2003, 2004, and 2008.

Table 6 displays metabolic conditions by race/ethnicity and social class in England. Obesity prevalence increased among all race/ethnic groups from 2001 to 2009. In 2009, Asians had the lowest obesity prevalence, followed by South Asians, whites, and blacks. With respect to hypertension and diabetes prevalence, white populations had the lowest prevalence (hypertension, 20.8%; diabetes, 2.1%) of any race/ethnicity group in 2009, followed by black populations (hypertension, 22.1%; diabetes, 3.7%). Among all social classes, hypertension prevalence generally decreased from 2001 to 2009 and diabetes prevalence generally increased, with the highest social class experiencing lower prevalence of both metabolic conditions compared with other classes.

Table 6

Time trends in age-adjusted metabolic factors overall and by race/ethnicity, socioeconomic classification,%. England a , b , c

b In 2001, the measure of socio-economic position used in official statistics, known as the Registrar General’s social class, was replaced by the NS-SEC (socioeconomic classification). Both measures are based on occupation, but they are difficult to compare. Therefore, we report only data from 2001 and onward. Social class is based on the Office of National Statistics socioeconomic classification (NS-SEC) and is hierarchically structured where class I is considered the highest and class VII the lowest.

c South Asian included Indian, Pakistani, Bangladeshi, and Sri Lankan. Asian included Chinese, Japanese, Philippino, and Vietnamese. Includes adults aged 20–65.

f Systolic blood pressure (BP) ≥ 140 mm Hg or diastolic BP ≥ 90 mm Hg or currently taking antihypertensive medications.

g Diabetes defined as a health care professional having diagnosed with diabetes (excludes during pregnancy).

Other Developed Countries

Table 7 summarizes key mortality and behavioral risk factor indicators for eight other developed countries, contrasting data from the mid-1990s with data from the mid-2000s. At the national level, all countries generally experienced gains in life expectancy, declines in infant mortality, declines in all-cause mortality, declines in tobacco consumption, and increases in obesity.

Table 7

Time trends in mortality, behavioral risk factors and overweight/obesity for 8 developed countries,% a

e Percentage of adult population with a body mass index (BMI) > 30 kg/m 2 , based on self-reported height and weight.

Progress Reducing Health Inequalities Over Time

Figures 1 – 3 show changes in differences by race and SES over time for key health indicators in the United States and the United Kingdom. The figures show the differences in selected indicators between race or SES groups, comparing the earliest year measured to the latest year measured. Figure 1 shows that in the United States, progress has been made to reduce health inequalities by SES in smoking prevalence and that in the United Kingdom progress has been made to reduce inequalities by SES in hypertension. Inequalities by SES in the United States have increased for hypertension prevalence and have increased in the United Kingdom for smoking prevalence. In both the United States and the United Kingdom, inequalities by SES have increased for diabetes prevalence. In both the United States and the United Kingdom, the gap between SES groups narrowed with respect to obesity prevalence. However, this time trend is not necessarily indicative of progress in reducing inequalities but could rather be that all groups experienced an increase in obesity prevalence over time.

Differences by socioeconomic status (SES) in selected behavioral risk factors and metabolic conditions, comparing early to later years. Notes: Data reflect differences between low- and high-SES groups, defined by education strata in the United States and social class in England. For U.S. smoking prevalence, the early year is 1990 and the later year is 2009. For U.S. obesity, hypertension, and diabetes prevalence, the early year is 1988–1994 and later year is 2008. For all England indicators, the early year is 2001 and the later year is 2009.

Differences by race and socioeconomic status (SES) in life expectancy at birth, comparing early to later years. Notes: U.K. data reflect differences between social class I and social class VII. For US data, the early year is 1980 and the later year is 2007. For the U.K. data, the early year is 1982 and the later year is 2006.

Figure 2 shows differences in race in selected indicators, comparing the earliest year measured to the latest year measured. Figure 2 shows progress has been made in the United Kingdom to reduce inequalities by race in hypertension. However, race inequalities have increased in both the United States and the United Kingdom for obesity prevalence and diabetes prevalence.

Differences by race in selected behavioral risk factors and metabolic conditions, comparing early to later years. *, Smoking reflects difference in prevalence between white and black populations, indicating a higher prevalence among white compared with black populations. Notes: Data reflect differences between non-Hispanic black and white populations. For U.S. smoking prevalence, the early year is 1990 and the later year is 2009. For U.S. obesity, hypertension, and diabetes prevalence, the early year is 1988–1994 and the later year is 2008. For all England indicators, the early year is 2001 and the later year is 2009.

