Introduction
With greater participation of women in the workforce over recent decades in most parts of the world, both men and women are involved in work and family life [
1,
2]. In Brazil, women have only relatively recently entered the labour market, but their contribution has grown rapidly. The proportion of women in the workforce increased from 32 % in 1980 to 57 % in 2009. The female-to-male labour force participation rate also increased from 52.2 % in 1990 to 73.3 % in 2010 and has continued to increase steadily [
3,
4]. This is good for the emancipation and economic independence of women but can also have its drawbacks as women and men now need to balance their responsibilities at home and work.
The division of household tasks and childcare responsibility between working men and women, however, has not undergone similar changes and is still unequal [
5]. It also varies by country and region [
6]. For example, in Sweden, a country with high gender equality, women carry out an average of 26 h of unpaid work each week, whereas men do about 21 h [
7]. In Europe as a whole, women spend an average of 26 h per week on care and household activities, compared with 9 h for men (European Commission, Report on Progress on equality between women and men in 2013). In Brazil, the average unpaid work per week is 25 h for women and about 10 h for men [
3]. Although men have slightly increased their participation in housework and childcare in Brazil, women still perform most family tasks and spend more time on unpaid domestic work even if they are in full-time paid work [
1,
3,
8‐
11].
Balancing work and family demands is challenging, and one or other may require more time and attention than is available. The work–family conflict is defined as ‘a form of interrole conflict in which the role pressures from the work and family domains are mutually incompatible in some respect’ [
12]. This imbalance is also conceptualized as work–life conflict or work–life imbalance [
13,
14]. Although correlated, work–family conflict and work–life conflict measures are, however, different [
15]. The work–family conflict is more related to the lack of boundaries between work and family spheres and could be moderated by family status. Work–life imbalance research focuses on the spillover effect in a broader context, in which work influences experiences in the non-work sphere (for example, time for leisure, friends and family life) [
15]. In the present study, we focused on work–family boundary management (rather than broader work–life issues) in two basic directions: work-to-family or family-to-work conflict [
16‐
22]. Most previous studies have focused on work-to-family conflict, viewed as resulting from occupational conditions [
17,
19,
20,
22,
23]. Less often, family-to-work conflict has been investigated, and is viewed as arising from home and life circumstances [
17‐
19,
24]. Some authors have postulated that family-to-work conflict could have more long-term consequences than work-to-family conflict [
25,
26] and also have a greater influence on women’s health [
22,
26]. Other studies have also discussed work-to-family conflict as being more detrimental to women’s health than to men’s health [
27,
28]. A few studies have described characteristics of work–family conflict as two distinguishable forms: time-based (time devoted to one role makes it difficult to participate in another) and strain-based (excessive effort to perform in one domain affects performance in the other) [
19,
22]. An additional form of conflict, behaviour-based work–family conflict, refers to specific behaviours in one role being incompatible with behaviours in the other [
17,
19,
21]. However, little is known about gender-based antecedents or outcomes for each of these forms [
17,
19,
22].
More recently, some authors have suggested that work and non-work are no longer separate domains and can simultaneously affect quality of life, leisure and health, with a different pattern according to gender [
2,
18‐
20,
24,
29]. Based on this literature, we included a measure in the present study of both domains (work and family) simultaneously affecting leisure time and self-care.
Previous studies have investigated the association between work–family conflict and health status, such as common symptoms, mental health or depression [
16,
19,
30‐
32], and whether work–family conflict may reduce the well-being benefits of employment [
19,
33]. Some studies have also reported an association between work–family conflict and poorer self-rated health [
16,
34‐
36]. Self-rated health expresses subjective as well as objective aspects of health and could reflect gender differences in stress response. It has been shown to be a predictor of future morbidity and mortality, functional decline and disability and higher utilization of health care [
37‐
39].
Much of the literature shows that gender differences in work environment and family characteristics affect the association between work–family conflict and health [
19,
27,
31,
34]. Gender is an essential determinant of inequalities in work–family conflict [
36]. Most previous studies have distinguished between genders, and the results generally show a higher prevalence of work–family conflict and suboptimal self-rated health among women [
36,
40,
41], although some studies found similar results in men and women [
27,
32,
34].
