HEALTH PSYCHOLOGY, 1991, 70(2), 102-111 Copyright © 1991, Lawrence Erlbaum Associates, Inc.

Gender Differences in Social Support and Physical Health Sally A. Shumaker The Bowman Gray School of Medicine Wake Forest University

D. Robin Hill

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Olney, Maryland A large body of prospective data has accumulated linking social support to health, and most social scientists agree that low levels of support are associated with poor physical and mental health. Unfortunately, most of the research has been limited to White men. When women and people of color are included in the designs, the relationships between social support and physical health are more complicated. Prospective population-based studies provide evidence that low support is associated with increased risk of mortality in women. However, in several studies, results indicated that, for specific age groups, women with high social support have increased risk of mortality. Factors that may contribute to the observed gender differences in the social support-physical health relationship are discussed. Future research should include adequate numbers of women and more sophisticated measures of social support to move the field forward. Key words: social support, gender, mortality

In the past 20 years, a body of data has accumulated linking social support to health (for reviews, see Broadhead et al., 1983; Cohen & Syme, 1985; Hazuda, in press; Shumaker & Czajkowski, in press; Wallston, Alagna, DeVellis, & DeVellis, 1983). In spite of diverse research methodologies (with variations in measures of social support, health status, health behaviors, demographics, and morbidity and mortality; differing study populations; and varied research designs), a remarkably robust association persists between lower levels of social support and higher incidences of morbidity and mortality. Based on the accumulating evidence in this area, House, Landis, and Umberson (1988) recently argued that the data on social support now meet "reasonable criteria" for identifying insufficient social support as an important risk factor for mortality and morbidity for a wide range of diseases. Although others may disagree with this optimistic interpretation of the data (cf. Hazuda, in press), few social scientists question that low levels of social support are associated with poor physical and mental health. Unfortunately, investigations of the association between social support and physical health have been almost exclusively limited to White men. When people of color or women are included in study designs, the results are more complex and often weaker than those obtained on the White male samples (Berkman, 1986). In this article, we critically review the data on gender differences in social support and physical health and discuss factors that may account for these differences. Because these factors are directly linked to definitions of support and health, as well as proposed mechanisms linking

Requests for reprints should be sent to Sally A. Shumaker, Department of Public Health Sciences, The Bowman Gray School of Medicine, Wake Forest University, 300 South Hawthorne Road, Winston-Salem, NC 27103.

support to health, we begin with a brief consideration of support, health, and mechanisms. DEFINING SOCIAL SUPPORT As noted by Antonucci and others, social support suffers from a lack of specificity in both definitions and measures (Antonucci, 1985; Antonucci & E. H. Johnson, in press; Orth-Gomer & Unden, 1987; Shumaker & Brownell, 1984). Few people agree on a single definition of social support, and studies, which reflect this lack of agreement, apply the concept to a broad range of measures and aspects of social relations (Cohen, 1988; House & Kahn, 1985). Although actual measures may vary widely across studies, there is reasonable consensus on the basic components of social support. For example, Cohen and Syme (1985) proposed that a simple distinction between structure and function captures most of the measures in the field. Structure refers to the existence and types of connections within a social network, and function refers to the types of resources provided (e.g., affection, material aid, feelings of belonging). Sherbourne and Stewart (in press) suggested that measures of both structure and function may include the existence, actual usage, and perceived adequacy of social networks. In addition, investigators have emphasized the interpersonal nature of social support, characterizing it as an exchange process involving both recipients and providers (Antonucci, 1985; Kahn & Antonucci, 1980; Shumaker & Brownell, 1984).

MEASURING HEALTH Just as measures of social support vary across studies, so do measures of health. In this article, we focus on physical

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

GENDER, SOCIAL SUPPORT, AND HEALTH health, and the broadest distinction is between mortality and morbidity outcomes. With respect to mortality, studies include all-cause mortality, as well as disease-specific mortality (e.g., cardiovascular disease, cancer). Verification may be based on death certificates or death registries. Morbidity includes evidence of disease onset and progression. Additional health-related measures include current health status, health behaviors (e.g., utilization of health services; risk behaviors such as smoking, alcohol consumption, and diet), blood pressure and blood lipids, and family history of disease. Each of these health-related variables has been measured by selfreport, clinical assessment, or direct assessments (i.e., laboratory tests). Broader definitions of health status characterized as quality of life and based on the World Health Organization's (1948) definition of wellness have been proposed (cf. Kaplan, in press; Spilker, 1990; Wenger, Mattson, Furberg, & Elinson, 1984). However, to date, few studies other than randomized clinical trials reflect this trend in health research.

MECHANISMS LINKING SOCIAL SUPPORT TO HEALTH Few investigations examine the mechanisms underlying the relationship between social support and health, although several possible mechanisms have been proposed in recent years (Cohen, 1988; Davidson & Shumaker, 1987; House et al., 1988). Social support may influence health by directly or indirectly affecting health behaviors (Berkman, 1982, 1984; Cohen, 1988; Cohen, Kaplan, & Manuck, in press; Dean, 1986): by promoting healthy or unhealthy behaviors (cf. Kaplan & Hartwell, 1987; Whalen & Kleiwer, in press), by the provision of information that occurs in supportive exchanges (Berkman, 1982; Cohen, 1988), and by the provision of tangible resources, such as economic aid, housing, and transportation (Berkman, 1984; Caplan, 1974; Cohen, 1988). Another proposed mechanism linking social support to health is psychologically based; that is, social support may be associated with more positive affective states, such as increased feelings of belonging, intimacy, improved sense of self-worth (Berkman, 1982, 1984; Cohen, 1988), and an increased sense of control (Cohen, 1988). The positive psychological states derived from support systems may increase health promoting behaviors, or they may dampen or prevent the pathogenic physiological reactions associated with negative mental states. Positive psychological states may also alter the appraisal of threatening events. That is, people in a positive mood state may be able to reappraise a threatening event as benign, thereby attenuating the physiological responses associated with the threats. Several researchers have suggested that neuroendocrine, immunologic, and hemodynamic responses play an important role in the relationship of social support and health (Berkman, 1982, 1984; Broadhead et al., 1983; Cohen, 1988; Cohen et al., in press). These factors have been examined particularly as they relate to provocative psychosocial stimuli. The neuroendocrine responses most frequently assessed include the sympathetic adrenal medullary hormones of epinephrine and

