SSM: Population Health (Jun 2023)

A quantitative assessment of the frequency and magnitude of heterogeneous treatment effects in studies of the health effects of social policies

  • Dakota W. Cintron,
  • Laura M. Gottlieb,
  • Erin Hagan,
  • May Lynn Tan,
  • David Vlahov,
  • M. Maria Glymour,
  • Ellicott C. Matthay

Journal volume & issue
Vol. 22
p. 101352

Abstract

Read online

Substantial heterogeneity in effects of social policies on health across subgroups may be common, but has not been systematically characterized. Using a sample of 55 contemporary studies on health effects of social policies, we recorded how often heterogeneous treatment effects (HTEs) were assessed, for what subgroups (e.g., male, female), and the subgroup-specific effect estimates expressed as Standardized Mean Differences (SMDs). For each study, outcome, and dimension (e.g., gender), we fit a random-effects meta-analysis. We characterized the magnitude of heterogeneity in policy effects using the standard deviation of the subgroup-specific effect estimates (τ). Among the 44% of studies reporting subgroup-specific estimates, policy effects were generally small ( 0.1 SMDs. For 26% of study-outcome-dimensions, the magnitude of τ indicated that effects of opposite signs were plausible across subgroups. Heterogeneity was more common in policy effects not specified a priori. Our findings suggest social policies commonly have heterogeneous effects on health of different populations; these HTEs may substantially impact disparities. Studies of social policies and health should routinely evaluate HTEs.

Keywords