Educational level also affects the experience of work–family conflict and the resulting mental health consequences [
23,
42]. Individuals with higher educational attainment tend to express more work–family conflict. This might be due to high-pressure jobs and working longer hours than people with lower levels of education [
23]. Educational level is also closely related to inequalities in health and is often used as a proxy for occupational prestige [
23]. Groups with lower levels of education have a higher risk of mortality [
43] and worse self-rated health than highly educated groups [
44]. It is therefore possible that education level might modify the association between work–family conflict and self-rated health. To our knowledge, no previous studies have investigated this interaction considering gender stratification.
The association between work–family conflict and health status has been well-studied, mostly in western Europe and North America. In Brazil, the most populous country in South America, income and gender inequality remain high [
3], but studies about influence of work–family conflict on health are scarce. This study therefore aims to investigate gender differences in the association between work–family conflict and self-rated health, and to evaluate whether educational attainment modifies this association, using data from the baseline of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).
Results
The mean age was similar for men and women. Women generally had higher levels of education; they were more likely to be divorced, separated, widowed or single, worked fewer hours per week and more often in day shifts. The frequency of self-reported chronic diseases was lower among women. Similar proportions of men and women reported having children under 5 years of age and having a maid (Table
1). Over 90 % of women vs 70 % of men worked in non-manual jobs. The occupational nature of a participant’s present job (classified into four levels: routine/manual; non-routine/manual; routine/non-manual; and non-routine/non-manual) were strongly correlated with educational level for both women and men (Spearman’s correlation coefficient 0.68 and 0.76, respectively,
p < 0.001) (data not shown).
Table 1
Prevalence of suboptimal self-rated health among men and women, by covariables, ELSA-Brasil baseline (2008–10; n = 12,017)
Age, mean (SD) | 49.5 (7.4) | 51.1 (6.9)*** | 48.9 (7.1) | 50.1 (7.0)*** |
Educational level (%) |
University degree | 49.6 | 12.3*** | 55.6 | 12.1*** |
Complete high school | 35.4 | 20.1 | 37.2 | 24.0 |
Complete elementary school | 7.9 | 30.6 | 4.5 | 35.8 |
Never attender or incomplete elementary school | 7.1 | 45.3 | 2.8 | 45.2 |
Marital status (%) |
Married/living together | 81.1 | 19.0** | 55.1 | 17.6*** |
Divorced/separated/widowers | 13.4 | 19.4 | 30.8 | 21.3 |
Single | 5.6 | 14.4 | 14.1 | 15.1 |
Children under 5 years |
Yes | 13.2 | 17.5 | 10.0 | 20.0 |
No | 86.8 | 18.8 | 90.0 | 18.2 |
Presence of a maid |
Yes | 22.2 | 13.6*** | 25.5 | 12.3*** |
No | 77.8 | 20.1 | 74.5 | 20.5 |
Working hours | | | | |
<39 | 12.8 | 25.4*** | 22.3 | 24.4*** |
40 to 59 | 72.0 | 18.4 | 67.8 | 16.9 |
≥ 60 | 15.2 | 14.4 | 9.9 | 14.8 |
Type of shift work (%) |
Daytime | 65.9 | 18.7 | 65.6 | 18.4 |
Daytime shifts | 12.5 | 17.6 | 17.3 | 17.3 |
Mixed or nightshifts | 21.6 | 19.8 | 17.1 | 19.9 |
Presence of self-reported chronic diseasesa
|
Yes | 36.4 | 32.4*** | 30.9 | 31.7*** |
No | 63.6 | 10.8 | 69.1 | 12.5 |
The overall prevalence of suboptimal self-rated health was 18.7 % and comparable in men and women (18.7 and 18.4 %, respectively;
p = 0.72). Men and women who reported suboptimal health were older, had lower educational levels and worked fewer hours per week than those with good self-rated health. Higher levels of suboptimal health were observed in divorced, separated or widowed respondents, those who had no maid and those who reported chronic diseases. Type of work shift and presence of children under 5 years of age were not associated with higher levels of suboptimal health (
p > 0.05) (Table
1).
In general, women reported frequent work–family conflicts more often than men. For both genders, participants with higher education reported work–family conflict more often. An exception was observed for family-to-work conflict, which was similar for both genders with those with lower education commonly reporting more frequent conflict. In men, frequent family-to-work conflict was associated with a higher level of suboptimal health (
p < 0.001). For women, the same tendency was observed for three out of four work–family conflict indicators:
work-to-family strain-based, family-to-work conflict and
lack of time for leisure and personal care (Table
2).
