Identifying county-level factors for female breast cancer incidence rate through a large-scale population study

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Appl Geogr. 2020 Dec;125:102324. doi: 10.1016/j.apgeog.2020.102324. Epub 2020 Sep 23.


Female breast cancer (FBC) incidence rate (IR) varies greatly across counties in the United States (U.S.). Factors contributing to these geographic disparities have not been fully understood at the population level. In this study, we investigated the relationships between the county-level FBC IR and a diverse set of variables in demographics, socioeconomics, life style, health care accessibility, and environment. Our study included 1,277 counties in the U.S. where the female population was 10,000 or above for at least one race/ethnicity. After controlling for the racial/ethnic and other significant factors, percent of husband-wife family households (pHWFH) for a racial/ethnic group in a county is negatively associated with FBC IR (p < 0.001). A 10% increase in married family households may lower a county’s IR by 5.2 cases per 100,000 females per year. We also found that PM2.5 (fine inhalable particles with a diameter of 2.5 micrometers or less) is positively associated with FBC IR (p < 0.001). Counties with the highest level of PM2.5 have approximately 4 additional FBC new cases per 100,000 females per year than counties with the lowest level of PM2.5. Furthermore, we found that the county-level factors contributing to FBC IR vary significantly for different racial groups using race-specific models. While confirming most of the previously known patient- and neighborhood-level risk factors (such as race/ethnicity, income, and health care accessibility), our study identified two significant county-level factors contributing to the spatial disparity of FBC IR across the U.S. The newly-identified beneficial factor (marriage) and risk factor (PM2.5), together with the verified known factors, may help provide insights to officials of health departments/organizations for them to make decisions on cancer intervention strategies.

PMID:33041393 | PMC:PMC7543978 | DOI:10.1016/j.apgeog.2020.102324