Sociological differences between women and men: Implications for autoimmunity

Autoimmunity Reviews 11 (2012) A413–A421

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Review

Sociological differences between women and men: Implications for autoimmunity Andrea T. Borchers, M. Eric Gershwin ⁎ Division of Rheumatology, Allergy and Clinical Immunology, University of California at Davis School of Medicine, Davis, CA 95616, United States

a r t i c l e

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Available online 3 December 2011

a b s t r a c t There are an enormous number of incorrect stereotypes that characterize the differences between women and men. Indeed, nearly all of these stereotypes are based on cultural inaccuracies and faulty data without consideration of biology and the distinct sociological differences between genders. Sociological differences are those that relate to the development, structure, interaction and behavior of organized groups of human beings, or societies, and their values and beliefs. Gender is a social construct referring “to the culturally and historically based differences in the roles, attitudes and behaviors of men and women” ([1], p.1) as shaped by norms and stereotypes. Sex, on the other hand, serves to classify living things according to their reproductive organs and functions assigned by chromosomal complement (according to the US Institute of Medicine) and the physical and biological characteristics arising from these organs and functions. The two terms are generally viewed as dichotomous; however, they are closely intertwined in as yet hardly understood ways, and it is frequently difficult to distinguish between them since gendered life experiences can have profound effects on body structure and function [2]. In this review, we will examine to what extent gender roles and stereotypes shape the daily lives of women in their roles as students, employees, wives, and mothers and their health. These data have implications for the etiology of autoimmunity and also for differences in the natural history of disease. © 2011 Elsevier B.V. All rights reserved.

Contents 1. Fallacy #1: Men are smarter than women 2. Fallacy #2. Women work less than men . 3. Women earn less than men . . . . . . . 4. Occupational gender segregation . . . . 5. Motherhood penalty . . . . . . . . . . 6. Women are poorer than men . . . . . . 7. Male to female differences in health . . . 8. Disability . . . . . . . . . . . . . . . 9. Life expectancy . . . . . . . . . . . . 10. Health care utilization rate . . . . . . . 11. Conclusions . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . .

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1. Fallacy #1: Men are smarter than women When some of the first female students were attending medical school in Germany, a famous male professor lectured on the larger

⁎ Corresponding author at: Division of Rheumatology, Allergy and Clinical Immunology, University of California at Davis School of Medicine, 451 Health Sciences Drive, Suite 6510, Davis, CA 95616, United States. Tel.: +1 530 752 2884; fax: +1 530 752 4669. E-mail address: [email protected] (M.E. Gershwin). 1568-9972/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.autrev.2011.11.016

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size of the male compared to the female brain and asked: “And what do we conclude from that?” One of the female students promptly answered: “That quality, not quantity, matters.” Subsequently, study after study indeed showed only minimal differences in overall intelligence between males and females. This was considered a paradox since male brains are on average 10% larger than female brains (as recently confirmed by a MRI study [3]); and brain size had been found to correlate with intelligence (actually the correlations have ranged from 0 to 0.6, with a recent study of children and adolescents finding a correlation coefficient of 0.22) [4].

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In 1994, Richard Lynn resolved this paradox [5]. He reanalyzed data from a variety of studies using different hierarchical models for determining IQ and consistently found a male advantage for general intelligence of approximately 3.8 IQ points [5]. This observed difference was equal to the expected difference of 4 IQ points (male brain size advantage = 0.78 standard deviation units, correlation between brain size and IQ = 0.35; 0.78 × 0.35 = 0.27 SD units, which in turn equal 4 IQ points). This close agreement between the expected and observed difference in IQ points proved beyond a doubt that males were more intelligent than females and that this was due to biological, not sociological, differences, i.e., their larger brain size. The difference in IQ between males and females is not evident until late adolescence. Lynn argues this is because girls mature faster and reach adult brain size faster. Actually recent MRI studies of brain volume in children and adolescents show that boys have larger brain volumes (by ~ 10%) even at the youngest ages examined [3,6]. In addition, the difference in total brain volume remained quite constant with age (although both white matter and grey matter underwent highly dynamic changes over time, and the magnitude of these changes differed between males and females). One of the most consistent male–female differences on intelligence tests is the better performance of males on tasks measuring visuo-spatial ability, with the largest differences seen on mental rotation tasks. (Again, the male advantage does not become pronounced until late adolescence.) Females generally outperform males on measures of verbal intelligence. Now, if quantity really matters more than quality, why would males not have higher scores on all measures of intelligence? Lynn hypothesizes that the space constraint in female brains necessitates taking over part of the right cerebral hemisphere in addition to the left hemisphere for verbal abilities, which shrinks the area usually available for spatial and mechanical abilities [5]. This does not explain, however, why females would need such terrific verbal skills as to devote a major portion of their brains to it – to the detriment of spatial abilities that seem to be so important for males. There are several hypotheses at least to explain why spatial abilities are vital for males. As Elaine Morgan so aptly summarizes ([7], p.11): “… despite all the new evidence recently brought to light, the generally accepted picture of human evolution has changed very little. Smack in the centre of it remains the Tarzanlike figure of the prehominid male who came down from the trees, saw a grassland teeming with game, picked up a weapon, and became the Mighty Hunter. Almost everything about us is held to have derived from this. If we walk erect, it was because the Mighty Hunter had to stand tall to scan the distance for prey. If we lived in caves if was because hunters need a base to come home to. If we learned to speak it was because hunters need to plan the next safari and boast about the last.” While this makes it even more mysterious why females developed stronger verbal skills, the need for hunting prowess is thought to explain why men developed greater spatial abilities than females. (Dare we ask why women needed fewer spatial skills for their gathering activities, making pottery and weaving baskets than men did for waiting for prey at waterholes and fashioning weapons? [8]). There is also the possibility that men need spatial abilities in order to do what bonobos do, namely “to search high and low, risking life and limb, to find sex” — as Robert Wright puts it in “The Moral Animal”([9], p.51). However, humans live in social groups; therefore, when trying to impregnate females, charm or stealth are probably more useful than “the ability to find one's way around a cluster of huts” ([8], p.4). It has also been hypothesized that prenatal testosterone is responsible for differences in brain organization such that sex differences in “systemizing,” i.e. the ability to understand objects and mechanical

