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PAPER CONTRIBUTION A

The Contribution of Social and Behavioral Research to an Understanding of the Distribution of Disease: A Multilevel Approach

George A.Kaplan, Ph.D.; Susan A.Everson, Ph.D., M.P.H.; and John W.Lynch, Ph.D., M.P.H

INTRODUCTION

The popular and scientific press are replete with articles that eagerly herald great breakthroughs in public health, medicine, and biology that will arise from our expanding knowledge in genomics, bioinformatics, and biomedicine. The coming description of the human genome married with rapid advances in biotechnology is thought by many to presage an era in which many of the major sources of disease and disabilities in world populations will be prevented, delayed, or cured. Without a doubt, the increased knowledge of the molecular basis of the pathobiology of disease portends tremendous advances in our understanding and treatment of disease. However, the premise of this paper is that these advances, in and of themselves, will not be able to accomplish these goals. Instead, we argue for a public health-based approach that incorporates knowledge across a multitude of levels, ranging from the pathobiology of disease to the social and economic policies that result in differential patterns of exposure of individuals and populations to risk factors and pathogenic environments. Central

Dr. Kaplan is professor and chair, Department of Epidemiology, School of Public Health, and senior research scientist, Institute for Social Research, University of Michigan; Dr. Everson is assistant research scientist, Department of Epidemiology, School of Public Health, University of Michigan; and Dr. Lynch is assistant professor, School of Public Health, and faculty associate, Institute for Social Research, University of Michigan. This paper was prepared for the symposium “Capitalizing on Social Science and Behavioral Research to Improve the Public' s Health,” the Institute of Medicine and the Commission on Behavioral and Social Sciences and Education of the National Research Council, Atlanta, Georgia, February 2–3, 2000.



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Promoting Health: Intervention Strategies from Social and Behavioral Research PAPER CONTRIBUTION A The Contribution of Social and Behavioral Research to an Understanding of the Distribution of Disease: A Multilevel Approach George A.Kaplan, Ph.D.; Susan A.Everson, Ph.D., M.P.H.; and John W.Lynch, Ph.D., M.P.H INTRODUCTION The popular and scientific press are replete with articles that eagerly herald great breakthroughs in public health, medicine, and biology that will arise from our expanding knowledge in genomics, bioinformatics, and biomedicine. The coming description of the human genome married with rapid advances in biotechnology is thought by many to presage an era in which many of the major sources of disease and disabilities in world populations will be prevented, delayed, or cured. Without a doubt, the increased knowledge of the molecular basis of the pathobiology of disease portends tremendous advances in our understanding and treatment of disease. However, the premise of this paper is that these advances, in and of themselves, will not be able to accomplish these goals. Instead, we argue for a public health-based approach that incorporates knowledge across a multitude of levels, ranging from the pathobiology of disease to the social and economic policies that result in differential patterns of exposure of individuals and populations to risk factors and pathogenic environments. Central Dr. Kaplan is professor and chair, Department of Epidemiology, School of Public Health, and senior research scientist, Institute for Social Research, University of Michigan; Dr. Everson is assistant research scientist, Department of Epidemiology, School of Public Health, University of Michigan; and Dr. Lynch is assistant professor, School of Public Health, and faculty associate, Institute for Social Research, University of Michigan. This paper was prepared for the symposium “Capitalizing on Social Science and Behavioral Research to Improve the Public' s Health,” the Institute of Medicine and the Commission on Behavioral and Social Sciences and Education of the National Research Council, Atlanta, Georgia, February 2–3, 2000.

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Promoting Health: Intervention Strategies from Social and Behavioral Research FIGURE 1 Geographic distribution of female life expectancy at birth by county and county clusters, United States, 1990. to such a focus is an important role for economic, behavioral, and social factors, whether manifested at the individual or population level. For it is to these factors that we will largely have to look to develop a complete explanation of core epidemiologic observations concerning group and geographic differentials in the prevalence and incidence of disease and time trends in disease. In what follows we will review selected information on variations in life expectancy and the occurrence of a number of major public health problems and discuss how such a multilevel approach provides critical perspectives on the causes of these variations and on opportunities to reduce them. Life Expectancy and Death Rates from All Causes Overall life expectancy at birth reached 76.5 years in the United States in 1997, with almost steady increases since 1950 (NCHS, 1999). Since 1980, life expectancy at birth increased by 5.1% for males to 73.6 years, and by 2.6% for females to 79.4 years, and life expectancy at age 65 increased by 12.8% to 80.9 years, and by 4.9% to 84.2 years, for males and females, respectively. Despite these increases the United States still compares poorly to many countries—ranking twenty-fifth for males and nineteenth for females on a list of 36 countries compiled by the National Center for Health Statistics (NCHS, 1999).

