4
Social Risk Factors

Among the greatest advances in elucidating the determinants of disease over the past two decades has been the identification of social and psychological conditions that seem to influence morbidity and mortality directly through physiological processes and indirectly via behavioral pathways. This chapter examines a set of sociopsychological factors for which substantial evidence exists for effects on health outcomes: socioeconomic status; social support and networks; occupational stress, unemployment, and retirement; social cohesion and social capital, and religious belief Although it was previously believed that some diseases were caused by psychological states with little biological basis and that others were purely “physical,” it is now understood that in almost all cases that distinction is false. Most psychosomatic diseases involve various genetic and environmental determinants, and all states of health and disease are influenced to some extent by psychosocial conditions. Disorders rarely have discrete causes.

This chapter reviews the evidence accumulated during the 1980s and 1990s, identifying strengths and weaknesses and identifying areas for future investigations as they relate to social conditions that are risk related or health promoting.



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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences 4 Social Risk Factors Among the greatest advances in elucidating the determinants of disease over the past two decades has been the identification of social and psychological conditions that seem to influence morbidity and mortality directly through physiological processes and indirectly via behavioral pathways. This chapter examines a set of sociopsychological factors for which substantial evidence exists for effects on health outcomes: socioeconomic status; social support and networks; occupational stress, unemployment, and retirement; social cohesion and social capital, and religious belief Although it was previously believed that some diseases were caused by psychological states with little biological basis and that others were purely “physical,” it is now understood that in almost all cases that distinction is false. Most psychosomatic diseases involve various genetic and environmental determinants, and all states of health and disease are influenced to some extent by psychosocial conditions. Disorders rarely have discrete causes. This chapter reviews the evidence accumulated during the 1980s and 1990s, identifying strengths and weaknesses and identifying areas for future investigations as they relate to social conditions that are risk related or health promoting.

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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences SOCIOECONOMIC STATUS A strong and consistent finding of epidemiologic research is that there are health differences among socioeconomic groups. Lower mortality, morbidity, and disability rates among socioeconomically advantaged people have been observed for hundreds of years and have been replicated using various indicators of socioeconomic status (SES) and multiple disease outcomes (Kaplan and Keil, 1993; Syme and Berkman, 1976). Educational differentials in mortality have increased over the past three decades in this country (Feldman et al., 1989; Pappas et al., 1993; Tyroler et al., 1993). Moreover, formal comparisons of the mortality differences associated with education show that relationships between educational attainment and mortality are stronger in the United States than they are in most European countries (Kunst and Mackenbach, 1994). Results from the National Longitudinal Mortality Study (NLMS) are representative of recent research that has documented the link between SES and health. The NLMS is a large national database on the U.S. noninstitutionalized population assembled from survey information collected between 1978 and 1985; deaths were ascertained using the National Death Index for 1979–1989 (Sorlie et al., 1995). Mortality was strongly associated with education, income, and occupation (Rogot et al., 1992; Sorlie et al., 1992, 1995). For example, among those aged 25–64, white men and women with 0–4 total years of education had age-adjusted death rates that were 66% and 44% higher, respectively, than those with 5 or more years of college. For African American men and women, the corresponding increases in mortality were 73% and 78%, respectively. Similar findings were observed when income was used as a proxy for SES. Age-adjusted death rates among white men and women with annual family incomes of less than $5,000 were 80% and 30% higher, respectively, than were those among their counterparts in households with incomes of $50,000 or more. As with education, even greater differentials were seen among African Americans: men in African American households earning less than $5,000 were twice as likely to die during follow-up than were those in families earning $50,000 or more. Poor African American women were 80% more likely to die than were wealthier women. Socioeconomic differentials in mortality have been observed for many causes of death. The Multiple Risk Factor Intervention Trial (MRFIT) followed 320,909 white and African American men for 16 years (Davey Smith et al., 1996a,b). Median family income in ZIP code of residence was predictive of death from a variety of medical conditions in analyses

