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Gender and Physical Health
Gender and Physical Health Gerdi Weidner, San Francisco State University, Tiburon, CA, USA Ó 2015 Elsevier Ltd. All rights reserved. This article is a revision of the previous edition article by G. Weidner, volume 9, pp. 5904–5907, Ó 2001, Elsevier Ltd.
Abstract This article reviews factors that contribute to the gender gap in life expectancy, focusing on the leading cause of death, heart disease. A brief summary of gender differences in biological factors is followed by a presentation of behavioral and psychosocial contributions to women’s greater longevity, and implications for prevention and treatment are discussed.
Gender Gap in Life Expectancy Considerable gains in life expectancy have been observed for both sexes during the past decades. However, men still die about 5 years earlier than women (Murphy et al., 2013). This gender gap in life expectancy is largest when measured at birth, but shrinks with age. For example, if a man lives to 75 years of age in 2010, his life expectancy is only 1.9 years shorter than that of a woman’s of the same age (Murphy et al., 2013). This shrinking gender gap with age is because men are more likely to die at younger ages than women. In the United States, the 15 leading causes of death in 2010 were (1) heart disease, (2) cancer, (3) chronic lower respiratory diseases, (4) stroke, (5) accidents (unintentional injuries), (6) Alzheimer’s disease, (7) diabetes mellitus, (8) kidney disease, (9) influenza and pneumonia, (10) suicide, (11) septicemia, (12) chronic liver disease and cirrhosis, (13) hypertension, (14) Parkinson’s disease, and (15) pneumonitis (inflammation of the lung). These 15 causes of mortality accounted for 80.4% of all deaths in 2010 (Murphy et al., 2013). Almost all of these 15 leading causes of death show men to be at a greater risk than women. That is, the male-to-female mortality ratios (i.e., male age-adjusted death rate divided by the female age-adjusted death rate) ranged from 4.0 for suicide to 1.2 for septicemia. For heart disease, the major cause of death, the ratio was 1.5, and 1.4 for cancer, diabetes mellitus, kidney disease, and influenza/pneumonia. The only cause of death for which the ratio of male-to-female death rate was less than 1 was Alzheimer’s disease (0.8), and women were as likely as men to die from stroke and hypertension (ratios ¼ 1.0; Murphy et al., 2013). Several factors contribute to the gender gap in life expectancy. These can be grouped into three categories: biological, behavioral, and psychosocial (for more extensive coverage, see section on Gender in Whitfield et al., 2012).
Factors Contributing to the Gender Gap in Life Expectancy Biological Factors In her classic article, ‘Why Do Women Live Longer Than Men?’ Waldron concluded that “physiological differences have not been shown to make any substantial contribution to higher male death rates” (Waldron, 1976: p. 356). This conclusion has
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not changed much over the past decades (Gorman and Read, 2007; Waldron, 2005). Interestingly, international data on heart disease mortality from 46 communities in 24 countries have shown that male:female ratios vary widely, ranging from 10:1 in Iceland to 10:6 in Beijing, China (Jackson et al., 1997; also see Waldron, 2005). The fact that the differences between countries are larger than the difference between the sexes suggests that male anatomy is not destiny, at least in regard to heart disease. Additionally, the epidemic of cardiovascular diseases among young and middle-age Eastern European men has widened the gender gap in life expectancy over a very brief time span, which suggests that other than biological factors play a role in men’s greater mortality risk (Weidner, 2010; Weidner et al., 2002; Weidner and Cain, 2003).
Behavioral Factors Behavioral factors, such as smoking, excessive alcohol use, poor diet, and physical inactivity, are clearly involved in many of the major chronic diseases and causes of death worldwide (Lopez et al., 2006). For example, cigarette smoking has been linked to heart disease, lung cancer, chronic obstructive pulmonary disease, and pneumonia. Excessive alcohol consumption increases the risk for a number of diseases, foremost among them heart and liver disease. Excessive alcohol consumption, along with lack of seat belt use, also plays a major role in accidents and injuries in general. Other accidental deaths, such as homicide and suicide, often involve firearms. Overeating, unhealthy diets, and lack of exercise (associated with obesity) contribute to almost all chronic diseases, including diabetes, cancers, and strokes (Weidner, 2012). An evaluation of lifestyle practices (i.e., smoking, physical inactivity, and unhealthy eating habits) in the INTERHEART study confirms their importance for myocardial infarction (MI), collectively accounting for more than 55% of the population attributable risk (PAR) in women and men (Anand et al., 2008), that is, the reduction in incidence that would be observed if the population were unexposed to these healthdamaging lifestyle factors. Generally, men are more likely to engage in healthdamaging behaviors (e.g., smoking, unhealthy eating, excessive alcohol use) when compared to women. For example, women’s diets have a lower ratio of saturated to polyunsaturated fat and higher vitamin C content than men’s diets (Connor et al., 2002).