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Promoting Health: Intervention Strategies from Social and Behavioral Research Within the United States there is considerable variation in life expectancy. For example, Figure 1 presents variations in female life expectancy at birth for counties and county clusters in the United States in 1990 (Murray et al., 1998). Life expectancy at birth differs between areas by as much as 16.5 years for males and 13.3 years for females. In these analyses, the largest difference in life expectancy is between American Indian or Alaskan Native males in the cluster of Bennett, Jackson, Mellette, Shannon, Todd, and Washabaugh counties in South Dakota (56.5 years) and Asian Pacific Islander females in Bergen County in New Jersey (97.7 years). As Murray et al. (1998, p. 9) point out, this 41-year range in life expectancy within the United States is “…equal to 90 percent of the global range from the population with the lowest life expectancy, males in Sierra Leone, to the population with the highest, females in Japan.” There also is substantial geographic variation in life expectancy at birth within race/ethnicity and sex subgroups. For example, while American Indian and Alaskan Native males have a life expectancy of 56.5 in the six-county area in South Dakota previously mentioned, this group has a life expectancy of 92.3 years in Los Angeles County. Life expectancy for white males and females also varies considerably by county—with ranges of 9.9 years and 7.6 years, respectively. As might be expected from trends and differences in life expectancy, consideration of age-adjusted mortality rates from all causes also indicates substantial variation by gender, race/ethnicity, and time. Figure 2 (Hoyert et al., 1999) FIGURE 2 Age-adjusted, all cause mortality rates by sex, United States, 1940 – 1997.

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Promoting Health: Intervention Strategies from Social and Behavioral Research FIGURE 3 Life expectancy at age 45 by family income, race, and sex, United States, 1979–1989. shows the decline in age-adjusted mortality rates from all causes for males and females between 1940 and 1997. During this period, rates declined by 50% for males and 60% for females. However, these declines were not experienced equally by all groups. For example, during the period from 1950 to 1997, age-adjusted mortality rates from all causes declined by 40.4% for white males, 33.6% for black males, 44.5% for white females, and 50.7% for black females. Thus, during this period, mortality differentials between white and black males increased, while for females they decreased. Detailed information for other race and ethnicity groups is not available for this period. There is considerable variation between states in overall mortality rates. For example, in 1997, the state with the lowest age-adjusted (1990 standard) mortality rate was Hawaii (572.5 per 100,000 population), and the highest rate (exclusive of the District of Columbia) was found in West Virginia (865.1 per 100,000). This level of geographic variation in age-adjusted mortality, a difference of almost 300 deaths per 100,000 population, is very significant given that

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Promoting Health: Intervention Strategies from Social and Behavioral Research FIGURE 4 Age-Adjusted death rates among adults, age 25–65, by cause of death, sex and education, United States, 1995. it is 40% of the overall rate for the United States (742.7 deaths per 100,000 population using the 1990 U.S. standard population). Socioeconomic variations in mortality have been widely noted (Kaplan et al., 1987). For most diseases and health status indicators and for most measures of socioeconomic position there is an inverse relationship (Haan et al., 1987). Figure 3 shows the relationship between family income and life expectancy (1979–1989) at age 45 for white and black men and women (all ethnicities) in the United States (NCHS, 1998). The gradient between socioeconomic position and death rates is clearly seen for broad classes of causes of death, as shown in Figure 4 (NCHS, 1998). The strong effects of socioeconomic position on mortality, coupled with substantial heterogeneity by race/ethnicity and geographic place in mortality rates and strong secular trends can lead to phenomena of major public health significance. In analyses of 1984–1993 trends in coronary heart disease (CHD) mortality in North Carolina, Barnett et al. (1999) found that declines in mortality were experienced by white men of all social classes, with the greatest benefit among those in the highest social class, while only the highest social class of

