Examining the relationship between income and both mental and physical health among adults in the UK: Analysis of 12 waves (2009-2022) of Understanding Society

PLoS One. 2025 Mar 6;20(3):e0316792. doi: 10.1371/journal.pone.0316792. eCollection 2025.

ABSTRACT

There is growing evidence of a causal relationship between income and health. At the same time, pressure on reactive health and care services in the UK is increasing. Previous work to quantify the relationship has focused on particular age groups, conditions, or single-item self-rated health. This article reports findings from a study that aimed to provide more comprehensive estimates with an objective of creating an evidential basis for microsimulation modelling of upstream income interventions. We analyse the relationship between income and two health measures – SF-12 Mental Component Summary (MCS-12) and Physical Component Summary (PCS-12) – across 12 waves (2009/11-2020/22) of Understanding Society: The UK Household Longitudinal Study. Using a ‘within-between’ model (Model 1), we find that increases in income compared with an individual’s average and a higher income compared with the sample average is associated with better mental health (higher MCS-12 score) and better functional physical health (higher PCS-12 score). However, for a given increase in household income (say £100 per month), the association with better mental and physical health is smaller at higher incomes. This suggests that redistribution from high-income to lower income households would increase average population physical and mental health, other things being equal. Using a random-effects logistic regression (Model 2), we similarly find that average income quintile is inversely and monotonically associated with the probability of having clinically significant symptoms of depressive disorders (MCS-12 ≤ 45.6) and physical health problems (PCS-12 score ≤ 50.0), with smaller changes in these probabilities from increases in income at higher points in the income distribution. These findings facilitate microsimulation modelling including an estimation of the impact of changes in QALYs, from changes in income, enabling a more detailed and complete understanding of which socioeconomic interventions might begin to address some of the causes of long-term health conditions that are underpinned by socioeconomic determinants.

PMID:40048442 | DOI:10.1371/journal.pone.0316792