The Impact of Unemployment on Depression: Combining the Parametric G-Formula and Individual Intercepts to Adjust for Time-Varying Confounding and Unobserved Selection

Maarten J. Bijlsma, Max Planck Institute for Demographic Research
Ben Wilson, Stockholm University
Lasse Tarkiainen, University of Helsinki
Mikko Myrskyla , Max Planck Institute for Demographic Research
Pekka Martikainen, University of Helsinki

The estimated effect of unemployment on depression may be biased by time-varying, intermediate, and time-constant confounding. To address this, we apply a g-formula with individual-level fixed-effect intercepts to estimate how antidepressant purchasing is affected by a hypothetical intervention that provides employment to the unemployed. We use sample of the Finnish adult population (n = 49,753). We compare estimates that adjust for various baseline confounders and time-varying socio-economic covariates (confounders and mediators) with estimates that also include individual-level fixed-effect intercepts. In the empirical data around 10% of person-years are unemployed. Setting these person-years to employed, the g-formula without individual intercepts found a 5% (95% CI: 2.5 to 7.4%) reduction in antidepressant purchasing at the population-level. However, when also adjusting for individual intercepts, we find no effect (-0.1%, 95% CI: -1.8 to 1.5%). The results indicate that the relationship between unemployment and depression is confounded by residual time-constant confounding (selection).

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 Presented in Session 5. Health & Mortality 1