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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences adjusted for age, smoking status, blood pressure, serum cholesterol, previous myocardial infarction, and treatment for diabetes. To assess the 11-year mortality risk associated with individual family income, Anderson et al. (1997) linked NLMS data to census tract information on income for 239, 187 persons. Among persons aged 25–64, the mortality rate ratios (that is, the ratio of mortality rate at the low income to the mortality rate at high income) associated with individual family income were 2.03 for white men, 2.10 for African American men, 1.61 for white women, and 1.92 for African American women. The rate ratios associated with median census tract income, adjusting for individual-level income, were 1.26 for white men, 1.49 for African American men, 1.61 for white women, and 1.30 for African American women. Although family income had a stronger association with mortality than did median census tract income, the results indicate that community SES makes an independent contribution to mortality. With regard to specific disease outcomes, the relationship between SES and cardiovascular disease has received the most attention. SES appears to be an important factor in the development and progression of cardiovascular disease (Kaplan and Keil, 1993), the leading cause of death in this country (National Center for Health Statistics, 1992). The British Whitehall study of civil servants found that those in the lowest grades of employment were at highest risk for heart disease (Marmot et al., 1991) and that low levels of personal control in the work environment could explain much of this association (Bosma et al., 1997; Marmot et al., 1997). Perhaps the most striking finding that emerges from these analyses is the graded and continuous nature of the association between income and mortality, with differences persisting well into the middle-class range of incomes. This phenomenon also has been observed in several European investigations (Blane et al., 1997; Davey Smith et al., 1990; Macintyre, 1997; Macintyre et al., 1998). For example, in the Whitehall longitudinal studies (Davey Smith et al., 1990; Marmot et al., 1991), each employment grade had worse health and higher mortality than did the grade above it. Executive-grade civil servants (level 2) are not poor by any absolute standard, but they had higher mortality than did administrators (level 1). The fact that socioeconomic differences in health are not confined to segments of the population that are materially deprived in the conventional sense argues against an interpretation of socioeconomic differences simply as a function of absolute poverty. The pathways involved are likely

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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences to be complex; diverse explanations for the socioeconomic gradient in health have been proposed and examined. Material Conditions SES is clearly associated with the material condition of a person’s life. However, there are many examples of people who live in relative deprivation who exhibit greater disease resistance and general health than would be expected from their circumstances. Access to medical care and exposure to specific environmental conditions must be considered. Distribution of Medical Care There is ample evidence that SES is strongly related to access to and quality of preventive care, ambulatory care, and high-technology procedures (Kaplan and Keil, 1993). It appears unlikely, however, that these factors account for more than a small percentage of the variation. Because causes of death that are purportedly “not amenable” to medical care show socioeconomic gradients similar to those of potentially treatable causes (Davey Smith et al., 1996a; Mackenbach et al., 1989), it has been argued that differential access to healthcare programs and services is not entirely responsible for socioeconomic differentials in health (Wilkinson, 1996). Toxic Physical Environments Despite enormous improvements in sanitary engineering, which have contributed to the sharp increase in life expectancy observed among all socioeconomic groups during the past century, the socioeconomic gradient in health status persists. It has been proposed that the SES gap is still attributable to effects of crowded and unsanitary housing, air and water pollution, inadequate food supply, poor working conditions, and other such deficits that disproportionately affect those in the lower socioeconomic strata. Studies that incorporate assessments of material deprivation and the physical environment will be important to sort out the degree to which this is an important pathway. However, inasmuch as the gradient in morbidity and mortality persists even between middle-class and well-to-do men and women and even in societies in which material conditions are very good, it seems unlikely that gradients are solely the result of these material circumstances.