International Encyclopedia of the Social & Behavioral Sciences, 2nd edition, Volume 9
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The only behavioral gender difference favoring men consistently appears to be physical activity. However, this finding may be due to the use of questionnaires designed for men, which focus on sports and neglect physical activities associated with housework (Barrett-Connor, 1997). Furthermore, stress may play a greater role for health-damaging behaviors among men than among women. For example, job strain appears to be associated with increases in healthdamaging behaviors (e.g., cigarette smoking, excessive alcohol and coffee consumption, lack of exercise) among men, but not among women (Weidner et al., 1997; Weidner and Collins, 1993). Thus, considering the major behaviors involved in the leading causes of death, women appear to fare better than men.
Psychosocial Factors Systematic assessment of psychosocial factors has not always been a part of large population studies of health outcomes. Most of what we know about psychosocial contributions to physical health conditions comes from studies of heart disease, the number one cause of death in the United States, accounting for 24.2% of total deaths in 2010 (Murphy et al., 2013). Psychosocial factors such as hostility/anger, depression/vital exhaustion, lack of social support, and work stress have prospectively been linked to premature mortality from all causes and heart disease mortality in both sexes (e.g., HoltLunstad et al., 2010; Kuper et al., 2002; Orth-Gomér et al., 2010; also see Depression, Pessimism, and Health in this section). The importance of psychosocial factors for MI in both women and men has been most strongly illustrated by findings from the largest global study of MI, the INTERHEART study (Anand et al., 2008; Yusuf et al., 2004). This study compared over 15 152 cases with 14 820 sex- and agematched controls in 52 countries on all continents. Most interestingly, in addition to eight commonly assessed risk factors of heart disease (e.g., hypertension, abnormal lipids, diabetes, smoking, exercise, moderate alcohol consumption), INTERHEART also included an assessment of eating a healthy diet and a psychosocial stress index. This index consisted of depression, stress at work or at home, financial stress, major life events, and low locus of control. Together, these risk factors were significantly associated with MI in both women and men and accounted for more than 90% of the PAR in both sexes. Interestingly, the lower burden of MI among women at younger ages (<60 years) was largely explained by their lower levels of risk factors: after statistical adjustment of these factors, the gender difference in the probability of MI before the age of 60 was reduced by 80% (Anand et al., 2008). The main contributors to the increased risk among the younger men were a high prevalence of lipid abnormalities and smoking, although men did appear to benefit from their greater (moderate) alcohol consumption. Examining gender differences in the PARs across all ages revealed several differences: higher PARs in women than in men were observed for hypertension, diabetes, abdominal obesity, physical inactivity, lack of moderate alcohol intake, and the psychosocial stress index. Men’s PAR was significantly larger for smoking. In sum, findings from the INTERHEART study
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indicate that most premature MI is preventable and that interventions may benefit from targeting risk factors in a gender-specific fashion. Gender-specific associations of personality attributes (hostility/mistrust), negative emotions (particularly depression), and social support/social isolation, as well as work stress, with health and well-being are discussed elsewhere (Barefoot et al., 1995; Leifheit-Limson et al., 2010; Orth-Gomér et al., 2010; Schwarzer and Rieckmann, 2002; Weidner and Spaderna, 2013). Generally, high levels of hostility/mistrust and depression and low levels of social support are related to harmful health outcomes in both sexes. Men consistently score higher on measures of hostility/mistrust and report less social support than women, which contributes to their increased health risk. Interestingly, both of these attributes are characteristics of the male (‘macho’) gender role, which has been linked to behavioral risk factors such as smoking, excessive alcohol consumption, and lack of seat belt use (Courtenay, 2009), as well as to decreased motivation to learn stressmanagement skills (Sieverding, 2002). Additionally, women not only report more social support than men, but also have more sources of social support, thus decreasing their dependency on a single source. For example, studies of middle-aged people in Massachusetts found that men were more than twice as likely as women to name their spouse (or their partner) as their primary provider of social support (65.5 vs 26.4%). Furthermore, 24.2% of men (but only 6.1% of women) said this was their only source of support (New England Research Institutes, 1997). These data may, in