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Severe Maternal Morbidity: An Investigation of Racial-Ethnic Disparities, Social Disadvantage & Maternal Weight

严重的孕产妇发病率：对种族差异、社会弱势的调查

基本信息

批准号：
10660008
负责人：
SUZAN L CARMICHAEL
金额：
$ 60.08万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-01-19 至 2028-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10660008
关键词：
Address Affect Anemia Birth Black American Body mass index California Censuses Cesarean section Child Communities Country Data Death Certificates Disparity Education Ensure Equity Ethnic Origin Exclusion Fetal Death Health Healthcare Hemorrhage Hospitals Hypertension Income Individual Inequality Inequity Infection Intervention Investigation Joints Knowledge Life Cycle Stages Link Live Birth Masks Maternal Health Maternal Mortality Mediation Medical Methods Morbidity - disease rate Mothers Multiple Pregnancy Native Americans Neighborhoods New Jersey Organ failure Outcome Outcome Study Persons Phase Population Population Research Postpartum Period Poverty Pregnancy Prevention strategy Proxy Race Records Recurrence Research Resources Risk Risk Assessment Risk Factors Risk Reduction Sepsis Social Environment Social Identification Survivors Time Translating Translations Virginia Woman Work community engagement community organizations data resource disparity elimination ethnic disparity health disparity high risk improved intersectionality large scale data longitudinal dataset marginalization maternal morbidity maternal outcome maternal weight neighborhood disadvantage next generation parent grant people of color pregnancy disorder pregnancy health pregnant prepregnancy racial disparity reproductive segregation severe maternal morbidity social social disparities social structure socioeconomics success

项目摘要

ABSTRACT Severe maternal morbidity (SMM), which encompasses conditions that put pregnant people most at risk of dying (e.g., hemorrhage, sepsis, organ failure), doubled in the last two decades. The most common precursors to SMM – anemia, hypertensive disorders of pregnancy (HDP), and cesarean birth – are also increasing. People of color, especially Black and Native American people, are at increased risk for all these outcomes. This Renewal proposal builds on our prior work to address inequities in maternal outcomes. Via the Parent Grant, our team enhanced current understanding of the contribution of social context (focusing on neighborhood social disadvantage) and maternal pre-pregnancy health (focusing on body mass index) to SMM risk, using a unique data resource we built of California (CA) births. This Renewal uses theoretically grounded approaches to address several remaining gaps in our understanding of maternal health in the U.S. that were illuminated by the Parent Grant. We will build a unique resource of 16 million births in three states from 1997-2021. The dataset longitudinally links vital records (live birth and fetal death certificates) with hospital discharge data for mother and baby; includes residential address; and links data for repeat pregnancies to the same person over time, thus providing the type of large-scale data with high-quality information on maternal health and social context that the field needs to advance population-level research on maternal health. All phases of the research will be guided by a community advisory board (CAB). Using an intersectionality framework, Aim 1 will examine joint impacts of multiple forms of marginalization on SMM, its subtypes (i.e., hypertension-, hemorrhage-, and sepsis-related SMM), and its precursors (i.e., HDP, anemia, mode of birth). Indicators of marginalization include race-ethnicity, education, health care payer, nativity, and census tract-level markers of social disadvantage and structural inequality (e.g., poverty, segregation). Using a reproductive life-course framework, Aim 2 will determine the cumulative impact of social and medical risk factors across successive pregnancies on maternal health (i.e., SMM, SMM subtypes, SMM precursors). We will examine how factors related to social context (e.g., persistent census tract poverty), morbidity (e.g., persistent HDP), and mode of birth (primary cesarean birth) affect subsequent occurrence and recurrence of the study outcomes. Aim 3 will use findings from Aims 1 and 2 to identify and prioritize strategies to improve maternal health and equity. We will use a) causal inference methods (mediation and g-computation) to understand mechanisms and compare the potential impact of selected hypothetical interventions on study outcomes and disparities, and b) community-engaged prioritization methods to synthesize our findings and prioritize next steps. By understanding risks across multiple forms of marginalization and successive pregnancies, and guided by rigorous analytics and community-grounded knowledge, our work will contribute to advancing the next generation of actionable population-level SMM equity research.

摘要