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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences Psychosocial Risk Factors Considerable evidence links low SES to adverse psychosocial conditions. People who work in low-paid jobs are not only the most materially disadvantaged, but they also have higher job and financial insecurity; experience more unemployment, work injury, lack of control, and other social and environmental stressors; report fewer social supports; and more frequently have a cynically hostile or fatalistic outlook (Adler et al., 1994; Berkman and Syme, 1979; Bosma et al., 1997; House et al., 1988; Karasek and Theorell, 1990). Psychosocial Context The most successful interventions of the many clinical trials incorporated elements of social or organizational change to modify individual behavioral risk factors, such as alcohol and tobacco consumption, diet, and physical activity. Most behaviors are not randomly distributed in the population, but rather are socially patterned and often cluster with one another. Thus, many people who drink also smoke cigarettes, and those who follow health-promoting dietary practices also tend to be physically active. People who are poor, have low levels of education, or are socially isolated are more likely to engage in a wide array of risk-related behaviors and less likely to engage in health-promoting ones (Adler et al., 1994; Matthews et al., 1989). This patterned behavioral response led Link and Phelan (1995) to speak of situations that place individuals “at risk of risks.” Understanding why “poor people behave poorly” (Lynch et al., 1997a) requires recognition that specific behaviors once thought of as falling exclusively within the realm of individual choice occur in a social context. The social environment influences behavior by shaping norms; enforcing patterns of social control (which can be health promoting or health damaging); providing or not providing environmental opportunities to engage in particular behaviors; and reducing or producing stress, for which engaging in specific behaviors might be an effective short-term coping strategy (Berkman and Kawachi, 2000). Environments, especially social contexts, place constraints on individual choice. Incorporating the social context into behavioral interventions led to a new array of clinical trials that take advantage of communities, schools, and worksites to achieve behavioral change (see Sorensen et al., 1998; Chapter 6, this volume).

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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences Relationship to Health-Related Behaviors and Biological Risk Factors Given the fact that socioeconomic stressors are disproportionately concentrated in lower socioeconomic groups (McLeod and Kessler, 1990), it is not surprising that many investigations indicate an inverse relationship between SES and adverse health behaviors (such as smoking, physical inactivity, less nutritious diets, and excessive alcohol consumption), and between SES and biological risk factors (such as high blood pressure, high serum cholesterol and fibrinogen, and obesity; Davey Smith et al., 1996a,b; Kaplan and Keil, 1993; Lynch et al., 1997a; Marmot et al., 1991). Statistical adjustment for such biological and behavioral risk factors generally leads to attenuation of excess mortality among lower groups. However, socioeconomic gradients still persist (Davey Smith et al., 1996a,b; 1990; Haan et al., 1987; Marmot et al., 1991). For example, in the MRFIT study (Davey Smith et al., 1996a,b), stratification by smoking status revealed similar gradients in income and coronary heart disease for smokers and nonsmokers. Conceptualization and Measurement of SES Commonly used measures of SES in epidemiologic studies include education, income, and occupation (Liberates et al., 1988; Lynch and Kaplan, 2000; Morgenstern, 1985), but some work suggests that additional measures of wealth might be important and that increased attention should be paid to gender and life course issues (Anderson and Armstead, 1995; Lynch and Kaplan, 2000). In the social sciences, theoretical perspectives focus on different aspects of stratification. Social class as described by Weber (1946) has three domains: (1) class, by which he meant ownership and economic resources; (2) status, by which he meant prestige, community ranking, or honor; and (3) political power. This tripartite definition has led many social scientists to identify multiple indicators of social class. In the United States, these three domains are often assessed by income or wealth to tap economic resources and occupational rankings based on prestige to tap status. Political power per se is rarely assessed. Because occupationally based scales are often unavailable in the United States, most measures are based on income and education. In contrast, in Europe occupationally based scales are the most common indicators of social class. Common measures in Europe include the Erikson-Goldthorpe-Portocarero scheme. This scheme was developed to facilitate international comparisons of social stratification. It is still rarely used in

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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences the United States because routine data on the key elements are not commonly collected. (Kunst et al., 1998). Several reviews have outlined common measures of SES in the United States (Berkman and MacIntrye, 1997). It is possible that different aspects of SES may lead to poor health through different pathways. For instance, income may influence outcomes very directly through material resources whereas occupational-based rankings may impact job-related psychosocial stresses and education may influence health-related behaviors. However, because these aspects of SES are usually highly correlated with each other, these distinct pathways are extremely difficult to identify. Thus, disentangling distinct effects of education or income for example remains a major challenge. Almost all studies of income and health have measured income at only one point in adulthood. That fails to capture the health effects of sustained exposure to low income, to account for transitions into and out of low-income groups, or to allow for exploration of dynamic interrelationships between health and income. There is considerable volatility in income during adulthood: 26–39% of U.S. residents aged 45–65 experience income reductions of at least 50% in some 11-year period (Duncan et al., 1996), suggesting a need to measure income at multiple points in time (for example, through socioeconomic trajectories or careers). Lynch et al. (1997b) found significantly worse health outcomes among persons with sustained, as opposed to transitory, economic hardship. General Susceptibility versus Disease Specificity It has been argued that unfavorable socioeconomic position increases susceptibility to disease in general, and potential biological mechanisms of stress-related immune suppression and neuroendocrine activation have been postulated to account for this phenomenon (McEwen, 1998). However, within the general pattern of increased mortality, there is marked heterogeneity of the strength of the associations observed (Davey Smith et al., 1996a, b). Results from an examination of site-specific cancer mortality (Davey Smith et al., 1991) suggest that, although general susceptibility might be operative, research on disease-specific pathways should not be neglected.

