A data linkage study of the effects of the Great Recession and austerity on antidepressant prescription usage.

Abstract

BACKGROUND\nInternational literature shows unemployment and income loss during the Great Recession worsened population mental health. This individual-level longitudinal study examines how regional economic trends and austerity related to depression using administrative prescription data for a large and representative population sample.\n\n\nMETHODS\nRecords from a sample of the Scottish Longitudinal Study (N=86\xa0500) were linked to monthly primary care antidepressant prescriptions (2009-15). Regional economic trends were characterized by annual full-time employment data (2004-14). Economic impact of austerity was measured via annual income lost per working age adult due to welfare reforms (2010-15). Sequence analysis identified new cases of antidepressant use, and group-based trajectory modelling classified regions into similar economic trajectories. Multi-level logistic regression examined relationships between regional economic trends and new antidepressant prescriptions. Structural equation mediation analysis assessed the contributory role of welfare reforms.\n\n\nRESULTS\nEmployed individuals living in regions not recovering post-recession had the highest risk of beginning a new course of antidepressants (AOR 1.23; 95% CI 1.08-1.38). Individuals living in areas with better recovery trajectories had the lowest risk. Mediation analyses showed that 50% (95% CI 7-61%) of this association was explained by the impact of welfare benefit reforms on average incomes.\n\n\nCONCLUSIONS\nFollowing the Great Recession, local labour market decline and austerity measures were associated with growing antidepressant usage, increasing regional inequalities in mental health. The study evidences the impact of austerity on health inequalities and suggests that economic conditions and welfare policies impact on population health. Reducing the burden of mental ill-health primarily requires action on the social determinants.