BACKGROUND: Socioeconomic status (SES) has been associated with melanoma incidence and outcomes. Examination of the relationship between melanoma and SES at the national level in the United States is limited. Expanding knowledge of this association is needed to improve early detection and eliminate disparities. OBJECTIVE: We sought to provide a detailed description of cutaneous melanoma incidence and stage of disease in relationship to area-based socioeconomic measures including poverty level, education, income, and unemployment in the United States. METHODS: Invasive cutaneous melanoma data reported by 44 population-based central cancer registries for 2004 to 2006 were merged with county-level SES estimates from the US Census Bureau. Age-adjusted incidence rates were calculated by gender, race/ethnicity, poverty, education, income, unemployment, and metro/urban/rural status using software. Poisson multilevel mixed models were fitted, and incidence density ratios were calculated by stage for area-based SES measures, controlling for age, gender, and state random effects. RESULTS: Counties with lower poverty, higher education, higher income, and lower unemployment had higher age-adjusted melanoma incidence rates for both early and late stage. In multivariate models, SES effects persisted for early-stage but not late-stage melanoma incidence. LIMITATIONS: Individual-level measures of SES were unavailable, and estimates were based on county-level SES measures. CONCLUSION: Our findings show that melanoma incidence in the United States is associated with aggregate county-level measures of high SES. Analyses using finer-level SES measures, such as individual or census tract level, are needed to provide more precise estimates of these associations.
BACKGROUND: Socioeconomic status (SES) has been associated with melanoma incidence and outcomes. Examination of the relationship between melanoma and SES at the national level in the United States is limited. Expanding knowledge of this association is needed to improve early detection and eliminate disparities. OBJECTIVE: We sought to provide a detailed description of cutaneous melanoma incidence and stage of disease in relationship to area-based socioeconomic measures including poverty level, education, income, and unemployment in the United States. METHODS: Invasive cutaneous melanoma data reported by 44 population-based central cancer registries for 2004 to 2006 were merged with county-level SES estimates from the US Census Bureau. Age-adjusted incidence rates were calculated by gender, race/ethnicity, poverty, education, income, unemployment, and metro/urban/rural status using software. Poisson multilevel mixed models were fitted, and incidence density ratios were calculated by stage for area-based SES measures, controlling for age, gender, and state random effects. RESULTS: Counties with lower poverty, higher education, higher income, and lower unemployment had higher age-adjusted melanoma incidence rates for both early and late stage. In multivariate models, SES effects persisted for early-stage but not late-stage melanoma incidence. LIMITATIONS: Individual-level measures of SES were unavailable, and estimates were based on county-level SES measures. CONCLUSION: Our findings show that melanoma incidence in the United States is associated with aggregate county-level measures of high SES. Analyses using finer-level SES measures, such as individual or census tract level, are needed to provide more precise estimates of these associations.
Authors: Thomas B Richards; Christopher J Johnson; Zaria Tatalovich; Myles Cockburn; Melody J Eide; Kevin A Henry; Sue-Min Lai; Sai S Cherala; Youjie Huang; Umed A Ajani Journal: J Am Acad Dermatol Date: 2011-11 Impact factor: 11.527
Authors: Richard J Q McNally; Nermine O Basta; Steven Errington; Peter W James; Paul D Norman; Alan W Craft Journal: J Invest Dermatol Date: 2014-06-13 Impact factor: 8.551
Authors: Cristina A Fernandez; Laura A McClure; William G Leblanc; Tainya C Clarke; Robert S Kirsner; Lora E Fleming; Kristopher L Arheart; David J Lee Journal: South Med J Date: 2012-10 Impact factor: 0.954
Authors: Ashley Meilleur; S V Subramanian; Jesse J Plascak; James L Fisher; Electra D Paskett; Elizabeth B Lamont Journal: Cancer Epidemiol Biomarkers Prev Date: 2013-10 Impact factor: 4.254