part, explain why men’s health is more seriously affected by partner loss through separation, divorce, or widowhood (Miller and Wortman, 2002). In regard to negative emotions, gender differences appear to favor men. In most studies, women report more negative emotions such as depression than men (although this is not consistently found in populations where women and men have similar roles, such as college students; Nolen-Hoeksema and Girgus, 1994). Although women may report more depression, they may be coping more effectively than men. Generally, men are more likely to use avoidant-coping strategies, such as denial and distraction, whereas women are more likely to use vigilant-coping strategies, paying attention to the stressor and its psychological and somatic consequences (Weidner and Collins, 1993). Which style is more adaptive depends largely on the situation. Most stressful experiences consist of uncontrollable daily hassles, which are short-lived and typically of no great consequence. Here avoidant strategies would be more adaptive (“what I cannot control and what can’t hurt me is best ignored”). Thus, men’s strategies are likely to pay off for these types of events, contributing to their lesser experience (or report) of emotional discomfort or distress. But what if disaster hits? How do people cope with uncontrollable events requiring long-term adaptation, such as divorce, loss of a loved one, job loss, and sudden financial crisis and economic uncertainty? Here it may be women’s greater vigilance that is more adaptive, such as preparing for the crisis, and seeking help and advice. Consistent with this reasoning are data from the Hungarian population that showed that women tended to accept their negative mood as a disorder to be treated, whereas
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men were more likely to engage in self-destructive behavior, such as excessive alcohol consumption (Réthelyi et al., 2002). Similarly, research on how people cope with disasters (e.g., hurricanes and tornadoes) has supported the notion of men’s maladaptive coping: Increases in alcohol consumption and depression were related to personal disaster exposure among men, whereas no such direct relationship was evident among women (Solomon, 2002; Solomon et al., 1987). Furthermore, socioeconomic deprivation appears to be more closely related to depression in men than in women (Kopp et al., 2002). Thus, men’s psychosocial risk factor profile appears to further enhance their risk for ill health.
Implications for Prevention and Treatment Gender differences in behavioral and psychosocial lifestyle factors are likely contributors to the gender gap in several major causes of death. In regard to prevention, several large studies have now demonstrated significant health benefits to adopting a healthy lifestyle (e.g., a combination of a prudent diet, regular exercise, maintaining healthy body weight, and not smoking) for both women and men (Chiuve et al., 2006; King et al., 2007; Knoops et al., 2004). However, analyses of data from a community study of 15 708 middle-aged adults found that only 8.5% practiced healthy lifestyles (King et al., 2007). Although the percentage of women following healthy lifestyle practices was significantly larger than that of men, the low overall percentage is disconcerting. During a 4-year follow-up, 8.4% of participants newly adopted a healthy lifestyle (i.e., diets high in fruits and vegetables, regular exercise, maintaining a healthy body weight, and not smoking), and experienced a rather prompt benefit: mortality and cardiovascular disease risk were significantly reduced (40 and 35%, respectively) compared to participants with less healthy lifestyles (King et al., 2007). The authors also noted that men in general, African-Americans, and individuals with lower socioeconomic status were less likely to adopt a healthy lifestyle. Although this study clearly demonstrates the benefits of adopting a healthy lifestyle, it also illustrates the problems associated with behavior change in primary prevention. Overall, efforts to reduce risk factors (via educational methods) in the general population have been disappointing. In their review of 39 trials, Ebrahim et al. (2006) conclude that “different approaches to behavior change are needed . the availability of healthier foods and better access to recreational and sporting facilities may have greater impact on dietary and exercise patterns . than health professional advice” (p. 2; also see Weidner and Kendel, 2010). In contrast, attempts to change lifestyle behaviors in secondary and tertiary prevention trials (i.e., in people at high risk for disease and patients with the disease) have been more successful (Weidner and Kendel, 2010), but not without problems, especially in regard to overcoming barriers to participation. For example, the low utilization of cardiac rehabilitation by eligible patients has been attributed to several factors, including female gender (due to referral bias), medical insurance coverage, education, and ease of access to rehabilitation (Jackson et al., 2004).
