84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 1 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION P A R T I HEALTH OF THE NATION Part I of the book presents the broad outcomes achieved by the health care system and a conceptual framework for understanding health determinants. This part consists of two critical areas represented by two chapters: health outcomes (Chapter 1) and conceptual framework of health determinants (Chapter 2). Chapter 1 focuses on the nation’s health outcomes. After a summary of the U.S. achievements in combating behavior risks, health problems and disparities are highlighted, with particular attention to vulnerable populations. Since the United States is often compared to other nations in terms of its achievements and deficiencies, the concept of global health is also introduced. Chapter 2 introduces some dominant health determinants conceptual framework both international and domestic. The chapter also includes articles that illustrate what a conceptual framework is and how a conceptual framework might be used to understand health and healthcare problems and identify solutions. Part I provides the outcome measurement for the other parts of the book that address input and process respectively. Part I is also a foundation for the rest of the book, providing a “big-picture” view on how much we have accomplished and how much we have yet to achieve. A clear grasp of the materials in Part I will assist in developing a more comprehensive and balanced critique of the U.S. health care system. 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 2 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 3 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION Health Outcomes T are wide discrepancies in the health status of populations within the country, comparing only the health status of white Americans to other countries produced the same dismal results. White Americans are still doing worse than other developed nations for all standard measures of health status. The U.S. also has one of the highest amendable death rates, defined as mortality caused by bacterial infections, treatable cancers, diabetes, cardiovascular disease, cerebrovascular disease, and complications from common surgical procedures (Nolte and McKee 2008). Comparing 50-to-74-year-old Americans to Europeans while adjusting for wealth still placed Americans at worse health than the Europeans (Davies et al. 2007). While Americans were worse off for all levels of health, the discrepancy between Americans and Europeans were worst for poor Americans. Yet, the U.S. has by far the most costly health system in the world, using up 17 percent of the country’s gross domestic product, and has the highest rate of specialist physicians per capita (Davies et al. 2007; Simms 2009). Both physicians and patients consistently provide low ratings to the health care system, with reports of facing numerous barriers to care as well he World Health Organization (WHO) defines health as “a complete state of physical, mental, and social well-being, and not merely the absence of disease or infirmity” (WHO 1948). Over the past century, the United States has made great strides in improving the health of its populations. Since 1900, the average lifespan of persons in the U.S. has lengthened by greater than 30 years and 25 years of this gain are attributable to advances in public health (CDC 1999). The ten public health achievements include vaccination, motorvehicle safety, safer workplaces, control of infectious diseases, decline in deaths from coronary heart disease and stroke, safer and healthier foods, healthier mothers and babies, family planning, fluoridation of drinking water, and recognition of tobacco use as a health hazard. Despite these achievements, the U.S. still ranks low among the developed nations in health status. Out of 30 developed nations in the Organization for Economic Cooperation and Development (OECD), the U.S. is near the bottom in all standard measures of health status (Schroeder 2007). In 2004, the U.S. ranked 46th in life expectancy and 42nd in infant mortality out of 192 nations. While it is true that there 3 C H A P T E R 1 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 4 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 4 CHAPTER 1 HEALTH OUTCOMES as inadequacies of insurance coverage. Compared to other counties, U.S. patients pay much more out of pocket for their medical expenses and are less likely to have a regular source of care, which then affects getting timely care (Avendano et al 2009). In addition, the health status of individuals in the U.S. is mired with inequalities and disparities as a result of numerous factors, including but not limited to socioeconomic status (SES), race/ethnicity, and insurance coverage. SES most commonly incorporates measures of income, education, and occupation. An unfortunate truism in the U.S., and in nearly every other developed country, is that individuals with higher SES have better health. They also have greater ability to access health services and obtain better quality care. SES is related to health and health care in two ways that have been previously labeled material deprivation and lack of social participation (Marmot 2002). Material deprivation includes access to material goods that are required for good health, including clean water and good sanitation, adequate nutrition and housing, reliable transportation, and a safe and comfortable environment. Social participation includes having time for leisure activity and group participation, having friends or family around for entertainment and support, opportunities for professional achievement, and ultimately having sufficient control over one’s life that leads to fulfillment and satisfaction. Without access to material goods and supportive social participation, health may falter, and greater barriers may be experienced in obtaining needed health care services. One of the most prominent inequalities within the U.S. health care system is defined by race (Davies et al. 2007; Blendon et al. 2007). However, race/ ethnicity frequently serves as a proxy measure for other factors that are more appropriate explanatory factors than skin color. Race/ethnicity can be a reflection of biological factors; socioeconomic status; cultural practices, beliefs, or acculturation; or political factors (King and Williams 1995). Race/ethnicity may also serve as a proxy measure of experiencing discrimination. In the case of health outcomes, race/ethnicity may serve as a proxy for biological factors (blacks are more prone to sickle cell anemia, for example), cultural behaviors or practices regarding health, or access to material goods and services that support health. In the case of health care experiences, race/ethnicity may serve as a proxy for socioeconomic factors (enabling the purchase of services), language factors (creating barriers to accessing services), or discrimination based on skin color. Until recently, the U.S. was the only developed nation that does not guarantee its citizens access to health care through a system of universal health coverage. In 2000, WHO released a report ranking countries on the quality of their health systems. The report placed the U.S. in the 37th spot for health system performance and 72nd for health outcome performance (out of 191), primarily because of its failure to ensure access to primary care for the uninsured and because of the relatively low life expectancy and high infant mortality despite the fact that the U.S. spends more than all the other nations on health care (World Health Organization 2000). With the exception of individuals living in close proximity to free health care clinics or community health centers, the uninsured are particularly vulnerable to financial barriers in accessing health care (Kronick 2009; Levy and Meltzer 2008). Once a person is insured, there are three mechanisms by which insurance may be related to health and health care experiences: (1) health plan policies may affect care-seeking and cost-sharing behaviors of beneficiaries, (2) providers’ incentives and reimbursement strategies may influence provider behavior, and (3) perceptions of health insurance plans may create feelings of stigma and affect the use of services and reports of quality. This chapter focuses on the nation’s health. After summarizing our achievements in combating behavior risks, we highlight our health problems and disparities, particularly for one of the most vulnerable populations, the American Indians. Since the United States is often compared to other nations in terms of its achievements and deficiencies, the concept of global health is also introduced. Below are synopses of the readings included for this chapter. In We Can Do Better—Improving the Health of the American People, the author points out that the greatest opportunity to improve the health of Americans and reduce the number of premature deaths lies in personal behavior. History has shown this as a possible solution. There has been a marked increase in the use of seatbelts in the last couple of decades, and recently, Americans have decreased their high consumption of saturated fats. There was also the rapid fall of tobacco use from the mid-1960s to the present with the help of laws, regulations, and litigations, including smoke-free public areas and increased tax on cigarettes. The next problem to be tackled will be obesity, which poses the same obstacles smoking once did on the population. The largest hurdle in dealing with the obesity epidemic is the use of BMI to classify obesity, since the method often misclassifies individuals with large amounts of muscle mass as obese. Litigation is also more difficult since the food industry is not as concentrated as the tobacco industry. 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 5 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION HEALTH OUTCOMES There are more stakeholders involved in the food industry. Improving population health also requires using non-behavioral determinants of health, such as social and environmental factors. Class, as defined by income, total wealth, education, employment, and residential neighborhood, is often an ignored determinant of health, despite obvious gradients in health among members of different social classes. The United Kingdom is at the forefront of addressing effects of class on health. In 1998, they placed the Acheson Commission in charge of reducing health disparities, focusing particularly on social policies for health care, which is absent in the U.S. health care policy framework. Access and quality of care can also influence the health status of a population. The U.S. trails in access to care with 45 million people lacking insurance and several million more underinsured. Lack of insurance or insufficient insurance often leads to poor health because it limits an individual’s access to the health care system. It is difficult to improve population health in the U.S. for several reasons. The system focuses on the health of the middle and upper class, more so than it does on the affected poor with worse health outcomes. Most progress in health care only occurs when the middle class takes action and brings the problem to the forefront. One of the reasons for this is that the poor have no representation in politics. There is no active labor movement in the U.S., unlike other developed nations. In addition, it is difficult to increase the role of U.S. government in health care due to the American culture of individual responsibility that results in reluctance to intervene. In U.S. Disparities in Health: Descriptions, Causes, and Mechanisms, the authors cite Healthy People 2010’s definition of “health disparities” as differences that occur by gender, race or ethnicity, education or income, disability, geographic location, or sexual orientation. Disparities in race/ethnicity have been shown in certain diseases. Compared to whites, blacks have higher standard mortality rates (SMR) for homicides, hypertensive heart disease, esophageal cancer, and pulmonary circulation, and lower SMRs for suicide, leukemia, and COPD. Socioeconomic status (SES) has been found to contribute to a large portion of racial/ethnic disparities. A gradient within the SES correlates to a gradient in health outcomes with lower SES associated with poorer