Figure 3 shows inequalities in life expectancy at birth by race in the United States and by social class in the United Kingdom. In the United States, race inequalities in life expectancy have decreased among both males and females. In the United Kingdom, social class inequalities in life expectancy have increased among both males and females.

More complicated patterns were observed for time trends in smoking prevalence. In the United States, smoking prevalence decreased at a faster rate among racial/ethnic minorities compared with whites (see Figure 2 ); simultaneously, inequalities in smoking prevalence by education strata decreased (see Figure 1 ). A different pattern occurred in the United Kingdom, where smoking prevalence also declined at a faster rate among ethnic/minority populations (see Figure 2 ) than among whites, but simultaneous inequalities in smoking prevalence increased comparing the highest to lowest social class (see Figure 1 ).

It is important to note two limitations to the data presented here. First, data sets lacking information by subgroup may mask important differences by gender, race/ethnicity, or SES. Second, the data presented here do not distinguish between native-born and immigrant populations. The extent to which minority groups are composed of native-born individuals versus immigrants may be an important consideration when examining national-level time trends in the health of minority groups.

POLICY COMMITMENTS TO ADDRESS INEQUALITIES

Table 8 details key policy activities related to health inequalities by country and year. It also identifies whether the relevant activity is focused primarily on information (descriptive reports or data), priority setting (policy actions or documents that include goals, objectives, or targets), or action (activities that change programs or law or that create accountability to the public). To determine the focus of the policy action, two authors (S.N.B. and M.P.J.) qualitatively determined whether the focus was disseminating information, priority setting, creating a policy change, or a combination of these three criteria. Where there was disagreement, a third author (T.A.L.) reviewed the policy action and the majority opinion was reported. The results of Table 8 are described below by race/ethnicity, SES, and other health inequalities. Most major policy actions have involved priority setting. Several countries have undertaken action steps, such as changes to health programs, law, or data collection. Governmental entities have also published reports providing new information to the public or synthesizing research on health inequalities.

Table 8

Policy commitments to address health inequalities by country

a Information is defined as reports or data that provide descriptive information. Priority setting is defined as policy actions or documents that include goals, objectives, or targets. Action steps are defined as policy actions that change programs or law or that create accountability to the public.

b An Accord refers to an agreement between the national government of Canada and the First Ministers (i.e., heads of government) in each of the Canadian provinces and territories.

Race/Ethnicity

United States

In the United States, policy attention has focused largely on addressing health inequalities between different racial/ethnic groups. In 1985, the U.S. DHHS published the Secretary’s Task Force Report on Black and Minority Health (87), which documented strikingly worse health outcomes among minority racial and ethnic populations as compared with white Americans. The report led to the creation of the Office of Minority Health within the DHHS in 1986, as well as other offices in the federal government focusing on health among minority populations such as the Office of Research on Minority Health in the National Institutes of Health (NIH) (in 1990). Since the early 1990s, the DHHS has included the elimination of health inequalities among different populations as a national health objective via the Healthy People goals (88, 89, 91). In 1994, the NIH put forth new guidelines requiring that women and minority groups be represented in all human subject research (7, 57). In 1997, Congress provided $30 million for the Special Diabetes Program for Indians, which seeks to address the disproportionate share of diabetes experienced by American Indians (the program has since been expanded and now receives $150 million each year) (37, 67). The Minority Health and Health Disparities Research and Education Act [Pub. L. 106–525 (2000)] in 2000 elevated the Office of Research on Minority Health in the NIH to a center at the NIH and changed its name to the National Center on Minority Health and Health Disparities within the NIH. The act also authorized funds for research and education focused on health inequalities. The Patient Protection and Affordability Care Act of 2010 (PPACA) elevated the National Center for Minority Health and Health Disparities to institute status and changed the agency’s name to the National Institute on Minority Health and Health Disparities [Pub. L. 111–148 (2010)]. Additional provisions of the PPACA seek to improve data collection on sociodemographic characteristics and health and calls for cultural competency training. The PPACA also reauthorized the Indian Health Care Improvement Act (first enacted in 1976), which aims to improve American Indian health care and permit tribes greater autonomy in the provision of health programs.

