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A Bayesian approach for exploring the effects of household income on self-reported mental health measures during the COVID-19 pandemic

AI Summary
  • Older age associated with lower depression and anxiety in both genders during the COVID-19 pandemic.
  • Higher income consistently linked to better mental health in males across both waves.
  • In females, higher income was weakly linked to more symptoms early then became protective by Wave 6; lowest income showed similar distress across genders.
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PLOS Ment Health. 2026 Aug 25;3(8):e0000691. doi: 10.1371/journal.pmen.0000691. eCollection 2026.

ABSTRACT

The relationship between income and mental health is well-established yet complex, as both can be confounded by age, gender, and other demographic factors. To clarify these dynamics, this study examines the effects of age and income on symptoms of depression and generalised anxiety across female and male genders during the COVID-19 pandemic in the UK. Data from Wave-1 and Wave-6 of the COVID-19 Psychological Research Consortium (C19PRC) study were analysed using Bayesian hierarchical ordered-logistic mediation models. Results showed that older age was linked to less depression and anxiety in both genders. Higher income was linked to better mental health in males in both waves. For females, however, higher income was only weakly linked to more symptoms early in the pandemic, but by Wave‑6, it had become a substantially protective factor for their mental health. Additionally, males reported better mental health than females across most income groups, except at the lowest income group, where both genders experienced comparable distress. Using robust inferential statistical models, our findings explain the nuanced relationships between socioeconomic factors and mental health across genders during a public health crisis. This evidence can inform targeted mental health policies and economic support programs for future emergencies.

PMID:42640907 | DOI:10.1371/journal.pmen.0000691

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