health. Disparities have also been known to change over a life course. There are higher disparities among infants at birth depending on their mother’s education, income, and lifestyle behaviors, but these disparities 5 drop off during childhood, adolescence, and young adulthood. Disparities widen once again during middle age and finally decrease in older populations, most likely as a result of the “weaker” individuals in the population dying off at earlier ages to leave a healthier population at this late stage of life. In Changing Patterns of Mortality Among American Indians, the authors note that the mortality rates of American Indians have shown an alarmingly increasing trend in recent years. For the Navajos, the largest tribe living on a reservation, the mortality rate began to increase at 46 per 100,000 individuals since the mid-1980s, while whites continued to decrease their rates within that same time period. The major source of mortality came from lung cancer, diabetes, and cardiovascular disease while there were decreases in deaths caused by infectious diseases. Morbidity among Navajos saw an increase in non-insulin-dependent diabetes as a result of the increasing rates of obesity made worse by changes in diet and activity patterns. Access to screening and prevention services is limited to the Navajo community. The best solutions to tackle the growing problem of mortality from chronic conditions within this population are primary prevention, i.e., the prevention or reduction of the underlying causes of risk factors. In addition, implementing a broad range of services, rather than only health services, may be better at solving chronic diseases. In Towards a Common Definition of Global Health, the authors start by reviewing two related terms: public health and international health. Public health emerged in Europe and the United States from social reforms and an increased understanding of medicine, including a better understanding of the causes and treatments of infectious diseases. Public health has four important factors: (1) evidence-based decisions, (2) a focus on population care, rather than individual needs, (3) an emphasis on seeking social justice and equity, and (4) prevention rather than treatment. International health focuses on health care abroad, relating more to health practices, policies and systems, and stressing differences among countries. Public health is applied to international health as a means to fix the problems and challenges that affect mostly low-income or middle-income countries. Global health is considered a mixture of both public health and international health. It focuses on problems with an international scope, rather than where the problem exists, embracing all health threats in addition to infectious diseases and maternal and child care that are problems in low-income and middle-income countries. Important topics in global health consist of under- and over-nutrition, 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 6 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 6 CHAPTER 1 HEALTH OUTCOMES HIV/AIDS, tobacco use, malaria, and mental health. While global health emphasizes prevention, it also covers aspects of clinical medicine, including treatment and rehabilitation. The proposed definition of global health states that “global health is an area for study, research, practice that places a priority on improving health and achieving equity in health for all people worldwide . . . emphasizing transnational health issues, determinants, and solutions involving many disciplines within and beyond the health sciences and promotes interdisciplinary collaboration synthesis of population-based prevention with individual clinician care.” References Avendano et al. “Health Disadvenatges in US Adults Aged 50 to 74 Years: A Comparison of the Health of Rich and Poor Americans With That of Europeans.” American Journal of Public Health. 99(2009):540-548. Blendon et al. Disparities in Health: Perspectives of A Multi-Ethnic, Multi-Racial America. Health Affairs. 26(2007):1437-1447. The Centers for Disease Control and Prevention (CDC). Ten Great Public Health Achievements—United States, 1900-1999. MMWR April 02, 1999/ 48(12);241-243. Davies et al. “Mirror, Mirror on the Wall: An International Update on the Comparative Performance of American Health Care.” The Commonwealth Fund, 2007. King G; Williams D. Race and health: A multidimensional approach to African-American health. In B. Amick III, S. Levine, A.Talov, and D. Chapman Walsh (Eds.), Society and Health. Pp.93-130, New York, Oxford University Press, 1995. Kronick, R. Health Insurance Coverage and Mortality Revisited. Health Services Research 44(2009): 1211-1231 Levy, H; Meltzer, D. The Impact of Health Insurance on Health. Ann. Rev. Public Health 29(2008):399-409. Marmot, M. The influence of income on health: Views of an epidemiologist. Does money really matter? Or is it a marker for something else? Health Affairs 21(2):31-46, 2002. Nolte E; McKee CM. Measuring the health of nations: Updating an earlier analysis. Health Aff 2008;27: 58-71. Schroeder SA. Shattuck Lecture. We can do better— improving the health of the American people. N Engl J Med 2007;357:1221-8. Simms, Chris. Inequalities in the Ameican health-care system. The Lancet. 373(2009):1252 World Health Organization (WHO). Preamble to the Constitution. Geneva, Switzerland, 1948. World Health Organization (WHO). World health report 2000: Health system performance. Geneva, Switzerland, 2000. 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 7 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION R E A D I N G 1 We Can Do Better—Improving the Health of the American People HEALTH STATUS OF THE AMERICAN PUBLIC Source: Schroeder SA. Shattuck Lecture. We can do better—improving the health of the American people. N Engl J Med 2007;357:1221-8. Copyright © 2007 Massachusetts Medical Society. All rights reserved. Among the 30 developed nations that make up the Organization for Economic Cooperation and Development (OECD), the United States ranks near the bottom on most standard measures of health status (Table 1).1-4 (One measure on which the United States does better is life expectancy from the age of 65 years, possibly reflecting the comprehensive health insurance provided for this segment of the population.) Among the 192 nations for which 2004 data are available, the United States ranks 46th in average life expectancy from birth and 42nd in infant mortality.5,6 It is remarkable how complacent the public and the medical profession are in their acceptance of these unfavorable comparisons, especially in light of how carefully we track health-systems measures, such as the size of the budget for the National Institutes of Health, trends in national spending on health, and the number of Americans who lack health insurance. One reason for the complacency may be the rationalization that the United States is more ethnically heterogeneous than the nations at the top of the rankings, such as Japan, Switzerland, and Iceland. It is true that within the United States there are large disparities in health status—by geographic area, race and ethnic group, and class.7-9 But even when comparisons are limited to white Americans, our performance is dismal (Table 1). And even if the health status of white Americans matched that in the leading nations, it would still be incumbent on us to improve the health of the entire nation. The United States spends more on health care than any other nation in the world, yet it ranks poorly on nearly every measure of health status. How can this be? What explains this apparent paradox? The two-part answer is deceptively simple— first, the pathways to better health do not generally depend on better health care, and second, even in those instances in which health care is important, too many Americans do not receive it, receive it too late, or receive poor-quality care. In this lecture, I first summarize where the United States stands in international rankings of health status. Next, using the concept of determinants of premature death as a key measure of health status, I discuss pathways to improvement, emphasizing lessons learned from tobacco control and acknowledging the reality that better health (lower mortality and a higher level of functioning) cannot be achieved without paying greater attention to poor Americans. I conclude with speculations on why we have not focused on improving health in the United States and what it would take to make that happen. 7 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 8 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 8 CHAPTER 1 HEALTH OUTCOMES Table 1 Health Status of the United States and Rank among the 29 Other OECD Member Countries U.S. Rank Top-Ranked Health-Status Measure United States Country in OECD* in OECD Infant mortality (first year of life), 2001 All races 6.8 deaths/ 25 Iceland 1000 live births (2.7 deaths/ 1000 live births) Whites only 5.7 deaths/ 22 1000 live births Maternal mortality, 2001† All races 9.9 deaths/ 22 Switzerland 100,000 births -(1.4 deaths/ 100,000 births) Whites only 7.2 deaths/ 19 100,000 births Life expectancy from birth, 2003 All women 80.1 yr 23 Japan (85.3 yr) White women 80.5 yr 22 All men 74.8 yr 22 Iceland (79.7 yr) White men 75.3 yr 19 Life expectancy from age 65, 2003‡ All women 19.8 yr 10 Japan (23.0 yr) White women 19.8 yr 10 All men 16.8 yr 9 White men 16.9 yr 9 *The number in parentheses is the value for the indicated health-status measure. †OECD data for five countries are missing. ‡OECD data for six countries are missing. PATHWAYS TO IMPROVING POPULATION HEALTH Health is influenced by factors in five domains— genetics, social circumstances, environmental exposures, behavioral patterns, and health care (Fig. 1).10,11 When it comes to reducing early deaths, medical care has a relatively minor role. Even if the entire U.S. population had access to excellent medical care—which it does not—only a small fraction of these deaths could be prevented. The single greatest opportunity to improve health and reduce premature deaths lies in personal behavior. In fact, behavioral causes account for nearly 40% of all deaths in the United States.12 Although there has been disagreement over the actual number of deaths that can be attributed to obesity and physical inactivity combined, it is clear that this pair of factors and smoking are the top two behavioral causes of premature death (Fig. 2, not included).12 Addressing Unhealthy Behavior Clinicians and policymakers may question whether behavior is susceptible to change or whether attempts to change behavior lie outside the province of traditional medical care.13 They may expect future successes to follow the pattern whereby immunization and antibiotics improved health in the 20th century. If the public’s health is to improve, however, that improvement is more likely to come from behavioral change than from technological innovation. Experience demonstrates that it is in fact possible to change behavior, as illustrated by increased seat-belt use and decreased consumption of products high in saturated fat. The case of tobacco best demonstrates how rapidly positive behavioral change can occur. The Case of Tobacco The prevalence of smoking in the United States declined among men from 57% in 1955 to 23% in 2005 and among women from 34% in 1965 to 18% in 2005.14,15 Why did tobacco use fall so rapidly? The 1964 report of the surgeon general, which linked smoking and lung cancer, was followed by multiple reports connecting active and passive smoking to myriad other diseases. Early antismoking advocates, initially isolated, became emboldened by the cascade 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 9 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION READING 1: We Can Do Better—Improving the Health of the American People of scientific evidence, especially with respect to the risk of exposure to secondhand smoke. Countermarketing—first in the 1960s and more recently by several states and the American Legacy Foundation’s “truth ®” campaign—linked the creativity of Madison Avenue with messages about the duplicity of the tobacco industry to produce compelling antismoking messages16 (an antismoking advertisement is available with the full text of this article at www.nejm.org). Laws, regulations, and litigation, particularly