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OP159 How would the introduction of a Universal Basic Income influence mental health inequalities in the UK? A microsimulation modelling study
  1. Rachel M Thomson1,
  2. Daniel Kopasker1,
  3. Patryk Bronka2,
  4. Matteo Richiardi2,
  5. Vladimir Khodygo1,
  6. Andrew J Baxter1,
  7. Erik Igelström1,
  8. Anna Pearce1,
  9. Alastair Leyland1,
  10. S Vittal Katikireddi1
  1. 1MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
  2. 2Institute for Social and Economic Research, University of Essex, Essex, UK


Background Population mental health has deteriorated in many high-income countries over the last decade. Novel welfare policies such as Universal Basic Income (UBI) have been suggested as potential approaches to improve mental health. However, no studies have trialled or modelled UBI at a whole population level or considered impacts on mental health inequalities. We simulated the effects of introducing a UBI on mental health for UK working-age adults.

Methods We used the SimPaths microsimulation model, which integrates econometric and causal epidemiology analyses to model effects of UK tax/benefit policies on mental health. Adults aged 25–64 were simulated from 2022–2026. Data from the nationally representative UK Household Longitudinal Study were used to generate the simulated population, and causal effect estimates of income/employment transitions on short-term mental health using marginal structural modelling. Three counterfactual UBI scenarios of increasing generosity were simulated from 2023: ‘Partial’ (equivalent to existing benefits), ‘Full’ (equivalent to the 2022 UK Minimum Income Standard), and ‘Full+’ (retained means-tested benefits for disability, housing, and childcare). The ‘Baseline’ scenario simulated planned tax/benefit policies for 2023–26. Likely common mental disorder (CMD) was measured using the General Health Questionnaire (GHQ-12, score ≥ 4). Relative and slope indices of inequality (RII/SII) by education were calculated. Simulations were run 1,000 times to generate 95% uncertainty intervals. Sensitivity analyses relaxed assumptions about likely employment effects of UBI in Full/Full+ scenarios.

Results Partial UBI slightly reduced poverty (before housing costs) but had no impact on mental health. Full UBI scenarios substantially reduced poverty, from 9.1% (8.5–9.7) to 0.01% (0.00–0.03), but decreased employment from 78.9% (77.9–79.9) to 74.1% (72.6–75.4). In our primary analysis, with Full+ UBI absolute CMD prevalence increased by 0.38% (0.13–0.69), a rise of 158,004 cases (54,054–286,902). In sensitivity analyses assuming minimal employment effects, CMD prevalence instead fell by 0.26% (-0.46, -0.05), a reduction of 108,108 cases (20,790–191,268). In both analyses, effects waned by 2026. Despite a small gradient in effect by education, there was no significant effect of any scenario on mental health inequalities: for Full+ UBI, RII reduced from 1.33 (1.13, 1.56) in the Baseline scenario by 0.03 points (-0.09, 0.02) in primary analysis and 0.02 (-0.06, 0.02) in sensitivity analysis.

Conclusion UBI has potential to improve short-term population mental health, but impacts are highly contingent on individual choices around employment following its introduction. In our simulation, UBI had no clear impact on mental health inequalities.

  • Welfare policy
  • policy modelling
  • mental health

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