Mobley Lee R, Kuo Tzy-Mey, Urato Matthew, Subramanian Sujha, Watson Lisa, Anselin Luc
RTI International.
Arizona State University.
Ann Assoc Am Geogr. 2012;102(5):1113-1124. doi: 10.1080/00045608.2012.657494.
Each state is autonomous in its comprehensive cancer control (CCC) program, and considerable heterogeneity exists in the program plans. However, researchers often focus on the concept of nationally representative data and pool observations across states using regression analysis to come up with average effects when interpreting results. Due to considerable state autonomy and heterogeneity in various dimensions-including culture, politics, historical precedent, regulatory environment, and CCC efforts-it is important to examine states separately and to use geographic analysis to translate findings in place and time. We used 100 percent population data for Medicare-insured persons aged 65 or older and examined predictors of breast cancer (BC) and colorectal cancer (CRC) screening from 2001-2005. Examining BC and CRC screening behavior separately in each state, we performed 100 multilevel regressions. We summarize the state-specific findings of racial disparities in screening for either cancer in a single bivariate map of the 50 states, producing a separate map for African American and for Hispanic disparities in each state relative to whites. The maps serve to spatially translate the voluminous regression findings regarding statistically significant disparities between whites and minorities in cancer screening within states. Qualitative comparisons can be made of the states' disparity environments or for a state against a national benchmark using the bivariate maps. We find that African Americans in Michigan and Hispanics in New Jersey are significantly more likely than whites to utilize CRC screening and that Hispanics in 6 states are significantly and persistently more likely to utilize mammography than whites. We stress the importance of spatial translation research for informing and evaluating CCC activities within states and over time.
每个州在其综合癌症控制(CCC)项目中都具有自主性,项目计划存在相当大的异质性。然而,研究人员在解释结果时,往往关注全国代表性数据的概念,并使用回归分析汇总各州的观察结果以得出平均效应。由于在文化、政治、历史先例、监管环境和CCC工作等各个方面存在相当大的州自主性和异质性,单独审视各州并利用地理分析在特定地点和时间解读研究结果非常重要。我们使用了65岁及以上医疗保险参保人员的100%人口数据,研究了2001年至2005年乳腺癌(BC)和结直肠癌(CRC)筛查的预测因素。在每个州分别研究BC和CRC筛查行为,我们进行了100次多层次回归分析。我们在一张包含50个州的单变量地图上汇总了每个州在这两种癌症筛查中种族差异的特定州结果,分别绘制了每个州非裔美国人和西班牙裔相对于白人的差异地图。这些地图有助于在空间上呈现关于各州白人与少数族裔在癌症筛查方面具有统计学显著差异的大量回归分析结果。通过这些双变量地图,可以对各州的差异环境进行定性比较,或者将一个州与全国基准进行比较。我们发现,密歇根州的非裔美国人比白人更有可能进行CRC筛查,新泽西州的西班牙裔比白人更有可能进行CRC筛查,并且在6个州,西班牙裔比白人更有可能且持续地进行乳房X光检查。我们强调空间转化研究对于了解和评估各州内部及不同时期的CCC活动的重要性。