at the state and community levels, led to smoke-free public places and increases in the tax on cigarettes—two of the strongest evidence-based tobacco-control measures.14,17,18 In this regard, local governments have been far ahead of the federal government, and they have inspired European countries such as Ireland and the United Kingdom to make public places smoke-free.14,19 In addition, new medications have augmented face-to-face and telephone counseling techniques to increase the odds that clinicians can help smokers quit.15,20,21 It is tempting to be lulled by this progress and shift attention to other problems, such as the obesity epidemic. But there are still 44.5 million smokers in the United States, and each year tobacco use kills 435,000 Americans, who die up to 15 years earlier than nonsmokers and who often spend their final years ravaged by dyspnea and pain.14,20 In addition, smoking among pregnant women is a major contributor to premature births and infant mortality.20 Smoking is increasingly concentrated in the lower socioeconomic classes and among those with mental illness or problems with substance abuse.15,22,23 People with chronic mental illness die an average of 25 years earlier than others, and a large percentage of those years are lost because of smoking.24 Estimates from the Smoking Cessation Leadership Center at the University of California at San Francisco, which are based on the high rates and intensity (number of cigarettes per day plus the degree to which each is finished) of tobacco use in these populations, indicate that as many as 200,000 of the 435,000 Americans who die prematurely each year from tobacco-related deaths are people with chronic mental illness, substance-abuse problems, or both.22,25 Understanding why they smoke and how to help them quit should be a key national research priority. Given the effects of smoking on health, the relative inattention to tobacco by those federal and state agencies charged with protecting the public health is baffling and disappointing. The United States is approaching a “tobacco tipping point”—a state of greatly reduced smoking prevalence. There are already low rates of smoking in some segments of the population, including physi- 9 cians (about 2%), people with a postgraduate education (8%), and residents of the states of Utah (11%) and California (14%).25 When Kaiser Permanente of northern California implemented a multisystem approach to help smokers quit, the smoking rate dropped from 12.2% to 9.2% in just 3 years.25 Two basic strategies would enable the United States to meet its Healthy People 2010 tobacco-use objective of 12% population prevalence: keep young people from starting to smoke and help smokers quit. Of the two strategies, smoking cessation has by far the larger short-term impact. Of the current 44.5 million smokers, 70% claim they would like to quit.20 Assuming that one half of those 31 million potential non-smokers will die because of smoking, that translates into 15.5 million potentially preventable premature deaths.20,26 Merely increasing the baseline quit rate from the current 2.5% of smokers to 10%—a rate seen in placebo groups in most published trials of the new cessation drugs— would prevent 1,170,000 premature deaths. No other medical or public health intervention approaches this degree of impact. And we already have the tools to accomplish it.14,27 Is Obesity the Next Tobacco? Although there is still much to do in tobacco control, it is nevertheless touted as a model for combating obesity, the other major, potentially preventable cause of death and disability in the United States. Smoking and obesity share many characteristics (Table 2). Both are highly prevalent, start in childhood or adolescence, were relatively uncommon until the first (smoking) or second (obesity) half of the 20th century, are major risk factors for chronic disease, involve intensively marketed products, are more common in low socioeconomic classes, exhibit major regional variations (with higher rates in southern and poorer states), carry a stigma, are difficult to treat, and are less enthusiastically embraced by clinicians than other risk factors for medical conditions. Nonetheless, obesity differs from smoking in many ways (Table 2). The binary definition of smoking status (smoker or nonsmoker) does not apply to obesity. Body-mass index, the most widely used measure of obesity, misclassifies as overweight people who have large muscle mass, such as California governor Arnold Schwarzenegger. It is not biologically possible to stop eating, and unlike moderate smoking, eating a moderate amount of food is not hazardous. There is no addictive analogue to nicotine in food. Nonsmokers mobilize against tobacco because they fear injury from secondhand exposure, which is not a peril that attends obesity. The food industry is less concentrated than the tobacco 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 10 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 10 CHAPTER 1 HEALTH OUTCOMES Table 2 Similarities and Differences between Tobacco Use and Obesity Characteristic Tobacco Obesity High prevalence Yes Yes Begins in youth Yes Yes 20th-century phenomenon Yes Yes Major health implications Yes Yes Heavy and influential Yes Yes industry promotion Inverse relationship to Yes Yes socioeconomic class Major regional variations Yes Yes Stigma Yes Yes Difficult to treat Yes Yes Clinician antipathy Yes Yes Relative and debatable definition No Yes Cessation not an option No Yes Chemical addictive component Yes No Harmful at low doses Yes No Harmful to others Yes No Extensively documented Yes No industry duplicity History of successful litigation Yes No Large cash settlements by industry Yes No Strong evidence base for treatment Yes No Economic incentives available Yes Yes Economic incentives in place Yes No Successful counter-marketing campaigns Yes No industry, and although its advertising for children has been criticized as predatory and its ingredientlabeling practices as deceptive, it has yet to fall into the ill repute of the tobacco industry. For these reasons, litigation is a more problematic strategy, and industry payouts—such as the Master Settlement Agreement between the tobacco industry and 46 state attorneys general to recapture the Medicaid costs of treating tobacco-related diseases—are less likely.14 Finally, except for the invasive option of bariatric surgery, there are even fewer clinical tools available for treating obesity than there are for treating addiction to smoking. Several changes in policy have been proposed to help combat obesity.28-30 Selective taxes and subsidies could be used as incentives to change the foods that are grown, brought to market, and consumed, though the politics involved in designating favored and penalized foods would be fierce.31 Restrictions could also apply to the use of food stamps. Given recent data indicating that children see from 27 to 48 food advertisements for each 1 promoting fitness or nutrition, regulations could be put in place to shift that balance or to mandate support for sustained social-marketing efforts such as the “truth®” campaign against smoking.16,32 Requiring more accurate labeling of caloric content and ingredients, especially in fast-food outlets, could make customers more aware of what they are eating and induce manufacturers to alter food composition. Better pharmaceutical products and counseling programs could motivate clinicians to view obesity treatment more enthusiastically. In contrast to these changes in policy, which will require national legislation, regulation, or research investment, change is already underway at the local level. Some schools have banned the sale of soft drinks and now offer more nutritionally balanced lunches. Opportunities for physical activity at work, in school, and in the community have been expanded in a small but growing number of locations. Nonbehavioral Causes of Premature Death Improving population health will also require addressing the nonbehavioral determinants of health that we can influence: social, health care, and environmental factors. (To date, we lack tools to change our genes, although behavioral and environmental factors can modify the expression of genetic risks such as obesity.) With respect to social factors, people with lower socioeconomic status die earlier and have more disability than those with higher socioeconomic status, and this pattern holds true in a stepwise fashion from the lowest to the highest classes.33-38 In this context, class is a composite construct of income, total wealth, education, employment, and residential neighborhood. One reason for the class gradient in health is that people in lower classes are more likely to have unhealthy behaviors, in part because of inadequate local food choices and recreational opportunities. Yet even when behavior is held constant, people in lower classes are less healthy and die earlier than others.33-38 It is likely that the deleterious influence of class on health reflects both absolute and relative material deprivation at the lower end of the spectrum and psychosocial stress along the entire continuum. Unlike the factors of health care and behavior, class has been an “ignored determinant of the nation’s health.”33 Disparities in health care are of concern to some policymakers and researchers, but because the United States uses race and ethnic group rather than class as the filter through which social differences are analyzed, studies often highlight disparities in the receipt of health care that are based on race and ethnic group rather than on class. But aren’t class gradients a fixture of all societies? And if so, can they ever be diminished? The fact is that nations differ greatly in their degree of 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 11 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION READING 1: We Can Do Better—Improving the Health of the American People social inequality and that—even in the United States—earning potential and tax policies have fluctuated over time, resulting in a narrowing or widening of class differences. There are ways to address the effects of class on health.33 More investment could be made in research efforts designed to improve our understanding of the connection between class and health. More fundamental, however, is the recognition that social policies involving basic aspects of life and well-being (e.g., education, taxation, transportation, and housing) have important health consequences. Just as the construction of new buildings now requires environmental-impact analyses, taxation policies could be subjected to health-impact analyses. When public policies widen the gap between rich and poor, they may also have a negative effect on population health. One reason the United States does poorly in international health comparisons may be that we value entrepreneurialism over egalitarianism. Our willingness to tolerate large gaps in income, total wealth, educational quality, and housing has unintended health consequences. Until we are willing to confront this reality, our performance on measures of health will suffer. One nation attempting to address the effects of class on health is the United Kingdom. Its 1998 Acheson Commission, which was charged with reducing health disparities, produced 39 policy recommendations spanning areas such as poverty, income, taxes and benefits, education, employment, housing, environment, transportation, and nutrition. Only 3 of these 39 recommendations pertained directly to health care: all policies that influence health should be evaluated for their effect on the disparities in health resulting from differences in socioeconomic status; a high priority should be given to the health of families with children; and income inequalities should be reduced and living standards among the poor improved.39 Although implementation of these recommendations has been incomplete, the mere fact of their existence means more attention is paid to the effects of social policies on health. This element is missing in U.S. policy discussions—as is evident from recent deliberations on income-tax policy. Although inadequate health care accounts for only 10% of premature deaths, among the five determinants of health (Fig. 1, not included), health care receives by far the greatest share of resources