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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences Reverse Causation and Social Selection The idea that poor health might lead to a worsening of SES rather than the other way around suggests a “reverse-causation” or “social-selection” hypothesis. If the less healthy are more likely to experience downward social mobility or are less likely to be upwardly mobile, the result will be a concentration of ill people in the lower social classes. Although evidence of reverse causation is strong for some conditions (most notably schizophrenia and other severe mental illnesses), such selection appears to have a relatively small influence on the overall socioeconomic gradient of health (Black et al., 1988; Marmot et al., 1995, 1987). Commonly cited evidence against the social-selection hypothesis includes the tendency of educational attainment, a measure not affected by illness that occurs after early adulthood, to be as strongly predictive of adult health outcomes as are other SES measures. Moreover, in longitudinal surveys, SES-related mortality differentials generated by social selection would be greatest early in the follow-up period if social selection were operative, but this has not been observed (Fox et al., 1985). It is nevertheless possible that conditions operating at an early age— say between birth and entry into the workforce—are important in shaping social positions observed in adulthood and in influencing adult health directly (Lynch et al., 1997a). Early influences might shape developmental biology (Chapter 2), the lives people lead, and the environments in which they live and work as adults. SOCIAL NETWORKS AND SOCIAL SUPPORT A social network is the web of social relationships that surround an individual and the structural characteristics of that web. Many researchers have measured social networks in a general way that taps the degree to which an individual is integrated into society. Examples include the degree to which an individual participates in voluntary associations or the number of friends a person has. Social support is a distinct function of social relationships; it is clear that not all relationships are supportive. Other functions of networks can influence health outcomes, including patterns of social influence, social engagement, and person-to-person contacts (which can promote the spread of infectious diseases; Berkman and Glass, 2000). People form ties with others from the moment they are born. The

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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences survival of newborns depends on their attachment to and nurturance by others over an extended period (Baumeister and Leary, 1995). The need to belong does not stop in infancy, but rather affiliation and nurture and social relationships are essential for physical and psychological well-being throughout life (Cohen and Syme, 1985; Seeman, 1996). Affirmative social interactions—those that satisfy the need for autonomy, competence, and relatedness—are related to feeling understood and appreciated (Reis and Judd, 2000). Cognitive or interpersonal deficits in childhood and adolescence can further impair individual ability to acquire the social and instrumental skills people need to avoid life stressors and achieve age-appropriate social roles. Positive Social Relations Initial assessments of social isolation (or integration) emphasized objective features of social support, such as the size or density of one’s social network and frequency of contact with relatives and friends. Subsequent studies elaborated more subjective or functional aspects, such as the perception of emotional and instrumental support or the amount of assistance provided by others (Cohen, 1988; Cohen and Wills, 1985; Vaux, 1988). Research on social support has increasingly differentiated into specific substantive areas, such as the role of social support in stress and coping (Thoits, 1995), social support in family relationships (Pierce et al., 1996), social support and personality (Pierce et al., 1997), and social support in differential survival from particular health challenges, such as myocardial infarction (e,g., Ruberman et al., 1984), or cancer (e,g., Spiegel et al., 1989). Buffering One concept used to explain how social support affects health is buffering. For example, stress-induced decrements in immune function have been shown by research on medical students undergoing exams, but the decline was particularly pronounced for those lacking social buffers—those who reported being lonely (Glaser et al., 1992; Kiecolt-Glaser et al., 1994). Research involving people going through major life transitions (such as loss of a spouse or birth of a child) illustrates that social networks and social support influence the coping process and buffer the effects of stressors on health (Hirsch and Dubois, 1992; Rhodes et al., 1994; Walker et al., 1977).

