Evidence map›Paper›PMID 39635463›Full record

ArticleSSM - population health2024

Using a causal decomposition approach to estimate the contribution of employment to differences in mental health profiles between men and women.

Christa Orchard, Elizabeth Lin, Laura Rosella, Peter M Smith

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Article in SSM - population health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Christa OrchardDalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
Elizabeth LinICES, Ontario, Canada.
Laura RosellaDalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
Peter M SmithDalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mental health disorders are known to manifest differently in men and women, however our understanding of how gender interacts with mental health and well-being as a broader construct remains limited. Employment is a key determinant of mental health and there are historical differences in occupational roles among men and women that continue to influence working lives (Bonde, 2008; Cabezas-Rodríguez, Utzet, & Bacigalupe, 2021; Drolet, 2022; Gedikli, Miraglia, Connolly, Bryan, & Watson, 2023; Moyser, 2017; Niedhammer, Bertrais, & Witt, 2021; Stier & Yaish, 2014; Van der Doef & Maes, 1999). This study aims to explore differences in multidimensional mental health between men and women, and to quantify how these differences may change if women had the same employment characteristics as men. Methods: Working-age adults (25-64) were identified through a household survey in Ontario, Canada during 2012. We created multifaceted measures of employment to capture both employment and job quality, as well as multidimensional mental health profiles that capture mental health disorders and well-being using survey data. A causal decomposition approach with Monte Carlo simulation methods estimated the change in differences in mental health profiles between men and women, if women had the same employment characteristics as men. Results: Among 2458 eligible respondents, women were more likely to exhibit clinical mood disorders compared to men, with men more likely to exhibit absence of flourishing without a diagnosable disorder. Among those who were flourishing, women more often expressed at least some life stress compared to men. When women were assigned men's employment characteristics, which amounted to an increase in employment and higher quality employment, some of the gender differences in risk of clinical mood disorder decreased. However, differences between men and women in the remaining mental health profiles increased. Conclusions: This study provided an estimate of the contribution of employment to the observed differences in multidimensional mental health between men and women. This adds to the literature by including a broader range of mental health indicators than disorders alone, and by formalizing the causal framework used to study these relationships.

Indexed as

Causal analysisEmploymentGender roleMental healthSocial determinants of healthWell-being

Identifiers

PMID39635463
PMCPMC11615145

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.