Caitlin Kennedy1, Yang Liu2, Xia Meng3, Heather Strosnider1, Lance A Waller4, Ying Zhou5. 1. Environmental Health Tracking Section, Division of Environmental Health Practice and Science, National Center for Environmental Health (NCEH), Centers for Disease Control and Prevention (CDC), Atlanta, GA. 2. Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA. 3. School of Public Health, Fudan University, Shanghai, China. 4. Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA. 5. Environmental Health Tracking Section, Division of Environmental Health Practice and Science, National Center for Environmental Health (NCEH), Centers for Disease Control and Prevention (CDC), Atlanta, GA. Electronic address: yzhou2@cdc.gov.
Abstract
PURPOSE: Skin cancer is the most common, yet oftentimes preventable, cancer type in the United States. Exposure to ultraviolet radiation from sunlight is the most prominent environmental risk factor for skin cancer. Besides environmental exposure, demographic characteristics such as race, age, and socioeconomic status may make some groups more vulnerable. An exploratory spatial clustering method is described for identifying clusters of vulnerability to skin cancer incidence and mortality based on composite indices, which combine data from environmental and demographic risk factors. METHODS: Based on county-level ultraviolet data and demographic risk factors, two vulnerability indices for skin cancer were generated using an additive percentile rank approach. With these indices, univariate local Moran's I spatial autocorrelation identified significant clusters, or hotspots, of neighboring counties with high overall vulnerability indices. Clusters were identified separately for skin cancer incidence and mortality. RESULTS: Counties with high vulnerabilities were spatially distributed across the United States in a pattern that generally increased to the South and West. Clusters of counties with high skin cancer incidence vulnerability were mostly observed in Utah and Colorado, even with highly conservative levels of significance. Meanwhile, clusters for skin cancer mortality vulnerability were observed in southern Alabama and west Florida as well as across north Alabama, north Georgia and up through the Tennessee-North Carolina area. CONCLUSIONS: Future skin cancer research and screening initiatives may use these innovative composite vulnerability indices and identified clusters to better target resources based on anticipated risk from underlying demographic and environmental factors.
PURPOSE:Skin cancer is the most common, yet oftentimes preventable, cancer type in the United States. Exposure to ultraviolet radiation from sunlight is the most prominent environmental risk factor for skin cancer. Besides environmental exposure, demographic characteristics such as race, age, and socioeconomic status may make some groups more vulnerable. An exploratory spatial clustering method is described for identifying clusters of vulnerability to skin cancer incidence and mortality based on composite indices, which combine data from environmental and demographic risk factors. METHODS: Based on county-level ultraviolet data and demographic risk factors, two vulnerability indices for skin cancer were generated using an additive percentile rank approach. With these indices, univariate local Moran's I spatial autocorrelation identified significant clusters, or hotspots, of neighboring counties with high overall vulnerability indices. Clusters were identified separately for skin cancer incidence and mortality. RESULTS: Counties with high vulnerabilities were spatially distributed across the United States in a pattern that generally increased to the South and West. Clusters of counties with high skin cancer incidence vulnerability were mostly observed in Utah and Colorado, even with highly conservative levels of significance. Meanwhile, clusters for skin cancermortality vulnerability were observed in southern Alabama and west Florida as well as across north Alabama, north Georgia and up through the Tennessee-North Carolina area. CONCLUSIONS: Future skin cancer research and screening initiatives may use these innovative composite vulnerability indices and identified clusters to better target resources based on anticipated risk from underlying demographic and environmental factors.
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