and attention. In the case of heart disease, it is estimated that health care has accounted for half of the 40% decline in mortality over the past two decades.40 (It may be that exclusive reliance on international mortality comparisons shortchanges the results of America’s health care system. Perhaps the 11 high U.S. rates of medical technology use translate into comparatively better function. To date, there are no good international comparisons of functional status to test that theory, but if it could be substantiated, there would be an even more compelling claim for expanded health insurance coverage.) U.S. expenditures on health care in 2006 were an estimated $2.1 trillion, accounting for 16% of our gross domestic product.41 Few other countries even reach double digits in health care spending. There are two basic ways in which health care can affect health status: quality and access. Although qualitative deficiencies in U.S. health care have been widely documented,42 there is no evidence that its performance in this dimension is worse than that of other OECD nations. In the area of access, however, we trail nearly all the countries: 45 million U.S. citizens (plus millions of immigrants) lack health insurance, and millions more are seriously underinsured. Lack of health insurance leads to poor health.43 Not surprisingly, the uninsured are disproportionately represented among the lower socioeconomic classes. Environmental factors, such as lead paint, polluted air and water, dangerous neighborhoods, and the lack of outlets for physical activity also contribute to premature death. People with lower socioeconomic status have greater exposure to these health-compromising conditions. As with social determinants of health and health insurance coverage, remedies for environmental risk factors lie predominantly in the political arena.44 THE CASE FOR CONCENTRATING ON THE LESS FORTUNATE Since all the actionable determinants of health—personal behavior, social factors, health care, and the environment—disproportionately affect the poor, strategies to improve national health rankings must focus on this population. To the extent that the United States has a health strategy, its focus is on the development of new medical technologies and support for basic biomedical research. We already lead the world in the per capita use of most diagnostic and therapeutic medical technologies, and we have recently doubled the budget for the National Institutes of Health. But these popular achievements are unlikely to improve our relative performance on health. It is arguable that the status quo is an accurate expression of the national political will—a relentless search for better health among the middle and upper classes. This pursuit is also evident in how 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 12 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 12 CHAPTER 1 HEALTH OUTCOMES we consistently outspend all other countries in the use of alternative medicines and cosmetic surgeries and in how frequently health “cures” and “scares” are featured in the popular media.45 The result is that only when the middle class feels threatened by external menaces (e.g., secondhand tobacco smoke, bioterrorism, and airplane exposure to multidrugresistant tuberculosis) will it embrace public health measures. In contrast, our investment in improving population health—whether judged on the basis of support for research, insurance coverage, or government-sponsored public health activities—is anemic.46-48 Although the Department of Health and Human Services periodically produces admirable population health goals—most recently, the Healthy People 2010 objectives49—no government department or agency has the responsibility and authority to meet these goals, and the importance of achieving them has yet to penetrate the political process. WHY DON’T AMERICANS FOCUS ON FACTORS THAT CAN IMPROVE HEALTH? The comparatively weak health status of the United States stems from two fundamental aspects of its political economy. The first is that the disadvantaged are less well represented in the political sphere here than in most other developed countries, which often have an active labor movement and robust labor parties. Without a strong voice from Americans of low socioeconomic status, citizen health advocacy in the United States coalesces around particular illnesses, such as breast cancer, human immunodeficiency virus infection and the acquired immunodeficiency syndrome (HIV–AIDS), and autism. These efforts are led by middle-class advocates whose lives have been touched by the disease. There have been a few successful public advocacy campaigns on issues of population health—efforts to ban exposure to secondhand smoke or to curtail drunk driving—but such efforts are relatively uncommon.44 Because the biggest gains in population health will come from attention to the less well off, little is likely to change unless they have a political voice and use it to argue for more resources to improve health-related behaviors, reduce social disparities, increase access to health care, and reduce environmental threats. Social advocacy in the United States is also fragmented by our notions of race and class.33 To the extent that poverty is viewed as an issue of racial injustice, it ignores the many whites who are poor, thereby reducing the ranks of potential advocates. The relatively limited role of government in the U.S. health care system is the second explanation. Many are familiar with our outlier status as the only developed nation without universal health care coverage.50 Less obvious is the dispersed and relatively weak status of the various agencies responsible for population health and the fact that they are so disconnected from the delivery of health services. In addition, the American emphasis on the value of individual responsibility creates a reluctance to intervene in what are seen as personal behavioral choices. HOW CAN THE NATION’S HEALTH IMPROVE? Given that the political dynamics of the United States are unlikely to change soon and that the less fortunate will continue to have weak representation, are we consigned to a low-tier status when it comes to population health? In my view, there is room for cautious optimism. One reason is that despite the epidemics of HIV–AIDS and obesity, our population has never been healthier, even though it lags behind so many other countries. The gain has come from improvements in personal behavior (e.g., tobacco control), social and environmental factors (e.g., reduced rates of homicide and motor-vehicle accidents and the introduction of fluoridated water), and medical care (e.g., vaccines and cardiovascular drugs). The largest potential for further improvement in population health lies in behavioral risk factors, especially smoking and obesity. We already have tools at hand to make progress in tobacco control, and some of these tools are applicable to obesity. Improvement in most of the other factors requires political action, starting with relentless measurement of and focus on actual health status and the actions that could improve it. Inaction means acceptance of America’s poor health status. Improving population health would be more than a statistical accomplishment. It could enhance the productivity of the workforce and boost the national economy, reduce health care expenditures, and most important, improve people’s lives. But in the absence of a strong political voice from the less fortunate themselves, it is incumbent on health care professionals, especially physicians, to become champions for population health. This sense of purpose resonates with our deepest professional values and is the reason why many chose medicine as a profession. It is also one of the most productive expressions of patriotism. Americans take great pride in asserting that we are number one in terms of wealth, 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 13 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION READING 1: We Can Do Better—Improving the Health of the American People number of Nobel Prizes, and military strength. Why don’t we try to become number one in health? ACKNOWLEDGMENTS Supported in part by grants from the Robert Wood Johnson and American Legacy Foundations. The sponsors had no role in the preparation of the Shattuck Lecture. No potential conflict of interest relevant to this article was reported. I thank Stephen Isaacs for editorial assistance; Michael McGinnis, Harold Sox, Stephen Shortell, and Nancy Adler for comments on an earlier draft; and Kristen Kekich and Katherine Kostrzewa for technical support. References 1. OECD health data 2006 (2001 figures). Paris: Organisation for Economic Cooperation and Development, October 2006. 2 Infant, neonatal, and postneonatal deaths, percent of total deaths, and mortality rates for the 15 leading causes of infant death by race and sex: United States, 2001. Hyattsville, MD: National Center for Health Statistics. (Accessed August 24, 2007, at http://www.cdc.gov/search.do? action=search &queryText=infant+mortality +rate+2001&x= 18&y=15.) 10. McGinnis JM,Williams-Russo P, Knickman JR. The case for more active policy attention to health promotion. Health Aff (Millwood) 2002;21(2):78-93. 11. McGinnis JM, Foege WH. Actual causes of death in the United States. JAMA 1993;270:2207-12. 12. Mokdad AH, Marks JS, Stroup JS, Gerberding JL. Actual causes of death in the United States, 2000. JAMA 2004;291: 1238-45. [Errata, JAMA 2005;293:293-4, 298.] 13. Seldin DW. The boundaries of medicine. Trans Assoc Am Phys 1981;38:lxxv-lxxxvi. 14. Schroeder SA. Tobacco control in the wake of the 1998 Master Settlement Agreement. N Engl J Med 2004;350:293-301. 15. Idem. What to do with the patient who smokes? JAMA 2005;294:482-7. 16. Farrelly MC, Healton CH, Davis KC, et al. Getting to the truth: evaluating national tobacco countermarketing campaigns. Am J Public Health 2002; 92:901-7. [Erratum, Am J Public Health 2003;93:703.] 17. Warner KE. Tobacco policy research: insights and contributions to public health policy. In: Warner KE, ed. Tobacco control policy. San Francisco: Jossey-Bass, 2006:3-86. 3. Hoyert DL. Maternal mortality and related concepts. Vital Health Stat 3 2007;33:4. 18. Schroeder SA. An agenda to combat substance abuse. Health Aff (Millwood) 2005;24:1005-13. 4. Chartbook on trends in the health of Americans. Table 27: life expectancy at birth, at age 65 years of age, and at age 75 years of age, by race and sex: United States, selected years 1900-2004:193. Hyattsville, MD: National Center for Health Statistics. (Accessed August 24, 2007, at http://www. cdc.gov/nchs/fastats/lifexpec.htm.) 19. Koh HK, Joossens LX, Connolly GN. Making smoking history worldwide. N Engl J Med 2007;356:1496-8. 5. WHO core health indicators. Geneva: World Health Organization. (Accessed August 24, 2007, at http://www3.who.int/whosis/core/core_select_ process.cfm.) 6. Minino AM, Heron M, Smith BL. Deaths: preliminary data for 2004. Health E-Stats. Released April 19, 2006. (Accessed August 24, 2007, at http://www.cdc.gov/nchs/products/pubs/pubd/hestats/ prelimdeaths04/preliminarydeaths04.htm.) 13 20. Fiore MC, Bailey WC, Cohen SJ, et al. Treating tobacco use and dependence: clinical practice guideline. Rockville, MD: Public Health Service, 2000. 21. Schroeder SA, Sox HC. Trials that matter: varenicline—a new designer drug to help smokers quit. Ann Intern Med 2006;145:784-5. 22. Lasser K, Boyd JW, Woolhandler S, Himmelstein DU, McCormick D, Bor DH. Smoking and mental illness: a population-based prevalence study. JAMA 2000;284: 2606-10. 8. Murray JL, Kulkarni SC, Michaud C, et al. Eight Americas: investigating mortality disparities across races, counties, and race-counties in the United States. PLoS Med 2006;3(9):e260. 23. Zeidonis DM, Williams JM, Steinberg ML, et al. Addressing tobacco dependence among veterans with a psychiatric disorder: a neglected epidemic of major clinical and public health concern. In: Isaacs SL, Schroeder SA, Simon JA, eds. VA in the vanguard: building on success in smoking cessation. Washington, DC: Department of Veterans Affairs, 2005: 141-70. (Accessed, August 24, 2007, at http://smokingcessationleadership.ucsf. edu/AboutSCLC_vanguard.html.) 9. Woolf SH, Johnson RE, Phillips RL, Philipsen M. Giving everyone the health of the educated: an examination of whether social change would save more lives than medical advances. Am J Public Health 2007;97:679-83. 