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Updated: Oct 13, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Historical redlining and breast cancer screening in a regional spatial analysis
Derrick Asante1, Atikur Rahman1, Isuru Ratnayake1
1Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.
Background:
Redlining, introduced in 1933 by the Homeowners' Loan Corporation, created enduring structural inequities in housing, health care access, and neighborhood investment. These historical patterns may contribute to persistent disparities in breast cancer screening. This study examines how historical redlining, alongside contemporary socioeconomic factors, shapes screening disparities across the University of Kansas Cancer Center (KUCC) catchment area.
Methods:
We conducted a census tract-level spatial analysis across 123 counties (Kansas and western Missouri) by linking CDC PLACES breast cancer screening data with historical redlining maps. Explanatory variables included rurality, mammography facility availability, income inequality, gender pay gap, and uninsured rates. Logistic regression assessed overall associations, while geographically weighted binomial logistic regression evaluated spatial heterogeneity.
Results:
Screening rates ranged from 56.9% to 84.5% across census tracts. Redlining was associated with lower screening odds in unadjusted models but was attenuated after accounting for socioeconomic and geographic factors. Rurality and income inequality were consistently associated with lower screening, whereas greater mammography facility availability was associated with higher screening rates. Spatial analyses revealed meaningful geographic variation, with localized negative associations of redlining and persistent, spatially varying effects of socioeconomic factors.
Conclusion:
Breast cancer screening disparities in this region reflect the combined influence of historical structural inequities and current socioeconomic conditions. Expanding access to mammography and implementing spatially targeted, equity-focused interventions may improve screening uptake and reduce disparities in underserved communities.