Maternal Morbidity Predicted by an Intersectional Social Determinants of Health Phenotype: A Secondary Analysis of the NuMoM2b Dataset

Elise N. Erickson, Nicole S. Carlson

Research output: Contribution to journalArticlepeer-review

Abstract

Maternal race, ethnicity and socio-economic position are known to be associated with increased risk for a range of poor pregnancy outcomes, including maternal morbidity and mortality. Previously, researchers seeking to identify the contributing factors focused on maternal behaviors and pregnancy complications. Less understood is the contribution of the social determinants of health (SDoH) in observed differences by race/ethnicity in these key outcomes. In this secondary analysis of the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b) dataset, latent mixture modeling was used to construct groups of healthy, nulliparous participants with a non-anomalous fetus in a cephalic presentation having a trial of labor (N = 5763) based on SDoH variables. The primary outcome was a composite score of postpartum maternal morbidity. A postpartum maternal morbidity event was experienced by 350 individuals (6.1%). Latent class analysis using SDoH variables revealed six groups of participants, with postpartum maternal morbidity rates ranging from 8.7% to 4.5% across groups (p < 0.001). Two SDoH groups had the highest odds for maternal morbidity. These higher-risk groups were comprised of participants with the lowest income and highest stress and those who had lived in the USA for the shortest periods of time. SDoH phenotype predicted MM outcomes and identified two important, yet distinct groups of pregnant people who were the most likely have a maternal morbidity event.

Original languageEnglish (US)
JournalReproductive Sciences
DOIs
StateAccepted/In press - 2022
Externally publishedYes

Keywords

  • Maternal morbidity
  • nulliparous
  • pregnancy
  • social determinants of health

ASJC Scopus subject areas

  • Obstetrics and Gynecology

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