103

norepinephrine. Increased sympathetic medullary activity results in increased blood pressure, heart rate, and circulating levels of epinephrine and norepinephrine, among other responses (Guyton, 1982). Cohen et al. (in press) reviewed the evidence for biological models linking social support to cardiovascular disease. Most of the research in this area emphasizes the effects that acute neuroendocrine and cardiovascular responses to stressful stimuli have on atherogenesis or the precipitation of acute clinical events (myocardial ischemia, myocardial infarction, arrhythmia, and sudden cardiac death). Because stress is thought to be associated with physiological responses that enhance the development of early lesions, it is thought that social support may buffer the physiological responses and ultimately influence the development of lesions. In a recent study, Kamarck, Manuck, and Jennings (1989) found that the presence of a supportive person can attenuate reactivity to psychological stressors for women in a laboratory situation. GENDER, SOCIAL SUPPORT, AND HEALTH Mortality Studies Five prospective, population-based studies examined the relationship between social support and mortality for men and women (Berkman & Syme, 1979; House, Robbins, & Metzner, 1982; Orth-Gomer, in press; Orth-Gomer & J. V. Johnson, 1987; Schoenbach, Kaplan, Fredman, &Kleinbaum, 1986; for reviews of these studies, see also Broadhead et al., 1983; Cohen, 1988; Hazuda, in press). In the Alameda County, California, study (Berkman, 1984, 1985; Berkman & Syme, 1979), 2,229 men and 2,496 women completed a selfadministered questionnaire in 1965. Mortality data were collected from 1965 through 1974. These investigators constructed a Social Network Index (SNI) composed of four structure-based measures of social support: (a) marital status, (b) number and frequency of contacts with family and close friends, (c) church group membership, and (d) group affiliation, with greater weight assigned to the more "intimate" measures (a and b). Berkman and Syme's analyses yielded a linear relationship between SNI and mortality such that decreases in SNI were related to increases in mortality at each SNI level. The overall, age-adjusted relative risk was 2.3 for men and 2.8 for women. The linear pattern was consistent for men and women across age groups with one exception: 50- to 59-year-old women with a moderate SNI had a decreased mortality rate, whereas women with a high SNI had an increased mortality rate. In examining each of the social support measures separately, interesting gender differences emerged. For example, the relative risk for nonmarried versus married was about 1.4 for women at each age group, whereas for men the relative risk was much higher in the two youngest age groups: 2.9 and 2.1 for 30 to 49 and 50 to 59, respectively. For both men and women, the relationship between (a) the measure of number and frequency of contacts with friends and relatives and (b) mortality followed the same linear pattern as exhibited by the SNI; however, the effect was much greater for women than

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

104

SHUMAKER AND HILL

for men in each age group (for men, 1.8 at 30 to 49, 1.3 at 50 to 59, and 1.8 at 60 to 69; for women, 2.8, 1.9, and 2.9, respectively). The relationship between social support and mortality held true for all-cause mortality as well as for specific causes (ischemic heart disease, cancer, cerebrovascular and circulatory diseases). After controlling for self-reported baseline measures of health behaviors, physical health status, healthcare utilization, and socioeconomic status (SES), the relationship decreased but remained significant for both men and women. A measure of marital satisfaction (more closely related to a functional component of social support) was unrelated to mortality. In the Tecumseh (Michigan) Community Health Study (House et al., 1982), 1,322 men and 1,432 women underwent an extensive physical exam and completed a face-to-face interview at baseline (from 1967 to 1969). Mortality data were collected through 1979. Four structure-based aspects of social support (confounded to some degree with physical functioning) were assessed: (a) marital status, visits with friends and relatives, and going on pleasure drives and picnics; (b) formal organizational involvement including churches, meetings, and voluntary organizations; (c) active and social leisure activities (e.g., classes, movies); and (d) passive and solitary leisure activities (e.g., reading). Looking at each of the social support measures separately, the relative risk for men ranged from 1.9 for marital status to 2.8 for meetings of voluntary associations. Although all the relationships were in the hypothesized direction for women, only church attendance was significant. After controlling for baseline morbidity status and health risk behaviors, a cumulative index of social support yielded a significant relationship between social support and mortality for men but not for women. Furthermore, the relationship for men appeared to be nonlinear with the largest effect occurring at the contrast between low levels of social support versus all other levels of support. Secondary analyses of disease-specific causes of death yielded a strong relationship between the cumulative index of social support and ischemic heart disease in women, comparable to the all-cause mortality data on men (House et al., 1982). However, the authors cautioned against overinterpretation of these data given the small sample size and skewed distributions. Finally, after controlling for intensity or frequency of activities and relationships, there was no evidence for a relationship between satisfaction with relationships and activities (functional social support measures) and mortality. In the Evans County, Georgia, study (Schoenbach et al., 1986), 605 White men, 719 White women, 297 Black men, and 438 Black women were interviewed between 1967 and 1969, with mortality data collected through 1980. In addition, medical histories were obtained and respondents completed physical activities questionnaires and underwent comprehensive physical examinations. Structure-based measures of social support included (a) marital status, (b) number of relatives living nearby, (c) number of close friends, (d) number of neighbors known well enough to visit, (e) number of relative families seen often, (f) frequency of church attendance, and (g) spare time spent in church activities. Control variables in

