Short-term impacts of Universal Basic Income on population mental health inequalities in the UK: a microsimulation modelling study

Thomson, R. M. , Kopasker, D. , Bronka, P., Richiardi, M., Khodygo, V. , Baxter, A. J. , Igelström, E. , Pearce, A. , Leyland, A. H. and Katikireddi, S. V. (2024) Short-term impacts of Universal Basic Income on population mental health inequalities in the UK: a microsimulation modelling study. PLoS Medicine, 21(3), e1004358. (doi: 10.1371/journal.pmed.1004358) (PMID:38437214)

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Abstract

Background: Population mental health in the United Kingdom (UK) has deteriorated, alongside worsening socioeconomic conditions, over the last decade. Policies such as Universal Basic Income (UBI) have been suggested as an alternative economic approach to improve population mental health and reduce health inequalities. UBI may improve mental health (MH), but to our knowledge, no studies have trialled or modelled UBI in whole populations. We aimed to estimate the short-term effects of introducing UBI on mental health in the UK working-age population. Methods and findings: Adults aged 25 to 64 years were simulated across a 4-year period from 2022 to 2026 with the SimPaths microsimulation model, which models the effects of UK tax/benefit policies on mental health via income, poverty, and employment transitions. Data from the nationally representative UK Household Longitudinal Study were used to generate the simulated population (n = 25,000) and causal effect estimates. Three counterfactual UBI scenarios were modelled from 2023: “Partial” (value equivalent to existing benefits), “Full” (equivalent to the UK Minimum Income Standard), and “Full+” (retaining means-tested benefits for disability, housing, and childcare). Likely common mental disorder (CMD) was measured using the General Health Questionnaire (GHQ-12, score ≥4). Relative and slope indices of inequality were calculated, and outcomes stratified by gender, age, education, and household structure. Simulations were run 1,000 times to generate 95% uncertainty intervals (UIs). Sensitivity analyses relaxed SimPaths assumptions about reduced employment resulting from Full/Full+ UBI. Partial UBI had little impact on poverty, employment, or mental health. Full UBI scenarios practically eradicated poverty but decreased employment (for Full+ from 78.9% [95% UI 77.9, 79.9] to 74.1% [95% UI 72.6, 75.4]). Full+ UBI increased absolute CMD prevalence by 0.38% (percentage points; 95% UI 0.13, 0.69) in 2023, equivalent to 157,951 additional CMD cases (95% UI 54,036, 286,805); effects were largest for men (0.63% [95% UI 0.31, 1.01]) and those with children (0.64% [95% UI 0.18, 1.14]). In our sensitivity analysis assuming minimal UBI-related employment impacts, CMD prevalence instead fell by 0.27% (95% UI −0.49, −0.05), a reduction of 112,228 cases (95% UI 20,783, 203,673); effects were largest for women (−0.32% [95% UI −0.65, 0.00]), those without children (−0.40% [95% UI −0.68, −0.15]), and those with least education (−0.42% [95% UI −0.97, 0.15]). There was no effect on educational mental health inequalities in any scenario, and effects waned by 2026. The main limitations of our methods are the model’s short time horizon and focus on pathways from UBI to mental health solely via income, poverty, and employment, as well as the inability to integrate macroeconomic consequences of UBI; future iterations of the model will address these limitations. Conclusions: UBI has potential to improve short-term population mental health by reducing poverty, particularly for women, but impacts are highly dependent on whether individuals choose to remain in employment following its introduction. Future research modelling additional causal pathways between UBI and mental health would be beneficial.

Item Type:Articles
Additional Information:This work was supported by the Wellcome Trust (218105/Z/19/Z and 205412/Z/16/Z), European 586 Research Council (949582), Health Foundation (2135162), Medical Research Council 587 (MC_UU_00022/2) and Chief Scientist Office (SPHSU17).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Igelström, Erik and Pearce, Dr Anna and Katikireddi, Professor Vittal and Kopasker, Dr Daniel and Baxter, Dr Andy and Thomson, Dr Rachel and Leyland, Professor Alastair and Khodygo, Dr Vladimir
Authors: Thomson, R. M., Kopasker, D., Bronka, P., Richiardi, M., Khodygo, V., Baxter, A. J., Igelström, E., Pearce, A., Leyland, A. H., and Katikireddi, S. V.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
Journal Name:PLoS Medicine
Publisher:Public Library of Science
ISSN:1549-1277
ISSN (Online):1549-1676
Published Online:04 March 2024
Copyright Holders:Copyright © 2024 Thomson et al.
First Published:First published in PLoS Medicine 21(3): e1004358
Publisher Policy:Reproduced under a Creative Commons License
Data DOI:10.5255/UKDA-SN-6614-19

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
306430Predicting the impacts of universal basic income on mental health inequalities in the UK population: a microsimulation modelRachel ThomsonWellcome Trust (WELLCOTR)218105/Z/19/ZSHW - MRC/CSO Social & Public Health Sciences Unit
174091Improving life chances & reducing child health inequalities: harnessing the untapped potential of existing dataAnna PearceWellcome Trust (WELLCOTR)205412/Z/16/ZSHW - MRC/CSO Social & Public Health Sciences Unit
308851HEEDSrinivasa KatikireddiEuropean Research Council (ERC)949582SHW - MRC/CSO Social & Public Health Sciences Unit
311928Assessing the impacts of economic policy responses to the COVID-19 pandemic on mental health: A microsimulation modelling studySrinivasa KatikireddiThe Health Foundation (HEALFOU)2135162SHW - MRC/CSO Social & Public Health Sciences Unit
3048230021Inequalities in healthAlastair LeylandMedical Research Council (MRC)MC_UU_00022/2HW - MRC/CSO Social and Public Health Sciences Unit
3048230071Inequalities in healthAlastair LeylandOffice of the Chief Scientific Adviser (CSO)SPHSU17HW - MRC/CSO Social and Public Health Sciences Unit