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

> **NIH NIH F31** · UNIVERSITY OF CALIFORNIA BERKELEY · 2022 · $43,106

## Abstract

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 l...

## Key facts

- **NIH application ID:** 10471194
- **Project number:** 5F31HD106772-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** Xing Gao
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $43,106
- **Award type:** 5
- **Project period:** 2021-09-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10471194

## Citation

> US National Institutes of Health, RePORTER application 10471194, Impact of historical redlining and contemporary gentrification on severe maternal morbidity racial/ethnic disparities (5F31HD106772-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10471194. Licensed CC0.

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