properties, and “empathizing” are hardwired. While the evidence for an effect of prenatal testosterone on brain organization is relatively good in zebra finches and rats, it is less than convincing in humans ([10], p.101). And the one study [11] that is cited everywhere in popular discussions as demonstrating this very sex difference in newborns has numerous methodological flaws, including the use of the principal investigators face as the “social stimulus” and her awareness of the infants sex in at least some instances (among many others, as thoroughly discussed in [12,13] and [10], pp.112–115). Most importantly, no other study has been able to demonstrate that the understanding of objects and their mechanical relations is better developed in boys compared to girls, as would be expected if male infants truly had a natural predisposition towards systemizing. On the contrary, girls acquire some of these abilities somewhat earlier than boys [12]. Few researchers consider the potential influence of differences in socialization, i.e., that boys still get to play with transportation vehicles and construction materials much more often than girls do and that such toys enhance spatial skills [13]. This seems important, however, since there are indications that females may simply need a bit of practice in order to perform as well as males on mental rotation tasks [14]. In all fairness, however, it should be mentioned that extended training benefitted both males and females and that full convergence of the male and female performance on spatial tasks may be difficult to achieve. Nonetheless the improvement with practice is greater than the typical differences between men and women [15]. Perhaps more importantly, it is often sufficient to tell women that a specific test has been administered to numerous groups without ever showing a performance difference between men and women in order to improve their performance to the point where it equals or even surpasses that of men [16]. Even on mental rotation tasks, a domain where males quite consistently outperform females under standard test conditions, women obtain scores very similar to, or even slightly higher than, those of men when told that previous tests had shown that women performed better than men [17] or when the spatial nature of the test is de-emphasized [18]. This provides evidence for the existence of “stereotype threat.” According to the stereotype threat theory, the fear of confirming a negative stereotype about the cognitive abilities of one's group (e.g., minorities, women, etc.) can significantly impair the performance of group members in test-taking situations. In other words, gender stereotypes become self-fulfilling prophecies. The triggers of stereotype threat and poor performance in women can be as subtle as having to mark “female” on the cover sheet of a test, filling out a brief questionnaire that makes gender salient, or looking around and finding that there are more men than women taking the test. Conversely, members of a non-stereotyped group may perform better when told that an out-group is negatively stereotyped in the tested domain, i.e., may experience stereotype lift. A related concept, stereotype susceptibility, refers to the performance boost resulting from the activation of an in-group positive stereotype, i.e., reminding group members that they are stereotypically thought to perform better than a comparison group. This is thought to be mediated by boosting self-esteem. There are indications that men do not suffer from a lack of self-esteem, but rather tend to overestimate their own performance, while women underestimate theirs [15,19]. Only time will tell, whether the differences in IQ and particularly in spatial ability between men and women can ever be completely overcome. It is abundantly clear, however, that women (and other stereotyped groups) do not get the chance to live up to their full potential, but instead are held back by gendered and other role norms and stereotypes. 2. Fallacy #2. Women work less than men One of the most dramatic changes in recent decades has been the massive influx of women into the labor market in essentially all

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industrialized countries (See Fig. 1 for U.S. data). Conversely, the labor force participation rates of men have been declining gradually ever since the 1950's (see Fig. 1 and Table 1 for changes since 1970). Of particular note, in the U.S. the labor force participation rate of women with at least one child b 18 years of age is higher than the national average (70% vs. 59.5), whereas 60% of women with at least one child b6 years of age were employed in 2008. Similarly, 72.9% of Canadian women with children b16 years and living at home were employed in 2009, while the national average was 62.5%. Somewhat more detailed data are available from Europe, where the proportion of women aged 25–54 who are employed decreases with each additional child (the 2009 figures are: 75.8% for women without children, 71.3% for women with 1 child, 69.2% with two children and 54.7% with three or more children) [20]. In marked contrast, the employment rate of men increases with each child, although the rate is somewhat lower for fathers of 3 or more children compared to fathers with 1 or 2 children, but still higher compared to men without children (80.3% without a child, 87.4% with 1 child, 90.6% with 2 children, 85.4% with ≥3 children). Women also work part-time much more frequently than men do (see Table 2). In Canada, the reasons women give for their part-time employment differ between age groups, with the need to care for children being cited by about 1/3 of women aged 25–44 years, but going to school in more than 70% of younger women and personal preference in almost 2/3 of women > 45 years [21]. An analysis of data from participants of the Luxembourg Income Study indicated that, after controlling for age, education, partnered status, and other household income, the effect of children on mothers’ employment hours varied considerably across countries from essentially no effect in Russia to a reduction of 4.4 h per child in Germany [22]. These cross-country differences are at least in part due to variations in family policies like maternity leave, paternity leave, parental leave and availability of publicly funded or state-supported child care facilities. In addition to being in the labor force more frequently, men work more hours on their jobs compared to women. For example, in the US, men put in an average of 7.9 h of paid work on the days they worked compared to 5.5 h for women in 2010 [25]. This is largely due to the higher frequency of part-time work among women. However, even when comparing full-time (≥35 h per week) workers, men worked 8.2 h, women only 7.8 h. Similarly, employed Canadian men spent 8.5 h per day on paid work, compared to 7.5 h for women [26]. On the other hand, domestic work, including housework and childcare, remains predominantly the responsibility of women (see Table 3). On an average day in the US in 2010, 84% of women and 67% of men spent some time on household activities, with only 20% of men but 49% of women doing some cleaning or laundry [25]. In the overall

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Table 1 Labor force participation rates for the U.S. and select countries 1970–2010 (adjusted to U.S. concepts [23]). Country United States Canada Australia Germany France Italy The Netherlands Sweden United Kingdom Japan

Men Women Men Women Men Women Men Women Men Women Men Women Men Women Men Women Men Women Men Women

1970

1980

1990

2000

2010

79.7 43.3 77.8 38.3 84.1 40.4 78.8 38.4 77.5 39.8 73.7 26.4 – – 78.5 50.0 – – 81.5 48.7

77.4 51.5 79.5 51.0 79.1 45.5 71.2 40.3 72.0 44.1 67.9 30.1 77.4 34.3 74.9 59.3 78.5 48.6 79.1 46.6

76.4 57.5 76.6 58.5 76.4 53.0 68.5 43.1 67.7 48.1 63.0 32.7 70.4 44.2 72.0 63.0 75.7 54.0 76.7 49.3

74.8 59.9 72.8 59.5 73.1 55.8 65.6 48.4 64.3 50.1 60.7 36.6 72.6 53.8 68.5 59.2 71.1 55.2 75.5 48.7

71.2 58.6 71.8 62.4 73.2 59.8 65.1 51.6 61.9 51.7 59.1 38.3 69.9 58.8 69.1 60.4 69.9 56.8 70.8 48.1

– = not available.

population of employed men and women in 29 European countries in 2005, women aged 25–39 years reported doing three times as much unpaid work as men [27]. In dual-earner couples with children below the age of 6 years, women spent about twice as much time on domestic work compared to men, and when women's paid and unpaid work was added up, women had a longer total work week than men in 9 of 14 European countries [27]. That is not the case in the U.S. and Canada, where the total workday of men and women is about equal, although it remains true that women do at least 50% more of the housework in dual-employed households with at least one child [23,26]. Interestingly, as wives personal income rises, her hours of paid work increase, while her share of housework decreases [26,28]. If a Canadian woman earns more than $100,000, she and her partner share the housework equally; in stark contrast, his earning more than $100,000 drives up her share of housework [26]. Since one would expect that in a partnership of equals earnings would be pooled and then redistributed for the maximum benefit of each of the partners and the entire household, this finding only underscores the gender segregation of domestic work [28]. Of note, the contribution of men to household activities and childcare has increased in recent decades [26,27,29]. This resulted in a narrowing of the gender gap in time spent on domestic work. However,

Fig. 1. Trends in Labor Force Participation Rates for Men and Women in the U.S. 1950–2010. Note that the participation for women peaked at 60% in 1999. (Source {Bureau of Labor Statistics, 2008 #223}).

