Multilevel Determinants of Racial and Ethnic Disparities in Maternal Morbidity and Mortality in the Context of COVID-19 Pandemic

  • Funded by National Institutes of Health (NIH)
  • Total publications:2 publications

Grant number: 3R01AI127203-05S2

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2021.0
    2023.0
  • Known Financial Commitments (USD)

    $886,186
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    . Xiaoming Li
  • Research Location

    United States of America
  • Lead Research Institution

    UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Disease susceptibility

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Pregnant women

  • Occupations of Interest

    Unspecified

Abstract

Abstract Annually in the U.S., nearly 60,000 women experience severe maternal morbidity and mortality (SMMM) with substantial health disparities by race/ethnicity, even prior to the COVID-19 pandemic. The unprecedented COVID-19 pandemic has hit communities of color the hardest. Non-Hispanic Black and Hispanic women who are pregnant appear to have disproportionate SARS-CoV-2 infection and death rates. Questions regarding the impact of the COVID-19 pandemic on racial disparities in SMMM and the dynamics and interactions of multilevel determinants such as broader social contexts of SMMM remain unanswered. The overarching goal of this study is to investigate racial/ethnic disparities in maternal morbidity and mortality (MMM), the contributing roles and mediating pathways of social contexts (e.g., residential segregation, racial discrimination in poverty, education, unemployment, and home ownership), and their long-standing health consequences postpartum. We will achieve our goal by studying the distributions of COVID-19 cases and multilevel determinants of maternal health in South Carolina (SC), a state with persistent racial disparities in SMMM within historical systemic Southern contexts, and in the U.S. We will build upon our existing statewide SC COVID-19 Cohort (S3C) by creating a pregnancy cohort that will link COVID-19 testing data, electronic health records (EHR), and birth certificate data for all births in SC in 2019-2020. To ensure the generalizability of our findings, we will confirm them using EHR data from the ongoing National COVID Cohort Collaborative (N3C). Nationwide social context databases and time-varying COVID-19 severity and social distancing policies will be added to S3C and N3c data. We will use the socio-ecological framework and employ a concurrent triangulation, mixed methods study design to achieve three specific aims: 1) to examine the impacts of the COVID-19 pandemic on racial/ethnic disparities in MMM; 2) to examine and explore how the key features of social contexts have contributed to the widening of racial/ethnic disparities in MMM during the pandemic (Aim 2a) and identify distinct mediating pathways through maternity care and mental health (Aim 2b); and 3) to examine the role of social contextual factors and identify protective factors for racial/ethnic disparities in pregnancy-related, long-standing morbidities using machine learning algorithms. For Aim 2b, a convergent parallel design will be used, which includes a quantitative analysis of data from SC PRAMS and qualitative interviews of postpartum women (20 Black, 20 Hispanics) and 10 maternal care providers. Our experienced team is well positioned to investigate the complexity of racial disparities in MMM during the COVID-19 pandemic, while considering historical structural racism in a racially, socioeconomically, and geographically diverse population of pregnant women. A rigorous examination of social contexts on racial/ethnic disparities in MMM and mental health during the pandemic will inform continuing efforts to reverse the rising trends of SMMM in the U.S. Our proposal addresses Areas 1, 2, & 4 in the NOT-OD-21-071.

Publicationslinked via Europe PMC

Last Updated:18 hours ago

View all publications at Europe PMC

Risk for stillbirth among pregnant individuals with SARS-CoV-2 infection varied by gestational age.

Temporal Events Detector for Pregnancy Care (TED-PC): A rule-based algorithm to infer gestational age and delivery date from electronic health records of pregnant women with and without COVID-19.