Evaluating whether social policies reduce health inequalities is complicated by the fact that these upstream determinants may also change the socioeconomic distribution. Failure to account for these compositional changes may severely bias the effect estimation procedure. In this article, we illustrate how a health inequality impact assessment of a policy that (also) changes the socioeconomic distribution may produce biased results. First, we show why analyses that do not account for compositional changes fail to estimate the correct counterfactual outcome. This problem most notably occurs when using repeated cross-sectional data, often the only available option to evaluate the health effect of large-scale policies. Second, we conducted a microsimulation study to estimate the magnitude of the bias under various conditions. The results showed that the actual impact of the policy on health inequalities is often underestimated and may even produce results that are in the opposite direction of the actual causal effect of the policy. Future studies should explore new strategies, such as simulation methods, to assess the impact of policies that (also) cause changes in the socioeconomic composition of the population, to enable researchers to accurately estimate their effect on health inequalities.
Bibliographical noteFunding Information:
The study was supported by a grant from the Netherlands Organization for Health Research and Development (ZonMw) (project number 531003013 ). The funders had no role in the study design or the analysis and interpretation of the data. All authors and their institutions reserve intellectual freedom from the funders.
© 2021 The Author(s)