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Table 2 Part-time work among men and women (part-time refers to work b30 h/week). Country

U.S. Canada Australia New Zealand Denmark Germany France The Netherlands Sweden United Kingdom Japan OECD (weighted average)

Total incidence of part-time employment

Women's share in part-time employment

13.5 19.4 24.9 21.9 19.5 21.7 13.6 37.1 14.0 24.6 20.3 16.6

66.9 67.3 70.4 72.0 63.2 80.4 78.1 75.0 63.3 66.9 70.3 70.0

Part-time employment as percentage of total employment Women

Men

18.4 27.4 38.6 33.8 25.9 37.9 22.3 60.6 18.8 39.4 33.9 26.3

8.8 12.1 13.5 11.5 13.6 7.9 5.7 17.2 9.7 11.6 10.4 8.9

Data source: OECD [24], p.253.

another important component of this narrowing at least during the 1970s and 1980s was the reduction in the time women spent on domestic work, which was greater than the increase in men's share [29]. Importantly, the routine household chores – those that traditionally have been considered to be feminine tasks, like cooking, cleaning, and doing the laundry – are still done predominantly by women, whereas men tackle mostly the less routine “masculine” tasks like mowing the lawn or repairing things around the house or the car. In addition, while men contribute more time to childcare than they did in the 1960s, the responsibility (emotional, moral and social) for children still rests with the mother [30].

3. Women earn less than men Even though most industrialized countries have had equal-payfor-equal-work laws in place for decades, the famous gender gap in pay persists, although it narrowed substantially between the 1970s and 1990s, after which it remained stable in most countries or actually widened again (see Table 4). Its magnitude very much depends on the type of earnings considered. The gap is greatest when calculated on the basis of weekly (monthly or yearly) earnings regardless of the number of hours worked because women work part-time so much more frequently. It is much smaller when expressed as a percentage of hourly wages, but varies depending on whether the mean or median earnings are used and whether earnings are reported before or after taxes. For example, in Australia in 2004, average weekly total earnings of females amounted to 68% of the average weekly male earnings. When hourly wages of full-time non-managerial employees were compared, female earnings amounted to 92% of male

Table 4 Gender pay gap. Country

OECD data

U.S. Canada Australia U.K. Germany Denmark France Sweden Japan Korea Italy New Zealand Norway

1999 23 24 19 25 23 15 9 17 35 41 8 8 10

European Union data 2009 20 20 23 20 22 12 13 15 28 39 12 8 9

2009

20.4 23.2 16.8 16.5 16

5.5

The OECD data refer to the unadjusted gender wage gap, calculated as the difference between median earnings of men and women relative to median earnings of men [24] (emphasis added). The EU data (available at Eurostat, epp.eurostat.ec.europa.eu) represent the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees (emphasis added).

earnings. The gender pay gap also depends on whether the focus of analysis is the whole work force or only segments of it. For example, when only new entrants into the labor market are considered, the gender wage gap is smaller than the overall average, whereas it is more pronounced in blue collar jobs [31]. The gender gap in pay is largely due to the persistence of a system that requires, and most highly rewards, continuous employment and long hours of work. Such continuity may not be possible for women who have children. Because the roles of spouse, mother, and caregiver put higher demands on their time and energy, women may have to exit the work force at least temporarily and may not be willing or able to work such long hours when they return to paid labor. They also may not be given the opportunity because the – predominantly male – managers still frequently assume that men, the breadwinner, need the money of extra work hours more than women do, since the stereotype persists that women work for pin money [32]. The specific factors accounting for much of the hourly wage differential between male and female full-time employees include education and field of study, occupational segregation, the “motherhood penalty,” and discrimination. The size of the contribution of each of these factors varies considerably between countries. For example, women in many countries have lower levels of educational attainment and training than men do. In contrast, in the U.S. and other OECD countries, differences in educational attainment do not contribute greatly to the earnings differential, at least in younger age groups. In almost all OECD countries, the majority of university graduates are now female, although they still represent a minority

Table 3 Division of Housework and Childcare in the U.S. Household activities + shopping (hours)

Childcare (h)

Age of youngest child

Employed Female Male F/M Not employed Female Male F/M

b6 years

6–17 years

None b18 years

b6 years

6–17 years

1.77 + 0.45 = 2.22 1.12 + 0.28 = 1.4 1.59

2.14 + 0.48 = 2.62 1.29 + 0.28 = 1.57 1.67

1.68 + 0.41 = 2.09 1.26 + 0.30 = 1.56 1.34

1.79 1.12 1.6

0.66 0.41 1.61

3.00 + 0.53 = 3.53 2.17 + 0.50 = 2.67 1.32

2.91 + 0.52 = 3.43 1.87 + 0.27 = 2.14 1.6

2.74 + 0.43 = 3.17 2.01 + 0.33 = 2.34 1.35

2.84 1.43 1.99

1.05 0.4 2.6

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in mathematics, computing, and engineering. However, women's share of doctorate degrees is generally below 50%. One exception is the U.S., where 52% of all doctorates and a similar proportion of professional degrees were conferred to women in 2008/9; the percentage of degrees conferred to females was even higher for black African-American and Hispanic women compared to white women [33]. There is considerable evidence that college major or field of study has a substantial influence on the gender pay gap [34–36]. In particular, some of the highest-paying occupations are in science and engineering, and women are markedly underrepresented in these fields. The underlying reasons are manifold and likely to include aspects of socialization that induce girls and women themselves, as well as their teachers and parents, to underestimate their mathematical and scientific abilities; preferences for working with people rather than things; the fear of discrimination; and, of course, intrinsic lack of ability [34,36]. There is evidence that visuo-spatial ability and mechanical reasoning, domains in which males consistently perform better than females, are relevant to performance in science and engineering [8]. And we already know how deficient women are in that area. Then there is the theory, pronounced with greatest media fanfares by Lawrence Summers, then president of Harvard, that there is higher variability in the IQ distribution of males compared to females, resulting in more males in the upper ranges and, ultimately, their dominance in science and engineering jobs. The evidence supporting this differential distribution is mixed, however [12]. 4. Occupational gender segregation There is substantial occupational gender segregation, with women frequently working in what have been called the “five C's” — caring, cashiering, catering, clerical, and cleaning, whereas men are much more likely to work in occupations like engineering, construction, or computing. To give a concrete example, in the UK in 2001, women's share of the workforce was 84% in personal services, 78% in administration and secretarial work, and 71% in sales and customer service. In many instances, such “female-type” jobs pay considerably less than typically male-dominated. In the UK, for each 10% increase in the proportion of men in an occupation, the wages increase by 1.3%. Occupational segregation makes the greatest contribution to the portion of the gender pay gap that can be explained by statistical models [35]. In addition to this horizontal segregation, there is vertical segregation (or the “glass ceiling”), i.e., barriers to the advancement of qualified women into managerial positions. On the other hand, the few men entering female-dominated occupations, such as nursing or teaching take the glass elevator, i.e., are pressured into quick advancement up the career ladder. The root causes of horizontal and vertical gender segregation are largely the same as those underlying the gender pay gap in general and the gap arising in the form of the motherhood penalty in particular, which will be discussed next. 5. Motherhood penalty In the U.S., the gender pay gap now seems to be essentially a matter of “mother versus other”. Even after controlling for a variety of job characteristics and for job experience (which decreases when women take time off after the birth of a child), the wage penalty was found to be 5% for one child, 11% for two children, and 15% for three or more children [37]. However, the impact of children on women's earnings varies considerably across countries and by educational attainment and life cycle [22,36]. For example, a direct comparison revealed that besides the U.S. a variety of other countries showed significant motherhood penalties, whereas there was no significant penalty in some countries, including Australia, Finland and Sweden [22]. This is because several state family policy factors can influence the magnitude of the childhood penalty both in paid working hours and