United Kingdom

Policy attention in the United Kingdom has mostly focused on SES, but it is important to note that the 1998 Acheson report (1) also included recommendations that race/ethnicity be taken into account as part of efforts to address health inequalities.

Other developed countries

In Canada, several initiatives were put forth in the past decade to address health inequalities, with particular attention to the indigenous populations (2, 6). The Canadian First Ministers’ Health Accord set national priorities to reduce health inequalities (32). In 2005, the government published a 10-year action plan outlining specific commitments to improve the health status of aboriginal populations, including community engagement in health planning, collaboration to improve determinants of health such as housing and education, and disease-prevention strategies (33). In Australia and New Zealand, recent policy actions have also focused on improving the health of aboriginal populations. The Prime Minister of Australia in 2008 signed a statement committing to develop a long-term plan of action to end health inequalities between indigenous and nonindigenous populations (38). In New Zealand, the government has been taking action to implement a framework to reduce inequalities (70).

Socioeconomic Status

United States

Although policy commitments to eliminate health inequalities between groups of different SES have not been as prominent in the United States as in other developed countries, it is important to note the presence of many redistributive policies in the United States. These include Supplemental Security Income (SSI; a need-based monthly stipend for individuals aged 65 or older, blind, or disabled), Temporary Assistance for Needy Families (TANF; a federal-state program to provide cash assistance and employment aid to low-income families); the Earned Income Tax Credit (EITC; a refundable tax credit to lower-income, working individuals), and the Supplemental Nutrition Assistance Program (formerly called food stamps; in which low-income individuals receive government vouchers to purchase food). In addition, the 1994 NIH guidelines specifically called for researchers to consider socioeconomic differences among study populations, including occupation, education, and income (57).

United Kingdom

Of all the developed countries, policy development in the United Kingdom with respect to SES has been the most high profile (51). In 1980, what came to be known as The Black Report, published by the Working Group on Inequalities in Health, reported growing inequalities in health between groups of different SES, despite universally available national health care. The Black Report recommended a series of policy actions to address these inequalities, including redistributive policies, social benefits changes, and tobacco restrictions (79). In 1987, Whitehead authored The Health Divide (79), which sought to update documentation of unequal distribution of health status by class. As noted by Mackenbach & Bakker (51), it was more than a decade after the publication of The Black Report that policy action began to occur with respect to health inequalities (8, 25). In 1998, the Acheson report (1) called for specific policy changes to address health inequalities between different social strata, including increased income support benefits, better funding for education in poor areas, and restrictions on tobacco use in public. In early 2001, the United Kingdom announced a national target to reduce inequalities in infant mortality and life expectancy at birth by 10% by 2010 (80), with a strategy that included support for families, community engagement, preventive care, and attention to underlying determinants of health (81). Under the theme of enacting structural changes to address socioeconomic disparities, the United Kingdom has implemented redistributive policies, including the Working Families Tax Credit and Children’s Tax Credit, that provide employment-based benefits for adults.

Other developed countries

Elsewhere in Europe, governments have also focused policy efforts on reducing health inequalities between groups of different SES. The Netherlands began such efforts in the late 1980s, when the government launched the first of two multiyear initiatives to support research into socioeconomic inequalities in health (50, 52). In response to these research initiatives, in 2001 the country’s Program Committee on Socioeconomic Inequalities in Health published a report setting specific quantitative health targets to achieve by 2020: for instance, reducing by half the difference in smoking prevalence and obesity prevalence between groups with lower and higher educational attainment (52). In Spain, a government-sponsored commission published a report on socioeconomic inequalities in health in 1996, although the report was not widely circulated at the time (14, 59, 60). During the following decade, however, Spain did take policy action, with the publication in 2006 of the National Health System Quality Plan, which called for the collection of information that would facilitate the promotion of practices to reduce socioeconomic health inequalities (73). In 2008, Spain formed the Commission to Reduce Social Inequalities in Health in Spain, which in 2010 published a report proposing short-, middle-, and long-term strategies to reduce health inequalities (20). In addition, Spain has created the Observatory for Inequalities in Health, which is tasked with collecting and disseminating evidence of health inequalities by social class (65). In Sweden, the Health on Equal Terms Report, published in 2001, created 18 national goals for public health focused largely on socioenvironmental determinants of health, including a supportive social environment for all individuals and safe and healthy environments for all children (75). In 2002 (35), and then again in 2007, Sweden implemented public health objective bills that charged the national public health agency with supporting, coordinating, and evaluating efforts to realize the national health goals. Finland has also set national health targets designed to reduce health inequalities. The country’s revised constitution, enacted in 2000, requires the government to guarantee social and health services and to promote the health of the population (Const. Finl. § 19). In 2001, the government published 15-year national health targets, which include a target of reducing health inequalities between population groups (49).