Table 2
Work–family conflict indicators by education level and prevalence of suboptimal self-rated health among men and women; ELSA-Brasil baseline (2008–10; n = 12,017)
Work-to-family time-based |
Never to rarely | 41.8 | 48.1 | 35.4*** | 19.3 | 39.8 | 47.8 | 33.3*** | 18.9 |
Sometimes | 32.3 | 31.4 | 33.2 | 17.8 | 28.2 | 26.4 | 29.7 | 17.4 |
Frequently | 25.9 | 20.5 | 31.4 | 18.7 | 32.0 | 25.8 | 36.9 | 18.6 |
Work-to-family strain-based |
Never to rarely | 54.3 | 61.2 | 47.3*** | 18.4 | 45.4 | 53.9 | 38.7*** | 17.9*** |
Sometimes | 29.7 | 26.4 | 33.2 | 17.9 | 29.6 | 25.6 | 32.8 | 16.8 |
Frequently | 16.0 | 12.5 | 19.5 | 21.1 | 25.0 | 20.5 | 28.5 | 21.2 |
Family-to-work |
Never to rarely | 67.0 | 70.2 | 63.8*** | 17.4*** | 68.6 | 70.2 | 65.5*** | 17.6** |
Sometimes | 25.5 | 21.0 | 30.1 | 19.4 | 25.5 | 22.4 | 28.2 | 19.0 |
Frequently | 7.5 | 8.8 | 6.1 | 27.0 | 6.8 | 7.4 | 6.4 | 23.8 |
Lack of time for leisure and personal care |
Never to rarely | 44.2 | 54.2 | 34.0*** | 18.4 | 32.9 | 42.5 | 25.3*** | 19.3*** |
Sometimes | 32.0 | 30.2 | 33.8 | 18.3 | 32.6 | 30.0 | 34.7 | 15.6 |
Frequently | 23.8 | 15.6 | 32.1 | 19.7 | 34.5 | 27.5 | 40.1 | 20.2 |
In men, the crude analyses showed frequent family-to-work conflict was associated with greater odds of suboptimal self-reported health (OR 1.75; 95 % CI 1.39–2.20; Table
3). After adjustment for covariates, all work–family conflict indicators were associated with suboptimal self-rated health, in a dose–response gradient. This gradient was statistically significant in the case of the family-to-work and lack of time for leisure and personal care indicators. Higher frequency of conflicts in those domains gave increased chances of suboptimal self-reported health. Adjustment by age and education had a mild effect on the association. Working hours and presence of disease showed the highest influence on the association (Table
3). The interaction terms by chi-square test indicated no influence of educational level on the association between work–family conflict indicators and suboptimal self-rated health among men (
p > 0.10).
Table 3
Crude and adjusted odds ratios of the association between work–family conflict indicators and suboptimal self-rated health among men, ELSA-Brasil, baseline (2008–10)
Work to family time-based |
Never to rarely | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Sometimes | 0.91 (0.78–1.06) | 0.91 (0.78–1.07) | 0.98 (0.84–1.15) | 1.03 (0.88–1.21) | 1.07 (0.90–1.26) |
Frequently | 0.96 (0.82–1.14) | 0.97 (0.82–1.14) | 1.14 (0.96–1.35) | 1.28 (1.07–1.53) | 1.36 (1.13–1.64) |
AIC
|
5524.1
|
5468.4
|
5305.8
|
5289.9
|
4989.0
|
Work to family strain-based |
Never to rarely | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Sometimes | 0.97 (0.83–1.13) | 0.98 (0.84–1.15) | 1.10 (0.94–1.29) | 1.15 (0.98–1.35) | 1.18 (1.00–1.39) |
Frequently | 1.19 (0.99–1.42) | 1.21 (1.01–1.46) | 1.43 (1.19–1.73) | 1.62 (1.33–1.97) | 1.67 (1.36–2.05) |
AIC
|
5521.3
|
5464.9
|
5295.3
|
5275.5
|
4975.9
|
Family to work |
Never to rarely | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Sometimes | 1.14 (0.98–1.33) | 1.18 (1.01–1.38) | 1.31 (1.12–1.54) | 1.33 (1.13–1.56) | 1.34 (1.14–1.58) |
Frequently | 1.75 (1.39–2.20) | 1.75 (1.39–2.20) | 1.66 (1.31–2.10) | 1.70 (1.35–2.16) | 1.82 (1.42–2.32) |
AIC
|
5503.3
|
5447.1
|
5284.9
|
5271.7
|
4971.0
|
Lack of time for leisure and personal care |
Never to rarely | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Sometimes | 0.99 (0.85–1.16) | 1.03 (0.88–1.21) | 1.18 (1.01–1.39) | 1.23 (1.05–1.44) | 1.25 (1.06–1.47) |
Frequently | 1.09 (0.92–1.29) | 1.14 (0.97–1.35) | 1.53 (1.28–1.82) | 1.71 (1.42–2.05) | 1.77 (1.47–2.14) |
AIC
|
5524.3
|
5467.3
|