In regard to psychosocial interventions, a meta-analysis of psychological treatment studies with heart disease patients concludes that psychological treatment is effective in reducing 2-year mortality by 27% (Linden et al., 2007). However, mortality was not reduced for women, for patients who perceived no reductions in stress, and for those whose treatment started right after the cardiac event (<2 months). Interestingly, the majority of women included in this meta-analysis were enrolled in the Enhancing Recovery in Coronary Heart Disease (ENRICHD) study. This study was a major multicenter, randomized clinical trial that tested the effects of a psychosocial intervention (aimed at decreasing depression and increasing social support) on reinfarction and mortality in 3000 post-MI patients at high psychosocial risk (i.e., depressed and/or socially isolated patients). Fifty percent of the patients were women. The study’s results, with respect to the main outcome, were discouraging (Writing Committee for the ENRICHD Investigators, 2003). Considering that the intervention in ENRICHD started within 2 months after the cardiac event (a condition found to be ineffective in the later metaanalysis by Linden et al., 2007), the study’s overall disappointing results may not be surprising. The unfortunate timing of the intervention may also explain the lack of benefit for women observed by Linden et al., as most of the women included in this meta-analysis were participants in ENRICHD. Regardless of the reasons for the lack of benefit for women in Linden et al.’s meta-analysis, psychological treatments may have to be gender specific to yield beneficial outcomes for both sexes. The need for gender specific interventions may be most obvious for social support. For example, social support interventions seeking to elicit support from one’s partner may be effective for men, who tend to see their spouse as their primary source of social support, but not for women, whose primary source of social support consists of friends and family members (New England Research Institutes, 1997). Consistent with this reasoning is the observation that single marital status and lack of spousal support predicted dropout from a comprehensive lifestyle change program among men with coronary artery disease (Koertge et al., 2003). Thus, soliciting social support from one’s partner may be a promising intervention strategy for men but not for women, who could even experience exacerbated stress responses, as suggested by Kirschbaum et al.’s (1995) findings. The need for gender-specific interventions also received support from a study conducted by Frasure-Smith and her colleagues. In their study aiming to reduce stress in male and female post-MI patients, significant gender differences were observed: direct advice about lifestyle changes seemed helpful for men, whereas listening to worries reduced stress in female patients (Cossette et al., 2001). Another investigation demonstrated a remarkable decrease in mortality among women with heart disease who were assigned to a stress reduction intervention specifically tailored to women (Orth-Gomér et al., 2009). Finally, considering the fact that chronic diseases are influenced by a multitude of risk factors that are interrelated, implementing interventions aimed at the reduction of one factor alone may not be the most effective treatment strategy. As suggested by the findings from the INTERHEART study,
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clinical, behavioral, and psychosocial risk factors contributed overwhelmingly to the risk of an initial acute MI. Most important, all identified risk factors are potentially modifiable. Thus, it would make sense to design interventions that target as many of these factors as possible. One intervention that targets multiple risk factors (diet, exercise, stress management, and social support) has been found to be beneficial for both women and men at various stages of heart disease and at different socioeconomic levels (for a review of this program of research, see Weidner and Kendel, 2010). In sum, interventions targeting standard health risks (e.g., traditional medical risk factors such as hypertension, dyslipidemia), unhealthy behaviors (e.g., smoking, physical inactivity, unhealthy eating patterns), and psychosocial factors (e.g., social isolation, depression, maladaptive coping styles) are likely to benefit both women and men. However, given that there are many situational differences between men’s and women’s lives, a broader perspective on gender differences in health and well-being appears to be indicated (cf Courtenay, 2009). As a consequence, the design of gender-specific interventions may be required to yield effective outcomes.
See also: Behavioral Medicine; Cardiac Disease, Coping with; Coronary Heart Disease: Psychosocial Aspects; Depression, Pessimism, and Health; Gender and Health Care; Health Care Markets: Theory and Empirical Evidence; Health Insurance: Economic and Risk Aspects; Health Interventions, Communitybased; Health-Related Support and Self-help Mutual Aid Groups; Men’s Health; Public Health as Social Science; Social Epidemiology; Social Integration, Social Networks, and Health.