data analyses included age, presence of chronic disease, systolic blood pressure, electrocardiogram abnormalities, weight/height index, social status, and leisure-time physical activity (for men only). Schoenbach et al. examined the relationship of individual measures of social support, as well as indices designed to approximate Berkman and Syme's (1979) SNI, to mortality. Results supported an overall pattern of increased mortality associated with a low score on a cumulative index of the social support measures for White men and women over 60 years of age. This relationship was reversed for White women under 60; that is, lower social support scores were associated with lower mortality. In terms of specific measures, marital status was predictive for all strata except Black women. Unlike the Alameda data, but similar to the Tecumseh data, the relationship between social support and mortality was nonlinear; that is, most of the effect was accounted for by the lowest level of support. Orth-Gomer and J. V. Johnson (1987) used data from the Swedish National Survey of Living Conditions (SNSLC) to examine the relationship between social support and mortality in men and women. Their analyses were based on a sample of 17,433 Swedish men and women between the ages of 29 and 74 who were interviewed in 1976 and 1977. (The sampling frame for the SNSLC study was the entire adult Swedish population between the ages of 16 and 74.) Mortality data were collected for 6 years. The social support measure from this study was structure based and consisted of respondents' listings of individuals in their network (e.g., parent, sibling) and the frequency with which they visited each person, yielding an estimate of the number of sources of social contact and the frequency of contact with each source. These investigators generated a "social network interaction index," with a single score ranging from 0 to 106. In addition to the social support measure, data were obtained on long-term illness and disability, SES, and health risk behaviors. The social support scores were normally distributed, and respondents were divided into low, median, and high tertiles on support for the analyses. In all age groups except the highest (65 to 74), for both men and women, mortality rates were highest in the lowest support tertile. Similar to the Tecumseh and Georgia data, there were no differences in mortality between the middle- and high-support tertiles. Data on respondents 65 to 74 were more complex. For men, there was a linear effect between social-support tertile and mortality; in contrast, older women with the highest support score had the highest mortality rate. Controlling for risk factors and baseline health status reduced the relative risk, but the relationship remained significant for both men and women. These investigators also examined cardiovascular-related deaths and obtained similar results as from all-cause mortality. Data from a study in North Karelia (Finland) included two population-based surveys conducted in 1972 and 1977 of 13,300 men and women between the ages of 39 and 59; mortality from all causes and from cardiovascular disease (CVD) were ascertained over a 5-year follow-up period (reported in Orth-Gomer, in press). A structure-based index of social support was constructed from the survey data and included measures of marital status, frequency of visiting friends and relatives, number of people encountered every day, and participation in informal groups and organizations.

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

GENDER, SOCIAL SUPPORT, AND HEALTH For men, there was an increased relative risk of all-cause and CVD mortality for the lower levels of social support as compared to the upper levels (a threshold effect). Although there was a similar trend for women, it was not significant. Furthermore, after controlling for all predictors of CVD, the social-support measure was not significantly related to CVD mortality for women. Several studies have linked marital status to mortality (for discussions, see Berkman, 1984, 1985; Ell, 1989; Morell, Sullaway, & Leppin, in press). In general, unmarried people are at an increased risk for mortality than are married individuals, though this association appears to be weaker for women than for men (Stroebe & Stroebe, 1983). In a 10-year prospective study of 1,400 male and female patients with myocardial infarctions, unmarried people were more likely to die during and following hospitalization (Chandra, Szklo, Goldberg, & Tonascia, 1983). Similarly, in a population-based analysis of 27,779 cancer cases, unmarried men and women with cancer had a decreased survival rate (as reported in Ell, 1989). In a study conducted in Rancho Bernardo, California (Wingard, Suarez, & Barrett-Connor, 1983), 1,535 men and 1,981 women, ages 30 to 69, were followed from 1972 for a minimum of 7 years. Marital status was a significant predictor of all-cause mortality in men but not in women. In a crosssectional study based on the National Center for Health Statistics vital statistics data from 1959 to 1961 of 15- to 64-year-old men and women, nonmarried persons had an excess of ischemic heart disease deaths relative to married persons, and this excess was greater among men than women (as reported in Hazuda, in press). Morbidity and Health Behavior Studies In a study of 119 men and 40 women, ages 30 to 70, referred for angiography with a diagnosis of angina pectoris, coronary artery disease (CAD), or recent myocardial infarction, Seeman and Syme (1987) assessed the relationship of both structural and functional measures of social support to CAD. CAD was operationalized as percentage occlusion in all four arteries. Results from combined analyses of men and women indicated that network size and emotional support were not related to CAD. In contrast, the function-based measures of instrumental support and "feeling loved" were negatively related to CAD. No gender differences emerged in the combined analyses. In gender-specific analyses of social support and CAD, Seeman and Syme found that, for men, the relationships remained the same as the overall analyses. For women, however, there were no significant associations between any of the social-support measures and CAD. As noted by the investigators, interpretation of these findings is limited by the small number of women (40) included in the study. In another study of 86 male and 27 female patients undergoing angiography, Blumenthal et al. (1987) examined the relationships among social support, Type A behavior, and CAD. These investigators found a Social Support x Type A Behavior interaction such that Type A patients with high levels of social support had significantly lower levels of CAD as compared to Type As with low levels of social support. There was no interaction by gender of patient, and gender-specific

105

analyses were not reported. However, as in the Seeman and Syme study, the small number of women in the study precluded a reasonable test for an interaction by gender of subject, and the lack of an interaction should not be interpreted as indicating a comparable effect of social support and Type A behavior on CAD for both men and women. In addition to the inadequate number of women in this research to date, angiographic studies are subject to selection biases because they are limited to individuals presenting with symptoms related to CAD (Cohen & Matthews, 1987). The gender differences in health-seeking behavior, with women more likely than men to see a health provider when symptoms emerge (see Verbrugge & Wingard, 1987), coupled with the fact that physicians are more likely to refer men than women on for angiography when both present with the same symptoms (Morell et al., in press), would confound any future angiographic studies even if they were sufficiently powered to test for gender differences in social support and CAD. Kaplan and Hartwell (1987) investigated the relationship of social support to measures of diabetes control and compliance to a medical regimen for 32 male and 44 female noninsulin-dependent diabetes mellitus patients. The Social Support Questionnaire (developed by Sarason, Levine, Basham, & Sarason, 1983) was used to assess social support and includes availability and satisfaction measures. Kaplan and Hartwell's results indicated that, for women, network size was positively related to (a) failure to participate in the intervention program as determined by several measures and (b) an increase in reported symptoms. For men, network size was positively correlated with an increase in weight, cholesterol, and triglycerides and a decrease in reported symptoms. Control of diabetes was positively related to satisfaction with support for women and negatively related for men. Kaplan and Hartwell interpreted these complex findings in terms of gender differences in the measure and functions of social support. Investigators have considered the role of social support in buffering the negative health effects of stressful work environments, although most of these studies excluded women (see J. V. Johnson & Hall, in press, for a recent review). A notable exception is a study conducted by J. V. Johnson (1986) on a representative random sample of approximately 14,000 Swedish male and female workers, in which he looked at the combined effects of social support at work, job demand, and job control on CVD prevalence. Results indicated that interaction with co-workers buffered work stress against CVD prevalence for both men and women. In looking at support and control concurrently, Johnson determined that both support and control are necessary to modify the effects of job demands on CVD for men and women (J. V. Johnson, 1986; J. V. Johnson & Hall, 1988). Finally, several studies have examined the relationship between social support and adherence to medical regimens and health behavior changes, adjustment to chronic diseases, and participation in rehabilitation programs (for recent reviews, see Dracup, in press; Ell & Dunkel-Schetter, in press; Shumaker et al., 1990). Unfortunately, most of these investigations focus on male patients. When women are included in the sample, gender differences are rarely assessed. To some degree this research trend simply reflects gender differences in diseases, although these differences do not sufficiently

106

SHUMAKER AND HILL

account for the remarkable imbalance in research (see Morell et al., in press, for a discussion of this issue). One exception is a recent study by Kutner (1987), in which social support was related to perceived health in 332 male and female patients visiting an outpatient clinic. Although Kutner reported marked gender differences among various measures of support, there were no differences between men and women in the relationship of social support to perceived health.