5287.2
|
5265.3
|
4965.1
|
Higher odds of suboptimal self-reported health in crude analyses were observed for women who reported frequent work-to-family strain-based (OR = 1.24; 95 % CI = 1.06–1.44) or family-to-work (OR = 1.46; 95 % CI = 1.16–1.85) conflict (Table
4). Like men, after adjustment for covariates, women with frequent work–family conflict, as measured by all indicators had greater odds of suboptimal self-reported health, and we also observed a dose–response gradient except in lack of time for leisure and personal care. Adjustment for education showed the highest influence on the association between work–family conflict and suboptimal self-rated health (Table
4, Model 3). In fact, educational level interacted with three out of four work–family conflict indicators among women (
time-based work-to-family conflict p = 0.08;
strain-based work-to-family conflict p = 0.07; and
lack of time for leisure and personal care p < 0.001), but there was no evidence of interaction among women for family-to-work conflict (
p = 0.26).
Table 4
Crude and adjusted odds ratios of the association between work–family conflict indicators and suboptimal self-rated health among women, ELSA-Brasil, baseline (2008–10)
Work to family time-based |
Never to rarely | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Sometimes | 0.90 (0.77–1.06) | 0.91 (0.78–1.07) | 1.02 (0.87–1.21) | 1.03 (0.88–1.21) | 1.06 (0.90–1.25) | 1.10 (0.93–1.30) |
Frequently | 0.98 (0.84–1.14) | 0.98 (0.85–1.14) | 1.18 (1.01–1.38) | 1.21 (1.03–1.41) | 1.29 (1.09–1.51) | 1.30 (1.10–1.53) |
AIC
|
6002.8
|
5964.6
|
5757.3
|
5749.0
|
5743.6
|
5532.8
|
Work to family strain-based |
Never to rarely | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Sometimes | 0.92 (0.79–1.08) | 0.95 (0.81–1.11) | 1.10 (0.94–1.29) 1.11 (0.94–1.30) | 1.14 (0.97–1.34) | 1.15 (0.98–1.35) | |
Frequently | 1.24 (1.06–1.44) | 1.27 (1.09–1.48) | 1.51 (1.29–1.78) | 1.54 (1.31–1.80) | 1.63 (1.38–1.92) | 1.62 (1.37–1.92) |
AIC
|
5992.6
|
5953.3
|
5736.2
|
5727.3
|
5719.5
|
5511.1
|
Family to work |
Never to rarely | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Sometimes | 1.10 (0.95–1.27) | 1.13 (0.97–1.31) | 1.22 (1.05–1.42) | 1.23 (1.06–1.44) | 1.24 (1.06–1.44) | 1.23 (1.05–1.44) |
Frequently | 1.46 (1.16–1.85) | 1.48 (1.17–1.87) | 1.46 (1.15–1.86) | 1.47 (1.16–1.88) | 1.47 (1.16–1.88) | 1.53 (1.19–1.96) |
AIC
|
5994.5
|
5954.9
|
5748.9
|
5740.6
|
5738.7
|
5527.3
|
Lack of leisure time and personal care |
Never to rarely | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Sometimes | 0.77 (0.65–0.90) | 0.79 (0.67–0.93) | 0.92 (0.78–1.09) 0.94 (0.79–1.11) | 0.95 (0.81–1.13) | 0.98 (0.83–1.16) | |
Frequently | 1.05 (0.91–1.23) | 1.10 (0.95–1.29) | 1.39 (1.18–1.62) | 1.42 (1.21–1.67) | 1.49 (1.27–1.76) | 1.55 (1.31–1.83) |
AIC
|
5987.5
|
5948.4
|
5734.8
|
5724.8
|
5718.3
|
5506.1
|
Table
5 shows the fully adjusted regression models, including a multiplicative interaction term for women. The results show that the association between frequent work–family conflict and suboptimal self-reported health was stronger in women with higher levels of education. For work-to-family time-based conflict, women with higher levels of education had higher odds for suboptimal self-related health (OR = 1.54; 95 % CI = 1.19–1.99) than less educated women (OR = 1.14; 95 % CI = 0.92–1.42). Similarly, for work-to-family strain-based conflict, women with higher and lower levels of education had OR = 1.91 (95 % CI = 1.48–2.47) and OR = 1.40 (95 % CI = 1.12–1.75). For lack of time for leisure and personal care, women with higher and lower educational levels had OR = 2.60 (95 % CI = 1.95–3.47) and OR = 1.11 (95 % CI = 0.90–1.38).