Health authorities in Australia published a report in 1994 setting targets for better health outcomes that highlighted the importance of monitoring different health outcomes between different groups (22). Monitoring reports published in 2004 (26) and 2006 (66), however, found that marked health inequalities persisted among different socioeconomic groups and called for action on this front, including changes to social and economic policies, improvement of living and working conditions, community engagement, and tackling high-risk behaviors. Similarly, the New Zealand Health Strategy (62) set a priority to improve the health of disadvantaged populations, with attention to those groups that have low SES relative to the local community or society as a whole.

Other Health Inequalities

As described above, policy commitments to address health inequalities have focused primarily on the domains of race/ethnicity and SES. To a lesser extent, governmental authorities have considered policies related to additional factors that may drive health inequalities, such as geographical characteristics and gender.

For instance, globally, the WHO has launched the Healthy Cities project, which aims to promote local policies to achieve healthy equity, focusing particularly on inequalities in urban settings (97). In 2009, European political leaders issued a statement recognizing the responsibility of city governments to address “social, economic, and environmental determinants of health” (p. 2) and reiterating commitment to “health, healthy equity, social justice and sustainable development” (p. 4) via the Healthy Cities project (96).

Canada’s health research initiative to reduce health inequalities applies to all “vulnerable populations” but recognizes specific subgroups including homeless people, those with HIV/AIDS, and those with disabilities; it applies also to gender inequalities (6). Spain included gender inequalities as a focus of its national health care quality plan in 2006 (73), and the observatory for health inequalities in Spain collects and disseminates information about inequalities by gender, age, and region (65). In the United States, major concern that women of child-bearing age were not sufficiently represented in clinical trials (7) led to the 1994 NIH guidelines requiring their inclusion (57). Another policy approach has been Project REACH (administered by the U.S. Centers for Disease Control and Prevention), which uses community engagement initiatives that seek to address environmental, cultural, and social factors that affect health, such as behavioral risk factors that differ by community (48, 86).

EVALUATING POLICIES AND PROGRESS

The body of research describing trends and patterns of health inequalities has helped move the issue onto the policy agenda and, subsequently, spur political action. As a result, attention in many developed countries has now shifted toward the implementation and monitoring of strategies to reduce or eliminate health inequalities (28). Methods to measure and infer relationships between stated policy goals and observed trends in health inequalities represent a relatively new area of research. Despite a wealth of literature describing health inequalities and policy commitments to address them, Exworthy et al. (28) note “there is surprisingly little high-quality evidence for the effectiveness of policy interventions to address them” (p. 81). In addition, there is not universal agreement about which types of data collection and methods can best connect policy-making to practice. We describe some key methodological and data collection issues, highlight recent relevant policy developments in the United States and United Kingdom, and briefly discuss implications for future research evaluating interventions or policies to reduce health inequalities.

Measuring Policy Effects Over Time

The challenges inherent in evaluating the relationship between policy and health can be illustrated by the experience of Spain, where socioeconomic inequalities have lessened in recent years as measured by the Gini coefficient, a widely used statistic that measures the degree to which total income of a geographic area is distributed evenly. A Gini coefficient of 0 indicates perfect equality, where everyone has an equal share of the country’s income. As the Gini score approaches 1, this would indicate increasing concentration of income among a smaller group of individuals. Between the mid-1990s to the mid-2000s, Spain’s Gini coefficient declined from 0.341 to 0.319, and calculated differences in income between the richest and poorest groups also declined. Regidor et al. (68) analyzed data over a 15-year time period to examine income inequalities and inequalities in mortality and disability and found that, despite decreasing income inequalities, health inequalities between the richest and poorest groups actually increased over time. Thus, although the policy objective of reducing social inequalities was achieved, Spain did not experience a concurrent decline in health inequalities between different income strata. One explanation for such an apparent disconnect between policy goals and observed health outcomes could be a time lag between implementation of policies to reduce social inequalities and observed health inequalities. A meta-analysis by Kondo et al. (41) provides evidence to support this hypothesis, finding that the relationship between income equality and health was weakest when time lags were not included in analyses. Additionally, Subramanian & Kawachi (74) suggest that there may exist a threshold effect of social inequality (i.e., a Gini coefficient greater than 0.3) above which health inequalities will always persist.

