Spatial trends of breast and prostate cancers in the ...



Title Spatial trends of breast and prostate cancers in the United States between 2000 and 2005
Author(s) R. Mandal, S. St-Hilaire, J. G. Kie, D. Derryberry
Journal International Journal of Health Geographics
Date 2009
Volume 8
Issue 53
Start page (29 Se
End page (29 Se
Abstract Background: Breast cancer in females and prostate cancer in males are two of the most common cancers in the United States, and the literature suggests that they share similar features. However, it is unknown whether the occurrence of these two cancers at the county level in the United States is correlated. We analyzed Caucasian age-adjusted county level average annual incidence rates for breast and prostate cancers from the National Cancer Institute and State Cancer Registries to determine whether there was a spatial correlation between the two conditions and whether the two cancers had similar spatial patterns. Results: There was a significant correlation between breast and prostate cancers by county (r=0.332, p<0.001). This relationship was more pronounced when we performed a geographically-weighted regression (GWR) analysis (r=0.552) adjusting for county unemployment rates. There was variation in the parameter estimates derived with the GWR; however, the majority of the estimates indicted a positive association. The strongest relationship between breast and prostate cancer was in the eastern parts of the Midwest and South, and the Southeastern U.S. We also observed a north-south pattern for both cancers with our cluster analyses. Clusters of counties with high cancer incidence rates were more frequently found in the North and clusters of counties with low incidence rates were predominantly in the South. Conclusion: Our analyses suggest breast and prostate cancers cluster spatially. This finding corroborates other studies that have found these two cancers share similar risk factors. The north-south distribution observed for both cancers warrants further research to determine what is driving this spatial pattern.
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