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Abstract This article reviews factors that contribute to the gender gap in life expectancy, focusing on the leading cause of death, heart disease. A brief summary of gender differences in biological factors is followed by a presentation of behavioral and psychosocial contributions to women’s greater longevity, and implications for prevention and treatment are discussed.
Gender Gap in Life Expectancy Considerable gains in life expectancy have been observed for both sexes during the past decades. However, men still die about 5 years earlier than women (Murphy et al., 2013). This gender gap in life expectancy is largest when measured at birth, but shrinks with age. For example, if a man lives to 75 years of age in 2010, his life expectancy is only 1.9 years shorter than that of a woman’s of the same age (Murphy et al., 2013). This shrinking gender gap with age is because men are more likely to die at younger ages than women. In the United States, the 15 leading causes of death in 2010 were (1) heart disease, (2) cancer, (3) chronic lower respiratory diseases, (4) stroke, (5) accidents (unintentional injuries), (6) Alzheimer’s disease, (7) diabetes mellitus, (8) kidney disease, (9) influenza and pneumonia, (10) suicide, (11) septicemia, (12) chronic liver disease and cirrhosis, (13) hypertension, (14) Parkinson’s disease, and (15) pneumonitis (inflammation of the lung). These 15 causes of mortality accounted for 80.4% of all deaths in 2010 (Murphy et al., 2013). Almost all of these 15 leading causes of death show men to be at a greater risk than women. That is, the male-to-female mortality ratios (i.e., male age-adjusted death rate divided by the female age-adjusted death rate) ranged from 4.0 for suicide to 1.2 for septicemia. For heart disease, the major cause of death, the ratio was 1.5, and 1.4 for cancer, diabetes mellitus, kidney disease, and influenza/pneumonia. The only cause of death for which the ratio of male-to-female death rate was less than 1 was Alzheimer’s disease (0.8), and women were as likely as men to die from stroke and hypertension (ratios ¼ 1.0; Murphy et al., 2013). Several factors contribute to the gender gap in life expectancy. These can be grouped into three categories: biological, behavioral, and psychosocial (for more extensive coverage, see section on Gender in Whitfield et al., 2012).
Factors Contributing to the Gender Gap in Life Expectancy Biological Factors In her classic article, ‘Why Do Women Live Longer Than Men?’ Waldron concluded that “physiological differences have not been shown to make any substantial contribution to higher male death rates” (Waldron, 1976: p. 356). This conclusion has
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not changed much over the past decades (Gorman and Read, 2007; Waldron, 2005). Interestingly, international data on heart disease mortality from 46 communities in 24 countries have shown that male:female ratios vary widely, ranging from 10:1 in Iceland to 10:6 in Beijing, China (Jackson et al., 1997; also see Waldron, 2005). The fact that the differences between countries are larger than the difference between the sexes suggests that male anatomy is not destiny, at least in regard to heart disease. Additionally, the epidemic of cardiovascular diseases among young and middle-age Eastern European men has widened the gender gap in life expectancy over a very brief time span, which suggests that other than biological factors play a role in men’s greater mortality risk (Weidner, 2010; Weidner et al., 2002; Weidner and Cain, 2003).
Behavioral Factors Behavioral factors, such as smoking, excessive alcohol use, poor diet, and physical inactivity, are clearly involved in many of the major chronic diseases and causes of death worldwide (Lopez et al., 2006). For example, cigarette smoking has been linked to heart disease, lung cancer, chronic obstructive pulmonary disease, and pneumonia. Excessive alcohol consumption increases the risk for a number of diseases, foremost among them heart and liver disease. Excessive alcohol consumption, along with lack of seat belt use, also plays a major role in accidents and injuries in general. Other accidental deaths, such as homicide and suicide, often involve firearms. Overeating, unhealthy diets, and lack of exercise (associated with obesity) contribute to almost all chronic diseases, including diabetes, cancers, and strokes (Weidner, 2012). An evaluation of lifestyle practices (i.e., smoking, physical inactivity, and unhealthy eating habits) in the INTERHEART study confirms their importance for myocardial infarction (MI), collectively accounting for more than 55% of the population attributable risk (PAR) in women and men (Anand et al., 2008), that is, the reduction in incidence that would be observed if the population were unexposed to these healthdamaging lifestyle factors. Generally, men are more likely to engage in healthdamaging behaviors (e.g., smoking, unhealthy eating, excessive alcohol use) when compared to women. For example, women’s diets have a lower ratio of saturated to polyunsaturated fat and higher vitamin C content than men’s diets (Connor et al., 2002).