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Promoting Health: Intervention Strategies from Social and Behavioral Research black men showed any decline at all. For example, black men in social classes III and IV (e.g., occupations such as mechanic, butcher, janitor, welder, truck driver, laborer, animal caretaker) had average annual changes in Coronary Heart Disease (CHD) mortality of +0.8% and 0.0%, respectively, whereas white men in the same social classes had average annual changes of -2.1% and -6%. Over the 10-year period, black men in the lowest social class experienced an 8.0% increase in CHD mortality, and white men in the same social class experienced a 16% decline. UNDERSTANDING VARIATIONS IN HEALTH These large variations in life expectancy and mortality, and similar variations in other health outcomes, present fundamental challenges to our understanding of the determinants of health in individuals and populations and of how we can reduce the burdens of disease and disability. We propose that there is no single or simple explanation for such heterogeneity, and that it is highly unlikely that the triad of genomics, bioinformatics, and biomedicine, with their focus on molecular etiologic forces located within the individual, will help explain very much of the heterogeneity in health and disease among social groups, places, and times. While such an individualistic focus can help us explain events within individuals it is unlikely to be very successful in explaining the patterning of disease by subgroups, places, or eras (Rose, 1992). However, we do not argue that we should completely dismiss such pursuits and replace them solely with a focus on macrolevel determinants of health. Such an ecologic or macrolevel focus is likely to miss many opportunities for increased understanding of disease mechanisms and intervention opportunities and suffers from its own version of tunnel vision. Observations of the complex patterning of disease, the “lens” of epidemiology, leads instead to a new approach that attempts to bridge various levels of explanation and intervention, bringing together theory and empirical work that tie together observations of causal influence and mechanism at multiple levels. It thus represents an explanatory enterprise that does not exclusively privilege the proximal, but seeks opportunities for understanding and intervention at both upstream and downstream vantage points (Figure 5). Such a pursuit is in its infancy and represents a major challenge that will succeed only with a broad interdisciplinary vision accompanied by state-of-the-art thinking in multiple domains. In what follows we describe some general epidemiologic and demographic features of six major public health problems: low birthweight, childhood asthma, firearm-related deaths in adolescents and young adults, coronary heart disease, breast cancer, and osteoporosis. After describing the general patterns with which these problems appear, we then sketch out some examples of the type of multilevel approach that is suggested in Figure 5.

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Promoting Health: Intervention Strategies from Social and Behavioral Research FIGURE 5 Multilevel approach to epidemiology. THE DISTRIBUTION OF DISEASE-SOME ILLUSTRATIVE EXAMPLES Low Birthweight Overall Low birthweight, defined as a live birth less than 2,500 grams, is one of the most vexing problems facing the public health community in the United States. Low birthweight can result from babies being born prematurely and/or being born too small, and it is the major underlying cause of infant mortality and early childhood morbidity. The United States has significantly higher rates of low birthweight than other comparably developed nations. For instance, the average rate of low birthweight in the United States between 1990 and 1994 was 7 births per 1,000, while in countries like Norway, Sweden, and Finland, rates were as low 4–5 per 1,000 (UNICEF, 1998). Within some U.S. population subgroups these rates of low birthweight exceed 12 per 1,000 and match the very high levels found in some Sub-Saharan African and other developing countries. Infant mortality has declined significantly over the last 30 years, in large part due to the effects of neonatal intensive care and drug therapies that have helped to increase the survival of low-birthweight infants. In stark contrast, rates of low birthweight have remained stubbornly high (NCHS, 1998). Thus, the United States has a serious and persistent problem of low birthweight, which so far seems intractable to advances in medical care and technology.

