Local Breast Cancer Spatial Patterning: A Tool for Community Health Resource Allocation to Address Local Disparities in Breast Cancer Mortality

被引:6
|
作者
Brantley-Sieders, Dana M. [2 ]
Fan, Kang-Hsien [1 ,3 ]
Deming-Halverson, Sandra L. [2 ,5 ]
Shyr, Yu [1 ,3 ,4 ]
Cook, Rebecca S. [1 ,4 ]
机构
[1] Vanderbilt Univ, Sch Med, Dept Canc Biol, Nashville, TN 37212 USA
[2] Vanderbilt Univ, Sch Med, Dept Med, Nashville, TN 37212 USA
[3] Vanderbilt Univ, Sch Med, Dept Biostat, Nashville, TN 37212 USA
[4] Vanderbilt Univ, Sch Med, Vanderbilt Ingram Comprehens Canc Ctr, Nashville, TN 37212 USA
[5] Social & Sci Syst Inc, Durham, NC USA
来源
PLOS ONE | 2012年 / 7卷 / 09期
基金
美国国家卫生研究院;
关键词
INSURANCE STATUS; UNITED-STATES; MAMMOGRAPHY; SURVIVAL; WOMEN; IMPACT; RATES; STAGE; ASSOCIATION; ETHNICITY;
D O I
10.1371/journal.pone.0045238
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Despite available demographic data on the factors that contribute to breast cancer mortality in large population datasets, local patterns are often overlooked. Such local information could provide a valuable metric by which regional community health resources can be allocated to reduce breast cancer mortality. We used national and statewide datasets to assess geographical distribution of breast cancer mortality rates and known risk factors influencing breast cancer mortality in middle Tennessee. Each county in middle Tennessee, and each ZIP code within metropolitan Davidson County, was scored for risk factor prevalence and assigned quartile scores that were used as a metric to identify geographic areas of need. While breast cancer mortality often correlated with age and incidence, geographic areas were identified in which breast cancer mortality rates did not correlate with age and incidence, but correlated with additional risk factors, such as mammography screening and socioeconomic status. Geographical variability in specific risk factors was evident, demonstrating the utility of this approach to identify local areas of risk. This method revealed local patterns in breast cancer mortality that might otherwise be overlooked in a more broadly based analysis. Our data suggest that understanding the geographic distribution of breast cancer mortality, and the distribution of risk factors that contribute to breast cancer mortality, will not only identify communities with the greatest need of support, but will identify the types of resources that would provide the most benefit to reduce breast cancer mortality in the community.
引用
收藏
页数:11
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