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The only behavioral gender difference favoring men consistently appears to be physical activity. However, this finding may be due to the use of questionnaires designed for men, which focus on sports and neglect physical activities associated with housework (Barrett-Connor, 1997). Furthermore, stress may play a greater role for health-damaging behaviors among men than among women. For example, job strain appears to be associated with increases in healthdamaging behaviors (e.g., cigarette smoking, excessive alcohol and coffee consumption, lack of exercise) among men, but not among women (Weidner et al., 1997; Weidner and Collins, 1993). Thus, considering the major behaviors involved in the leading causes of death, women appear to fare better than men.
Psychosocial Factors Systematic assessment of psychosocial factors has not always been a part of large population studies of health outcomes. Most of what we know about psychosocial contributions to physical health conditions comes from studies of heart disease, the number one cause of death in the United States, accounting for 24.2% of total deaths in 2010 (Murphy et al., 2013). Psychosocial factors such as hostility/anger, depression/vital exhaustion, lack of social support, and work stress have prospectively been linked to premature mortality from all causes and heart disease mortality in both sexes (e.g., HoltLunstad et al., 2010; Kuper et al., 2002; Orth-Gomér et al., 2010; also see Depression, Pessimism, and Health in this section). The importance of psychosocial factors for MI in both women and men has been most strongly illustrated by findings from the largest global study of MI, the INTERHEART study (Anand et al., 2008; Yusuf et al., 2004). This study compared over 15 152 cases with 14 820 sex- and agematched controls in 52 countries on all continents. Most interestingly, in addition to eight commonly assessed risk factors of heart disease (e.g., hypertension, abnormal lipids, diabetes, smoking, exercise, moderate alcohol consumption), INTERHEART also included an assessment of eating a healthy diet and a psychosocial stress index. This index consisted of depression, stress at work or at home, financial stress, major life events, and low locus of control. Together, these risk factors were significantly associated with MI in both women and men and accounted for more than 90% of the PAR in both sexes. Interestingly, the lower burden of MI among women at younger ages (<60 years) was largely explained by their lower levels of risk factors: after statistical adjustment of these factors, the gender difference in the probability of MI before the age of 60 was reduced by 80% (Anand et al., 2008). The main contributors to the increased risk among the younger men were a high prevalence of lipid abnormalities and smoking, although men did appear to benefit from their greater (moderate) alcohol consumption. Examining gender differences in the PARs across all ages revealed several differences: higher PARs in women than in men were observed for hypertension, diabetes, abdominal obesity, physical inactivity, lack of moderate alcohol intake, and the psychosocial stress index. Men’s PAR was significantly larger for smoking. In sum, findings from the INTERHEART study
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indicate that most premature MI is preventable and that interventions may benefit from targeting risk factors in a gender-specific fashion. Gender-specific associations of personality attributes (hostility/mistrust), negative emotions (particularly depression), and social support/social isolation, as well as work stress, with health and well-being are discussed elsewhere (Barefoot et al., 1995; Leifheit-Limson et al., 2010; Orth-Gomér et al., 2010; Schwarzer and Rieckmann, 2002; Weidner and Spaderna, 2013). Generally, high levels of hostility/mistrust and depression and low levels of social support are related to harmful health outcomes in both sexes. Men consistently score higher on measures of hostility/mistrust and report less social support than women, which contributes to their increased health risk. Interestingly, both of these attributes are characteristics of the male (‘macho’) gender role, which has been linked to behavioral risk factors such as smoking, excessive alcohol consumption, and lack of seat belt use (Courtenay, 2009), as well as to decreased motivation to learn stressmanagement skills (Sieverding, 2002). Additionally, women not only report more social support than men, but also have more sources of social support, thus decreasing their dependency on a single source. For example, studies of middle-aged people in Massachusetts found that men were more than twice as likely as women to name their spouse (or their partner) as their primary provider of social support (65.5 vs 26.4%). Furthermore, 24.2% of men (but only 6.1% of women) said this was their only source of support (New England Research Institutes, 1997). These data may, in part, explain why men’s health is more seriously