Addressing Confounding of Race and Socioeconomic Status

In recent years, research has progressed on how to address the confounding of race and SES in measuring health inequalities. One example is the Exploring Health Disparities in Integrated Communities (EHDIC) study—a multisite study of race disparities within U.S. communities where blacks and whites live together and where there are no race differences in SES (43). The key contribution of this study is its ability to overcome two critical issues in health disparities research, limitations that bias estimates of health inequality from national data sets. The first is that race and SES are confounded. Individuals from racial minority groups are more likely to have low SES as compared with whites. As a result, it is difficult to determine whether it is the interaction (race and class) or the association (race or class) that creates disparities in health status (58). The second challenge is racial segregation. Individuals from racial minority groups typically live in geographically separate communities, and this segregation can lead to different environmental and social risk exposures (44, 94).

Results from the EHDIC study point to the importance of understanding social and environmental exposures—i.e., the role of social context—when developing and evaluating policies aimed at addressing health inequalities. In particular, the findings indicate that in a racially integrated community without race differences in income, black–white race disparities in hypertension (78), female obesity (10) and diabetes (47) were attenuated or eliminated, as compared with a nationally representative sample of the U.S. population. These results are striking given decades of research documenting large and persistent race disparities in these areas (30, 56, 63).

The finding that inequalities in health status are linked to social context may pave the way for creative policy solutions focused on contextual rather than individual-level factors. The environment can be modified through a variety of policy levers, unlike individual characteristics such as race or ethnicity, which are immutable. However, more research is needed in this area because the first site for the EHDIC study was an urban, poor population and may not be generalizable to other geographical locations or income levels. Plans to test the EHDIC hypothesis in high-income communities are under way.

Data Collection and Reporting Practices

Separate from, but related to, aforementioned methodological issues are data collection and reporting practices that influence the policy-making environment to address health inequalities. Braveman et al. (18) note that systematic reporting of health inequalities by socioeconomic indicators is not conducted by U.S. agencies, raising implications for how policies are formulated and implemented. At the national level in the United States, the Agency for Healthcare Research and Quality (AHRQ) publishes a congressionally mandated annual health care disparities report (4). The report documents differences in access and utilization of health care. Some states and localities, including North Carolina (61), Washington (92), Wisconsin (12), and San Francisco (34), have published report cards documenting progress on health inequalities. Recently, Booske et al. (13) developed methods to grade all 50 states on morbidity and mortality within four life stages (infants, children and young adults, working-age adults, and older adults).

In the United Kingdom, the Scientific Reference Group on Health Inequalities is tasked with periodically evaluating progress toward national health targets to reduce socioeconomic inequalities. The most recent report, published in 2009, found that although lower socioeconomic groups experienced gains in life expectancy and infant mortality in the past decade, inequalities continue to persist between the best- and worst-off groups (82). The U.K. Department of Health provides funding to support the annual compilation of community health profiles, which provide information on population health indicators in local regions (5). Although the community health profiles do not rank localities, they do permit comparisons of health indicators across different localities or regions. Advantages to publishing health rankings or report cards include communicating areas of progress or need and potentially increasing public accountability (64); disadvantages are that such summaries result in data loss and are inevitably based on value judgments about how to categorize groups (13).

Recent Policy Efforts in the United States and United Kingdom

Recently, some governments have begun efforts to explore new methods to eliminate health inequalities. In the United States, the NIH is exploring research methods that promote community engagement and focus on the social determinants of inequalities (24). The recently enacted PPACA [Pub. L. 111–148 (2010)] also represents action on the policy front to move forward with understanding and eliminating health inequalities. The law focuses largely on expanding access to health insurance. Because racial/ethnic minorities in the United States tend to be overrepresented in the distribution of the uninsured population (69), the expansion of health insurance coverage is likely to benefit minority populations. Provisions specific to addressing health inequalities aim to improve data collection with respect to race, ethnicity, primary language spoken, and disability (39).