24. Colton CW, Manderscheid RW. Congruencies in increased mortality rates, years of potential life lost, and causes of death among public mental health clients in eight states. Prev Chronic Dis 2006;3:April (online only). (Accessed August 24, 7. Harper S, Lynch J, Burris S, Davey Smith G. Trends in the black-white life expectancy gap in the United States, 19832003. JAMA 2007;297:1224-32. 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 14 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 14 CHAPTER 1 HEALTH OUTCOMES 2007, at http://www.cdc.gov/pcd/issues/2006/ apr/ 05_0180.htm.) 25. Smoking Cessation Leadership Center. Partner highlights. (Accessed August 24, 2007, at http:// smokingcessationleadership.ucsf.edu/Partner Featured.html.) 26. Doll R, Peto R, Boreham J, Sutherland I. Mortality in relation to smoking: 50 years’ observations on male British doctors. BMJ 2004;328:1519-27. 27. Fiore MC, Croyle RT, Curry SJ, et al. Preventing 3 million premature deaths and helping 5 million smokers quit: a national action plan for tobacco cessation. Am J Public Health 2004;94:205-10. 28. Nestle M. Food marketing and childhood obesity— a matter of policy. N Engl J Med 2006;354:2527-9. 29. Mello MM, Studdert DM, Brennan TA. Obesity— the new frontier of public health law. N Engl J Med 2006;354:2601-10. 30. Gostin LO. Law as a tool to facilitate healthier lifestyles and prevent obesity. JAMA 2007;297: 87-90. 31. Pollan M. You are what you grow. New York Times Sunday Magazine. April 22, 2007:15-8. 32. Food for thought: television food advertising to children in the United States. Menlo Park, CA: Kaiser Family Foundation, March 2007:3. 33. Isaacs SL, Schroeder SA. Class—the ignored determinant of the nation’s health. N Engl J Med 2004;351:1137-42. 34. Adler NE, Boyce WT, Chesney MA, Folkman S, Syme SL. Socioeconomic inequalities in health: no easy solution. JAMA 1993;269:3140-5. 35. McDonough P, Duncan GJ, Williams DR, House J. Income dynamics and adult mortality in the United States,1972 through 1989. Am J Public Health 1997;87:1476-83. 36. Marmot M. Inequalities in health. N Engl J Med 2001;345:134-6. 37. Williams DR, Collins C. US socioeconomic and racial differences in health: patterns and explanations. Annu Rev Sociol 1995;21:349-86. 38. Minkler M, Fuller-Thomson E, Guralnik JM. Gradient of disability across the socioeconomic spectrum in the United States. N Engl J Med 2006;355:695-703. 39. Independent inquiry into inequalities in health report. London: Stationery Office, 1998 (Accessed August 24, 2007, at http://www.archive.official-doc uments.co.uk/document/doh/ih/contents.htm.) 40. Ford ES, Ajani UA, Croft JB, et al. Explaining the decrease in U.S. deaths from coronary disease, 1980–2000. N Engl J Med 2007;356:2388-98. 41. Poisal JA, Truffer C, Smith S, et al. Health spending projections through 2016: modest changes obscure Part D’s impact. Health Aff (Millwood) 2007;26:w242-w253 (Web only). (Accessed August 24, 2007, at http://content.healthaffairs.org/cgi/ content/full/26/2/w242.) 42. Institute of Medicine. To err is human: building a safer health system. Washington, DC: National Academy Press, 2000. 43. Idem. Hidden costs, value lost: uninsurance in America. Washington, DC: National Academy of Sciences, 2003. 44. Isaacs SL, Schroeder SA. Where the public good prevailed: lessons from success stories in health. The American Prospect. June 4, 2001:26-30. 45. Gawande A. Annals of medicine: the way we age now. The New Yorker. April 30, 2007:50-9. 46. McGinnis JM. Does proof matter? Why strong evidence sometimes yields weak action. Am J Health Promot 2001;15:391-6. 47. Kindig DA. A pay-for-population health performance system. JAMA 2006; 296:2611-3. 48. Woolf SH. Potential health and economic consequences of misplaced priorities. JAMA 2007;297:523-6. 49. Healthy People 2010: understanding and improving health. Washington, DC: Department of Health and Human Services, 2001. 50. Schroeder SA. The medically uninsured—will they always be with us? N Engl J Med 1996;334:1130-3. 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 15 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION R E A D I N G 2 U.S. Disparities in Health: Descriptions, Causes, and Mechanisms race/ethnicity and social class. Finally, we discuss potential pathways, including exposure to chronic stress and resulting psychosocial and physiological responses to stress, that serve as mechanisms by which social disadvantage results in health disparities. Source: Adler NE, Rehkopf DH. U.S. disparities in health: descriptions, causes, and mechanisms. Annu Rev Public Health 2008;29:235-52. ABSTRACT INTRODUCTION Eliminating health disparities is a fundamental, though not always explicit, goal of public health research and practice. There is a burgeoning literature in this area, but a number of unresolved issues remain. These include the definition of what constitutes a disparity, the relationship of different bases of disadvantage, the ability to attribute cause from association, and the establishment of the mechanisms by which social disadvantage affects biological processes that get into the body, resulting in disease. We examine current definitions and empirical research on health disparities, particularly disparities associated with race/ethnicity and socioeconomic status, and discuss data structures and analytic strategies that allow causal inference about the health impacts of these and associated factors. We show that although health is consistently worse for individuals with few resources and for blacks as compared with whites, the extent of health disparities varies by outcome, time, and geographic location within the United States. Empirical work also demonstrates the importance of a joint consideration of Few terms have had such a meteoric rise into common usage in the health literature as has “health disparities.” In the 1980s this was a key word in only one article, and in the 1990s there were fewer than 30 such articles. In contrast, during the five years from 2000 through 2004, more than 400 such articles appeared.3 An equivalent increase occurred in the number of articles containing the key term of “health inequalities.” Prior to this time, there was substantial work on the problem of health disparities, but it was usually framed in terms of specific factors such as race or poverty.60 One of the first uses of the term inequality with respect to health differences was in the title of the Working Group on Inequalities in Health, which issued the Black Report in Great Britain in 1980. In advance, it seemed likely that the working group would find reductions in social class differences in mortality following the provision of universal health care through the National Health Service. However, they found that the gap between the health of low and high social class individuals had actually 15 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 16 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 16 CHAPTER 1 HEALTH OUTCOMES widened. Around the same time, the Whitehall Study of British Civil Servants68 revealed significant differences in cardiovascular disease and mortality69 by occupational level within a population of officebased workers. Notably, differences were not just between those at the top and bottom. Rather, disease prevalence and mortality increased at each step down in occupational grade. Spurred by these and other data, another commission, the Independent Inquiry into Inequalities in Health, made recommendations for policies in Great Britain to reduce health inequalities.2 During this period, research on socioeconomic and racial/ethnic differences in health was also being conducted in the United States. Beginning in the 1970s, investigators linked death records to socioeconomic data from the Current Population Study, to the U.S. Census, and to Social Security Administration records. The findings documented at a nationwide level substantially higher age-adjusted mortality rates for nonwhites, individuals with less education, individuals with low incomes, and for some occupational categories.16,58,59 These data and the British findings provided an impetus to determine the extent and nature of health disparities in the United States and identify ways to reduce them. Efforts have included a report from the National Center for Health Statistics on differences in mortality and morbidity by socioeconomic status,80 Healthy People 2010,100 which established the goal of eliminating health disparities in addition to the goal of improving health, and the passage of the Minority Health and Health Disparities Research and Education Act of 2000. This legislation established the National Center on Minority Health and Health Disparities to coordinate activities among the NIH institutes. The Institute of Medicine recently reviewed the NIH plan and made a number of recommendations to improve its effectiveness.99 As reflected in the dual goals of Healthy People 2010, public health research and practice aim both to improve health and to eliminate disparities. Previous papers in the Annual Review of Public Health have examined substantive and methodological aspects of specific types of disparities. Some reviews concerned measurement issues and health effects of poverty, class, and/or socioeconomic status(e.g.,1,36,61), of race and ethnicity (e.g.,64,70,105), and of rural residence.88 None has considered disparities per se. Eliminating disparities requires a clear definition to allow measurement and monitoring of progress toward that goal and to understand their causes. Here we examine the definition of health dis- parities and empirical findings on disparities associated with race/ethnicity and socioeconomic status. We then consider methodological challenges and solutions to understanding the causes of health disparities. DEFINITION OF HEALTH DISPARITIES The literature lacks a consensually agreed on definition of health disparities. Healthy People 2010 referenced “differences that occur by gender, race or ethnicity, education or income, disability, geographic location, or sexual orientation.”100,p.14 Carter-Pokras & Baquet17 identified 11 different definitions of health disparities. Some were inclusive, some limited disparities to those associated with race and ethnicity, and still others defined it only in terms of disparities in health care. The various definitions imply and sometimes explicitly suggest the relevant comparison group for establishing a disparity. Definitions of racial/ethnic disparities suggest that a group’s health status be compared with the majority, the population average, or the healthiest group. Thus, one might compare African American mortality rates to national rates, to European Americans who are the majority group in the United States, or to Asian Americans, who have in aggregate the lowest mortality rates. Depending on the relative size and the relative health of the majority group and the healthiest group, one could reach different conclusions about the extent of a disparity. With the exception of Murray and colleagues,78 who examined a range of socio-demographic characteristics of groups with markedly different life expectancies, most approaches to disparities start with bases of social disadvantage, which result in differences that are unjust and avoidable.13,15 Healthy People 2010 distinguishes between a health difference, which results from inherent biological differences (e.g., only women are subject to ovarian cancer and men to prostate cancer), and a disparity, which results from social factors. What constitutes a difference versus a disparity may sometimes be unclear, however. In the example of ovarian and prostate cancer, differential investment in research on treatment and prevention of one disease versus the other could reflect the relative advantage of males versus females. If men have more power to allocate resources for research and health care and differentially provide funding for prostate versus ovarian cancer, the resulting death rates from these diseases could constitute a disparity. This suggests that simple com- 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 17 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION READING 2: U.S. Disparities in Health: Descriptions, Causes, and Mechanisms parisons