affected by partner loss through separation, divorce, or widowhood (Miller and Wortman, 2002). In regard to negative emotions, gender differences appear to favor men. In most studies, women report more negative emotions such as depression than men (although this is not consistently found in populations where women and men have similar roles, such as college students; Nolen-Hoeksema and Girgus, 1994). Although women may report more depression, they may be coping more effectively than men. Generally, men are more likely to use avoidant-coping strategies, such as denial and distraction, whereas women are more likely to use vigilant-coping strategies, paying attention to the stressor and its psychological and somatic consequences (Weidner and Collins, 1993). Which style is more adaptive depends largely on the situation. Most stressful experiences consist of uncontrollable daily hassles, which are short-lived and typically of no great consequence. Here avoidant strategies would be more adaptive (“what I cannot control and what can’t hurt me is best ignored”). Thus, men’s strategies are likely to pay off for these types of events, contributing to their lesser experience (or report) of emotional discomfort or distress. But what if disaster hits? How do people cope with uncontrollable events requiring long-term adaptation, such as divorce, loss of a loved one, job loss, and sudden financial crisis and economic uncertainty? Here it may be women’s greater vigilance that is more adaptive, such as preparing for the crisis, and seeking help and advice. Consistent with this reasoning are data from the Hungarian population that showed that women tended to accept their negative mood as a disorder to be treated, whereas
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men were more likely to engage in self-destructive behavior, such as excessive alcohol consumption (Réthelyi et al., 2002). Similarly, research on how people cope with disasters (e.g., hurricanes and tornadoes) has supported the notion of men’s maladaptive coping: Increases in alcohol consumption and depression were related to personal disaster exposure among men, whereas no such direct relationship was evident among women (Solomon, 2002; Solomon et al., 1987). Furthermore, socioeconomic deprivation appears to be more closely related to depression in men than in women (Kopp et al., 2002). Thus, men’s psychosocial risk factor profile appears to further enhance their risk for ill health.
Implications for Prevention and Treatment Gender differences in behavioral and psychosocial lifestyle factors are likely contributors to the gender gap in several major causes of death. In regard to prevention, several large studies have now demonstrated significant health benefits to adopting a healthy lifestyle (e.g., a combination of a prudent diet, regular exercise, maintaining healthy body weight, and not smoking) for both women and men (Chiuve et al., 2006; King et al., 2007; Knoops et al., 2004). However, analyses of data from a community study of 15 708 middle-aged adults found that only 8.5% practiced healthy lifestyles (King et al., 2007). Although the percentage of women following healthy lifestyle practices was significantly larger than that of men, the low overall percentage is disconcerting. During a 4-year follow-up, 8.4% of participants newly adopted a healthy lifestyle (i.e., diets high in fruits and vegetables, regular exercise, maintaining a healthy body weight, and not smoking), and experienced a rather prompt benefit: mortality and cardiovascular disease risk were significantly reduced (40 and 35%, respectively) compared to participants with less healthy lifestyles (King et al., 2007). The authors also noted that men in general, African-Americans, and individuals with lower socioeconomic status were less likely to adopt a healthy lifestyle. Although this study clearly demonstrates the benefits of adopting a healthy lifestyle, it also illustrates the problems associated with behavior change in primary prevention. Overall, efforts to reduce risk factors (via educational methods) in the general population have been disappointing. In their review of 39 trials, Ebrahim et al. (2006) conclude that “different approaches to behavior change are needed . the availability of healthier foods and better access to recreational and sporting facilities may have greater impact on dietary and exercise patterns . than health professional advice” (p. 2; also see Weidner and Kendel, 2010). In contrast, attempts to change lifestyle behaviors in secondary and tertiary prevention trials (i.e., in people at high risk for disease and patients with the disease) have been more successful (Weidner and Kendel, 2010), but not without problems, especially in regard to overcoming barriers to participation. For example, the low utilization of cardiac rehabilitation by eligible patients has been attributed to several factors, including female gender (due to referral bias), medical insurance coverage, education, and ease of access to rehabilitation (Jackson et al., 2004).
