The geographic distribution of melanoma incidence in Massachusetts, adjusted for covariates.
BACKGROUND
The aims of this study were to determine whether observed geographic variations in melanoma cancer incidence in both gender groups are simply random or are statistically significant, whether statistically significant excesses are temporary or persistent, and whether they can be explained by risk factors such as socioeconomic status (SES) or the percent of the population residing in an urban rather than a rural area. Between 1990 and 1999, 4774 female and 5688 male melanomas were diagnosed in Massachusetts residents. Cases were aggregated to census tracts and analyzed for deviations from random occurrence with respect to both spatial location and time.


RESULTS
Thirteen geographic areas that deviated significantly from randomness were uncovered in the age-adjusted analyses of males: five with higher incidence rates than expected and eight lower than expected. In the age-adjusted analyses of females, six areas with higher incidence rates and eight areas with lower than expected incidence rates were found. After adjustment for SES and percent urban, several of these areas were no longer significantly different.


CONCLUSIONS
These analyses identify geographic areas with invasive melanoma incidence higher or lower than expected, the times of their excess, and whether or not their status is affected when the model is adjusted for risk factors. These surveillance findings can be a sound starting point for the shoe-leather epidemiologist.
DeChello
Laurie M
LM
Department of Community Medicine and Health Care, University of Connecticut School of Medicine, 263 Farmington Ave, Farmington, CT 06030-6325, USA. dechello@nso.uchc.edu
Sheehan
T Joseph
TJ
D000367:Age Factors; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008404:Massachusetts / Q000453:epidemiology; D008545:Melanoma / Q000453:epidemiology*; D016012:Poisson Distribution; D012189:Retrospective Studies; D017678:Sex Distribution; D012878:Skin Neoplasms / Q000453:epidemiology*; D012959:Socioeconomic Factors; D013029:Space-Time Clustering; D019371:Topography, Medical / Q000379:methods / Q000706:statistics & numerical data