Mediation Analysis of Racial Disparity for Infant Mortality Using Bayesian Estimation of Potential Outcomes

Abstract

Background/Objectives: While the overall rate of infant mortality in the United States has been decreasing over decades, the racial disparity, defined as the difference between races, has increased. Even though a person’s race cannot change, it may be possible to identify factors that mediate or cause this racial disparity. Evaluating the factors that mediate or cause racial disparity is imperative because current clinical recommendations could be based on preventative modalities that are more effective for white women and their children. Methods: A Bayesian approach modeled the data from the full United States National Natality Database for the years 2016 to 2018. The binomial rate parameters for each combination of race and mediators provided the potential outcomes. Estimating the mediation outcomes, including total effect, controlled direct effect, mediated effect, and proportion mediated used common counterfactual definitions for these probabilities. Results: Maternal smoking, low birthweight, and teenage maternity interacted in causing racial disparity for infant mortality. The proportion of racial disparity attributable to low birthweight was approximately 0.73, with only small variations attributable to maternal smoking and teenage maternity. Conclusions: The novel approach facilitated modeling of multiple mediators. Low birthweight caused racial disparity for infant mortality. The model can be extended to evaluate additional mediational factors with the objective of identifying the preventable causes.