Princeton University, Princeton, NJ, USA.
University of Pennsylvania, Philadelphia, PA, USA.
J Health Soc Behav. 2022 Jun;63(2):232-249. doi: 10.1177/00221465211066108. Epub 2022 Jan 8.
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 () 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.
种族健康差异的定量研究通常使用自我报告的种族的静态衡量标准和常规回归估计器,批评者认为这与种族、种族化和种族主义的社会建构主义理论不一致。我们展示了一种替代的反事实方法,以解释多个种族化系统如何随时间动态塑造健康,研究了全国青少年至成人健康纵向研究中心血管代谢风险的种族不平等。该框架考虑了随时间变化的混杂和中介的动态,这在将“种族”变量作为社会过程的一部分(而不是可分离的个体特征)来操作时是必需的。我们将观察到的差异分解为三种效应:受控直接效应(“未观察到的种族主义”)、归因于相互作用的比例(“种族歧视”)和纯粹间接效应(“新兴歧视”)。我们讨论了反事实方法的局限性,同时强调了如何将它们与批判性理论相结合,以量化连锁系统如何产生种族健康不平等。