Bijou R Hunt1, Abigail Silva2,3, Derrick Lock4, Marc Hurlbert5. 1. Sinai Urban Health Institute, Sinai Health System, 1500 S. Fairfield Ave., Room K438, Chicago, IL, 60608, USA. bijou.hunt@sinai.org. 2. Department of Public Health Sciences, Loyola University Stritch School of Medicine, 2160 S. First Avenue, Maywood, IL, 60153, USA. 3. Center of Innovation for Complex Chronic Healthcare, Edward Hines Jr. VA Hospital, 5000 S. Fifth Avenue, Hines, IL, 60141, USA. 4. Chicago Medical School, Rosalind Franklin University, 3333 Green Bay Road, North Chicago, IL, 60064, USA. 5. Breast Cancer Research Foundation, 60 East 56th Street, 8th Floor, New York, NY, 10022, USA.
Abstract
PURPOSE: We employed a city-level ecologic analysis to assess predictors of race-specific (black and white) breast cancer mortality rates. METHODS: We used data from the National Center for Health Statistics and the US Census Bureau to calculate 2010-2014 race-specific breast cancer mortality rates (BCMR) for 47 of the largest US cities. Data on potential city-level predictors (e.g., socioeconomic factors, health care resources) of race-specific BCMR were obtained from various publicly available datasets. We constructed race-specific multivariable negative binomial regression models to estimate rate ratios (RR) and 95% confidence intervals (CIs). RESULTS: Predictors of the white BCMR included white/black differences in education (RR 0.95; CI 0.91-0.99), number of religious congregations (RR 0.87; CI 0.77-0.97), and number of Medicare primary care physicians (RR 1.15; CI 1.04-1.28). Predictors of the black rate included white/black differences in household income (RR 1.03; CI 1.01-1.05), number of mammography facilities (RR 1.07; CI 1.03-1.12), and mammogram use (RR 0.93; CI 0.89-0.97). CONCLUSIONS: Our ecologic analysis found that predictors of breast cancer mortality differ for the black and white rate. The results of this analysis could help inform interventions at the local level.
PURPOSE: We employed a city-level ecologic analysis to assess predictors of race-specific (black and white) breast cancer mortality rates. METHODS: We used data from the National Center for Health Statistics and the US Census Bureau to calculate 2010-2014 race-specific breast cancer mortality rates (BCMR) for 47 of the largest US cities. Data on potential city-level predictors (e.g., socioeconomic factors, health care resources) of race-specific BCMR were obtained from various publicly available datasets. We constructed race-specific multivariable negative binomial regression models to estimate rate ratios (RR) and 95% confidence intervals (CIs). RESULTS: Predictors of the white BCMR included white/black differences in education (RR 0.95; CI 0.91-0.99), number of religious congregations (RR 0.87; CI 0.77-0.97), and number of Medicare primary care physicians (RR 1.15; CI 1.04-1.28). Predictors of the black rate included white/black differences in household income (RR 1.03; CI 1.01-1.05), number of mammography facilities (RR 1.07; CI 1.03-1.12), and mammogram use (RR 0.93; CI 0.89-0.97). CONCLUSIONS: Our ecologic analysis found that predictors of breast cancer mortality differ for the black and white rate. The results of this analysis could help inform interventions at the local level.
Entities:
Keywords:
Big cities; Breast cancer; Local data; Race disparities
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