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Promoting Health: Intervention Strategies from Social and Behavioral Research FIGURE 6 Low birthweight by education and race/ethnicity, United States, 1996. Distribution by Race and Socioeconomic Position As alluded to above, the problem of low birthweight is not distributed randomly across population subgroups. Figure 6 shows rates of low birthweight in 1996, according to the education and race/ethnic group of mothers aged 20 or older (NCHS, 1998). These data show both educational and race/ethnicity differences in low birthweight. The highest levels of low birthweight, around 18 per 1,000, were among the least educated black, non-Hispanic women. The lowest rates, around 4 per 1,000, were among the most educated Hispanic, Asian Pacific Islander, and white, non-Hispanic women. While there are important educational gradients in almost every race/ethnic group, the largest differences are between race/ethnic groups (NCHS, 1998). This fact is further emphasized in a 1992 study in the New England Journal of Medicine showing that even among babies born to college-educated mothers, infant mortality was significantly higher among black babies. This difference in infant mortality was entirely attributable to the higher proportion of low birth-

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Promoting Health: Intervention Strategies from Social and Behavioral Research FIGURE 7 Low birthweight by zip code income tertiles and maternal nativity among “Blacks, “New York City, 1988–1994. weight black infants (Schoendorf et al., 1992). In making any comparisonbetween race/ethnic groups in seemingly equal socioeconomic strata, such as those with a college education, it is important to remember that the social meaning and economic value of a college education may be quite different for different race/ethnic groups. Health differences between race/ethnic groups largely reflect a wide array of accumulated social exposures, so it would be naive to expect that we can capture all of these social exposures in one socioeconomic factor such as education. We must be aware of the problems of incommensurability of socioeconomic indicators in comparing across race/ethnic groups (Krieger et al., 1993; Kaufman et al., 1997). Nevertheless, the differences in low birthweight across race/ethnic groups cannot be ignored and deserve more intensive investigation. Adding to the complexity of this picture is recent research showing that birthweights of African-born black women are more closely related to those of U.S.-born white women than to U.S.-born black women (David and Collins, 1997). (See Figure 7.) Additionally, Fang et al. (1999) have shown that rates of low birthweight among

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Promoting Health: Intervention Strategies from Social and Behavioral Research “black” women vary considerably across all income levels, according to the country of birth of the mother. Trends Low birthweight continues to be a stubborn public health problem, with little or no decline in rates over the last 20 years (See Figure 8.). In fact, between 1985 and 1996, New Hampshire was the only state that did not record an increase in the percentage of low-birthweight babies. For the United States, overall rates rose by an average of 9%, but in some midwestern states such as Minnesota, Iowa, Nebraska, and Indiana, low birthweight increased by as much as 20% (Annie E.Casey Foundation, 1999). Geographic Distribution Not unexpectedly, there also is considerable geographic variation in low birthweight across the United States. As Figure 9 shows, low birthweight is particularly concentrated in the southeastern states. These geographic differences may reflect both compositional and contextual influences on low birthweight. Compositional influences relate to characteristics of the individuals who reside FIGURE 8 Trends in low birthweight by race/ethnicity, United States, 1980 –1996.

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Promoting Health: Intervention Strategies from Social and Behavioral Research FIGURE 9 Geographic distribution of percent of live births under 2500 grams by state, United States. in a certain area, while contextual influences refer to nonindividual aspects of the environment that also may affect rates of low birthweight. For instance, Kaplan and colleagues (1996) have shown how the extent of income inequality within a state is correlated with rates of low birthweight even after adjustment for the average incomes in the state (r = -065, p < .001). As Paneth has argued, “The effects of poverty at the level of the individual, the family and the community need all to be taken account of; the context in which pregnancy occurs is larger than the womb” (1995, p. 31). Costs The assessment of costs for any health problem is a complex undertaking that requires making various assumptions about what should be included and excluded from cost estimates. In the case of low birthweight, there are direct and indirect costs. The direct costs are those associated with both the immediate medical care for low-birthweight babies and the longer-term implications that low birthweight has for enduring health problems in childhood. In addition, the health complications of low birthweight place additional burdens on later child care and educational needs. Lewitt et al. (1995) estimated that in 1988, for children aged 0–15 who had been born at low birthweights, the health care, child care, and educational costs directly attributable to their birthweight were between $5.5 billion and $6 billion more than if those children had been normal weight at birth.