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earnings. These include paid maternity leave, paternity leave, parental leave (longer leaves that enable parents to take care of young children in the home), and availability of publicly funded or statesubsidized childcare facilities. On the other hand, some of the very policies that are meant to support women's attachment to the labor force after giving birth to a child may actually enforce segregation [38]. Nonetheless, countries with more progressive family policies frequently exhibit lower gender wage gaps compared to countries with less generous welfare policies. There are indications that this is due to the simultaneous presence of greater wage compression (i.e., smaller disparities between the high and the low end of the wage scale) mainly because of greater unionization and more encompassing collective bargaining agreements [39]. Two main theories have been developed to explain the motherhood penalty and the gender pay gap arising from it: the theory of compensating differentials and the human capital theory. According to the theory of compensating differentials, men and women have different preferences for certain work conditions, with women opting for safe, agreeable, people-oriented, and – above all – family-friendly work environments with enough flexibility to allow them to combine the demands of family and paid work. It is assumed that women are willing to trade these job characteristics for lower pay, although that may be a necessary evil rather than a conscious choice they make. Family-friendly job characteristics do constitute a part of the motherhood wage penalty [37]. However, there is a slight problem when trying to explain the motherhood penalty with women's preference for flexible work hours: both in the U.S. and Europe, men are more likely to enjoy flexible working time arrangement, the ability to vary their work schedule, and “banking” working hours to take time off later [36,40] Proponents of the human capital explanation have hypothesized that women invest less in their education and training knowing that they will eventually drop out of the labor market. At least as far as formal education is concerned, this no longer seems to be the case. However, women often leave the labor force temporarily in order to have a child, or they become part-time workers in order to combine child rearing and employment. This also results in a reduction of human capital in the form of lost job experience and seniority and, at least in some fields, deterioration of their work skills. It has indeed been shown that reduced work experience explains a considerable portion of the motherhood wage penalty [37]. It is also possible that mothers become less productive because of the distractions and time demands of caring for a child. Finally, the motherhood penalty may be due to outright discrimination, which most likely stems from stereotype-based expectations that mothers are less committed, less productive because they are torn between their roles as mother and employee, and characterized by more absenteeism and tardiness. After all, a good mother is expected to be always there for her children; the ideal worker is expected to be always available to his or her employer such that face time is actually more important in the rating of an employee than actual performance or productivity [41]. When college undergraduates were asked to evaluate essentially identical job applicants who differed only in parental status, they perceived women with children as less committed, less competent and less promotable compared to women without children [42,43]. In contrast, fathers were judged to be equally competent and more committed compared to non-fathers. If the college students suggested mothers for hiring at all, which they did far less frequently compared to the nearly identical applicant who had no children, they held them to higher standards, whereas there were no gender differences in the standards for non-parents. In addition, they were willing to pay mothers substantially less starting salary. Audit data also showed that real-world employers discriminated against mothers (asked them for an interview significantly less frequently than equally qualified nonparent applicants) [42]. Fathers were called back more often than non-fathers, but the difference was not statistically significant.

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Several lines of evidence strongly suggest that discrimination not only explains part of the motherhood penalty, but also underlies the overall gender pay gap [36]. Studies in a variety of occupations show that the pay disparity between men and women is greater than the productivity difference. Regression analyses of the gender pay gap with extensive controls for human capital, working conditions, children, housework, productivity and a variety of other factors consistently yield an unexplained residual. In addition, there continues to be considerable sex discrimination litigation despite the fact that such law suits cost firms more than the simple cost of settling the dispute. Together his strongly suggests that discrimination accounts for much of these unexplained residuals [36].

6. Women are poorer than men Different states, in particular the U.S., use varying definitions of poverty. However, regardless of the definition used, women almost always have higher poverty rates compared to men. An analysis of data from the 1995 wave of the Luxembourg Income Study, which employs the same data collection for each of the participating states, indicated that overall poverty rates ranged from 3% in Sweden to 11% and 12% in the U.S. and Canada, respectively, when poverty was defined in relative terms as having a disposable income below 50% of the median for households in the nation [44]. In all countries except Sweden, females had higher poverty rates than males, and the highest levels of poverty were found for single mothers (ranging from b5% in Sweden to 40.5% in Canada and 47% in the U.S.). For comparison, the corresponding rates for single fathers were 17% in Canada and 22% in the U.S. Of note, in the U.S. poverty rates are higher among African Americans and Hispanics (24.5% and 21.5% compared to 8.2% for European Americans in 2007). African American and Hispanic women are more likely to be poor compared to their male counterparts (26.5% vs. 22.3% for African-American women and men and 23.6% vs. 19.6% for Hispanic women and men, respectively) [45]. It is important to underscore that poverty is measured at the household level in almost all relevant statistics [44]. Therefore, if all adults lived in households containing a person of the other sex, the poverty rates for men and women would be the same. The existence of a gender gap in poverty indicates that single women are poorer than single men. This has several reasons. Single women have children living in their households far more frequently than men do (see Table 5). This means that they have higher expenses compared to singles without children, but lack the security of a second income that could provide some protection in case of lay-offs or sickness. In addition, women in general have more intermittent work force participation patterns, work part-time more frequently and, even if

Table 5 Single-parent households — their share of all households, of all households with children, and the proportion of single-mother households. Country

Year Sole-parent families as % Of those: Sole-parent Sole-mother families as % of of all households with households all households children

U.S. Canada Australia New Zealand Denmark Finland France Germany The Netherlands Norway U.K.

9.2 15.7 5.8 9.3 5.1 7.6 8 5.9 5.8 8.6 9.8

Data source: OECD; – = not available.

