Men’s work, Women’s work, and mental health: A longitudinal investigation of the relationship between the gender composition of occupations and mental health

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Highlights

  • There were differences in male versus female dominated occupations.

  • Mental health varied in male versus female dominated occupations.

  • There is a need for research on gender specific selection into employment.

Abstract

This longitudinal investigation assesses the extent to which the gender composition of an occupation (e.g., the extent to which an occupation is comprised of males versus females) has an impact on mental health. We used 14 annual waves of the Household Income Labour Dynamics in Australia (HILDA) study to construct a measure representing the gender ratio of an occupation. The outcome measure was the Mental Health Inventory (MHI-5). A Mundlak model was used to compare within and between person effects, after controlling for possible confounders. Results suggest that males and females employed in occupations where their own gender was dominant had better mental health than those in gender-neutral occupations (between person effects). However, within-person results suggested that a movement from a gender-neutral to a male or female dominated occupation was associated with both a decline (females) and improvement (males) in mental health. These results highlight the need for more research on gender specific selection into and out of different occupations in order to progress understandings of gender as a social determinant of health in the work context.

Introduction

Gender is as an important social determinant of health (Krieger, 2003; Phillips, 2005) constructed through norms, roles and relationships within and between groups of women and men (WHO, 2015). This is separate from sex, defined as a biological construct premised upon biological characteristics enabling sexual reproduction (Phillips, 2005). Gender interacts with other social determinants of health, including education and income, as well as employment and working experiences (Hosseinpoor et al., 2012), and may influence health states directly as well as through interaction with other social determinants. Thus, gender may be considered as a fundamental cause of health and health problems (Link and Phelan, 1995).

In the employed population, there is gender patterning across different occupations. For example, in Australia (as in many high income countries), a greater proportion of men are employed in construction related jobs (about 20% of employed males and 4% of employed females), or in higher levels of management (about 16% of employed males and about 9% of employed females) (Australian Bureau of Statistics, 2006). In contrast, females are more likely to be employed in nursing (about 90% of nurses are female) and secretarial work (about 23% of employed females and 6% of employed males) (Australian Bureau of Statistics, 2006). Gender segregation of the workforce first came to the attention of social researchers in the late nineteenth century (Preston, 1999). This phenomenon has persisted across countries and over time. Since the 1960s (which is when women starting entering the workforce in substantial numbers), there has been persistent gender segregation of women into clerical, sales and service occupations in industrialised nations (Preston, 1999).

The nuances of gender in the workforce have generally been ignored in epidemiology, which has traditionally focused on working conditions (employment arrangements, working hours, psychosocial stressors) (Bildt and Michélsen, 2002; Plaisier et al., 2007). However, there is some evidence from a limited number of studies that the gender composition of a job (e.g., the extent to which a job is comprised of males versus females) has an impact on health (Elwer et al., 2013; Elwer et al., 2014; Evans and Steptoe, 2002; Hall, 1989; Hensing and Alexanderson, 2004; Mastekaasa, 2005; Sobiraj et al., 2015). In general, this evidence has suggested that working in a job where the other gender is dominant (e.g., males working in a female dominated occupation, and females working in a male dominated occupation) may have damaging effects on psychological health (Elwer et al., 2013; Sobiraj et al., 2015) and be associated with higher sickness absence (Evans and Steptoe, 2002; Hensing and Alexanderson, 2004).

Explanations for this have drawn on Kanter's (1993) theory of being in a minority demographic group. Kanter (1993) argues that being in a minority (e.g., female in a male dominated occupation) may be particularly damaging because the affected individual may have heightened visibility and thus be subject to stereotyping. Minority status at work might also affect mental health through mechanisms that include differential working conditions and pay (Blau and Kahn, 2016). Another theory posited by Blalock (1967) focuses on the dominance of the majority group and extent to which the minority group can be considered a threat to power and resources. Thus, as women increase in numbers in male-dominated jobs, they may experience poorer treatment, worse conditions and greater discrimination. Although this theory has also been used to describe the dynamics of gender at work, it is important to acknowledge that this theory was developed to explain race relations. Another perspective is that women and men employed in occupations where the other gender is dominant may experience gender-role conflict because they deviate from normative work-arrangements for male and females (Simon, 1995).

A limitation of most past research on the gender composition of the workforce and health is that it has been cross-sectional and/or has not controlled for within person (time invariant) influences (Evans and Steptoe, 2002; Hensing and Alexanderson, 2004; Mastekaasa, 2005; Sobiraj et al., 2015). This is problematic as a comparison between persons (e.g., a female employed in a male dominated versus female dominated occupation) may produce substantially different estimates compared to those that can be found within persons (e.g., a person who changes between a male and female dominated occupation). The analytic approach used in this paper enables us to estimate the differences in mental health between groups defined by the gender dominance of their occupation relative to their own gender. It also allows us to examine how changing the gender dominance of a person's occupation impacts on mental health within-persons, thus capturing the dynamic relationship between gender and work environment.

