Abstract
Basic Income is a largely unconditional, regular payment to all permanent residents to support basic needs. It has been proposed as an upstream health intervention by increasing income size and security. Modelling has quantified prospective effects on UK young people's mental health. This paper extends this analysis to mental and physical health among adults aged 18+ using data from the 2021/22 Family Resources Survey and 12 waves (2009/11-2020/22) of Understanding Society to model the effects of three prospective schemes: 1) (£ per week) £50 per under-18, £75 per 18-64, £205 per 65+; 2) £75, £185, £205; 3) £100, £295, £295. We estimated effects on cases of depressive disorders (SF-12 MCS ≤45.6) and physical health problems (SF-12 PCS ≤50), quality-adjusted life years (QALYs) and willingness-to-pay value gained, as well as direct NHS, personal social services and patients' associated costs savings regarding depressive disorders. Between 124,000 (95% CI: 86,000-150,000) and 1.005m (95% CI: 845,000-1.402m) cases of depressive disorders and 118,000 (70,000-156,000) to 1.042m (881,000-1.612m) cases of physical health problems could be prevented or postponed each year depending on the scheme. 129,000 (86,000-172,000) to 655,000 (440,000-870,000) QALYs could be gained, valued at £3.87bn (£2.58bn-£5.16bn) to £19.65bn (£13.21bn-£26.10bn). Estimated 2023 NHS and personal social services cost savings are between £126m (£88m-£154m) and £1.026bn (£872m-£1.432bn) assuming 50% of depressive disorders cases are diagnosed and treated at baseline. Estimating savings based on physical health problems is more difficult, but may reflect far greater related NHS and social care spend. Although non-income change impacts are not microsimulated, these findings indicate that Basic Income could provide substantial population health benefits, social return on investment and health and social care system savings. This gives policymakers and researchers an evidence base on which to base trial and policy design. Basic Income; Social determinants; Prevention; Upstream interventions; Microsimulation modelling.