Geographic Disparities In Late-Stage Breast Cancer Diagnosis Rates And Their Persistence Over Time

JOURNAL OF WOMENS HEALTH(2021)

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摘要
Background: Other than skin cancer, breast cancer is the most common cancer in the United States. Lower uptake of mammography screening is associated with higher rates of late-stage breast cancers. This study aims to show geographic patterns in the United States, where rates of late-stage breast cancer are high and persistent over time, and examines factors associated with these patterns.Materials and Methods: We examined all primary breast cancers diagnosed among all counties in 43 U.S. states with available data. We used spatial cluster analysis to identify hot spots (i.e., spatial clusters with above average late-stage diagnosis rates among counties). Demographic and socioeconomic characteristics were compared between persistent hot spots and those counties that were never hot spots.Results: Of the 2,599 counties examined in 43 states, 219 were identified as persistent hot spots. Counties with persistent hot spots (compared with counties that were never hot spots) were located in more deprived areas with worse housing characteristics, lower socioeconomic status, lower levels of health insurance, worse access to mammography, more isolated American Indian/Alaska Native, Black, or Hispanic neighborhoods, and larger income disparity. In addition, persistent hot spots were significantly more likely to be observed among poor, rural, African American, or Hispanic communities, but not among poor, rural, White communities. This analysis includes a broader range of socioeconomic conditions than those included in previous literature.Conclusion: We found geographic disparities in late-stage breast cancer diagnosis rates, with some communities experiencing persistent disparities over time. Our findings can guide public health efforts aimed at reducing disparities in stage of diagnosis for breast cancer.
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关键词
late-stage cancer diagnosis, geographic disparities, urban&#8211, rural disparities, spatial clusters
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