Table 5
Full adjusted logistic regression models of the association between work–family conflict indicators and suboptimal self-rated health including multiplicative interaction term (WFC*educational level) among women
Work to family time-based |
Never to rarely | 1.00 | 1.00 |
Sometimes | 1.11 (0.90–1.37) | 1.12 (0.85–1.47) |
Frequently | 1.14 (0.92–1.42) | 1.54 (1.19–1.99) |
Work to family strain-based |
Never to rarely | 1.00 | 1.00 |
Sometimes | 1.19 (0.96–1.47) | 1.13 (0.87–1.47) |
Frequently | 1.40 (1.12–1.75) | 1.91 (1.48–2.47) |
Lack of leisure time and personal care |
Never to rarely | 1.00 | 1.00 |
Sometimes | 0.92 (0.75–1.14) | 1.27 (0.93–1.74) |
Frequently | 1.11 (0.90–1.38) | 2.60 (1.95–3.47) |
Conclusion
Our findings are in line with previous research showing an association between work–family conflict and health. More frequent work–family conflict was associated with suboptimal self-rated health by all the work–family conflict indicators tested. We also found that educational level modified these associations, but only among women.
Future research should incorporate the role of cultural differences around gender in a Brazilian context, to show how this affects family and work spheres for both genders. It is also necessary to understand the effect of decision latitude, social support and other relevant moderating effects on the relationship between work–family conflicts and health, according to socioeconomic position and job occupation, and across gender groups. We believe that the opportunity for personal development for both genders and enrichment of everyday family life will be guaranteed by higher gender equality in taking care of home duties and looking after children. This change might decrease stress levels and positively influence priorities for women and men in the use of time for themselves, improving health and well-being. This is especially important in countries like Brazil, where large gender inequalities interact with other social and economic inequalities. Handling the spillover between job and family demands in modern life, especially in big cities, is a great challenge and more than individual (or family) arrangements are necessary. Macro-level and organizational policies are also necessary to promote changes in traditional patterns of behaviour and to foster gender equality and social justice.
Acknowledgments
The authors thank the ELSA-Brasil participants who agreed to take part in this study. The ELSA-Brasil baseline study was supported by Brazil’s Ministry of Health (Department of Science and Technology) and Ministry of Science and Technology (Study and Project Funding Agency-FINEP and National Research Council-CNPq) (grants 01 06 0010.00 RS, 01 06 0212.00 BA, 01 06 0300.00 ES, 01 06 0278.00 MG, 01 06 0115.00 SP, and 01 06 0071.00 RJ). This work was conducted during a Joint Brazilian–Swedish Research Collaboration supported by the International Cooperation Program CAPES/STINT. Financed by CAPES—Brazilian Federal Agency for Support and Evaluation of Graduate Education within the Ministry of Education of Brazil. This paper was prepared while RG was a visiting researcher at CHESS (Forte 2014–2680). ST is a senior researcher at CHESS (Forte 2012–0615). RHG, DC and EMA are research fellows of the National Research Council (CNPq). The funding source had no influence over the study design, data collection, analysis and interpretation, writing the paper or the decision to publish.