In the United Kingdom, a commission headed by Sir Michael Marmot published an independent review (known as the Marmot Review) of health inequalities in England with the goal of identifying the best evidence-based strategies to address health inequalities (54). Additionally, in response to a recent European Union statement on health inequalities in Europe (21), the European parliament adopted a resolution to call for a more equitable distribution of health, to improve the knowledge base about health inequalities, and to meet the needs of vulnerable groups (27).

Directions for Future Research

Additional research is needed to address gaps related to the evaluation and measurement of progress aimed at addressing health inequalities. Berkman (9) suggests that U.S. trends in health inequalities merit increased attention to the effects of socioeconomic condition, as well as the potential for interventions to have heterogeneous effects across different populations. From a U.K. perspective, Hunter et al. (36) identify three impediments to progress toward reducing health inequalities: interventions that too narrowly target individual behaviors, lack of coordination across governmental entities, and lack of sustained political will. As described above, efforts are being made in these areas.

Some concrete areas of future focus might include enhancing the scope of national and regional health surveys to include sufficient samples of lesser studied, high-risk groups such as Native Americans or aboriginal populations; improving the comparability of health indicators across individuals and countries, and over time; enhancing the knowledge base related to the determinants of health inequalities with a particular focus on social context and other environmental-level factors (rather than individual factors); refining existing measures of inequality so that they might better evaluate the health indicator being measured; and developing new measures of inequality targeted particularly at capturing progress among subpopulations.

CONCLUSION

Compared with several decades ago, there has been enormous progress in the knowledge base related to health inequalities in developed countries. Such evidence has served as an impetus for policy commitments to eliminate health inequalities in the United States, United Kingdom, and other developed countries. This review found that progress to reduce health inequalities at the national level varies by health indicator; progress has been made in some areas, such as smoking prevalence, whereas inequalities remain in other areas, such as infant mortality rates. Large gaps remain in our understanding of the mechanisms underlying health inequalities and the most effective methods for evaluating progress toward the reduction or elimination of health inequalities. Further research is needed to understand better the effects of social- and environmentallevel factors on health inequalities and to refine measures of inequality, particularly with respect to the ability to capture differences among subpopulations.

SUMMARY POINTS

National-level patterns and trends in health inequalities by sex, race/ethnicity, and socioeconomic status in developed countries are well documented in the literature.

The reduction or elimination of health inequalities has become a policy target for many developed countries.

Policy responses have included priority setting via national objectives or goals, information gathering and dissemination, and action steps to change health programs or law.

Despite numerous policy actions, the science of evaluating policies’ effects on health inequalities represents a relatively new area.

More research and better methods are needed to precisely measure relationships between stated policy goals and observed trends in health inequalities.

Glossary

APPENDIX: SUMMARY OF INDIVIDUAL-LEVEL DATA SOURCES USED TO ESTIMATES TRENDS AND PATTERNS

United States

The National Health Interview Survey is an annual, multipurpose health survey of the civilian, noninstitutionalized, households of the United States conducted by the National Center for Health Statistics. U.S. Census Bureau interviewers administer the survey in the respondents’ homes. Adults aged 17 and over are eligible to participate in the survey. All responses are based on self-report. Our analyses were restricted to data from the “Sample Adult Core.” Data sets were included for the following time periods: 1990–2009 (annually).

The National Health and Nutrition Examination Survey (NHANES) combines both in-person interviews and physical exams (including measured height and body weight and blood pressure) to determine the health and nutrition status of noninstitutionalized adults and children in the United States. Data sets were included for the following time periods: 1988–1994, 1999–2000, 2001–2002, 2003–2004, 2005–2006, and 2007–2008.

The Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing telephone survey that has been conducted annually since 1984 to track health conditions and risk behaviors in the United States. The program targets noninstitutionalized adults aged 18 and older in all 50 states, Puerto Rico, U.S. Virgin Islands, and Guam. More than 350,000 adults are interviewed each year. All responses are based on self-report. Data sets were included for the following time periods: 1990–2009.

United Kingdom

The Health Survey for England (HSE) is an annual nationwide household survey of the English population beginning in 1991. Members of a stratified random sample (drawn from the Postcode Address File) that is sociodemographically representative of the English population are invited to participate. Data are collected at two visits: first, an interviewer’s visit during which a questionnaire was administered, and second, a visit from a nurse who measured height, body weight, and blood pressure, among other investigations. All surveys include the adult population aged 16 and over living in private households in England. Data sets were included for the following time periods: 2001–2009.

Footnotes

DISCLOSURE STATEMENT

The authors are not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review.

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