Kirsten M M Beyer1,2,3, Yuhong Zhou1, Purushottam W Laud1,2,3, Emily L McGinley2, Tina W F Yen2,3,4, Courtney Jankowski1, Nicole Rademacher5, Sima Namin1, Jamila Kwarteng1,3, Sara Beltrán Ponce6, Ann B Nattinger2,3,7. 1. Institute for Health & Equity, Medical College of Wisconsin, Milwaukee, WI. 2. Center for Advancing Population Science, Medical College of Wisconsin, Milwaukee, WI. 3. MCW Cancer Center, Medical College of Wisconsin, Milwaukee, WI. 4. Division of Surgical Oncology, Department of Surgery, Medical College of Wisconsin, Milwaukee, WI. 5. Medical College of Wisconsin, Milwaukee, WI. 6. Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI. 7. Department of Medicine, Medical College of Wisconsin, Milwaukee, WI.
Abstract
PURPOSE: The objective was to examine the relationship between contemporary redlining (mortgage lending bias on the basis of property location) and survival among older women with breast cancer in the United States. METHODS: A redlining index using Home Mortgage Disclosure Act data (2007-2013) was linked by census tract with a SEER-Medicare cohort of 27,516 women age 66-90 years with an initial diagnosis of stage I-IV breast cancer in 2007-2009 and follow-up through 2015. Cox proportional hazards models were used to examine the relationship between redlining and both all-cause and breast cancer-specific mortality, accounting for covariates. RESULTS: Overall, 34% of non-Hispanic White, 57% of Hispanic, and 79% of non-Hispanic Black individuals lived in redlined tracts. As the redlining index increased, women experienced poorer survival. This effect was strongest for women with no comorbid conditions, who comprised 54% of the sample. For redlining index values of 1 (low), 2 (moderate), and 3 (high), as compared with 0.5 (least), hazard ratios (HRs) (and 95% CIs) for all-cause mortality were HR = 1.10 (1.06 to 1.14), HR = 1.27 (1.17 to 1.38), and HR = 1.39 (1.25 to 1.55), respectively, among women with no comorbidities. A similar pattern was found for breast cancer-specific mortality. CONCLUSION: Contemporary redlining is associated with poorer breast cancer survival. The impact of this bias is emphasized by the pronounced effect even among women with health insurance (Medicare) and no comorbid conditions. The magnitude of this neighborhood level effect demands an increased focus on upstream determinants of health to support comprehensive patient care. The housing sector actively reveals structural racism and economic disinvestment and is an actionable policy target to mitigate adverse upstream health determinants for the benefit of patients with cancer.
PURPOSE: The objective was to examine the relationship between contemporary redlining (mortgage lending bias on the basis of property location) and survival among older women with breast cancer in the United States. METHODS: A redlining index using Home Mortgage Disclosure Act data (2007-2013) was linked by census tract with a SEER-Medicare cohort of 27,516 women age 66-90 years with an initial diagnosis of stage I-IV breast cancer in 2007-2009 and follow-up through 2015. Cox proportional hazards models were used to examine the relationship between redlining and both all-cause and breast cancer-specific mortality, accounting for covariates. RESULTS: Overall, 34% of non-Hispanic White, 57% of Hispanic, and 79% of non-Hispanic Black individuals lived in redlined tracts. As the redlining index increased, women experienced poorer survival. This effect was strongest for women with no comorbid conditions, who comprised 54% of the sample. For redlining index values of 1 (low), 2 (moderate), and 3 (high), as compared with 0.5 (least), hazard ratios (HRs) (and 95% CIs) for all-cause mortality were HR = 1.10 (1.06 to 1.14), HR = 1.27 (1.17 to 1.38), and HR = 1.39 (1.25 to 1.55), respectively, among women with no comorbidities. A similar pattern was found for breast cancer-specific mortality. CONCLUSION: Contemporary redlining is associated with poorer breast cancer survival. The impact of this bias is emphasized by the pronounced effect even among women with health insurance (Medicare) and no comorbid conditions. The magnitude of this neighborhood level effect demands an increased focus on upstream determinants of health to support comprehensive patient care. The housing sector actively reveals structural racism and economic disinvestment and is an actionable policy target to mitigate adverse upstream health determinants for the benefit of patients with cancer.
Authors: Salma Shariff-Marco; Julie Von Behren; Peggy Reynolds; Theresa H M Keegan; Andrew Hertz; Marilyn L Kwan; Janise M Roh; Catherine Thomsen; Candyce H Kroenke; Christine Ambrosone; Lawrence H Kushi; Scarlett Lin Gomez Journal: Cancer Epidemiol Biomarkers Prev Date: 2017-02-02 Impact factor: 4.254
Authors: Lorraine T Dean; Sarah Gehlert; Marian L Neuhouser; April Oh; Krista Zanetti; Melody Goodman; Beti Thompson; Kala Visvanathan; Kathryn H Schmitz Journal: Cancer Causes Control Date: 2018-05-30 Impact factor: 2.506
Authors: Alejandro Cruz; Faith Dickerson; Kathryn R Pulling; Kyle Garcia; Francine C Gachupin; Chiu-Hsieh Hsu; Juan Chipollini; Benjamin R Lee; Ken Batai Journal: Int J Environ Res Public Health Date: 2022-02-12 Impact factor: 3.390
Authors: Carsten Bokemeyer; Christoph Oing; Christoph Seidel; Marcus Hentrich; Stefanie Zschäbitz; Pia Paffenholz; Axel Heidenreich; Tim Nestler; Ben Tran; Stefanie Fischer; Gedske Daugaard; Sebastian Ochsenreither; Margarida Brito; Friedemann Zengerling; Constantin Schwab Journal: World J Urol Date: 2022-01-07 Impact factor: 4.226
Authors: Adana A M Llanos; Jie Li; Jennifer Tsui; Joseph Gibbons; Karen Pawlish; Fechi Nwodili; Shannon Lynch; Camille Ragin; Antoinette M Stroup Journal: Front Oncol Date: 2022-04-08 Impact factor: 5.738
Authors: Xin Hu; Mark S Walker; Edward Stepanski; Cameron M Kaplan; Michelle Y Martin; Gregory A Vidal; Lee S Schwartzberg; Ilana Graetz Journal: JAMA Netw Open Date: 2022-08-01