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Promoting Health: Intervention Strategies from Social and Behavioral Research allows one to mitigate, or move away from, environmental exposures that might be important in the etiology and progression of childhood asthma, to live in environments with lower levels of stress and violence. Economic policies that alter workforce participation by women may have an effect on reproductive patterns, thereby altering the risk of breast cancer. The same forces may have an impact for both men and women on levels of job strain, which may alter the risk of developing CVD or its risk factors (Schnall et al., 1994) and triggering acute events (Mittleman and Maclure, 1997). Taxation polices also can have a substantial impact on the development and maintenance of unhealthy behaviors such as smoking (Hu et al., 1995). Taxation policies that reduce funding of education also may influence the availability of physical activity at school through reduction in physical education classes (Luepker, 1999). Zoning policies and the design of living, work, and educational environments can conceivably influence the amount and patterns of leisure time and occupational physical activity. Through mechanisms that are less well understood (Kaplan et al., 1996; Lynch et al., 2000), economic policies that alter the extent of income and wealth inequality in the population may alter disease risks independent of effects on individual incomes or wealth. In addition to being related to risk of death from all causes, increasing income inequality is associated with increased levels of CVD and other diseases (Kennedy et al., 1996; Kaplan and Lynch, 2000). The extent of variations in income inequality, presumably related to government taxation and transfer policies, on infant mortality was shown by Ross et al. (in press) who compared the association between income inequality and infant mortality in metropolitan areas in the United States and Canada. Metropolitan areas in Canada had much lower levels of income inequality than those in the United States and much less geographic variation in income inequality. This combination of decreased income inequality and restriction in the range of income inequality resulting from Canadian economic policies was associated with considerably lower rates of infant mortality in these analyses. Social policies also can have a substantial impact. The most obvious relates to access to health insurance and state-of-the-art medical care. To the extent that there is no consensus regarding the need for universal access, then we can expect to see substantial variations by SEP and race/ethnicity in low birthweight and the diagnosis and treatment of asthma, as well as screening, treatment, and outcomes of CVD, breast cancer, and osteoporosis. Social policies regarding regulation of gun ownership, types of weapons allowed, safety devices, enforcement of regulations, and policing may all have an impact on firearm-related deaths (Wintemute, 1999). In general, social policies that have an effect on employment, or lack of it, the nature of work, community neighborhood structures, transportation, housing, schools, medical care, and other social institutions may all have an impact on the distribution of public health problems within and between populations and areas. Social policies and norms related to factors such as tobacco and alcohol use also may have a substantial impact because even changes in average consumption lev-

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Promoting Health: Intervention Strategies from Social and Behavioral Research els may influence both the total burden of disease associated with consumption and the prevalence of heavy smoking and drinking (Rose, 1992). Institutions In a sense, institutions cannot be separated from the social, cultural, historical, and economic policies that create and sustain them. However, it is important to see the extent to which institutions, such as those related to the worlds of education, work, medical care, the criminal justice system, and housing, may be important determinants of public health problems and solutions. For example, it has been suggested that school and child care environments may increase the risk of childhood asthma and its complications via exposure to secondhand smoke (Bremberg, 1999) and through a lack of support for behavioral self-management strategies (Clark et al., 1999). Similarly, the school environment via promotion of poor nutritional habits through school lunch programs or on-site fast-food outlets, and reduction of school-based physical activity programs may contribute to increased risk of the development of CVD as well as decreased bone mass. The school environment also can support factors related to increased risk of later development of breast cancer, through both dietary and reproductive risk factors. School-related factors also may contribute to patterns of bullying, gang formation, and violence that may lead to firearm-related injuries. Workplaces, through both working conditions and the physical environment, zmay increase risk. Stressful working conditions, inflexible working schedules, and afterwork effects of physically and emotionally demanding jobs may all directly contribute to increased risk of CVD (Karasek and Theorell, 1992). Indirectly, they may contribute to patterns of smoking and alcohol use and physical inactivity that increase risks of low-birthweight, breast cancer, CVD, and osteoporosis. Work schedules that make it difficult to utilize preventive or curative services could increase risk of low-birthweight deliveries, CVD, and early detection of breast cancer and osteoporosis. The physical environment of workplaces and other institutional settings also can increase risk via exposure to tobacco smoke and other toxic substances. In addition, work environments that discourage physical activity in favor of taking elevators or discourage healthy eating via fast-food and vending machine availability also may increase risk of numerous outcomes. Neighborhoods, Communities, and Living Conditions A growing literature indicates that characteristics of neighborhoods and communities are associated with variations in health outcomes and individual level risk factors (Macintyre et al., 1993; Kaplan, 1996; Diez-Roux, 1998; Yen and Kaplan 1998, 1999). There are many pathways through which such area differences in health status and risk factors might be generated. Abatement of exposures to lead and other toxins, improvements in ambient air quality, and

