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

摘要 在美国，每年有近 60,000 名妇女经历严重的孕产妇发病率和死亡率 (SMMM) 即使在 COVID-19 大流行之前，种族/族裔之间的健康状况也存在巨大差异。史无前例的 COVID-19 大流行对有色人种社区的打击最为严重。非西班牙裔黑人和西班牙裔女性 孕妇的 SARS-CoV-2 感染率和死亡率似乎不成比例。有关的问题 COVID-19 大流行对 SMMM 种族差异的影响以及种族差异的动态和相互作用 SMMM 更广泛的社会背景等多层次决定因素仍未得到解答。总体目标 本研究的目的是调查孕产妇发病率和死亡率（MMM）的种族/民族差异， 社会背景（例如居住隔离、种族隔离）的贡献作用和中介途径 贫困、教育、失业和住房所有权方面的歧视）及其长期健康状况 产后的后果。我们将通过研究 COVID-19 病例的分布和 南卡罗来纳州（SC）孕产妇健康的多层次决定因素，该州在种族差异方面持续存在 SMMM 在南方历史系统背景下以及在美国，我们将在现有的全州范围内建立 SC COVID-19 队列 (S3C)，创建一个怀孕队列，将 COVID-19 检测数据、电子数据链接起来 2019-2020 年南卡罗来纳州所有出生的健康记录 (EHR) 和出生证明数据。为了保证普遍性 对于我们的发现，我们将使用正在进行的国家新冠肺炎队列协作的 EHR 数据来确认它们 （N3C）。全国社会背景数据库以及随时间变化的 COVID-19 严重程度和社交距离政策 将被添加到S3C和N3c数据中。我们将使用社会生态框架并采用并行的 三角测量，混合方法研究设计，以实现三个具体目标：1）检查 COVID-19 大流行对 MMM 中种族/民族差异的影响； 2）检查和探索关键特征 疫情期间，社会背景导致 MMM 中种族/民族差异的扩大 （目标 2a）并通过孕产妇护理和心理健康确定不同的中介途径（目标 2b）；和 3) 研究社会背景因素的作用并确定种族/民族差异的保护因素 使用机器学习算法来识别与怀孕相关的长期疾病。对于目标 2b，收敛 将使用并行设计，其中包括对 SC PRAMS 数据的定量分析和定性分析 对产后妇女（20 名黑人、20 名西班牙裔）和 10 名孕产妇护理人员的采访。我们经验丰富 团队处于有利地位，可以调查 COVID-19 期间 MMM 种族差异的复杂性 流行病，同时从种族、社会经济和地理角度考虑历史结构性种族主义 孕妇人群多样化。对种族/族裔差异的社会背景进行严格审查 MMM 和大流行期间的心理健康将为扭转不断上升的趋势的持续努力提供信息 美国的 SMMM 我们的提案涉及 NOT-OD-21-071 中的区域 1、2 和 4。

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.