Using 14 waves of longitudinal data from an Australian working population cohort, we create and describe an occupational gender ratio measure across a range of individual and job characteristics (Aim 1). We then assess the association between the occupational gender ratio and mental health, adjusting for known confounders (Aim 2). Following this, we test if changes in mental health occur for people who change from a gender neutral to a male or female dominated occupation across the 14-year study period (Aim 3). Last, we assess whether the relationship between occupational gender ratio and mental health is modified by a person's own gender (Aim 4). This is important considering gender differences in the working conditions and the overall prevalence of common mental health problems, as women are more likely to report mental health problems than men (WHO, 2015). A major contribution of this paper is to build understanding of the role that gendered contexts have in influencing health outcomes, thereby expanding the conceptualisation of gender from being an individual influence on health (e.g., a person's gender), to an environmental influence (e.g., normative expressions of gendered behaviours at work). From a public health perspective, this paper will provide information on whether the gender composition of a person's job may have an independent effect on their mental health. If so, then this would provide a rationale for targeted prevention initiatives in male or female dominated occupations.

Section snippets

Data source

The Household, Income and Labour Dynamics in Australia (HILDA) survey is a longitudinal, nationally representative study of Australian households established in 2001. It collects detailed information annually from over 13,000 individuals within over 7000 households (Wilkins, 2013). The response rate to wave 1 was 66% (Wilkins, 2013). The survey covers a range of dimensions including social, demographic, health and economic conditions using a combination of face-to-face interviews with trained

Results

Fig. 2 describes the sample selection into the study. Of the 20,231 employed people eligible for this analysis, 1176 had missing data leaving a final sample of 19,055 (Aim 2). Cases with missing data were slightly more likely to be younger and lower education, although differences from participants with non-missing data were non-significant. After restricting to those who changed occupation (Aim 3), there was 11,269 people remaining.

Discussion

This study indicates that: 1) across the working population of the HILDA cohort, being employed in an occupation where your own gender is dominant is associated with slightly higher mental health; 2) among the people who have changed jobs and occupational gender ratio categories, the shift into an occupation where the other gender is dominant is associated with varying (small) effects that are modified by gender. Below we summarise the main results of the paper by separately discussing the

Conclusion

In conclusion, the present study suggests that the gender composition of a person's job may have an independent effect on their mental health. This relationship appears to be nuanced and further research is required. In particular, we would suggest the need for further investigation into gender specific selection into occupations upon entry into the labour market, as well as the movement between and selection out of occupations by gender. At the same time, there is a pressing need for a greater

Contributions

The article and design was conceived by AM, who also conducted analysis. TK checked results and all authors contributed to interpretation of results. AM drafted the manuscript with feedback from all authors. All authors contributed to the final draft of the manuscript.

Financial support

AM is funded by a Victorian Health and Medical Research Fellowship.

Conflicts of interest

We declare no conflicts of interest.

Acknowledgments

This paper uses unit record data from the Household, Income and Labour Dynamics in Australia HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Social Services DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research Melbourne Institute). The findings and views reported in this paper, however, are those of the author and should not be attributed to either DSS or the Melbourne Institute. The data used in this

References (41)

  • D.M. Berwick et al.

    Performance of a five-item mental health screening test

    Med. Care

    (1991)
  • C. Bildt et al.

    Gender differences in the effects from working conditions on mental health: a 4-year follow-up

    Int. Arch. Occup. Environ. Health

    (2002)
  • H.M. Blalock

    Toward a Theory of Minority-group Relations

    (1967)
  • F.D. Blau et al.

    The Gender Wage Gap: Extent, Trends, and Explanations

    (2016)
  • P. Butterworth et al.

    The psychosocial quality of work determines whether employment has benefits for mental health: results from a longitudinal national household panel survey

    Occup. Environ. Med.

    (2011)
  • J. Campos-Serna et al.

    Gender inequalities in occupational health related to the unequal distribution of working and employment conditions: a systematic review

    Int. J. Equity Health

    (2013)
  • J.E. Clougherty et al.

    Gender and sex differences in job status and hypertension

    Occup. Environ. Med.

    (2011)
  • D.G. Contopoulos-Ioannidis et al.

    Reporting and interpretation of SF-36 outcomes in randomised trials: systematic review

    BMJ

    (2009)
  • J.L. Dieleman et al.

    Random-effects, fixed-effects and the within-between specification for clustered data in observational health studies: a simulation study

    PLoS One

    (2014)
  • S. Elwer et al.

    Patterns of gender equality at workplaces and psychological distress

    PLoS One

    (2013)
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