28.3 23.2 16 22 18.2 23 19.7 18.1 15.9 21.8 26.4

77.5 80.1 87 – 85.1 84.9 85.3 15.5 84.5 82 86.7

2000 2006 2006 2006 2001 2000 1999 – 2001 2001 2001

they work full-time earn less money than men do. For the same reasons, women accrue fewer retirement benefits compared to men and, as a result, poverty often becomes more pronounced during retirement. The Institute for Women's Policy Research reported that 11% of women aged 65–74 and 14% of those 75 and older lived below the poverty threshold in the US in 2000, compared to only 7% of men in both of these age groups [46]. Among unmarried women (widowed, divorced, separated or never married), the rate rose to ~20%. Mexican American and African American women faced even higher risks of poverty than women of European descent, with poverty rates of ≥45% in those aged ≥65 years. In both men and women, social security benefits constituted the major portion of retirement income, but in women they were frequently the only source, yet amounted to only 70% of the benefits of males of the same age, whereas older men more frequently also received pensions and/or still had earned income. Government transfers and tax benefits all influence the poverty rate of single women and a combination of income transfer policies and measures to enable the labor force participation of single women with children can greatly reduce or even eliminate the gender poverty gap [47]. 7. Male to female differences in health Into the 1990s, the reigning paradigm was that females suffered from excess morbidity and that women consistently reported poorer health than men. A somewhat more differentiated picture has emerged since then, showing that the direction and magnitude of male–female differences in health depend on the phase of the life cycle and the conditions examined [48,49]. Nonetheless, certain conditions and symptoms are significantly more frequent among adult women of essentially all ages compared to men, including migraine, chronic pain, arthritis, and depression (e.g., [48–51]). There are no complaints that are consistently more frequent among men with the exception of heart disease, which is reported more often by men past the age of 45 or 50 years compared to women of the sage age [48,49]. The female excess in chronic pain is partially explained by the higher prevalence of chronic conditions, and income and education account for the remainder [51]. But what explains the higher frequency of chronic conditions in women? The difference could result from differential symptom perception and reporting of men and women, could be biological (which is not the topic of this review), or could relate to socio-cultural aspects of men's and women's lives. It remains somewhat uncertain to what extent men and women perceive and report their symptoms differently, but the majority of studies do not reveal major dissimilarities. Socioeconomic disparities between men and women clearly play a role, but do not fully explain gender differences, particularly among ethnic minorities [52]. Recent attention has focused on the possible role of chronic (or daily life) stressors in the gender health gap. In particular, it has been hypothesized that the multiple roles of women (e.g., as employee, spouse, and perhaps also mother) may increase their stress levels and damage their health. Compared to men, women report more daily stressors and more frequent distress, mainly associated with home and family overload, whereas men report more stress from work- and finance-related stress [53,54]. Work-family conflict, i.e., the interference of work with family life or vice versa, is another potential cause of health problems [55]. While it affects men and women with about equal frequency, it may have differential effects on distress and physiological symptoms in men and women [56]. As is a common finding for employed men, employed women report being in good health more frequently than non-employed women [48,57,58]. This appears to be largely mediated by socioeconomic factors such as income and education [58]. Married or partnered women with children enjoy the best health and report the lowest prevalence of chronic conditions despite experiencing higher

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levels of chronic stress compared to married women without children [57,58]. In contrast, sole mothers report the poorest health and the highest frequency of chronic conditions, and this is only partially explained by socioeconomic factors [57–59]. Financial and social life stressors and worries about children emerged as important determinants of reporting long-standing health conditions [57]. Note that sole fathers also reported less than good health more frequently compared to couple mothers and fathers, and one was of the main mediators was financial stress [59]. The multiple role stress model cannot account for the findings that employed married women with children report the best health despite greater stress levels in their lives [57]. Nonetheless, there is some evidence that self-reported health of coupled mothers is somewhat worse compared to coupled fathers, although direct comparisons are largely lacking [59]. Thus, the greater stress levels mothers experience may still account for the health disparities between men and women. 8. Disability Elderly women quite consistently have a higher prevalence of functional limitations and disabilities compared to elderly men, probably due to the combined effects of earlier onset, higher incidence, and a lower frequency of transitioning from a disabled back to a non-disabled state. Some minorities in the U.S. and elsewhere suffer from even more functional limitations compared to men of European descent, with women of African extraction frequently facing the highest risk [60–63]. A gender gap, however, is consistently seen in all minority groups as well, even after adjusting for socioeconomic indicators, which explain some, if not all, of the ethnic differences [60–64]. In addition to socioeconomic indicators (e.g., education, occupation, income, perceived insufficiency of income, access to and affordability of health care), statistical analyses have revealed associations of disability with chronic conditions and comorbidities (in particular arthritis, but also diabetes, cardiovascular disease, obesity, and depression), health-related behaviors (e.g., smoking, heavy drinking, physical activity), and social relations (e.g., marital or cohabitation status, family structure) [64–69]. To what extent these factors explain the gender gap in disability varies considerably between populations and also seems to depend on the type of disability or limitations under considerations and the method used for its assessment. It is quite striking, however, that frequently a considerable portion of the difference between male and female disability rates remains unexplained, suggesting that other aspects not considered in the analyses are likely to play a role, possibly including biological factors. Since many of the studies of functional limitations rely on selfreports, it also needs to be considered that men and women may differ systematically in their perception and reporting of disabilities. The available literature on the subject yields conflicting results (e.g., [70,71]. 9. Life expectancy Paradoxically, despite their higher morbidity, women live longer than men in essentially every country in the world (See Table 6). The country with the highest life expectancy for women is Japan, where a female infant born in 2009 could expect to live for 86.5 years. Male life expectancy was highest in Iceland: 80.2 years. The size of the gender life expectancy gap varies considerably, with male life expectancy in Kazakhstan representing 84% of female life expectancy at birth, whereas the life expectancy of males and females in the Chad hardly differed (47.5 years for men 47.8 years for women, giving a ratio of 99.4%). Life expectancy in industrialized countries has been increasing quite steadily for at least a century (e.g., in the U.S. from 49 years in 1900 to 77.9 years in 2007 [72–74]). Note that African-Americans

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Table 6 Life expectancy at birth for select countries in 2009. Bold numbers indicate highest life expectancies for men and women, respectively. Country

Men

Women

M:F ratio

U.S. Canada Argentina Australia Belarus Brazil Chad Chile China Denmark Finland France Germany Iceland India Italy Japan Kazakhstan Mexico New Zealand Niger Russia Sweden U.K.

76.0 78.9 72.0 79.7 64.3 70.0 47.5 75.6 72.2 76.9 76.6 77.8 77.7 80.2 63.1 79.2 79.6 58.8 68.0 78.7 57.2 61.8 79.2 78.0

80.9 83.3 78.7 84.2 75.9 76.9 48.2 81.8 75.8 81.2 83.2 84.8 82.7 83.5 66.1 84.4 86.5 70.0 74.1 82.7 57.6 74.2 83.4 82.2

0.94 0.95 0.91 0.95 0.85 0.91 0.99 0.92 0.95 0.95 0.92 0.92 0.94 0.96 0.95 0.94 0.92 0.84 0.92 0.95 0.99 0.83 0.95 0.95

Source: WHO Life Expectancy Tables.