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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences Promoting Health-Enhancing Behaviors Other research examines possible mechanisms, such as the extent to which significant others promote and encourage positive health practices (Berkman, 1995; Taylor et al., 1997). For example, social integration could enhance the beneficial effects of restorative behaviors, such as sleep. Sleep is a quintessential active restoration performed without immediate social contact. Although lonely individuals in one study slept as many hours as did socially embedded people, responses to the Pittsburgh Sleep Quality Index (Buysse et al., 1989) revealed that lonely individuals reported poorer sleep quality, longer sleep latency, and greater daytime dysfunction due to sleepiness than did socially embedded individuals. Other data confirm that lonely people sleep less efficiently, take slightly longer to fall asleep, evidence longer rapid eye movement latency, and awaken more frequently during the night than do embedded individuals (Cacioppo et al., 2000). Another study (Lewis and Rook, 1999) found that control in social relationships (that is, influencing and regulating social networks) was associated with more health-enhancing behavior, but with greater distress. Altering Physiological Processes Extensive research explores the underlying physiological roots through which social ties influence health (e.g., Berkman, 1995; Cohen and Herbert, 1996; Kang et al., 1998; Kiecolt-Glaser et al., 1994; Seeman, 1996; Seeman and McEwen, 1996; Uchino et al., 1996). Meta-analyses of the experimental literature support the hypothesis that perceived social isolation is associated with physiological adjustments, with the most reliable effects found for blood pressure, catecholamines, and aspects of cellular and humoral immune function (Seeman and McEwen, 1996; Uchino et al., 1996). In a study of carotid arthrosclerosis in middle-aged men, higher intima media thickness of the carotid artery was found in those who lived alone than in those who cohabited—even after controlling for age, health status, education, saturated fat consumption, and smoking (Helminen et al., 1995). The biological effects of loneliness are evident even after controlling for common individual personality differences (e.g., extraversion, neuroticism) in intervention studies designed to reduce social isolation and improve physiological functioning (Cacioppo et al., 2000; Uchino et al., 1996). People’s beliefs, attitudes, and values pertaining to others appear to be especially important, as subjective indices of social isolation have been found to be more powerful predictors of stress and health than are objective indices (e.g., Uchino et al., 1996).

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Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences The relationship between social ties and the onset and progression of infectious disease has received growing attention recently. Socially supportive relationships appear to have beneficial effects on primary immune system parameters that regulate host resistance (Esterling et al., 1996; Kiecolt-Glaser et al., 1994; Uchino et al., 1996). Cohen et al. (1997) tested their hypothesis that diversity of network ties is related to susceptibility to cold. Participants were given nasal drops containing rhinovirus or placebo and monitored for the development of colds. Those who reported more types of social ties (e.g., spouse, parent, friend, workmate, and so on) were less susceptible to colds, produced less mucus, fought infection more efficiently, and shed less virus; moreover, susceptibility to infection decreased in a linear manner with increasing diversity of the social network. Further evidence that social ties mediate primary immune system parameters comes from a study by Theorell et al, (1995), who tracked the decline in the count of CD4 cells of the immune system over a 5-year period among a cohort of HIV-infected men in Sweden. The count declined more rapidly in men who reported lower “availability of attachments” at baseline. Although research on the physiological pathways that could link networks to health is just developing, researchers have documented associations among social integration and social support and several physiological mechanisms related to health outcomes, including cardiovascular reactivity and neuroendocrine and immune function (Seeman, 1996; Uchino et al., 1996). In one of the few observational studies to link social support and neuroendocrine measures in humans, Seeman et al. (1994) found that older men and women who reported more frequent emotional support excreted less epinephrine, norepinephrine, and cortisol in their urine. Several experimental studies have investigated the link between the social relationship and cardiovascular reactivity. Kamarck et al. (1990) found that participants asked to complete a laboratory task alone exhibited significantly greater systolic blood pressure and heart rate reactivity than did those who were allowed to have a friend with them. Lepore et al. (1993) varied the degree of social support available to participants asked to give a speech. The three social conditions were to give the speech alone, to give it in the presence of a nonsupportive confederate, and to give it in the presence of a supportive confederate. Participants in the last group exhibited the smallest increase in systolic pressure, followed by participants who gave their speeches alone. Links between neuroendocrine

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