Impact of historical redlining and contemporary gentrification on severe maternal morbidity racial/ethnic disparities

点击翻译按钮获取中文摘要

PROJECT SUMMARY In the United States, rates of severe maternal morbidity (SMM), which encompasses a broad spectrum of unexpected and life-threatening health complications that occur during the antepartum, intrapartum, or postpartum periods, increased threefold between 1993-2014. SMM disproportionately affects Black, Hispanic, Indigenous, Asian, and Pacific Islander women, an alarming and persistent disparity that remains an unaddressed public health crisis. Individual, clinical, and hospital-level factors have failed to account for these disparities, highlighting the need to examine upstream factors, such as structural racism, in relation to maternal health outcomes. Neighborhood context has been shown to be a profound determinant of infant health outcomes, but evidence on how neighborhood environments influence maternal health is lacking. Even fewer studies have examined sociopolitical and geospatial manifestations of structural racism, such as racial residential segregation and gentrification, that create differential neighborhood social and material conditions, which may in turn produce stark racial/ethnic differences in SMM. This study will address these important gaps in knowledge by leveraging state-wide data on over 11 million births in California between 1997-2018. The specific aims are to: 1. examine associations between historical redlining and SMM; 2. examine associations between contemporary gentrification and SMM; and 3. determine the joint effect of redlining and gentrification on SMM. Given the especially stark SMM disparities impacting Black and Indigenous mothers, we will determine whether specific racial/ethnic and socioeconomic subgroups are more vulnerable to the influence of redlining and gentrification on SMM. Study strengths and innovations include: using a large population-based dataset with sufficient racial/ethnic, geographic, and socioeconomic heterogeneity to assess SMM, a rare event that impacts 1% of the population; exploring novel exposure measures at the neighborhood-level, including redlining and gentrification, that have not been examined in relation to SMM; and employing rigorous causal inference methods to elucidate the proposed relationships. This research will inform both our understanding of how upstream sociopolitical processes influence SMM risk and the development of multi-level, place-based strategies to improve racial/ethnic inequities in SMM. With the support from this fellowship, mentorship from an interdisciplinary team, and a rich academic environment at UC Berkeley, the applicant will train in conceptualizing structural factors that drive racial/ethnic inequities in maternal health, reproductive epidemiology, and advanced biostatistical methods such as multi- level modeling and causal inference. By completing the research and training goals, the applicant will be well- prepared to transition into a postdoctoral and early-career investigator position. This fellowship will support the applicant’s long-term goal of becoming a social epidemiologist researching the intersection of structural racism, neighborhood context, and racial/ethnic inequities in women’s health across the life course.