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Promoting Health: Intervention Strategies from Social and Behavioral Research reduction of diesel exhaust could have an impact on asthma, low birthweight, and possibly osteoporosis. Environmental restrictions on smoking and the sale and consumption of alcoholic beverages, as well as local advertising in support of smoking and drinking, may influence the rates of all six of the public health problems highlighted in this chapter. Neighborhoods differ in the availability of affordable, nutritious food (Troutt, 1993) and in access to preventive and curative services, possibly having an impact on low birthweight, asthma, cardiovascular disease, breast cancer, and osteoporosis. Lack of access to parks and opportunities for safe recreational areas may influence levels of physical activity. Social and economic characteristics of communities also may have a great influence on public health (Haan et al., 1987; Macintyre et al., 1993; Sampson et al., 1997; Brooks-Gunn et al., 1997; Wing et al., 1988). The extent to which residents of an area feel interconnected, will help each other, and feel responsible for the “commons” is associated with lower rates of violence, much of which is firearm related (Sampson et al., 1997). Levels of social support can be influenced by neighborhood and housing design and may influence birth outcomes (Nuckolls et al., 1972), cardiovascular disease (Kaplan et al., 1988), treatment of childhood asthma (Smyth et al., 1999), and resolution of violence that can lead to firearm-related deaths. Living conditions, reflected in the quality of housing and residential environments, may be associated with low birthweight, asthma, cardiovascular disease, and osteoporosis and the risk of hip fracture. For example, levels of allergens and exposure to environmental tobacco smoke may be associated with asthma, and conditions that increase the risk of transmission of various infectious agents may thereby lead to exacerbation of asthma (Clark et al., 1999), increased risk of low birthweight (Romero et al. 1988), and possibly, cardiovascular disease (Patel et al., 1995). Environmental hazards in the home may be associated with increased risk of hip fracture (Rubenstein et al., 1988; Grisso et al., 1996), and environmental barriers outside the home could be associated with reduction in physical activity (Kaplan, 1997). Social Relationships The quantity, quality, and scope of social relationships can influence the incidence and progression of a variety of health problems (Cohen and Syme, 1985). Social support and social network participation have been shown to be associated with pregnancy complications (Nuckolls et al., 1972), cardiovascular disease (Kaplan et al., 1988), breast cancer prognosis (Spiegel et al., 1989; Reynolds and Kaplan, 1990; Reynolds et al., 1994; Shrock et al., 1999), recovery from hip fracture (Cummings et al., 1988), asthma symptoms (Clark et al., 1999), and pregnancy complications (Nuckolls et al., 1972). Social groups also may influence, in both a positive and a negative direction, the adoption and maintenance of adverse behavioral risk factors such as smoking and excessive alcohol consumption. Clearly, social processes are involved in the promotion or inhibition of violence and its sequelae such as firearm-related mortality. Strain

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Promoting Health: Intervention Strategies from Social and Behavioral Research associated with problematic relationships, or overload related to multiple social responsibilities, may increase cardiovascular risk and also may make it more difficult to access preventive or curative services. Individual Risk Factors There is ample evidence that the behaviors of individuals, such as tobacco and alcohol consumption, physical inactivity, and diet, are critically associated with important public health problems (McGinnis and Foege, 1993). Because this information is well known and readily available it is not reviewed in this paper. Other individual characteristics related to personality, negative affect, coping, and attitudes also are critically important. For example, considerable evidence now underscores the importance of psychological states related to negative affect and hostility in the pathogenesis and triggering of cardiovascular events and the progression of cardiovascular disease (Mittleman and Maclure, 1995; Everson et al., 1996, 1997), and there is some indication that psychological distress may exacerbate asthma symptoms (Smyth et al., 1999). These states can have indirect impacts on low birthweight, breast cancer, cardiovascular disease, and osteoporosis via their influence on access to and use of preventive and curative services, their impact on social relations, and, possibly, through the influence of psychological states on neuroendocrine and immune pathways. CONCLUSIONS We have briefly outlined the heterogeneity in prevalence, distribution, and trends for life expectancy and a number of important public health problems. The usual approach is to adopt either a perspective that privileges individual risk factors, which have been termed by some as the “real” causes of disease (McGinnis and Foege, 1993) or a perspective that similarly privileges an increasingly molecular understanding. Either approach, in our opinion, is likely to be extremely limited in understanding variations in disease incidence or prevalence between groups, places, or across time and consequently will generally be unsuccessful in suggesting effective intervention strategies to reduce the population burden from these problems. Instead, we have tried to argue for an integrated approach that views these problems within a multilevel framework and attempts to build bridges between levels rather than attributing primary importance to one level or another. It is likely that some success will come from efforts at specific levels, but our most complete understanding and most successful intervention attempts may very well come from a multilevel focus. In order to make progress, there is a need for considerably more information on determinants of health that lie “upstream” from individual behaviors. In an influential book on preventive medicine, the late Geoffrey Rose declared, “The primary determinants of disease are mainly economic and social, and therefore its remedies must be economic and social ” (Rose, 1992, p. 129),