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Summary of Research on Gender, Social Support, and Health Studies on the relationship between various indices of social support and mortality consistently demonstrate the protective role of support for White men (see also Blazer, 1982; Malcolm & Dobson, 1989; Ruberman, Weinblatt, Goldberg, & Chaudharg, 1984). When gender differences are assessed, however, the picture for women is less clear. The strongest support for a relationship between social support and mortality for women comes from the Alameda and Swedish studies (Berkman & Syme, 1979; Orth-Gomer & J. V. Johnson, 1987). In the former, a linear effect between increasing social support and decreasing mortality was found for women, whereas the latter reported a threshold effect with low levels of support predicting high mortality. The Tecumseh (Michigan), Georgia, and Finland studies all provided suggestive data of a relationship between support and increased mortality for women. Low support produced an increased relative risk for ischemic heart disease for women in Tecumseh, an increase in all-cause mortality for White women over 60 in Georgia, and a marginal increase in all-cause mortality for women in Finland if baseline disease status is not co varied. An interesting anomaly in the social support and mortality relationship for women occurs in three of the studies: Alameda County, California; Evans County, Georgia; and Sweden. In Alameda County, women with high levels of support between the ages of 50 and 59 had higher mortality rates; in Sweden, women with high levels of support between the ages of 65 and 74 had the highest mortality rate; and, in Georgia, women under 60 with the highest levels of support had the highest mortality rates. This unexpected reversal in the predicted relationship between support and mortality is not evidenced in any of the data on men and may reflect differences in the meaning of social support for men and women, as well as gender differences in the provider and recipient roles in supportive exchanges. Studies on marital status and mortality suggest a fairly consistent relationship for men: That is, unmarried men are more vulnerable. Again, however, this same relationship appears to be either weaker (Berkman & Syme, 1979; Hazuda, in press) or nonexistent (Wingard et al., 1983) for women. Finally, there were no significant effects for function-based measures of social support in any of the mortality studies. The morbidity data on gender differences in social support and health are considerably sparser than the data on mortality, and consistent patterns do not emerge. Even though there are no gender interactions in support and CAD in the two angiographic studies described (Blumenthal et al., 1987; Seeman & Syme, 1987), the small number of

women in each of these studies precludes a reasonable assessment of a gender effect. For both men and women, low support is associated with poorer perceived health among patients with chronic diseases (Kutner, 1987) and higher incidences of CVD in stressed workers (J. V. Johnson, 1986). The data on diabetic patients reported by Kaplan and Hartwell (1987) suggest a complex relationship of support to adherence and diabetes control for both men and women, with no obvious patterns emerging. FACTORS CONTRIBUTING TO THE GENDER DIFFERENCE IN SOCIAL SUPPORT AND PHYSICAL HEALTH There are some limitations in the available data that address the issue of gender differences in social support and physical health. Few studies include both men and women. When men and women are included, analyses on gender differences are often not reported. Among the studies that include both men and women there are marked variations in baseline health measures, populations studied, and measures of social support. However, these study design variations actually underscore the remarkably robust relationship between support and health for men as much as they make difficult interpretation of the different findings for women. And, in spite of the limited data available, our review of the research does suggest that there is a relationship between social support and physical health for women, albeit a weaker and somewhat more complex relationship than what appears to exist for men (Berkman, 1985; House et al., 1988). (Note that the same does not appear to be true for gender, social support, and mental health, where the relationship between social support and health may actually be stronger for women than for men; cf. Flaherty & Richman, 1989.) Several factors may contribute to the observed gender differences in the relationship between social support and health, including gender differences in (a) social support and the caregiving role, (b) the mechanisms linking social support to health, and (c) morbidity and mortality. Gender Differences in Social Support Socialization is differentiated by gender, and socialization experiences are inextricably tied to the development, maintenance, composition, and functions of social networks (cf. Belle, 1987; Flaherty & Richman, 1989; Troll, 1987; Vaux, 1988). Thus, it is not surprising that consistent differences by gender emerge in the structure and functions of social support, as well as in the provider and recipient roles. (The degree to which these differences are gender versus sex-role related is not known, although there is some evidence that sex role, independent of gender, contributes to differences in social support; see Vaux, Burda, & Stewart, 1986; Vaux & Harrison, 1985.) Support structure. Although there are some exceptions in older age groups, in general across the life span men tend to have more extensive but less intensive networks than women

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

GENDER, SOCIAL SUPPORT, AND HEALTH (Belle, 1987). Throughout the life span, girls and women are more likely to have confidants, and to have more confidants, than are boys and men (Flaherty & Richman, 1989; Lowenthal & Haven, 1968; Powers & Bultena, 1976). In adulthood, men often cite their spouses as their only confidants, whereas women cite spouses and friends with about the same frequency. In fact, men are much more likely than women to say that they have never had a confidant outside the family (Powers & Bultena, 1976). Studies of elderly adults demonstrate an overall shrinkage in network size with aging and possibly greater decreases occurring for men than for women (cf. Antonucci & Akiyama, 1987; Depner & Ingersoll-Dayton, 1988; Field & Minkler, 1988). Kessler, McLeod and Wethington (1985) reviewed several studies that show that women, compared with men, cast a "wider net of concern" (i.e., are involved with a greater number of people), have a greater inclination to get involved with caregiving activities, and are more responsive to the life events of others. Given the possibly smaller network size of older men, coupled with their increased reliance on spouses as confidants, Antonucci and Akiyama (1987) argued that "for men, quantitative support differences are relatively unimportant when a wife is present . . . [however] men can easily become isolated when the traditional marital role is disrupted and there is no wife present to maintain the supportive links" (p. 746). This hypothesis is consistent with the finding that unmarried men appear to be more vulnerable to disease than unmarried women. Support functions. As noted earlier support function refers to the type of resources exchanged in a supportive relationship (e.g., emotional, tangible). Women's networks are more multi faceted in that they are more variable and serve more functions than do men's (Antonucci & Akiyama, 1987). In addition, women report receiving more emotional and health-related support from their children and friends than do men (Depner & Ingersoll-Dayton, 1988). It appears that women both receive and use all types of support (Belle, 1987), especially emotional support, more than men do (Flaherty & Richman, 1989; Vaux, 1988). Overall, men's social participation is less affective than women's (Powers & Bultena, 1976). Provider and recipient roles. Studies across the life span suggest that women are more likely than men to be both support providers and support recipients. Kessler et al. (1985) found that, although there were no gender differences in the types of support provided (i.e., functions), women were 30% more likely to provide support to network members than were men. In general, women were more likely to be involved in all forms of help giving than men (see also Flaherty & Richman, 1989; Lowenthal & Haven, 1968). For older adults, when a spouse is not available to provide care, this task usually falls to an adult daughter or daughter-in-law rather than to an adult son. Furthermore, adult parents are more likely to live with an adult daughter than son (Margolin & Mclntyre-Kingsolver, 1988; Troll, 1987). The term "sandwich generation" has been used in recent years to describe the growing number of women in this culture who are simultaneously responsible for the caregiving of both their children and their (or their spouse's)

