Perinatal & Pediatric
Using spatial Bayesian models to estimate associations between structural racism and severe maternal morbidity disparities in Georgia Jasmin Eatman* Jasmin Eatman Katherine Campbell Kait Stanhope Sheree Boulet
The maternal health crisis is especially profound in the state of Georgia, where 35% of births are to Black-identifying people, and rates of severe maternal morbidity (SMM) exceed national averages. Our goal was to estimate associations between contemporary and historic indicators of structural racial discrimination (SRD) and Black-white county-level SMM disparities.
We used Georgia linked live birth/fetal death certificate and hospital discharge data for deliveries to Black and white birthing people for 2013-2020. Instances of SMM during hospitalization occurring intrapartum, delivery, or up to 42 days postpartum were included as an outcome event. Structural racism was defined at the county-level using multiple domains: residential processes, political representation, criminal justice, and historic oppression. We estimated the association of the change in SMM rate difference between Black and White birthing people with measures of SRD using Bayesian spatial models.
The sample included 709,335 deliveries to Black and White individuals and prevalence of SMM was higher among births to Black individuals (31.7 per 1,000) compared to White (18.0 per 1,000) with mean rate difference of 13.7 per 1,000 deliveries. Results of the SRD-SMM regression showed differences solely among residential processes measures comparing spatial polarization of income and the combination of race and income distributions. The estimated change in SMM rate difference between Black and white birthing people increased by 4.5 per 1,000 deliveries in the lowest income counties compared to the highest (B: 4.5, 95% CI: 1.1, 8.0) and increased by 3.8 per 1,000 for concentrated racial/economic disadvantage (B: 3.8, 95% CI: 0.2, 7.4).
Ecologic processes did not fully capture the relationship between SRD and SMM, highlighting the need for further research to elucidate the drivers of disparities in adverse maternal health outcomes.
