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

COVID-19 大流行背景下孕产妇发病率和死亡率的种族和民族差异的多层次决定因素

• 批准号: 10392607
• 负责人: Xiaoming Li
• 金额: $ 88.62万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-07 至 2023-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10392607
• 关键词: Address; Affect; Area; Birth; Birth Certificates; COVID-19; COVID-19 pandemic; COVID-19 severity; COVID-19 testing; Cardiovascular Diseases; Caring; Child Welfare; Clinical; Color; Communities; Community Healthcare; Complex; County; Data; Data Analyses; Data Sources; Databases; Death Rate; Diabetes Mellitus; Discrimination; Education; Electronic Health Record; Ensure; Environment; Ethnic Origin; Etiology; Family; Financial Hardship; Geography; Goals; Health; Hispanics; Home; Hour; Hypertension; Income; Individual; Infant Mortality; Institution; Intervention; Interview; Knowledge; Labor Complications; Lead; Link; Machine Learning; Maternal Health; Maternal Health Services; Maternal Mortality; Maternal and Child Health; Mediating; Medically Underserved Area; Mental Health; Methods; Modeling; Morbidity - disease rate; Mothers; Not Hispanic or Latino; Outcome; Ownership; Pathway interactions; Play; Policies; Population Heterogeneity; Positioning Attribute; Postpartum Period; Postpartum Women; Poverty; Pregnancy; Pregnancy Complications; Pregnant Women; Psychosocial Stress; Pulmonary Embolism; Research; Research Design; Risk; Role; SARS-CoV-2 infection; Social Distance; Social Environment; Societies; South Carolina; Structural Racism; Surveys; System; Time; Unemployment; Woman; analytical tool; base; black women; care providers; cohort; contextual factors; coronavirus disease; delivery complications; design; experience; health care quality; health disparity; high risk; improved; infection rate; innovation; learning algorithm; machine learning algorithm; maternal morbidity; mortality; mortality risk; pandemic disease; population based; pregnant; protective factors; racial and ethnic disparities; racial discrimination; racial disparity; racial diversity; residential segregation; response; severe maternal morbidity; socioeconomics; stem; trend; unhealthy lifestyle

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.

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)， 即使在新冠肺炎大流行之前，按种族/族裔划分的健康差距也很大。史无前例的 新冠肺炎疫情对有色人种社区的打击最严重。非西班牙裔黑人和西班牙裔女性 怀孕的人似乎有不成比例的SARS-CoV-2感染和死亡率。有关以下问题： 新冠肺炎大流行对SMMM种族差异的影响及其动态和相互作用 诸如SMMM更广泛的社会背景等多层次决定因素仍然没有得到回答。首要目标是 这项研究的目的是调查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)的贡献作用和调解途径 贫穷、教育、失业和拥有住房方面的歧视)和他们长期的健康状况 产后后果。我们将通过研究新冠肺炎案例的分布和 南卡罗来纳州(SC)孕产妇健康的多水平决定因素，该州在 SMMM在历史上系统的南方背景下，在美国，我们将在现有的全州范围内建立 SC新冠肺炎队列(S3C)通过创建怀孕队列，将新冠肺炎检测数据链接到电子 2019年至2020年南加州所有出生人口的健康记录(EHR)和出生证明数据。以确保通用性 对于我们的发现，我们将使用正在进行的国家COVID队列合作的EHR数据进行确认 (N3C)。全国性的社会背景数据库和时变的新冠肺炎严重程度和社会距离政策 将添加到S3c和N3c数据中。我们将使用社会生态框架并同时雇用一名 三角测量、混合方法研究设计实现了三个具体目的：1)检查影响 新冠肺炎大流行关于MM中的种族/民族差异；2)检查和探索 在大流行期间，社会环境促成了MM中种族/民族差距的扩大 (目标2a)并确定通过产妇保健和心理健康进行调解的不同途径(目标2b)； 审查社会背景因素的作用，并确定保护种族/民族差异的因素 使用机器学习算法的与怀孕有关的长期疾病。对于目标2b，收敛 将使用平行设计，其中包括对来自SC PRAM的数据进行定量分析和定性 采访了产后妇女(20名黑人，20名西班牙裔)和10名产妇护理提供者。我们经验丰富的 团队处于有利地位，可以在新冠肺炎期间调查MM种族差异的复杂性 大流行病，同时从种族、社会经济和地理角度考虑历史上的结构性种族主义 不同的孕妇群体。对社会背景下的种族/民族差距的严格审查 流行期间的MMM和心理健康将有助于继续努力扭转#年的上升趋势 我们的建议涉及NOT-OD-21-071中的区域1、2和4。

项目成果

The impact of COVID-19 pandemic on the dynamic HIV care engagement among people with HIV: real-world evidence.

• DOI: 10.1097/qad.0000000000003491
• 发表时间: 2023-05-01
• 期刊: AIDS (London, England)

Temporal Geospatial Analysis of COVID-19 Pre-Infection Determinants of Risk in South Carolina.

• DOI: 10.3390/ijerph18189673
• 发表时间: 2021-09-14
• 期刊: International journal of environmental research and public health
• 作者: Lyu T;Hair N;Yell N;Li Z;Qiao S;Liang C;Li X
• 通讯作者: Li X

Facilitators of Organizational Resilience Within South Carolina AIDS Service Organizations: Lessons Learned from the COVID-19 Pandemic.

• DOI: 10.1007/s10461-023-04089-x
• 发表时间: 2023-05-29
• 期刊: AIDS AND BEHAVIOR
• 影响因子: 4.4
• 作者: Qiao, Shan;Shirley, Callie;Garrett, Camryn;Weissman, Sharon;Olatosi, Bankole;Li, Xiaoming
• 通讯作者: Li, Xiaoming

ODT FLOW: Extracting, analyzing, and sharing multi-source multi-scale human mobility.

• DOI: 10.1371/journal.pone.0255259
• 发表时间: 2021
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Li Z;Huang X;Hu T;Ning H;Ye X;Huang B;Li X
• 通讯作者: Li X

Investigating the relationships between concentrated disadvantage, place connectivity, and COVID-19 fatality in the United States over time.

• DOI: 10.1186/s12889-022-14779-1
• 发表时间: 2022-12-14
• 期刊: BMC public health
• 影响因子: 4.5