A growing body of empirical research seeks to quantify the causal effects of social policies on health by exploiting variation in the timing of policy changes across places. However, multiple social policies are often adopted simultaneously or in close succession in the same locations, creating clustering which must be handled analytically for valid inferences. Although this is a substantial methodological challenge for studies aiming to isolate social policy effects, yet systematic assessments

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... of available analytic solutions and tradeoffs among approaches are lacking. We designated eight analytic solutions prior researchers have adopted, including efforts to disentangle individual policy effects and efforts to estimate the joint effects of clustered policies. We leveraged an existing systematic review of social policies and health to evaluate how often policy clustering is identified as a threat to validity and how often each analytic solution is applied in practice. Of the 55 studies, only 17 (31%) reported checking for any clustered policies, and 36 (67%) used at least one approach that helps address clustered policies. The most common approaches were adjusting for clustered policies, defining the outcome on subpopulations likely to be affected by the policy of interest but not other clustered policies, and selecting a less-correlated measure of policy exposure were the most common approaches. Systematically assessing policy clustering and applying analytic solutions when necessary would strengthen future studies on the health effects of social policies. Adequate reporting on these analytic decisions would facilitate evaluating validity and interpreting study findings.