The effect of time on associations between historical redlining and breast cancer survival

Sarah M Lima; Tia M Palermo; Lili Tian; Furrina F Lee; Tabassum Z Insaf; Helen C S Meier; Henry Louis Taylor Jr; Deborah O Erwin; Heather M Ochs-Balcom

doi:10.1002/cncr.70230

The effect of time on associations between historical redlining and breast cancer survival

Cancer. 2026 Feb 15;132(4):e70230. doi: 10.1002/cncr.70230.

Authors

Sarah M Lima^{1

2}, Tia M Palermo^{1

3}, Lili Tian⁴, Furrina F Lee⁵, Tabassum Z Insaf^{5

6}, Helen C S Meier⁷, Henry Louis Taylor Jr^{8

9}, Deborah O Erwin¹⁰, Heather M Ochs-Balcom¹

Affiliations

¹ Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York, USA.
² Cancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA.
³ Policy Research Solutions LLC (PRESTO), Buffalo, New York, USA.
⁴ Department of Biostatistics, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York, USA.
⁵ Bureau of Cancer Epidemiology, Division of Chronic Disease Prevention, New York State Department of Health, Albany, New York, USA.
⁶ Department of Epidemiology and Biostatistics, University at Albany, Albany, New York, USA.
⁷ Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA.
⁸ Department of Urban and Regional Planning, School of Architecture and Planning, University at Buffalo, Buffalo, New York, USA.
⁹ Community Health Equity Research Institute, University at Buffalo, Buffalo, New York, USA.
¹⁰ Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA.

Abstract

Background: Historical redlining, a 1930s residential segregation policy, has been associated with shorter breast cancer survival. It is unknown whether this disparity has changed over time, given the time since redlining increases and subsequent breast cancer advances have occurred. This study evaluated whether associations between historical redlining and all-cause survival of breast cancer have changed from 1995 to 2019.

Methods: This New York State Cancer Registry-based cohort included 135,827 patients with breast cancer who were diagnosed between 1995 and 2019 and resided in a historically graded census tract at diagnosis. Cases were assigned a historical redlining grade (range, A-D) and divided into 5-year diagnostic time periods. Cox models estimated associations with survival. Multiplicative interaction between redlining grade and period tested temporal effects. Models were stratified by stage, hormone receptor status, and race/ethnicity.

Results: A significant time interaction with historical redlining for survival was found (p < .0001). Survival disparities for D grade versus A grade were largest in 1995-1999 (hazard ratio [HR], 1.75; 95% CI, 1.55-1.98) and lowest in 2005-2009 (HR, 1.48; 95% CI, 1.32-1.66). Redlining associations for local and regional tumors were largest in 1995-1999 and attenuated over time. Redlining was generally not associated with survival among distant tumors. D-grade versus A-grade survival disparities grew over time among patients with hormone receptor-positive tumors. Significant temporal effects were detected among all race/ethnicity groups.

Conclusions: Associations between historical redlining and breast cancer survival have changed over time, with disparities generally narrowing. Results stratified by stage and hormone receptor status suggest that such disparities reflect differential access to advances in breast cancer treatment across time.

Keywords: breast cancer; disparities; historical redlining; neighborhood effects; segregation; survival; temporal effects.

Publication types

Historical Article

MeSH terms

Adult
Aged
Breast Neoplasms* / epidemiology
Breast Neoplasms* / history
Breast Neoplasms* / mortality
Breast Neoplasms* / pathology
Female
History, 20th Century
Humans
Middle Aged
New York / epidemiology
Proportional Hazards Models
Registries / statistics & numerical data
Social Segregation*
Time Factors