of mortality rates are not an adequate basis on which to evaluate health disparities. One also needs to know the biological potential of each group. Although women outlive men (a fact pointed to by some who advocate for more attention to men’s health as a disparity issue), the gap between current life expectancy and life expectancy under optimal conditions could potentially be greater for women than for men. Differences in biological potential have been raised in relation to racial/ethnic health disparities, suggesting these are differences rather than disparities. However, the contribution of unavoidable biological differences to overall disparities by race/ ethnicity is relatively small. A few diseases (e.g., sickle cell anemia) have a clear primary genetic basis, but these are of a limited number and there is little evidence for a differential genetic basis for the many diseases for which disparities occur.75 For example, African Americans have higher rates of hypertension than do European Americans, which some attribute to differential genetic vulnerability. However, prevalence of hypertension among blacks is lower in Caribbean countries than in the United States and lower still among blacks in Africa. Hypertension rates in Africa are, in fact, equivalent to or lower than rates among whites in the United States.26 These findings suggest that higher rates of hypertension for blacks in the United States compared with other racial/ethnic groups are more likely to be due to social factors than to underlying biological vulnerability. Health disparities result from both biological differences and social disparities. We focus on the latter not just because the effect is greater, but also because they are avoidable and inherently unjust. EMPIRICAL WORK ON DISPARITIES The bulk of research has focused either on disparities due to race/ethnicity or disparities due to social class and socioeconomic resources. Disparities by gender and geography have also been investigated, often in terms of how these factors modify racial/ethnic or social class disparities. Most research has not invoked an explicit model of disparities and studies are shaped and constrained by the availability of relevant data. For example, British studies emphasize social class as determined by occupational status using the Registrar General’s measure of social class. This measure has been in use for many years and provides a fine-grained hierarchical ordering of occupations. Nothing comparable exists in the United States, 17 where national data are more likely to include race/ethnicity than measures of socioeconomic position. For example, it was not until 1989 that education was added to the U.S. standard certificate of death, and health records of large population groups such as those enrolled in Kaiser Permanente often include only race/ethnicity but not socioeconomic status (SES). Thus, it has been easier to characterize racial/ethnic disparities in the United States than those linked to social class. The data show that African Americans have higher mortality and poorer health status than does any other group, as do Native Americans. Overall mortality rates are surprisingly higher for non-Hispanic whites than for Hispanics or Asian Americans; relative mortality varies for specific causes of death.3,94 For 1999-2001, male life expectancy for U.S.-born blacks and whites was 67.5 and 74.8 years, respectively. Life expectancy for U.S.born Hispanic males (75.2 years) was greater than for non-Hispanic whites and was greater still for U.S.-born Asian/Pacific Islanders (78.9 years). The same pattern is shown for women. For both men and women, the health advantage of Hispanic and Asians compared to U.S.-born whites is even greater for recent immigrants in these groups (see Foreign-Born Populations box). Intersection of SES and Race/Ethnicity Some definitions limit disparities to those associated with race/ethnicity. This focus has been fostered both by relative availability of data as described above and by social equity concerns based on current and historical racism and discrimination. Such a limitation can be problematic, however, given marked differences in the distribution of racial/ethnic groups across levels of education, income, occupation, and wealth.29,56 Examining race/ethnicity without simultaneously considering socioeconomic position can attribute too much influence to race/ethnicity per se, and may inadvertently foster an emphasis on biological differences. This point is forcefully made by Isaacs & Schroeder,52 who argue that social class is the “ignored determinant” of health in the United States. Researchers are increasingly looking at how SES and race/ethnicity function jointly and independently to affect health. Socioeconomic measures often account for a large part of racial/ethnic differences, although independent effects of race/ethnicity on health outcomes also exist, depending on what outcome is examined. Adequate control for SES across racial/ethnic groups may be difficult to achieve.54 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 18 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 18 CHAPTER 1 HEALTH OUTCOMES FOREIGN-BORN POPULATIONS Place of birth is a critical and frequently ignored component of socioeconomic and racial/ethnic disparities. To the extent that first-generation immigrants make up a substantial proportion of a given group’s population in the United States, immigrants’ health advantage may contribute to differences between groups. For most health outcomes (notable exceptions are stomach cancer and liver disease), foreign-born individuals in the United States have lower rates of disease than do their native-born peers. Controlling for demographic and socioeconomic factors, immigrant men and women 25 years of age and older had mortality rates 18% and 13% lower, respectively, than did nonimmigrants.95 Immigrants as a group lived 3.4 years longer on average than did those born in the United States in 19992001, an increase over a gap of 2.3 years two decades earlier.94 The gap was largest for native-born vs. immigrant blacks and Hispanics. Most analyses of health disparities do not include birth place and do not account for the generally lower rates of disease among foreign-born individuals.79 U.S. Hispanics as a group have lower all-cause mortality rates than do non-Hispanic blacks or non-Hispanic whites; a difference that becomes even greater after controlling for household income. The relatively lower rates of all-cause mortality among Hispanics as compared with non-Hispanics in the United States have been well documented, and a large literature investigating the substantive and potentially artifactual reasons for this has emerged (although no clear consensus has been reached yet).79 Asian Americans, too, show favorable health profiles, with the lowest prevalence of a number of diseases and the lowest all-cause mortality rate of any major racial/ethnic group, and the role of migration processes in these disparities is also an area of active research. SES indicators may have different meanings for different groups. For example, at the same income level, the amount of wealth and debt differ substantially by racial/ethnic group; Hispanics and African Americans have lower wealth than nonHispanic whites and Asians at a given income level.14,24 Similarly, at any given educational level, these groups have lower incomes than do whites.14 Although some studies “control” for SES by adjusting for an indicator such as education or income, this adjustment is insufficient given evidence for independent effects of the different domains of SES. Controlling for a single measure is unlikely to capture the effects of social class per se, and residual confounding may be erroneously interpreted as racial/ethnic differences.14,54 Descriptive Findings A descriptive understanding of socioeconomic and racial/ethnic disparities is important for (a) understanding both long- and short-term trends in health disparities, (b) informing causal investigations of health disparities, (c) targeting resources for prevention and treatments to reduce disparities in specific diseases, and (d) increasing public awareness of the existence and characteristics of health disparities. Below we briefly consider descriptive data regarding mortality disparities, cause-specific disparities, geographic variation in disparities, and time trends in these disparities. All-cause mortality. The first U.S. study with a sample size sufficient to allow the examination of socioeconomic disparities within race/ethnicity based on individual-level data was done by Kitigawa & Hauser,58 although data constraints limited comparisons to whites and nonwhites. Using data from the 1960 matched records of persons age 25 and over, they documented that compared with whites, age-adjusted all-cause mortality rates for nonwhites were 34% higher for females and 20% higher for males, correcting for net census undercount. They also examined mortality by education, occupation, income, and geographical location. For white men and women ages 25-64 mortality was respectively 64% and 105% higher for the least compared with the most educated. For nonwhite men and women the comparable difference in mortality by education was 31% and 70%, respectively. Pappas et al.81 revisited this work, with data from 1986, showing a relatively sharper decrease in mortality over this time period for higher-income and more-educated individuals, thus creating greater relative disparities by income and education overall and within racial/ ethnic groups over time. This and other work also highlights the importance of disparities based on social class for both women and men, despite some earlier work that suggested smaller social class disparities among women.72 In addition to dichotomizing race into white and nonwhite, earlier U.S. research generally dichotomized income into below versus above the poverty line. Publication of the Whitehall study inspired researchers to see if SES formed a graded association with health in the United States, as it did in England. Multiple studies have now demonstrated SES gradients by income and by education for a range of health outcomes including mortality, incidence of cardiovascular disease, arthritis, diabetes, asthma, cervical cancer, depression, and disability in children, adolescents, and both younger and older adults.4,22,43,76 Although these associations occur 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 19 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION READING 2: U.S. Disparities in Health: Descriptions, Causes, and Mechanisms across the distribution, they are generally stronger at the lowest levels of income and education.8,33,91 Cause-specific mortality. Studies uniformly find higher all-cause mortality for blacks than for whites under age 65, but within this overall trend there is heterogeneity by cause of death. For example, data from the National Longitudinal Mortality Study (NLMS) of 1.3 million persons89 reveal a racial/ ethnic difference for mortality from many but not all diseases. Black and white men under age 65 had approximately the same standardized mortality ratio (SMR) for ischemic heart disease, whereas (in order of magnitude of difference) black men had substantially higher SMRs than did whites for homicide, hypertensive heart disease, esophageal cancer, and pulmonary circulation but had relatively lower SMRs for aortic aneurysm, suicide, leukemia, and chronic obstructive pulmonary disease (COPD). Black women had substantially higher rates of homicide, hypertensive heart disease, diseases of pulmonary circulation, nephritis, and stomach cancer than did white women, with comparatively lower levels of suicide, COPD, and leukemia. Howard et al.51 also used data from the NLMS and found that SES accounted for different amounts of black-white mortality differences depending on the cause of death. For men, SES accounted for 30%55% of the black-white mortality differences for accidents, lung cancer, stomach cancer, stroke, and homicide, but less than 17% of the differences for prostate cancer, pulmonary disease, and hypertension. For women, SES accounted for 37%-67% of differences for accidents, ischemic heart disease, diabetes, and homicide, but less than 17% for hypertension, infections, and stomach cancers. However, only income