experienced greater gains since 1900 compared to EuropeanAmericans, but they still have shorter life expectancies, whereas Hispanic Americans can expect to live longer compared to EuropeanAmericans [73]. Even in the 19th century, women out-lived men by one or more years. However, their life expectancy increased much faster between ~ 1930 and ~1980 such that the greatest gender gap (> 7 years in the U.S., > 6 years in other industrialized countries) was observed around 1980 in many countries [72,75,76]. Then, emancipation became dangerous to women's health. At least, it has been hypothesized that women's greater economic and social independence resulted in their adoption of more high-risk behaviors, such as smoking, drinking more heavily, and even driving cars (well, it appears in the U.S. they did that much earlier). Consequently, the gender differential in mortality has narrowed again in most, but not all, industrialized countries to around 4–5 years [74]. There are indications that the increased rate of smoking among women explains essentially all of the decline in the gender mortality gap [77,78]. Improvements in the treatment of heart disease and cancer, which claim the lives of men earlier than those of women, also contributed. However, other analyses indicate that purely mathematical reasons (a more narrow age distribution of deaths in women) play a substantial role [74]. In addition to the greater prevalence of smoking, factors contributing to the differential life expectancies of men and women include the higher male infant mortality, and the greater risk of accidental deaths and suicides (and homicides in the U.S. and some other countries) faced by adolescent and young adult males [40,75,79]. By far the most important contributors to the gender mortality gap later in life are heart disease and cancer, particularly lung cancer [75,79]. Note that almost as many women as men eventually die of heart disease, but women develop heart disease at least 6 years later than men do [80]). This raises the question of what causes this gender gap in mortality? For once, socioeconomic status is of no help. Though it is clearly associated with better health, it should favor men, who on average have higher socioeconomic status compared to women and also have higher educational attainment except for the younger age groups. The most likely explanation seems to be that women practice healthier behavior.

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As already mentioned, smoking is less common among women, as are heavy drinking of alcohol and other drug use [81]. Women more readily seek help for medical and psychological problems, are more likely to have regular physical check-ups, to do self-examinations for breast cancer more often than males to do self-examinations for testicular cancer. They are frequently reported as having higher participation rates in screening for breast and ovarian cancer compared to the screening frequency of men for prostate cancer, although they undergo colon cancer screening less frequently than men. In addition, a majority of surveys show that women are more knowledgeable about aspects of nutrition, including governmental guidelines for the promotion of a healthy diet [82,83], attach more importance to healthy nutrition, and often report healthier food choices compared to men [84]. It has been hypothesized that this could be related to their role as “nutritional gatekeeper” for their families [84], which is consistent with the finding that women still do the vast majority of food preparation in the home. However, the healthier food choices of women are also driven by their more frequent dieting behavior [84,85]. This dieting behavior stems from the female preoccupation with body weight and attempts to achieve the cultural ideal of slimness, which is also reflected in the fact that 85-90% of those affected by eating disorders (anorexia nervosa, bulimia nervosa, and binge eating) are women. Women are less frequently overweight (BMI >25) than men, although the rates of obesity (BMI >30) are similar between men and women, with excess female rates in some countries and excess male rates in others (according to WHO data). On the other hand, the lower overall energy intake of women and their frequent dieting puts them at risk of nutrient deficiencies, especially since they try to lose weight by eating less rather than by increasing their energy requirement through physical activity. The one health-promoting behavior that clearly favors males is their higher level of physical activity compared to women [40,83,86]. Men in the US are more likely to participate in sports, exercise, or recreation than women (22% compared to 16% on any given day) and they also spend more time on these activities than women (1.9 compared to 1.3 h) [25].

10. Health care utilization rate The overall health care utilization rate of women is also higher compared to men, although it remains a matter of some debate whether this is largely due to obstetrical and gynecological reasons on the one hand and the greater longevity of women on the other hand or constitutes a true difference. So, do women live longer because or in spite of their greater health care utilization? After all, there is considerable evidence that women do not always receive the usual standard of care. Even with similar presentation and comorbidities, women tend to be evaluated less thoroughly and treated less aggressively than men for a wide variety of conditions, including heart disease, stroke, and diabetes [87–91], although this does not necessarily affect outcome [92]. More to the point, does the more health-promoting lifestyle of women simply prolong their lives overall, or does it also bring them greater healthy life expectancy (defined as life expectancy with good self-rated health)? In absolute terms, the answer is yes. Compared to men, women can expect to live more years of healthy life as well as more years of life with limitations, disabilities, and/or chronic conditions [80]. In relative terms, however, men generally can expect to live a longer portion of their remaining life expectancy in good health and without disabilities not only in the U.S., Canada, and Japan [80,93,94], but similar data are emerging from less developed countries. What Evelyn Forget ([95], p. e150) said about a typical individual seems to be particularly true of women, namely that she “… might anticipate many years of increasingly costly disability before dying an expensive death at an advanced age”.

11. Conclusions There are obviously enormous differences between women and men that have not been discussed herein. This dedicated issue on sex, gender and autoimmunity has focused in particular on the potential etiologies that explain the increased risk of autoimmunity in many autoimmune diseases. This issue also focuses on the importance of reproductive issues on the natural history of autoimmune disease and of course on the health of the fetus. Finally, we note that very few epidemiologic studies in autoimmunity address many of the key sociological differences between women and men. Indeed, it is not sufficient to look at the generic issues of smoking, alcohol use, etc., without taking into account the major differences in lifestyle. This special issue attempts to address many of these problems, with relevant papers on menopause, contraceptives, pregnancy, and lifestyle.