107

elderly parents. As noted by Margolin and MclntyreKingsolver (1988), "Society, the family, the professional community, and women themselves collude to delegate to women the primary responsibility for the well-being of the family" (p. 306). Men and women are more likely to rely on women than men as their primary sources of support (or confidants; cf. Antonucci & Akiyama, 1987; Belle, 1987; Kessler etal., 1985). In times of need, women are more likely to mobilize their support networks than are men; but, when men do mobilize support, they focus on their spouses for all types of support (Belle, 1987), and divorced men cite a spouse as the ideal support person (Belle, 1987). Overall, being married is the greatest influence of support satisfaction for men, whereas being in a reciprocal or balanced provider-and-recipient relationship is the greatest influence of support satisfaction for women (Antonucci & Akiyama, 1987). Along with their preponderance in the role of informal support provider, women also dominate formal support-giving roles (e.g., social worker, nurse, teacher; Belle, 1987). Thus, working women often "give at the office" as well as at home. There are several ways in which these gender differences in social support may be relevant to the gender, social support, and health relationship. For example, men's greater reliance on a single confidant coupled with their shrinking network as they age, may make them more vulnerable to isolation than women. Gender differences in the impact of marital status on mortality support this hypothesis. That is, the higher mortality rate among unmarried men as compared to unmarried women suggests that men have limited support resources to "fall back on" when they lose their primary source of support. It has also been suggested that the social networks in the Tecumseh and Georgia studies differed from those of the Alameda and Swedish studies in ways that could differentially affect the relationship between social support and health for men and women (Berkman, 1986; House et al., 1988). The rural settings of the Tecumseh and Georgia studies may promote networks that are denser (i.e., overlapping friendships) and more kinship based than the more diverse, urbanbased networks of the Alameda and Swedish studies. Thus, social ties in the rural environments may be less differentiated. The threshold effects for social support and health lend some credence to this argument. The effect of support on health would be more diminished for women than men in the nondiverse networks of the rural communities, given men's greater reliance on a single support provider. Research on the effects of diverse versus dense networks on women's health add support to this hypothesis. Women who work outside the home have more diverse and larger social networks than women who stay at home (Barnett & Baruch, 1987). In addition, multiple roles appear to be more healthful for women in the context of marriage (Verbrugge, 1983). Women have higher illness rates in countries where more women stay at home as full-time homemakers (HaavioMannila, 1986). In addition, unequal morbidity as a function of gender is smaller in families in which both men and women work outside the home, as compared to families in which women stay home (Haavio-Mannila, 1986). Women are more likely than men to develop and maintain the social networks used by both men and women. Networks

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

108

SHUMAKER AND HILL

can create or exacerbate distress when members convey disapproval or disrespect, betray confidences, fail to fulfill expectations, and place heavy demands on one another (Belle, 1987). In addition, "contagion of stress" may occur in the denser structure that characterizes women's networks. As "network tenders," women are more likely than men to be exposed to the negative social outcomes associated with network involvement (cf. Rook, 1984; Shinn, Lehmann, & Wong, 1984). In a study of 120 widowed 60- to 89-year-old women, Rook (1984) found that negative social outcomes (or network strain) were more consistent and more strongly related to poor mental health than was social support. The anomalies found in the population-based studies in which larger networks corresponded to larger mortality rates for a subgroup of women further support this hypothesis. Few studies include measures of both social support and network strain. The possible gender difference in exposure to network strain, which should covary with network size, provides an interesting hypothesis for the gender differences found in the studies on social support and health. Similar to the issue of women's increased exposure to negative social outcomes, is the fact that women are more likely than men to serve as providers of support. The role of care provider is emotionally and physically demanding for both men and women, and women may be more negatively affected by this role than men. Thus, for women, large social networks provide greater opportunities for support coupled with more demands and depletion of resources. This suggests that any positive effects for women of the structure-based measures of social support used in the population studies would be negated by women's caregiving roles within those networks. The inclusion of reciprocity measures of support (cf. Antonucci, 1985) would allow investigators to disentangle these effects. Gender Differences in Mechanisms Linking Support to Health The mechanisms through which social support influences health may differ by gender. For example, we know that women's health behaviors and health beliefs differ from men's. Kaplan and Hartwell (1987) argued that, at least among adolescents, peer norms relevant to health behavior may differ by gender. The degree to which these differences are attributable to different social influence patterns, however, is not clear and we are unaware of direct tests of this hypothesis. The relationship between risk behaviors and mortality also differ by gender. Unfortunately, however, studies of social support and physical health do not control for risk factors in the analyses, and do not test for gender differences in the potential path between social support, risk behaviors, and health (Berkman, 1986). One of the hypothesized mechanisms underlying the relationship between social support and health is through the buffering effect of support on stress (cf. Cohen & McKay, 1984). Women appear to be less biologically reactive to stress than men (Manuck & Polefrone, 1987), and the presence of a supportive person attenuates stress-reactivity for women

