Which is most important for mental health: Money, poverty, or paid work? A fixed-effects analysis of the UK Household Longitudinal Study
Background: The relative importance of income, poverty and unemployment status for mental health is unclear, and understanding this has implications for income and welfare policy design. We aimed to assess the association between changes in these exposures and mental health. Methods: We measured eff...
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doaj-d42d5445b60e4ef9a6c14fe0d38f8c8f2021-10-01T05:04:15ZengElsevierSSM: Population Health2352-82732021-09-0115100909Which is most important for mental health: Money, poverty, or paid work? A fixed-effects analysis of the UK Household Longitudinal StudyTheocharis Kromydas0Rachel M. Thomson1Andrew Pulford2Michael J. Green3S. Vittal Katikireddi4MRC/CSO Social & Public Health Sciences Unit, University of Glasgow, United KingdomMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, United KingdomMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, United Kingdom; Public Health Scotland, United KingdomMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, United KingdomMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, United Kingdom; Public Health Scotland, United Kingdom; Corresponding author. MRC/CSO Social and Public Health Sciences Unit, University of Glasgow Berkeley Square, 99 Berkeley St, Glasgow G3 7HR, United Kingdom.Background: The relative importance of income, poverty and unemployment status for mental health is unclear, and understanding this has implications for income and welfare policy design. We aimed to assess the association between changes in these exposures and mental health. Methods: We measured effects of three transition exposures between waves of the UK Household Longitudinal Study from 2010/11–2019/20 (n=38,697, obs=173,859): income decreases/increases, moving in/out of poverty, and job losses/gains. The outcome was General Health Questionnaire (GHQ), which measures likelihood of common mental disorder (CMD) as a continuous (GHQ-36) and binary measure (score ≥4 = case). We used fixed-effects linear and linear probability models to adjust for time invariant and time-varying confounders. To investigate effect modification, we stratified analyses by age, sex and highest education. Results: A 10% income decrease/increase was associated with a 0.02% increase (95% CI 0.00, 0.04) and 0.01% reduction (95% CI -0.03, 0.02) in likelihood of CMD respectively. Effect sizes were larger for moving into poverty (+1.8% [0.2, 3.5]), out of poverty (−1.8%, [-3.2, −0.3]), job loss (+15.8%, [13.6, 18.0]) and job gain (−11.4%, [-14.4, −8.4]). The effect of new poverty was greater for women (+2.3% [0.8, 3.9] versus +1.2% [-1.1, 3.5] for men) but the opposite was true for job loss (+17.8% [14.4, 21.2] for men versus +13.5% [9.8, 17.2] for women). There were no clear differences by age, but those with least education experienced the largest effects from poverty transitions, especially moving out of poverty (−2.9%, [-5.7, −0.0]). Conclusions: Moving into unemployment was most strongly associated with CMD, with poverty also important but income effects generally much smaller. Men appear most sensitive to employment transitions, but poverty may have larger impacts on women and those with least education. As the COVID-19 pandemic recedes, minimising unemployment as well as poverty is crucial for population mental health.http://www.sciencedirect.com/science/article/pii/S2352827321001841Mental healthIncomePovertyEmploymentWelfareHealth inequalities |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Theocharis Kromydas Rachel M. Thomson Andrew Pulford Michael J. Green S. Vittal Katikireddi |
spellingShingle |
Theocharis Kromydas Rachel M. Thomson Andrew Pulford Michael J. Green S. Vittal Katikireddi Which is most important for mental health: Money, poverty, or paid work? A fixed-effects analysis of the UK Household Longitudinal Study SSM: Population Health Mental health Income Poverty Employment Welfare Health inequalities |
author_facet |
Theocharis Kromydas Rachel M. Thomson Andrew Pulford Michael J. Green S. Vittal Katikireddi |
author_sort |
Theocharis Kromydas |
title |
Which is most important for mental health: Money, poverty, or paid work? A fixed-effects analysis of the UK Household Longitudinal Study |
title_short |
Which is most important for mental health: Money, poverty, or paid work? A fixed-effects analysis of the UK Household Longitudinal Study |
title_full |
Which is most important for mental health: Money, poverty, or paid work? A fixed-effects analysis of the UK Household Longitudinal Study |
title_fullStr |
Which is most important for mental health: Money, poverty, or paid work? A fixed-effects analysis of the UK Household Longitudinal Study |
title_full_unstemmed |
Which is most important for mental health: Money, poverty, or paid work? A fixed-effects analysis of the UK Household Longitudinal Study |
title_sort |
which is most important for mental health: money, poverty, or paid work? a fixed-effects analysis of the uk household longitudinal study |
publisher |
Elsevier |
series |
SSM: Population Health |
issn |
2352-8273 |
publishDate |
2021-09-01 |
description |
Background: The relative importance of income, poverty and unemployment status for mental health is unclear, and understanding this has implications for income and welfare policy design. We aimed to assess the association between changes in these exposures and mental health. Methods: We measured effects of three transition exposures between waves of the UK Household Longitudinal Study from 2010/11–2019/20 (n=38,697, obs=173,859): income decreases/increases, moving in/out of poverty, and job losses/gains. The outcome was General Health Questionnaire (GHQ), which measures likelihood of common mental disorder (CMD) as a continuous (GHQ-36) and binary measure (score ≥4 = case). We used fixed-effects linear and linear probability models to adjust for time invariant and time-varying confounders. To investigate effect modification, we stratified analyses by age, sex and highest education. Results: A 10% income decrease/increase was associated with a 0.02% increase (95% CI 0.00, 0.04) and 0.01% reduction (95% CI -0.03, 0.02) in likelihood of CMD respectively. Effect sizes were larger for moving into poverty (+1.8% [0.2, 3.5]), out of poverty (−1.8%, [-3.2, −0.3]), job loss (+15.8%, [13.6, 18.0]) and job gain (−11.4%, [-14.4, −8.4]). The effect of new poverty was greater for women (+2.3% [0.8, 3.9] versus +1.2% [-1.1, 3.5] for men) but the opposite was true for job loss (+17.8% [14.4, 21.2] for men versus +13.5% [9.8, 17.2] for women). There were no clear differences by age, but those with least education experienced the largest effects from poverty transitions, especially moving out of poverty (−2.9%, [-5.7, −0.0]). Conclusions: Moving into unemployment was most strongly associated with CMD, with poverty also important but income effects generally much smaller. Men appear most sensitive to employment transitions, but poverty may have larger impacts on women and those with least education. As the COVID-19 pandemic recedes, minimising unemployment as well as poverty is crucial for population mental health. |
topic |
Mental health Income Poverty Employment Welfare Health inequalities |
url |
http://www.sciencedirect.com/science/article/pii/S2352827321001841 |
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