Association of cutaneous melanoma incidence with area-based socioeconomic indicators–United States, 2004-2006

• Published in: Journal of the American Academy of Dermatology 2011-11, Vol.65 (5), p.S58.e1-S58.e12
• Main Authors: Singh, Simple D., MD, MPH, Ajani, Umed A., MBBS, MPH, Johnson, Christopher J., MPH, Roland, Katherine B., MPH, Eide, Melody, MD, MPH, Jemal, Ahmedin, DVM, PhD, Negoita, Serban, MD, DrPH, Bayakly, Rana A., MPH, Ekwueme, Donatus U., PhD
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Aged; cancer; cancer registry; Dermatology; disparities; Ethnic Groups; Female; Health Behavior; Humans; Incidence; Male; melanoma; Melanoma - epidemiology; Melanoma - etiology; Melanoma - prevention & control; Middle Aged; Registries - statistics & numerical data; Skin Neoplasms - epidemiology; Skin Neoplasms - etiology; Skin Neoplasms - prevention & control; Socioeconomic Factors; socioeconomic status; United States - epidemiology; Young Adult
• ISSN: 0190-9622; 1097-6787
• DOI: 10.1016/j.jaad.2011.05.035

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.