(Kamarck et al., 1989). A question that needs to be addressed is whether or not there is a gender difference in the effect of social support on stress-reactivity. Stress-reactivity as well as other biologically based factors associated with morbidity and mortality may be differentially affected by social support for women as compared to men. Gender Differences in Mortality and Morbidity Women's mortality rates are lower than men's at all age groups in most developed countries (U.S. Department of Commerce, Bureau of the Census, 1987; Verbrugge, 1989; Verbrugge & Wingard, 1987). In 1980 the life expectancy for men at birth was 70.0 years as compared to 77.5 years for women. An interesting gender difference in the decline of mortality from coronary heart disease (Thorn, 1987), coupled with increases in lung cancer among women, may in part account for a recent narrowing in the overall mortality gap between men and women (ratio of 1.8 in 1980; Verbrugge & Wingard, 1987). Gender differences for morbidity are more complex than for mortality. Women have higher overall rates of physical illnesses, disability days, physician visits, and prescription and nonprescription drug use than men (Verbrugge, 1989). Conversely, men have higher rates for impairments and lifethreatening chronic diseases than women. Women's rates of acute illnesses are higher than men's; yet men's injury rates are higher than women's. Overall, women have more chronic conditions than men; however, women's conditions are less severe and less life threatening than men's (e.g., arthritis, osteoporosis, digestive conditions; Verbrugge, 1989). Verbrugge (1989) suggested several explanations for the gender differences in mortality and morbidity, including differences between men and women in biological risks, acquired risks, illness behavior, health-reporting behavior, and prior health care. Several studies indicate a gender difference in the number and types of risk factors associated with poor health (cf. Dean, 1989; Eaker, Packard, Wenger, Clarkson, & Tyroler, 1987). Women often report more risk behaviors; however, the risk behaviors associated with men tend to have a more powerful influence on mortality (e.g., smoking). Also, isolation may increase the frequency of health-damaging behaviors, especially among men (Dean, 1989). Controlling for risk factors in mortality analyses reduces the male:female ratio; however, it does not eliminate it (Johansson, Vedin, & Wilhelmsson, 1983). Verbrugge concluded from her own and other data that acquired and psychosocial factors do not completely explain the gender differences in mortality and types of morbidity, and she suggested that biological factors must play an important role. Data from several sources support the role of biology in gender differences in mortality. Studies, for example, suggest a potentially protective role of reproductive hormones in CVD (cf. Eaker et al., 1987), although this role is most likely complex and interacts with behaviors (Matthews, 1989). Similarly, the prognosis for essential hypertension is better for women than for men; that is, women with the same blood

109

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

GENDER, SOCIAL SUPPORT, AND HEALTH

pressure as men are at lower risk for mortality (CornoniHuntley, LaCroix, & Hovlik, 1989). Studies of neuroendocrine and cardiovascular reactivity to stressors (a biobehavioral factor linked to cardiovascular morbidity and mortality) have demonstrated a consistent lower reactivity in women than in men (Manuck & Polefrone, 1987). Also, although men have a higher prevalence of myocardial infarctions, women have a significantly higher mortality rate following a myocardial infarction (Tofler et al., 1987). In summary, and as noted by Verbrugge and Wingard (1987) from a sociomedical viewpoint, women simply do not feel as well as men. Thus, women may live longer, but their quality of life may be significantly diminished (see Kaplan, Anderson, & Wingard, this issue). The gender differences in morbidity and mortality suggest that many of the studies on support and health may be underpowered to detect an effect for women. The small sample of women included in the two angiographic studies, coupled with the lower incidence of CAD in women were unquestionable deterrents to detecting a gender-specific relationship between social support and CAD. Although sample sizes were large in all the prospective, population-based studies, consistent with data on gender differences in mortality rates, incidences of mortality in all these studies were substantially lower for women than for men. Whether the event rates obtained for women were sufficient to detect a real effect for social support is unclear. However, the fact that risk ratios were reduced in all studies for both men and women, and that the social-support effect disappeared for women in the Finland study after controlling for health status at baseline, suggests that inadequate statistical power played an important role in these investigations. In addition, the two populationbased studies showing the strongest relationship between social support and health for women (Alameda and Sweden) used self-report health measures as baseline control variables, whereas the other studies used data from clinical exams. Gender differences in symptom reporting coupled with differences in the prognostic validity of biologically based risk factors for mortality suggest additional factors that may have contributed to the observed gender differences in support and health. Investigations of men and women at higher risk for mortality could attenuate the inadequate-power issue to some degree, although studies of at-risk populations limit the generalizability of the data obtained, as well as our understanding of the role played by social support in disease etiology (Cohen & Matthews, 1987). Longer follow-up periods for the existing population studies will increase event rates and may allow reexamination of the gender-specific relationship between social support and health. A provocative set of data exists suggesting a gender difference in the relationship between social support and physical health. We have reviewed the limitations of research in this area and provided several hypotheses for this gender effect. However, until more studies of the role of psychosocial factors in physical health include sufficient numbers of women to assess gender differences —as well as more sophisticated measures of social support, provider and recipient roles, and network reciprocity and health —our understanding

of the role that social support plays in physical health for women will continue to be vague and severely limited. ACKNOWLEDGMENTS Portions of this article were presented at the meeting of the American Psychological Association, New Orleans, August 1989. REFERENCES Antonucci, T. C. (1985). Social support: Theoretical advances, recent findings and pressing issues. In I. G. Sarason & B. R. Sarason (Eds.), Social support: Theory, research and applications (pp. 21-37). Boston: Martinus Nijhoff. Antonucci, T. C , & Akiyama, H. (1987). An examination of sex differences in social support in mid and late life. Sex Roles, 17, 737-749. Antonucci, T. C , & Johnson, E. H. (in press). Conceptualization and methods in social support theory and research as related to cardiovascular disease. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease. New York: Plenum. Barnett, R. C , & Baruch, G. K. (1987). Social roles, gender, and psychological distress. In R. C. Barnett, L. Biener, & G. K. Baruch (Eds), Gender and stress (pp. 122-156). New York: Free Press. Belle, D. (1987). Gender differences in the social moderators of stress. In R. C. Barnett, L. Biener, & G. K. Baruch (Eds.), Gender and stress (pp. 257-277). New York: Free Press. Berkman, L. F. (1982). Social network analysis and coronary heart disease. Advanced Cardiology, 29, 37-49. Berkman, L. F. (1984). Assessing the physical health effects of social networks and social support. Annual Review of Public Health, 5, 413-432. Berkman, L. F. (1985). The relationship of social networks and social support to morbidity and mortality. In S. Cohen & S. L. Syme (Eds.), Social support and health (pp. 241-262). New York: Academic. Berkman, L. G. (1986). Social networks, support, and health: Taking the next step forward. American Journal of Epidemiology, 123, 559-562. Berkman, L. F., & Syme, S. L. (1979). Social networks, host resistance, and mortality: A nine-year follow-up study of Alameda County residents. American Journal of Epidemiology, 109, 186-204. Blazer, D. G. (1982). Social support and mortality in an elderly community population. American Journal of Epidemiology, 115, 684-694. Blumenthal, J. A., Burg, M. M., Barefoot, J., Williams, R. B., Haney, T., & Zimet, G. (1987). Social support, Type A behavior, and coronary artery disease. Psychosomatic Medicine, 49, 331-339. Broadhead, W. E., Kaplan, B. H., James, S. A., Wagner, E. H., Schoenbach, V. J., Grimson, R., Heyden, S., Tibblin, G., & Gehlbach, S. H. (1983). The epidemiologic evidence for a relationship between social support and health. American Journal of Epidemiology, 117, 521-537. Caplan, G. (1974). Support systems and community mental health. New York: Behavioral Publications. Chandra, V., Szklo, M., Goldberg, R., & Tonascia, J. (1983). The impact of marital status on survival after acute myocardial

