{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T03:20:28Z","timestamp":1788405628743,"version":"build-2803163510"},"reference-count":54,"publisher":"American Medical Association (AMA)","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Geographic variation in breast cancer screening may reflect persistent structural inequities in access to preventive care. Understanding whether historical redlining remains associated with screening, independent of contemporary social vulnerability, neighborhood conditions, and geographic access, is critical for targeting interventions within cancer center catchment areas.<\/jats:p>\n <\/jats:sec>\n \n Objectives<\/jats:title>\n To examine the association between historical redlining and breast cancer screening prevalence, accounting for social vulnerability, neighborhood characteristics, and geographic access, and to characterize spatiotemporal screening patterns.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This cohort study used Census tract\u2013level data from 2016 to 2024 across the University of Kansas Cancer Center catchment area, including communities in Kansas and adjacent Missouri counties. The analytic sample included Census tracts with available Homeowners\u2019 Loan Corporation (HOLC) grades A (indicating the least redlining) to D (indicating the most redlining). Statistical analysis was performed from July to December 2025.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n HOLC grades; Social Vulnerability Index quintiles (with the first quintile indicating the lowest vulnerability and the fifth quintile indicating the highest); Census tract\u2013level socioeconomic, housing, and transportation indicators; and distance to the nearest mammography facility.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n Census tract\u2013level breast cancer screening prevalence from the Centers for Disease Control and Prevention\u2019s PLACES database, reported as odds ratios (ORs) with 95% credible intervals (CrIs).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n A total of 1152 historically redlined Census tracts were analyzed. Tracts were categorized by HOLC grades A (n\u2009=\u200927), B (n\u2009=\u200999), C (n\u2009=\u2009423), and D (n\u2009=\u2009603). The median (IQR) screening prevalence was highest in grade A tracts (79.6% [79.0%-80.0%]) and lowest in grade D tracts (75.2% [71.7%-79.2%]). Models demonstrated substantial spatial and temporal dependence with geographic clustering and localized variability. Compared with grade A tracts, grade C (OR, 0.94; 95% CrI, 0.90-0.99) and grade D tracts (OR, 0.94; 95% CrI, 0.89-0.99) had lower screening prevalence after adjustment. The highest Social Vulnerability Index quintile was associated with increased screening odds (OR, 1.08; 95% CrI, 1.01-1.14). Lower educational attainment (OR, 0.94; 95% CrI, 0.92-0.96) and higher mobile home prevalence (OR, 0.98; 95% CrI, 0.97-1.00) were associated with lower screening odds. Residual spatial heterogeneity persisted (711 of 1152 tracts [61.7%] excluding the null). Screening peaked in 2018 to 2019, stabilized through 2023, and declined in 2024, with most areas remaining below the Healthy People 2030 target of 80.3%.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n This study found that historical redlining was associated with lower breast cancer screening prevalence independent of contemporary social vulnerability, neighborhood conditions, and geographic access. These findings support sustained, place-based strategies addressing structural and socioeconomic barriers to improve screening uptake and progress toward national screening targets.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.30685","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T15:00:34Z","timestamp":1788361234000},"page":"e2630685","source":"Crossref","is-referenced-by-count":1,"title":["Historical Redlining and Spatiotemporal Patterns in Breast Cancer Screening"],"prefix":"10.1001","volume":"9","author":[{"given":"Md Atikur","family":"Rahman","sequence":"first","affiliation":[{"name":"Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isuru","family":"Ratnayake","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City"},{"name":"The 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