Structural racism and quantitative causal inference: A life course mediation framework for decomposing racial health disparities


Quantitative studies of racial health disparities often use static measures of self-reported race and conventional regression estimators, which critics argue is inconsistent with social-constructivist theories of race, racialization, and racism. We demonstrate an alternative counterfactual approach to explain how multiple racialized systems dynamically shape health over time, examining racial inequities in cardiometabolic risk in the National Longitudinal Study of Adolescent to Adult Health. This framework accounts for the dynamics of time-varying confounding and mediation that is required in operationalizing a race variable as part of a social process (racism) rather than a separable, individual characteristic. We decompose the observed disparity into three types of effects, a controlled direct effect (unobserved racism), proportions attributable to interaction (racial discrimination), and pure indirect effects (emergent discrimination). We discuss the limitations of counterfactual approaches while highlighting how they can be combined with critical theories to quantify how interlocking systems produce racial health inequities.

Journal of Health and Social Behavior
Nick Graetz
Nick Graetz
Postdoctoral Research Associate, Princeton University

My research interests include population health, structural racism, housing policy, small area estimation, and causal mediation analysis.