Methodological Perspectives on the Study of the Health Effects of Unemployment – Reviewing the Mode of Unemployment, the Statistical Analysis Method and the Role of Confounding Factors

Introduction: Studying the relationship between unemployment and health raises many methodological challenges. In the current study, the aim was to evaluate how different ways of measuring unemployment and the choice of statistical model affects the effect estimate. Methods: The Northern Swedish cohort was used, and two follow-up surveys thereof from 1995 and 2007, as well as register data about unemployment. Self-reported current unemployment, self-reported accumulated unemployment and register-based accumulated unemployment were used to measure unemployment and its effect on self-reported health was evaluated. Analyses were conducted with G-computation, logistic regression and three estimators for the inverse probability weighting propensity scores, and 11 potentially confounding variables were part of the analyses. Results were presented with absolute differences in the proportion with poor self-reported health between unemployed and employed individuals for all estimators but logistic regression. Results: Of the initial 1083 pupils in the cohort, 488–693 individuals were defined as employed and 61–214 individuals were defined as unemployed in our different analyses. In the analyses, the deviation was large between the unemployment measures, with a difference of at least 2.5% in effect size when unemployed was compared with employed for the self-reported and register-based unemployment modes. The choice of statistical method only had a small influence on effect estimates and the deviation was in most cases lower than 1%. When models were compared based on the choice of potential confounders in the analytical model, the deviations were rarely above 0.6% when comparing models with 4 and 11 potential confounders. Our variable for health selection was the only one that strongly affected estimates when it was not part of the statistical model. Conclusions: Misspecifications of the statistical model or choice of analytical method might not matter much for effect estimates of the relationship between unemployment and health except for the inclusion of a variable measuring earlier health status before becoming unemployed. On the other hand, how unemployment is measured is highly important.