and education were used as SES controls, which could underestimate the contribution of SES to black-white mortality differences. Kington & Smith57 found that with more complete demographic controls including wealth, racial/ethnic differences in functional limitation in health of older individuals were eliminated, although differences remain for other chronic diseases. Wong et al.106 also studied the contribution of education and race/ethnicity to different causes of death. Whereas many causes of death contributed in a similar way to both racial/ethnic and educational disparities in mortality (e.g., cardiovascular disease, liver disease), other causes were responsible for greater educational differentials (e.g., cancer, lung disease) or greater black-white differences (e.g., hypertension, lung disease, homicide).The data from these studies show that although the direction of disparities is fairly consistent, the extent of socioeco- 19 nomic and racial/ethnic disparities and their interactions differ substantially by cause. Geographic variation. Although marked differences in mortality rates across the United States have been noted, the extent to which socioeconomic factors and race/ethnicity explain these variations had not been adequately studied. However, data from within metropolitan areas reveal a geographic variation that can be substantially explained by considering these factors. These data also suggest that differences in local socioeconomic conditions have a greater impact on African American mortality than white mortality, resulting in an interaction between socioeconomic factors and race/ethnicity with respect to geography.23,98 This is consistent with data from the NLMS89 showing that the locations with the lowest mortality rates for whites and for blacks were at an equivalent level, even as overall rates were higher for blacks. These studies of geographic differences show the importance of area context for disparities and note that relationships among race/ethnicity, class, and health are not fixed, even within the United States during a given time period. Changes in disparities over time. The magnitude of disparities in mortality by race/ethnicity and by SES have changed over time, providing further evidence that these disparities are changeable and preventable. Preston & Ilo86 confirmed Pappas’s finding of increasing education gradients for all-cause mortality for men since 1960 but also found that education differentials in mortality declined for women 25-64 and remained stationary for women 65-74. Ward et al.104 examined disparities in cancer mortality by race/ethnicity 1975-2000. Prior to 1980 investigators saw no black/white disparities in breast cancer mortality among women and saw slightly higher rates of colorectal cancer mortality among white as compared with black men. But this changed, and by 2000, black women had higher breast cancer mortality than did white women and black men had higher colorectal cancer mortality than did white men. The black-white gap in overall life expectancy decreased from 1975 to1984, increased from 1984 to 1992-1994, then decreased again through 2004.48 Most of these changes stemmed from relative improvements for blacks in specific causes of death (e.g., relatively greater decreases from 1994 to 2004 in homicide and unintentional injuries for both sexes and for HIV for men and heart disease for women). Disparities in risk factors for disease have also changed over time. For example, Zhang & Wang108 examined obesity rates among U.S. women 20-60 years old from 1971 to 2000 using data from the National Health and Nutrition Examination Survey 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 20 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 20 CHAPTER 1 HEALTH OUTCOMES (NHANES). Owing to rapid increases in obesity prevalence among all educational groups, education disparities actually decreased, although all groups were worse off. These results highlight the importance of overall population trends for assessing progress in reducing health disparities. Changes in disparities over the life course. The extent and nature of health disparities changes over the life course. Substantial disparities begin at birth; babies born to mothers who are poor, have lower education, and/or are African American are smaller at birth and are more likely to die within the first year of life. Disparities are smallest during childhood, adolescence, and early adulthood and greatest in middle age, becoming weaker again in older populations.5 The primary explanation for diminished disparities in older populations is that the least healthy individuals are no longer in the population, and mortality will eventually be experienced by all regardless of socioeconomic status and race/ethnicity. Although selection over time can produce artifactual population patterns,102 the proportion of the narrowing of disparities explained by selection is unclear. There may also be etiologic reasons, including the provision of safety net supports such as Social Security and Medicare, which are available to older adults and may reduce and/or buffer the effects of disadvantage. Variation by measure of SES. Occupation, income, and education have different associations with health outcomes.58,89 As currently operationalized, education and income are generally more strongly associated with health in U.S. data than are measures of occupation other than employed versus nonemployed. However, weaker associations with occupation may be due to the use of standard U.S. occupational measures.14 Using a classification based on the new U.K. national statistics social class measure—which categorizes individuals as managers/professionals, intermediate, small employers and self employed, lower supervisory and technology, and semiroutine/routine or not in labor force—Barbeau et al.9 found occupational associations with current smoking status as strong as those with education or income. Variations by SES measure used speak to the frequent recommendation of using discrete measures of SES such as education or income rather than a composite.32 In addition to empirical reasons, use of specific SES measures clarifies intervention possibilities. UNDERSTANDING THE NATURE AND CAUSES OF DISPARITIES General patterns of disparities over the late twentieth century in the United States are similar: Those with fewer resources have worse health outcomes for a number of different causes. But variations by health outcome, place, time, and age point to the fact that these associations are not fixed or immutable, and that this heterogeneity should be used to better understand the causes of disparities. Kunitz63 places links between distribution of resources and health within particular historical, socioeconomic, and cultural contexts. Given these variations, a deeper understanding of off-diagonals may be informative about the nature of disparities. This analysis would include diseases that do not show disparities or are more prevalent in more advantaged groups (e.g., black-white differences in kidney function and socioeconomic differences in breast cancer). It would also include those who do not show expected patterns such as immigrants, low-SES individuals in good health, and high-SES individuals in poor health. Finally, international comparisons of socioeconomic disparities highlight the importance of national contexts for understanding the nature of health disparities. Establishing Causality There are clearly documented associations of SES and health outcomes, but the causal link is still debated. Some questions are methodological, dealing with alternative explanations for the associations. Others are concerned with the nature of the mechanisms by which these upstream factors influence health. SES is unlikely to affect health directly (e.g., having more dollars in one’s pocket is not health protective). Rather, it shapes life conditions that, in turn, influence health. In this section we first consider the methodological challenges to understanding causes of health disparities and then consider potential mechanisms by which SES may affect morbidity and mortality. Methodological challenges—alternative explanations. When asserting that a measure of SES leads to sub-optimal health and premature mortality, researchers must address possible alternative explanations for the associations that are found.42,45 The first possibility is that associations result from random chance; this possibility can be assessed by specifying confidence intervals around the effect estimate or p-values. Second, associations may be due to conditioning on an effect of the exposure and outcome occurring either through the selection of the sample (i.e., selection bias) or through use of inappropriate control variables.42,50 Avoiding this possibility requires using a causal understanding of the process that created the data to inform sample selection and an appropriate choice of control covariates. 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 21 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION READING 2: U.S. Disparities in Health: Descriptions, Causes, and Mechanisms A third challenge is that the presumed health outcome may cause the exposure (reverse causation or health selection bias).58,96 For example, illness may prompt individuals to decrease work hours, change to less demanding and lucrative jobs, or leave the labor force entirely. Using data from the Health and Retirement Study of individuals over the age of 50, Smith96 found that wealth decreased by $17,000, and earnings by $2,600 per year with the onset of major disease. Collecting measures of income that predate the health assessment through longitudinal designs, data linkage or retrospective earnings recall can decrease reverse causation potential between income and health. Using a lagged approach with longitudinal data, McDonough et al.71 found little difference in predicting all-cause mortality between a one-year lag and a five-year lag, thus questioning the importance of reverse causation for explaining the mortality associations. Using another approach to account for health selection, Benzeval & Judge10 controlled for initial health status in addition to using measures of income prior to disease onset, and the associations between income and health outcomes remained. There is less reason for concern about reverse causation between education and health. Generally the temporal lag between education exposure and adult health outcomes argues against adult health impacting education.58 However, childhood illnesses and low birth weight may contribute to lower educational attainment.18,25 These factors are themselves a function of SES. Haas46 demonstrated that disadvantaged social background led to sub-optimal health in childhood, which made a subsequent impact on adult social class. Overall, although health can affect SES, SES significantly affects health. The extent of reciprocal influence for specific outcomes is generally not understood. Longitudinal data with health, education, income, labor force participation, and wealth measures over time can more accurately model the process of social stratification and the extent to which causation and selection impact specific health outcomes at different points in the life course. A fourth concern is whether associations result from the joint association of SES and health with a common underlying cause such as genetic factors, time preferences/delayed gratification,39 or cognitive ability. 