In regard to psychosocial interventions, a meta-analysis of psychological treatment studies with heart disease patients concludes that psychological treatment is effective in reducing 2-year mortality by 27% (Linden et al., 2007). However, mortality was not reduced for women, for patients who perceived no reductions in stress, and for those whose treatment started right after the cardiac event (<2 months). Interestingly, the majority of women included in this meta-analysis were enrolled in the Enhancing Recovery in Coronary Heart Disease (ENRICHD) study. This study was a major multicenter, randomized clinical trial that tested the effects of a psychosocial intervention (aimed at decreasing depression and increasing social support) on reinfarction and mortality in 3000 post-MI patients at high psychosocial risk (i.e., depressed and/or socially isolated patients). Fifty percent of the patients were women. The study’s results, with respect to the main outcome, were discouraging (Writing Committee for the ENRICHD Investigators, 2003). Considering that the intervention in ENRICHD started within 2 months after the cardiac event (a condition found to be ineffective in the later metaanalysis by Linden et al., 2007), the study’s overall disappointing results may not be surprising. The unfortunate timing of the intervention may also explain the lack of benefit for women observed by Linden et al., as most of the women included in this meta-analysis were participants in ENRICHD. Regardless of the reasons for the lack of benefit for women in Linden et al.’s meta-analysis, psychological treatments may have to be gender specific to yield beneficial outcomes for both sexes. The need for gender specific interventions may be most obvious for social support. For example, social support interventions seeking to elicit support from one’s partner may be effective for men, who tend to see their spouse as their primary source of social support, but not for women, whose primary source of social support consists of friends and family members (New England Research Institutes, 1997). Consistent with this reasoning is the observation that single marital status and lack of spousal support predicted dropout from a comprehensive lifestyle change program among men with coronary artery disease (Koertge et al., 2003). Thus, soliciting social support from one’s partner may be a promising intervention strategy for men but not for women, who could even experience exacerbated stress responses, as suggested by Kirschbaum et al.’s (1995) findings. The need for gender-specific interventions also received support from a study conducted by Frasure-Smith and her colleagues. In their study aiming to reduce stress in male and female post-MI patients, significant gender differences were observed: direct advice about lifestyle changes seemed helpful for men, whereas listening to worries reduced stress in female patients (Cossette et al., 2001). Another investigation demonstrated a remarkable decrease in mortality among women with heart disease who were assigned to a stress reduction intervention specifically tailored to women (Orth-Gomér et al., 2009). Finally, considering the fact that chronic diseases are influenced by a multitude of risk factors that are interrelated, implementing interventions aimed at the reduction of one factor alone may not be the most effective treatment strategy. As suggested by the findings from the INTERHEART study,
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clinical, behavioral, and psychosocial risk factors contributed overwhelmingly to the risk of an initial acute MI. Most important, all identified risk factors are potentially modifiable. Thus, it would make sense to design interventions that target as many of these factors as possible. One intervention that targets multiple risk factors (diet, exercise, stress management, and social support) has been found to be beneficial for both women and men at various stages of heart disease and at different socioeconomic levels (for a review of this program of research, see Weidner and Kendel, 2010). In sum, interventions targeting standard health risks (e.g., traditional medical risk factors such as hypertension, dyslipidemia), unhealthy behaviors (e.g., smoking, physical inactivity, unhealthy eating patterns), and psychosocial factors (e.g., social isolation, depression, maladaptive coping styles) are likely to benefit both women and men. However, given that there are many situational differences between men’s and women’s lives, a broader perspective on gender differences in health and well-being appears to be indicated (cf Courtenay, 2009). As a consequence, the design of gender-specific interventions may be required to yield effective outcomes.
See also: Behavioral Medicine; Cardiac Disease, Coping with; Coronary Heart Disease: Psychosocial Aspects; Depression, Pessimism, and Health; Gender and Health Care; Health Care Markets: Theory and Empirical Evidence; Health Insurance: Economic and Risk Aspects; Health Interventions, Communitybased; Health-Related Support and Self-help Mutual Aid Groups; Men’s Health; Public Health as Social Science; Social Epidemiology; Social Integration, Social Networks, and Health.
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