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

110

SHUMAKER AND HILL

infarction: A population based study. American Journal of Epidemiology, 117, 320. Cohen, S. (1988). Psychosocial models of the role of social support in the etiology of physical disease. Health Psychology, 7, 269-297. Cohen, S., Kaplan, J. R., & Manuck, S. B. (in press). Social support and coronary heart disease: Underlying psychologic and biologic mechanisms. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease. New York: Plenum. Cohen, S., & Matthews, K. A. (1987). Social support, Type A behavior, and coronary artery disease [Editorial]. Psychosomatic Medicine, 49, 325-330. Cohen, S., & McKay, G. (1984). Social support, stress and the buffering hypothesis: A theoretical analysis. In A. Baum, J. E. Singer, & S. E. Taylor (Eds.), Handbook of psychology and health (Vol. 4, pp. 253-268). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Cohen, S., & Syme, S. L. (Eds.). (1985). Social support and health. New York: Academic. Cornoni-Huntley, J., LaCroix, A., & Hovlik, R. J. (1989). Race and sex differentials in the impact of hypertension in the United States. Archives of Internal Medicine, 149, 780-788. Davidson, D. M., & Shumaker, S. A. (1987). Social support and cardiovascular disease. Arteriosclerosis, 7, 101-104. Dean, K. (1986). Social support and health: Pathways of influence. Health Promotion, 1, 133-150. Dean, K. (1989). Self-care components of lifestyles: The importance of gender, attitudes and the social situation. Social Sciences and Medicine, 29, 137-152. Depner, C. E., & Ingersoll-Dayton, B. (1988). Supportive relationships in later life. Psychology and Aging, 3, 348-357. Dracup, K. (in press). Cardiac rehabilitation: The role of social support in recovery and compliance. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease. New York: Plenum. Eaker, E. D., Packard, B., Wenger, N. K., Clarkson, T. B., & Tyroler, H. A. (Eds.). (1987). Coronary heart disease in women. New York: Haymarket Doyma. Ell, K. (1989). Social support and coping with serious illness: The family connection. Unpublished manuscript, University of Southern California, Los Angeles. Ell, K., & Dunkel-Schetter, C. (in press). Social support and adjustment to myocardial infarction, angioplasty and coronary artery bypass surgery. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease. New York: Plenum. Field, D., & Minkler, M. (1988). Continuity and change in social support between young-old and old-old or very-old age. Journal of Gerontology, 43(4), P100-P106. Flaherty, J., & Richman, J. (1989). Gender differences in the perception and utilization of social support: Theoretical perspectives and an empirical test. Social Sciences and Medicine, 28, 1221-1228. Guyton, A. C. (1982). Local control of blood flow by the tissues, and nervous and humoral regulation. In A. C. Guyton (Ed.), Textbook of medical physiology (pp. 232-245). Philadelphia: Saunders. Haavio-Mannila, E. (1986). Inequalities in health and gender. Social Sciences and Medicine, 22, 141-149. Hazuda, H. P. (in press). A critical evaluation of United States epidemiologic evidence, including a special consideration of ethnic variation. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease. New York: Plenum. House, J. S., & Kahn, R. L. (1985). Measures and concepts of social support. In S. Cohen & S. L. Syme (Eds.), Social support and health (pp. 83-108). New York: Academic. House, J. S., Landis, K. R., & Umberson, D. (1988). Social relationships and health. Science, 241, 540-544. House, J. S., Robbins, C , & Metzner, H. L. (1982). The association

of social relationships and activities with mortality: Prospective evidence from the Tecumseh Community Health Study. American Journal of Epidemiology, 116, 123-140. Johansson, S., Vedin, A., & Wilhelmsson, C. (1983). Myocardial infarction in women. Epidemiologic Reviews, 5, 67-95. Johnson, J. V. (1986). The impact of workplace social support and work control upon cardiovascular disease in Sweden (Division of Environmental and Organizational Psychology Research Report No. 1). Stockholm: University of Stockholm. Johnson, J. V., & Hall, E. M. (1988). Job strain, workplace social support and cardiovascular disease: A cross sectional study of a random sample of the Swedish working population. American Journal of Public Health, 78, 1336-1342. Johnson, J. V., & Hall, E. M. (in press). Social support in the work environment and cardiovascular disease. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease. New York: Plenum. Kahn, R. L., & Antonucci, T. C. (1980). Convoys over the life course: Attachments, roles and social support. In P. B. Bakes & O. Brim (Eds.), Life-span development and behavior (Vol. 3, pp. 254-286). New York: Academic. Kamarck, T. W., Manuck, S. B., & Jennings, J. R. (1989, April). Social support reduces cardiovascular reactivity to behavioral challenge: A laboratory model. Paper presented at the meeting of the Society of Behavioral Medicine, San Francisco. Kaplan, R. M. (in press). Measures of health outcome in social support research. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease. New York: Plenum. Kaplan, R. M., & Hartwell, S. L. (1987). Differential effects of social support and social network on physiological and social outcomes in men and women with Type II diabetes mellitus. Health Psychology, 6, 387-398. Kessler, R. C , McLeod, J. D., & Wethington, E. (1985). The costs of caring: A perspective on the relationship between sex and psychological distress. In I. G. Sarason & B. R. Sarason (Eds.), Social support: Theory, research and applications (pp. 491-506). Boston: Martinus Nijhoff. Kutner, N. G. (1987). Social ties, social support, and perceived health status among chronically disabled people. Social Science and Medicine, 25(1), 29-34. Lowenthal, M. F., & Haven, C. (1968). Interaction and adaptation: Intimacy as a critical variable. American Sociological Review, 33, 20-30. Malcolm, J. A., & Dobson, A. J. (1989). Marriage is associated with a lower risk of ischaemic heart disease in men. Medical Journal of Australia, 151, 185-188. Manuck, S. B., & Polefrone, J. M. (1987). Psychophysiologic reactivity in women. In E. D. Eaker, B. Packard, N. K. Wenger, T. B. Clarkson, & H. A. Tyroler (Eds.), Coronary heart disease in women (pp. 164-171). New York: Haymarket Doyma. Margolin, G., & Mclntyre-Kingsolver, K. (1988). Family relationships. In E. Blechman & K. Brownell (Eds.), Behavioral medicine for women (pp. 305-317). New York: Pergamon. Matthews, K. A. (1989). Interaction effects of behavior and reproductive hormones on sex differences in risk for coronary heart disease. Health Psychology, 8, 373-387. Morell, M. A., Sullaway, M. E., & Leppin, A. (in press). Gender differences in Type A behavior, social support and ischemic heart disease. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease. New York: Plenum. Orth-Gomer, K. (in press). International epidemiological evidence for a relationship between social support and cardiovascular disease. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease. New York: Plenum. Orth-Gomer, K., & Johnson, J. V. (1987). Social network interaction