References [1] Warnke G. Debating Sex and Gender. New York: Oxford University Press, Inc.; 2011. [2] Springer KW, Mager Stellman J, Jordan-Young RM. Beyond a catalogue of differences: a theoretical frame and good practice guidelines for researching sex/gender in human health. Soc Sci Med 2011;12:2011 epub ahead of print accessed July. [3] Brain Development Cooperative Group. Total and regional brain volumes in a population-based normative sample from 4–18 years: the NIH MRI study of normal brain development. Cereb Cortex 2011 Epub 2011/05/27, accessed July 12, 2011. [4] Lange N, Froimowitz MP, Bigler ED, Lainhart JE. Associations between IQ, total and regional brain volumes, and demography in a large normative sample of healthy children and adolescents. Dev Neuropsychol 2010;35:296–317. [5] Lynn R. Sex differences in intelligence and brain size: a paradox resolved. Pers Individ Diff 1994;17:257–71. [6] De Bellis MD, Keshavan MS, Beers SR, Hall J, Fruscati K, Masalehdan A, et al. Sex differences in brain maturation during childhood and adolescence. Cereb Cortex 2001;11:552–7. [7] Morgan E. The Descent of Woman. The Classic Study of Evolution. London: Souvenir Press Ltd; 1985. Revised Edition. [8] Newcombe NS. Taking science seriously: straight thinking about spatial sex differences [online version]. In: Ceci S, Williams W, editors. Why aren't More Women in Science? Top Researchers Debate the Evidence. Washington, DC: APA Books; 2007. pp. available fromwww.temple.edu/psychology/newcombe/publications.htm. accessed 10/4/11. [9] Wright R. The Moral Animal: Why We Are the Way We Are. New York, NY: Random House Vintage Books; 1995. [10] Fine C. Delusions of Gender. How Our Minds, Society, and Neurosexism Create Difference. New York, NY: W.W. Norton and Company, Inc.; 2010. [11] Connellan J, Baron-Cohen S, Wheelwright S, Batki A, Ahluwalia J. Sex differences in human neonatal social perception. Infant Behav Dev 2000;23:113–8. [12] Spelke ES. Sex differences in intrinsic aptitude for mathematics and science? A critical review. Am Psychol 2005;60:950–8. [13] Nash A. Picking Barbie™'s brain: inherent sex differences in scientific ability? J Interdiscip Feminist Thought 2007;2 Art. 5. [14] Saccuzzo DP, Craig AS, Johnson NE, Larson GE. Gender differences in dynamic spatial abilities. Pers Individ Diff 1996;21:599–607. [15] Weiss EM, Kemmler G, Deisenhammer EA, Fleischhacker WW, Delazer M. Sex differences in cognitive functions. Pers Indiv Differ 2003;35:863–75. [16] Walton GM, Spencer SJ. Latent Ability. Grades and test scores systematically underestimate the intellectual ability of negatively stereotyped students. Psychol Sci 2009;20:1132–9. [17] Moè A. Are males always better than females in mental rotation? Exploring a gender belief explanation. Learn Individ Differ 2009;19:21–7. [18] Sharps MJ, Price JL, Williams JK. Spatial cognition and gender. Instructional and stimulus influences on mental image rotation performance. Psychol Women Quart 1994;18:413–25. [19] Niederle M, Vesterlund L. Do Women Shy Away From Competition? Do Men Compete Too Much? Cambridge, MA: National Bureau of Economic Research; 2005. [20] Eurostat. Women and men in the EU seen through figures. Brussels: European Commission; 2011. [21] Statistics Canada. Women in Canada. A Gender-based Statistical Report. Fifth Edition. Ottawa, Canada: Minister of Industry; 2006. [22] Misra J, Budig M, Boeckmann I. Work-family policies and the effects of children on women's employment and earnings. Luxembourg Income Study Working Paper; 2010. Luxemburg. [23] Bureau of Labor Statistics. Married Parents' Use of Time, 2003–06. Washington, DC: U.S. Department of Labor; 2008. [24] OECD. OECD Employment Outlook 2011. OECD Publishing; 2011. [25] Bureau of Labor Statistics. American Time Use Survey–2010 Results. Washington, DC: U.S. Department of Labor; 2011. [26] Marshall K. Converging gender roles. Perspectives on Labour and Income, Statistics Canada, Catalogue no. 75-001-XIE, 7; 2006. p. 5–17.

A.T. Borchers, M.E. Gershwin / Autoimmunity Reviews 11 (2012) A413–A421 [27] Fagan C. Analysis note. Men and Gender Equality–tackling gender segregated family roles and social care jobs. Directorate-General Employment, Social Affairs and Equal Opportunities. Brussels: European Commission; 2010. [28] Gupta S. Her money, her time. Women's earnings and their housework hours. Soc Sci Res 2006;35:975–99. [29] Kan MY, Sullivan O, Grshuny J. Gender convergence in domestic work: Discerning the effects of interactional and institutional barriers from large-scale data. Sociology 2011;42:234–51. [30] Doucet A. Dad and baby in the first year: gendered responsibilities and embodiment. Ann Am Acad Pol Soc Sci 2009;624:78–98. [31] Weichselbaumer D, Winter-Ebmer R. A meta-analysis of the international gender wage gap. J Econ Surv 2005;19:479–511. [32] Bettio F, Verashchagina A. Gender segregation in the labour market. Root causes, implications and policy reponses in the EU. Directorate-General for Employment, Social Affairs, and Equal Opportunities. Luxemburg: European Commission; 2009. [33] National Center for Education Statistics. What is the percentage of degrees conferred by sex and race? Washington, DC: U.S. Department of Education; 2011. [34] Shauman KA. Occupational sex segregation and the earnings of occupations: What causes the link among college-educated workers? Soc Sci Res 2006;35: 577–619. [35] Christie P, Shannon M. Educational attainment and the gender wage gap: evidence from the 1986 and 1991 Canadian censuses. Econ Educ Rev 2001;20:165–80. [36] Hersch J. Sex discrimination in the labor market. Found Trends® Microecon 2006;2:281–361. [37] Budig M, England P. The wage penalty for motherhood. Am Sociol Rev 2001;66: 204–25. [38] Mandel H, Semyonov M. Family policies, wage structures, and gender gaps: Sources of earnings inequality in 20 countries. Am Sociol Rev 2005;70:949–67. [39] Blau FD, Kahn LM. Understanding International Differences in the Gender Pay Gap. NBER Working Paper. Cambridge, MA: National Bureau of Economic Research; 2001. [40] Eurostat. The life of women and men in Europe. A statistical portrait. Luxemburg: Office for Official Publications of the European Communities; 2008. [41] Ridgeway CL, Correll SJ. Motherhood as a status characteristic. J Soc Issues 2004;60:683–700. [42] Correll SJ, Bernard S, Paik I. Getting a job: is there a motherhood penalty? Am J Sociol 2007;112:1297–338. [43] Fuegen K, Biernat M, Haines E, Deaux K. Mothers and fathers in the workplace: how gender and parental status influence judgments on job-related competence. J Soc Issues 2004;60:737–54. [44] Christopher K, England P, Smeeding TM, Ross Phillips K. The gender gap in poverty in modern nations. Single motherhood, the market, and the state. Sociol Perspect 2002;45:219–42. [45] U.S. Census Bureau. Current Population Survey. Annual Social and Economic Supplement. Washington, DC: U.S. Department of Commerce; 2008. [46] Lee S, Shaw L. Gender and Economic Security in Retirement. Washington, DC: Institute for Women's Policy Research; 2003. [47] Misra J, Moller S, Budig MJ. Work-family policies and poverty for partnered and single women in Europe and North America. Gender Soc 2007;21:804–27. [48] MacIntyre S, Hunt K, Sweeting H. Gender differences in health: are things really as simple as they seem? Soc Sci Med 1996;42:617–24. [49] Walters V, McDonough P, Strohschein L. The influence of work, household structure, and social, personal and material resources on gender differences in health: an analysis of the 1994 Canadian National Population Health Survey. Soc Sci Med 2002;54:677–92. [50] Case A, Paxson C. Sex differences in morbidity and mortality. Demography 2005;42:189–214. [51] Meana M, Cho R, DesMeules M. Chronic pain. The extra burden on Canadian women. BMC Womens Health 2004;4(Suppl 1):S17. [52] Cooper H. Investigating socio-economic explanations for gender and ethnic inequalities in health. Soc Sci Med 2002;54:693–706. [53] Almeida DM, Kessler RC. Everyday stressors and gender differences in daily distress. J Pers Soc Psychol 1998;75:670–80. [54] Matud MP. Gender differences in stress and coping styles. Pers Individ Diff 2004;37:1401–15. [55] Hämmig O, Bauer G. Work-life imbalance and mental health among male and female employees in Switzerland. Int J Public Health 2009;54:88–95. [56] Kinnunen U, Geurts S, Mauno S. Work-to-family conflict and its relationship with satisfaction and well-being: a one-year longitudinal study on gender differences. Work Stress 2004;18:1–22. [57] McDonough P, Walters V, Strohschein L. Chronic stress and the social patterning of women's health in Canada. Soc Sci Med 2002;54:767–82. [58] Lahelma E, Arber S, Kivela K, Roos E. Multiple roles and health among British and Finnish women: the influence of socioeconomic circumstances. Soc Sci Med 2002;54:727–40. [59] Westin M, Westerling R. Health and healthcare utilization among single mothers and single fathers in Sweden. Scand J Public Health 2006;34:182–9. [60] Mendes de Leon CF, Barnes LL, Bienias JL, Skarupski KA, Evans DA. Racial disparities in disability: recent evidence from self-reported and performance-based disability measures in a population-based study of older adults. J Gerontol B Psychol Sci Soc Sci 2005;60:S263–71. [61] Fuller-Thomson E, Nuru-Jeter A, Minkler M, Guralnik JM. Black-White disparities in disability among older Americans: further untangling the role of race and socioeconomic status. J Aging Health 2009;21:677–98. [62] Warner DF, Brown TH. Understanding how race/ethnicity and gender define agetrajectories of disability: an intersectionality approach. Soc Sci Med 2011;72:1236–48.