44 As with reverse causation, these confounders may themselves reflect SES. Early family environments affected by parents’ education and income may shape all three of these potential confounders, including the extent to which genetic potential is realized through epigenetic processes. As evidence of the importance of SES and child envi- 21 ronments for adult health increases, rather than viewing these factors as undermining evidence for the importance of socioeconomic factors on health, they should be viewed as part of the dynamic process between SES and health over the life course. Data structure and methods. In addition to collecting appropriate data to control for potential alternative explanations in regression models, several types of data structures can also facilitate better determination of causal relationships and help rule out alternative explanations for observed correlations. True experiments are rare because individuals cannot easily be randomly assigned to levels of education, income, or occupation. However, experimental trials of interventions that modify some aspect of SES or factors associated with it are informative. Researchers have also taken advantage of natural experiments to assess the effects of economic or policy changes that affect an individual’s SES but are not due to his or her own characteristics or behaviors. These reduce confounding and allow for a more easily conceptualized counterfactual.45 Relevant examples include using German reunification to estimate the effects of income on health,38 changes in the Earned Income Tax Credit to estimate the effects of household income on children’s test scores,28 enactment of schooling laws to estimate the effects of education on mortality,66 and changes in legislation affecting Social Security benefits to estimate the effects of income on mortality in an older population.97 With the exception of the Social Security payments, these studies confirm the effects from observational studies of socioeconomic factors to health. Data with repeated measures on individuals over time also provide some strength for making causal claims.87 Repeated measures allow observation of the temporal sequence of cause and effect. Birth cohorts provide particularly rich data for modeling early life confounders and exposures of interest. Three British studies of representative samples of children born in 1946, 1958, and 1970 have provided critical data about the causes of health disparities and have shown the impact on adult health and behaviors of early life exposures and socioeconomic position at different points in life.84,103 Using data from the 1958 cohort, Power at al.85 found a number of causes of health inequalities at age 33, including class at birth, socioemotional adjustment, educational level, and psychosocial job strain. In the absence of a birth cohort, follow-up of members of completed studies of children and adolescents can provide some of the same advantages.41 Analytic approaches. In addition to the design approaches described above, new analytic methods are facilitating a better understanding of the causes 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 22 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION 22 CHAPTER 1 HEALTH OUTCOMES of health disparities. Five methods that may be particularly useful are propensity score matching, instrumental variables, time-series analysis, causal structural equation modeling, and marginal structural models. Propensity scores provide an analytical method for balancing factors associated with being in either of the analytical comparison groups of interest in a particular study (e.g., high versus low education). If assumptions are met it allows for unbiased causal estimates of the exposure under study.27,90 They have been used to identify the effects of gun violence exposure on subsequent violent activity,11 neighborhood characteristics on dropping out of high school,47 and neighborhood socioeconomic environment on cardiovascular mortality.30 This approach is based on the same principle as adjusting for confounders in a regression model and similarly requires all confounders be measured. However, they facilitate assessment of whether overlap of confounding variables actually allows one to compare the analytic groups of interest appropriately, and they also provide power to control for a larger number of confounding covariates. Instrumental variables (IV) offer advantages when analyzing data from natural experiments or similar designs. The crucial assumption is the availability of a variable (the instrument) that does not directly affect the outcome but is only associated with the predictor of interest, and where the exposure (instrument) is not itself influenced by known confounders.7 This approach has been used to show causal effects of income on health outcomes34 and to demonstrate the effect of years of schooling on allcause mortality.66 Time-series analyses are particularly helpful for evaluating policy changes or other population exposures by analyzing the variation in health outcomes over time, while allowing investigators to identify and remove temporal autocorrelation and also account for lag effects between exposure and outcome. Particularly useful are data from multiple locations with different temporal ordering of the exposure to remove more general temporal trends. This approach has been used to demonstrate the effects of unemployment on alcohol abuse19 and on very low birth weight20 and to examine trends in black-white disparities over time.65 Structural equation models have been used extensively in the social sciences to understand complex relations between variables and to test relationships among hypothesized causes, mediators, and outcomes. Despite controversy, work over the past two decades by Pearland others82,83 has clarified the con- ditions under which the models may be used to represent cause. A significant innovation for gaining this understanding is the use of directed acyclic graphs (DAGs), a graphical language for describing causal relations. These form a framework for representing assumptions about elements of the causal pathways from social exposures to outcomes and information about possible confounders. Explicit delineation of the proposed causal structures through DAGs allows other researchers to evaluate the assumptions made and to build on the proposed structures. These models facilitate identification of valid empirical tests of proposed causal models.31 This is helpful in testing proposed mediators between social class and health.55 A causal structural modeling approach using DAGs is also mathematically equivalent to marginal structural models,82 which allow (when assumptions are met) a determination of the overall causal effect of an exposure within a framework based on treating unobserved counterfactuals as missing data.101 Chandola et al.21 used this approach with data from the 1958 British Birth Cohort to examine the relative contributions of six different pathways connecting education and health. The structural model included factors at age 7 (cognitive ability, father’s social class), age 16 (adolescent health), age 23 (education), age 33 (adult social class, sense of control, healthy behaviors), and age 42 (adult health). It showed no direct effect of education on adult health but showed significant effects through adult social class, control, and behaviors, with differences by gender in the strength of pathways.21 A similar approach was taken by Mulatu & Schooler77 in examining the relative strength of behavioral and psychosocial pathways between SES and health. Pathways and Mechanisms Much recent research has attempted to explicate the pathways and the mechanisms by which SES influences health. Although few studies have explicitly tested these through structural equation models, the studies provide many candidates. Physical and social environments, including a person’s home, school, work, neighborhood, and community, vary by SES and affect the likelihood of individuals’ exposure to both health-damaging conditions and healthprotecting resources. Health-damaging exposures within these pathways include early life conditions, inadequate nutrition, poor housing, exposure to lead and other toxins, inadequate healthcare, unsafe working conditions, uncontrollable stressors, social exclusion, and discrimination.5,6,105 84577_Ch01_001_042.qxd 8/20/10 6:14 PM Page 23 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION READING 2: U.S. Disparities in Health: Descriptions, Causes, and Mechanisms Some of the exposures listed above have direct effects on health, whereas others may influence psychological dispositions and behaviors that have health consequences. A vast literature demonstrates the contribution of psychosocial and behavioral factors to morbidity and mortality. These factors include cognition and emotion (e.g., depression, hopelessness, hostility, and lack of control) and behavior (e.g., use of cigarettes, alcohol, and other substances). Gallo & Matthews40 observed that substantial evidence links negative emotions with many health outcomes and links SES with negative emotions, but few studies have analyzed these pathways together. For example, hostility and hopelessness are strongly predicted by childhood socioeconomic position49 and are linked, in turn, to poorer health.12,37,40 However, the extent to which the links between childhood SES and adult health are accounted for by hostility and hopelessness has not been determined. The few studies that have considered mediation by psychosocial factors provide supportive findings, but these have used regression rather than structural equation models. For example, Marmot et al.67 examined the role of sense of control over one’s work in explaining health disparities within the Whitehall sample. The higher the grade of the civil servants, the more control they experienced in relation to their work conditions. Consistent with hypothesized mediation, the association of occupational grade with health was substantially reduced when adjusted for sense of control. A common element in many of the proposed mechanisms linking SES to health is differential exposure to stress. Disadvantaged environments expose individuals to greater uncertainty, conflict, and threats for which there are often inadequate resources to respond effectively. These experiences cumulate to create chronic stress. Until recently, stress research focused primarily on acute stress, which is more easily modeled in the lab, and was based on a model of homeostasis. The development of the model of “allostatic load” (AL)73 provided a major conceptual advancement to understand health disparities. This model posits that the body does not simply reestablish homeostasis after experiencing a perturbation associated with a stressor. Rather, with repeated exposures, set points for various systems involved in the stress response, including the endocrine, metabolic, cardiovascular, and immune systems, may shift. Although the body may be in balance, the systems become burdened and dysregulated by the costs of the repeated adaptation cycles.74 Precise ways to assess AL are still being developed, 23 but early findings suggest that it is a useful approach. Seeman et al.92,93 assessed AL in terms of 10 dysregulation indicators in a sample of older adults who had no major diseases at baseline. AL scores were higher in those with less education and predicted subsequent decline in physical and cognitive functioning, new cardiovascular disease, and seven-year mortality. Using data from the Normative Aging Study, Kubzanksy et al.62 also found higher AL among those with less education and further found evidence that the effect was partially mediated by hostility. Although the effects of chronic stress cumulate over time, the biological manifestations may be seen relatively early in life. Evans35 found that children from disadvantaged environments had higher AL than did children from more affluent backgrounds, and one indicator of AL was found in structural equation models to mediate the impact of poorer housing conditions on illness-related school absences.53 These examples are a few of thousands of studies on a variety of potential mechanisms and pathways. Most of these have not been linked specifically with health disparities but provide detailed information on different levels of cause that could result in disparities. Data sets with adequate measures of socioeconomic factors and race/ ethnicity, potential psychosocial and biological mechanisms, and health outcomes are necessary to best understand pathways. These then can be analyzed using techniques such as causal structural models that allow modeling and testing of multiple direct and indirect pathways to health outcomes that are the bases of disparities. CONCLUSION Substantial health disparities exist in the United States by social class and race/ethnicity. It would, of course, be preferable to eliminate disparities by addressing the root causes, changing the inequitable resource distribution that now accompanies SES and race/ethnicity as well as other bases of disparity. For effective policy development...
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