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

GENDER, SOCIAL SUPPORT, AND HEALTH and mortality: A six year follow-up study of a random sample of the Swedish population. Journal of Chronic Disease, 40, 949957. Orth-Gomer, K., & Unden, A. (1987). The measures of social support in population surveys. Social Sciences and Medicine, 24, 83-94. Powers, E., & Bultena, G. (1976). Sex differences in intimate friendships in old age. Journal of Marriage and the Family, 38, 739-747. Rook, K. S. (1984). The negative side of social interaction: Impact on psychological well-being. Journal of Personality and Social Psychology, 46, 1097-1108. Ruberman, W., Weinblatt, E., Goldberg, J., & Chaudharg, B. S. (1984). Psychosocial influences on mortality after myocardial infarction. New England Journal of Medicine, 311, 552-559. Sarason, I. G., Levine, H. M., Basham, R. B., & Sarason, B. R. (1983). Assessing social support: The Social Support Questionnaire. Journal of Personal and Social Psychology, 44, 127-139. Schoenbach, V. J., Kaplan, B. H., Fredman, L., & Kleinbaum, D. G. (1986). Social ties and mortality in Evans County, Georgia. American Journal of Epidemiology, 123, 577-591. Seeman, T. E., & Syme, S. L. (1987). Social networks and coronary artery disease: A comparison of the structure and function of social relations as predictors of disease. Psychosomatic Medicine, 49, 340-353. Sherbourne, C. D., & Stewart, A. (in press). The MOS social support survey. Social Science and Medicine. Shinn, M., Lehmann, S., & Wong, N. W. (1984). Social interaction and social support. Journal of Social Issues, 40(4), 55-76. Shumaker, S. A., & Brownell, A. (1984). Toward a theory of social support: Closing conceptual gaps. Journal of Social Issues, 40(4), 11-36. Shumaker, S. A., & Czajkowski, S. M. (Eds.), (in press). Social support and cardiovascular disease. New York: Plenum. Shumaker, S. A., Schron, E. B., Ockene, J. K., Parker, C. T., Probstfield, J. L., & Wolle, J. M. (Eds.). (1990). The handbook of health behavior change. New York: Springer. Spilker, B. (Ed.). (1990). Quality of life assessments in clinical trials. New York: Raven. Stroebe, M. S., & Stroebe, W. (1983). Who suffers more? Sex differences in health risks of the widowed. Psychological Bulletin, 93, 279-301. Thom, T. J. (1987). Cardiovascular disease mortality among United States women. In E. D. Eaker, B. Packard, N. K. Wenger, T. B. Clarkson, & H. A. Tyroler (Eds.), Coronary heart disease in women (pp. 33-41). New York: Haymarket Doyma.

111

Tofler, G. H., Stone, P. H., Muller, J. E., Willich, S. N., Davis, V. G., Poole, W. K., Strauss, H. W., Willerson, J. T., Jaffe, A. S., Robertson, T., Passamani, E., Braunwald, E., & MILIS Study Group. (1987). Effects of gender and race on prognosis after myocardial infaraction: Adverse prognosis for women, particularly Black women. Journal of the American College of Cardiology, 9, 473-482. Troll, L. E. (1987). Gender differences in cross-generation networks. Sex Roles, 17, 751-766. U.S. Department of Commerce, Bureau of the Census. (1987). An aging world (International Population Reports Series P-95, No. 78). Washington, DC: U.S. Government Printing Office. Vaux, A. (1988). Social support: Theory, research, and intervention. New York: Praeger. Vaux, A., Burda, P., & Stewart, D. (1986). Orientation towards utilizing support resources. Journal of Community Psychology, 14, 159-170. Vaux, A., & Harrison, D. (1985). Support network characteristics associated with support satisfaction and perceived support. American Journal of Community Psychology, 13, 245-268. Verbrugge, L. M. (1983, August). Pressures, satisfactions, and their link to physical health of young women. Paper presented at the meeting of the American Psychological Association, Anaheim, CA. Verbrugge, L. M. (1989). The twain meet: Empirical explanations of sex differnces in health and mortality. Journal of Health and Social Behavior, 30, 282-304. Verbrugge, L. M., & Wingard, D. L. (1987). Sex differentials in health and mortality. Women and Health, 12(2), 103-145. Wallston, B. S., Alagna, S. W., DeVellis, B. M., & DeVellis, R. F. (1983). Social support and physical health. Health Psychology, 2, 367-391. Wenger, N. K., Mattson, M. E., Furberg, C. D., & Elinson, J. (Eds.). (1984). Assessment of quality of life in clinical trials of cardiovascular therapies. New York: LeJacq. Whalen, C. K., & Kleiwer, W. (in press). Social influences on the development of cardiovascular risk during childhood and adolescence. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease. New York: Plenum. Wingard, D. L., Suarez, L., & Barrett-Connor, E. (1983). The sex differential in mortality from all causes and ischemic heart disease. American Journal of Epidemiology, 117, 165-172. World Health Organization. (1948). Constitution of the World Health Organization. Geneva: WHO Basic Documents.