A421

[63] Guerra RO, Alvarado BE, Zunzunegui MV. Life course, gender and ethnic inequalities in functional disability in a Brazilian urban elderly population. Aging Clin Exp Res 2008;20:53–61. [64] Read JG, Gorman BK. Gender inequalities in US adult health: the interplay of race and ethnicity. Soc Sci Med 2006;62:1045–65. [65] Nilsson CJ, Lund R, Avlund K. Cohabitation status and onset of disability among older Danes: is social participation a possible mediator? J Aging Health 2008;20: 235–53. [66] Murtagh KN, Hubert HB. Gender differences in physical disability among an elderly cohort. Am J Public Health 2004;94:1406–11. [67] Zunzunegui MV, Alvarado BE, Béland F, Vissandjee B. Explaining health differences between men and women in later life: a cross-city comparison in Latin America and the Caribbean. Soc Sci Med 2009;68:235–42. [68] Hardy SE, Allore HG, Guo Z, Gill TM. Explaining the effect of gender on functional transitions in older persons. Gerontology 2008;54:79–86. [69] Peek MK, Coward RT. Gender differences in the risk of developing disability among older adults with arthritis. J Aging Health 1999;11:131–50. [70] Melzer D, Lan TY, Tom BD, Deeg DJ, Guralnik JM. Variation in thresholds for reporting mobility disability between national population subgroups and studies. J Gerontol A Biol Sci Med Sci 2004;59:1295–303. [71] Iburg KM, Salomon JA, Tandon A, Murray CJL. Cross-population comparability of selfreported and physician-assessed mobility levels: Evidence from the Third National Health and Nutrition Examination Survey. Geneva: World Health Organization; 2001. [72] Armstrong RJ. Some trend comparison of United States Life-Table Data 1900–1981. Washington, DC: U.S. Department of Health and Human Services; 1987. [73] National Center for Health Statistics. National Vital Statistics Report. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Washington, DC; 2011. [74] Glei DA, Horiuchi S. The narrowing sex differential in life expectancy in high-income populations: effects of differences in the age pattern of mortality. Popul Stud (Camb) 2007;61:141–59. [75] Sandiford P. Gender inequality in New Zealand life expectancy: decomposition by age and cause. N Z Med J 2009;122:10–7. [76] Council of Europe. Recent demographic developments in Europe. Strasbourg, France: Council of Europe Publishing; 2003. [77] Pampel F. Forecasting sex differences in mortality in high income nations. The contribution of smoking. Demogr Res 2005;13:455–84. [78] Preston SH, Wang H. Sex mortality differences in the United States: the role of cohort smoking patterns. Demography 2006;43:631–46. [79] Trovato F, Odynak D. Sex differences in life expectancy in Canada: immigrant and native-born populations. J Biosoc Sci 2011;43:353–67. [80] Crimmins EM, Kim JK, Hagedorn A. Life with and without disease: women experience more of both. J Women Aging 2002;14:47–59. [81] Pinkhasov RM, Wong J, Kashanian J, Lee M, Samadi DB, Pinkhasov MM, et al. Are men shortchanged on health? Perspective on health care utilization and health risk behavior in men and women in the United States. Int J Clin Pract 2010;64: 475–87. [82] Lin W, Hang CM, Yang HC, Hung MH. 2005–2008 Nutrition and Health Survey in Taiwan: the nutrition knowledge, attitude and behavior of 19–64 year old adults. Asia Pac J Clin Nutr 2011;20:309–18. [83] Wei CN, Harada K, Ueda K, Fukumoto K, Minamoto K, Ueda A. Assessment of health-promoting lifestyle profile in Japanese university students. Environ Health Prev Med 2011. [84] Wardle J, Haase AM, Steptoe A, Nillapun M, Jonwutiwes K, Bellisle F. Gender differences in food choice: the contribution of health beliefs and dieting. Ann Behav Med 2004;27: 107–16. [85] Liebman M, Cameron BA, Carson DK, Brown DM, Meyer SS. Dietary fat reduction behaviors in college students: relationship to dieting status, gender and key psychosocial variables. Appetite 2001;36:51–6. [86] Lee RL, Loke AJ. Health-promoting behaviors and psychosocial well-being of university students in Hong Kong. Public Health Nurs 2005;22:209–20. [87] Chang AM, Mumma B, Sease KL, Robey JL, Shofer FS, Hollander JE. Gender bias in cardiovascular testing persists after adjustment for presenting characteristics and cardiac risk. Acad Emerg Med 2007;14:599–605. [88] Fowler RA, Sabur N, Li P, Juurlink DN, Pinto R, Hladunewich MA, et al. Sex-and age-based differences in the delivery and outcomes of critical care. CMAJ 2007;177:1513–9. [89] Nguyen JT, Berger AK, Duval S, Luepker RV. Gender disparity in cardiac procedures and medication use for acute myocardial infarction. Am Heart J 2008;155:862–8. [90] Kosiak B, Sangl J, Correa-de-Araujo R. Quality of health care for older women: what do we know? Womens Health Issues 2006;16:89–99. [91] Vimalananda VG, Miller DR, Palnati M, Christiansen CL, Fincke BG. Gender disparities in lipid-lowering therapy among veterans with diabetes. Womens Health Issues 2011;21:S176–81. [92] Kapral MK, Degani N, Hall R, Fang J, Saposnik G, Richards J, et al. Gender differences in stroke care and outcomes in Ontario. Womens Health Issues 2011;21:171–6. [93] Bélanger A, Martel L, Berthelot J-M, Wilkins R. Gender differences in disability-free life expectancy for selected risk fators and chronic conditions in Canada. J Women Aging 2002;14:61–83. [94] Tsuji I, Sauvaget C, Hisamichi S. Health expectancies in Japan. Gender differences and policy implications for women. J Women Aging 2002;14:135–48. [95] Forget EL, Roos LL, Deber RB, Walld R. Variations in lifetime healthcare costs across a population. Healthc Policy 2008;4:e148–67.