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Promoting Health: Intervention Strategies from Social and Behavioral Research and a recent report on the “future of medicine” (Hastings Center Report, 1996) called for an effort on the scope of the Human Genome Project directed at understanding the social determinants of health. As work proceeds at a fast pace on both the behavioral and the molecular bases of disease, we need to proceed apace at accumulating knowledge of the upstream determinants of health that include social relations, neighborhoods and communities, institutions, and social and economic policies. Such an effort bridged with expanding knowledge from more “downstream” pursuits could add to the twenty-first century 's armamentarium for improving the public's health. REFERENCES Albright F, Smith PH, Richardson AM. Postmenopausal osteoporosis: Its clinical features. Journal of the American Medical Association 1941; 116:2465–2474. American Cancer Society. Breast Cancer Facts and Figures, 1996. Atlanta: American Cancer Society, 1995. American Lung Association. Trends in Asthma Morbidity and Mortality. Washington, DC: Epidemiology and Statistics Unit, 1998. Arriaga EE. Measuring and explaining the change in life expectancies. Demography 1984;21(1):83–96. Arriaga EE. Changing trends in mortality decline during the last decades. In: Ruzicka L, Wunsch G, Kane P, eds., Differential Mortality: Methodological Issues and Biosocial Factors. Oxford: Clarendon Press, 1989;105–129. Baker SP, O'Neill B, Karpf RS. The Injury Fact Book, 2nd ed. New York: Oxford University Press, 1992. Barnett E, Armstrong DL, Casper ML. Evidence of increasing coronary heart disease mortality among black men of lower social class. Annals of Epidemiology 1999; 464–471. Baron JA, Barrett J, Malenka D, Fisher E, Kniffm W, Bubolz T, Tosteson T. Racial differences in fracture risk. Epidemiology 1994;5:42–47. Bason WE. Secular trends in hip fracture occurrence and survival: Age and sex differences. Journal of Aging and Health 1996; 8:538–553. Bremberg S. Evidence-Based Health Promotion for Children and Adolescents in Stock holm County. Stockholm: Stockholm County Council, 1999. Brooks-Gunn J, Duncan GJ, Aber JL. Neighborhood Poverty: Context and Consequences for Children, Vols. 1 and 2. New York: Russell Sage, 1997. Brown ML, Fintor L. The economic burden of cancer. In: Greenwald P, Kramer BS, Weed DL, eds., Cancer Prevention and Control. New York: Marcel Dekker, Inc., 1995; 69–81. Brown ML, Hodgson TA, Rice DP. Economic impact of cancer in the United States. In: Schottenfeld D, Fraumeni J, eds., Cancer Epidemiology and Prevention, 2nd ed. New York: Oxford University Press, 1993; 255–266. Annie E.Casey Foundation. Kids Count Data Book. Baltimore: The Annie E.Casey Foundation, 1999. Centers for Disease Control and Prevention. On-line, http://wonder.cdc.gov/ Centers for Disease Control and Prevention. Vital and Health Statistics. National Hospital Discharge Survey: Annual Summary, 1993. DHHS Publication No. PHS 95–1782, 1995.

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