Using spatial Bayesian models to estimate associations between structural racial discrimination and disparities in severe maternal morbidity.

INTRODUCTION

The United States maternal health crisis is especially profound in Georgia, disproportionately affecting Black birthing people. In Georgia, 35% of all births are to Black-identifying people, with rates of severe maternal morbidity (SMM) significantly exceeding national averages.

METHODS

The sample population comprised Georgia linked live birth/fetal death certificate and hospital discharge data for deliveries from 2013 to 2021. Structural racial discrimination (SRD) was defined at the county level using four domains. We estimated county-specific rates of SMM using Bayesian conditional autoregressive Poisson models and compared the rate difference in SMM for Black versus white birthing people across domain-specific strata of SRD.

RESULTS

The sample included 709,335 deliveries to Black and white birthing people. The prevalence of SMM was higher among births to Black individuals compared to white counterparts (3.2% vs. 1.7%), with a mean risk difference of 13.1 per 1000 deliveries between race groups. Results of the SRD-SMM regression demonstrated larger Black-white racial disparities in counties with the highest concentration of resource deprivation compared to the highest concentration of affluence (B: 4.5, 95% CI: 1.1, 8.0). Similarly, in counties with a greater polarization of Black and low-income residents, the disparity was larger compared to counties with greater racial and income homogeneity (B: 3.84, 95% CI: 0.22, 7.44).

CONCLUSIONS

Our results highlight the nuanced relationship between structural racism and health outcomes in Georgia. SMM rates were higher among Black birthing people compared to their white counterparts.