Neighborhood Contemporary Redlining and Racial Mortgage Lending Bias and Cardiovascular Outcomes in Women With Breast Cancer

BACKGROUND: Studies have demonstrated neighborhood structural inequities are associated with cardiovascular outcomes among breast cancer survivors. We investigated the associations between bias in mortgage lending practices (contemporary redlining and racial lending bias) and cardiovascular outcomes in women with breast cancer. METHODS: Using the SEER (Surveillance, Epidemiology, and End Results)-Medicare database, we identified 51 007 Black and White women diagnosed with breast cancer between 2010 and 2014 with follow-up through 2020. We used Home Mortgage Disclosure Act data to calculate census-tract contemporary redlining index and racial lending bias index, and assessed indices continuously and categorically (low, moderate, or high). We used Cox proportional hazards regression to estimate multivariable-adjusted, cause-specific hazard ratios (HRs) for major adverse cardiovascular events, ischemic heart disease, heart failure, stroke, and cardiovascular death. RESULTS: In the overall population, a 10%-unit increase in redlining was associated with increased risk of major adverse cardiovascular events (HR, 1.04 [95% CI, 1.02-1.06]). Among Black women, those in high redlining neighborhoods had an increased heart failure risk compared with those in low redlining neighborhoods (HR, 1.22 [95% CI, 1.05-1.41]). Similarly, White women in high redlining neighborhoods had an increased risk of ischemic heart disease (HR, 1.23 [95% CI, 1.15-1.30]) and stroke (HR, 1.09 [95% CI, 1.03-1.16]). Black women in high racial lending bias neighborhoods had reduced cardiovascular mortality risk compared with those in low racial lending bias neighborhoods (HR, 0.69 [95% CI, 0.54-0.90]). CONCLUSIONS: We identified associations between contemporary redlining and cardiovascular outcomes among breast cancer survivors. High racial lending bias was associated with reduced cardiovascular mortality risk among Black women. Bias in mortgage lending practices may serve as a structural driver of cardiovascular disparities.

Authors

Institutions

Publication Details

Journal
Journal of the American Heart Association
Published
2026-09-09
DOI
https://doi.org/10.1161/jaha.125.049367
Primary Topic
Economic and Financial Impacts of Cancer
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Neighborhood Contemporary Redlining and Racial Mortgage Lending Bias and Cardiovascular Outcomes in Women With Breast Cancer

Hyokyoung Grace Hong, Jared W. Magnani, Brittany L. Brown-Podgorski, Christian C. Abnet et al.
Journal of the American Heart Association
Economic and Financial Impacts of Cancer
article

Neighborhood Contemporary Redlining and Racial Mortgage Lending Bias and Cardiovascular Outcomes in Women With Breast Cancer

Hyokyoung Grace Hong, Jared W. Magnani, Brittany L. Brown-Podgorski, Christian C. Abnet, Kirsten M. M. Beyer, Michelle Doose, Jean C. Bikomeye, Aldenise Ewing, Mahasin S. Mujahid, Tiffany M. Powell‐Wiley, Arnethea L. Sutton, Alexandra R. Harris, Adana A. M. Llanos, LaPrincess C. Brewer, Wayne R. Lawrence, Tanisha Choudhury
article en

Abstract

BACKGROUND: Studies have demonstrated neighborhood structural inequities are associated with cardiovascular outcomes among breast cancer survivors. We investigated the associations between bias in mortgage lending practices (contemporary redlining and racial lending bias) and cardiovascular outcomes in women with breast cancer. METHODS: Using the SEER (Surveillance, Epidemiology, and End Results)-Medicare database, we identified 51 007 Black and White women diagnosed with breast cancer between 2010 and 2014 with follow-up through 2020. We used Home Mortgage Disclosure Act data to calculate census-tract contemporary redlining index and racial lending bias index, and assessed indices continuously and categorically (low, moderate, or high). We used Cox proportional hazards regression to estimate multivariable-adjusted, cause-specific hazard ratios (HRs) for major adverse cardiovascular events, ischemic heart disease, heart failure, stroke, and cardiovascular death. RESULTS: In the overall population, a 10%-unit increase in redlining was associated with increased risk of major adverse cardiovascular events (HR, 1.04 [95% CI, 1.02-1.06]). Among Black women, those in high redlining neighborhoods had an increased heart failure risk compared with those in low redlining neighborhoods (HR, 1.22 [95% CI, 1.05-1.41]). Similarly, White women in high redlining neighborhoods had an increased risk of ischemic heart disease (HR, 1.23 [95% CI, 1.15-1.30]) and stroke (HR, 1.09 [95% CI, 1.03-1.16]). Black women in high racial lending bias neighborhoods had reduced cardiovascular mortality risk compared with those in low racial lending bias neighborhoods (HR, 0.69 [95% CI, 0.54-0.90]). CONCLUSIONS: We identified associations between contemporary redlining and cardiovascular outcomes among breast cancer survivors. High racial lending bias was associated with reduced cardiovascular mortality risk among Black women. Bias in mortgage lending practices may serve as a structural driver of cardiovascular disparities.

Journal of the American Heart Association
University of North Carolina at Chapel Hill (US), National Institutes of Health (US), University of Pittsburgh (US), Virginia Commonwealth University (US), Medical College of Wisconsin (US), Columbia University Irving Medical Center (US), WinnMed (US), Humanity & Health (CN), Medical College of Wisconsin Cancer Center, The Ohio State University (US), Columbia University (US), University of California, Berkeley (US)
Good health and well-being
Openalex Percentile: Top 5%
Economic and Financial Impacts of Cancer
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.