Racial/Ethnic Differences in Pre-Pregnancy Conditions and Adverse Maternal Outcomes in the nuMoM2b Cohort

Abstract Objective To: (1) determine how pre-existing conditions contribute to racial disparities in adverse maternal outcomes; and (2) incorporate these conditions into models to improve risk prediction for racial minority subgroups. Design Secondary data analysis of a population-based cohort study. Setting Academic healthcare institutions in the United States. Population A cohort of 8,729 women included in the “Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be (nuMoM2b)”. Methods Poisson regression to estimate adjusted risk ratios, and mediation analysis to evaluate the contribution of multimorbidity to racial/ethnic disparities. Area under the receiver operating characteristic curve (AUC) to evaluate model performance. Main Outcome Measures Incidence of severe preeclampsia, postpartum readmission, and blood transfusion. Results In the nuMoM2b cohort (n=8729), accounting for pre-existing conditions attenuated the association between non-Hispanic Black race/ethnicity and risk of severe preeclampsia. Cardiovascular and kidney conditions were associated with risk for severe preeclampsia among all women (aRR, 1.77; CI, 1.61-1.96, and aRR, 1.27; CI, 1.03-1.56 respectively). The mediation analysis results were not statistically significant; however, cardiovascular conditions explained 36.6% of the association between severe preeclampsia and non-Hispanic Black race/ethnicity (p=0.07). The addition of pre-pregnancy conditions increased model performance for the prediction of blood transfusion and severe preeclampsia. Conclusions Pre-existing conditions may explain some of the association between severe preeclampsia and non-Hispanic Black race/ethnicity. Specific pre-pregnancy conditions were associated with adverse maternal outcomes and the incorporation of comorbidities improved the performance of most risk prediction models. Funding Research reported in this publication was supported in part by Imagine, Innovate and Impact (I 3 ) from the Emory School of Medicine, Georgia Tech, and through the Georgia CTSA NIH award (UL1-TR002378) and by the National Science Foundation under grant number DGE-2039655 (Meredith); any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.