Proportional melanoma incidence and occupation among white males in Los Angeles County (California, United States)

Cancer Causes Control. 1995 Sep;6(5):451-9. doi: 10.1007/BF00052186.


A case-control analysis of cancer registry data was used to examine the hypothesis that occupational exposure to sunlight influences the risk of melanoma. Occupation at diagnosis was available for 3,527 cutaneous melanomas and 53,129 other cancers identified by the Los Angeles County (California, United States) Cancer Surveillance Program among non-Spanish-surnamed White males aged 20 to 65 years between 1972 and 1990. Occupational exposure to sunlight was assessed by blinded expert coding of job titles as indoor, outdoor, and mixed indoor/outdoor. Relative to indoor occupations, proportionate odds ratios (OR) adjusted for age, level of education, and birthplace were 1.16 (95 percent confidence interval [CI] = 1.07-1.27) for indoor/outdoor occupations and 1.15 (CI = 0.94-1.40) for outdoor occupations. However, increasing levels of the education or training required for the occupation was associated more strongly with increased melanoma occurrence (ORs adjusted for age, occupational sun exposure, and birthplace, were 1.0, 1.63, 2.09, 2.23, and 2.99 for low-skill occupation, high school, college, postgraduate, and doctoral levels, respectively). Analysis of melanoma occurrence by job titles confirmed a clear variation by the required education or training level but not by the category of occupational sunlight exposure. The findings suggest that lifestyle factors associated with higher levels of education may be more important determinants of melanoma risk than characteristics of the work environment.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Case-Control Studies
  • Humans
  • Incidence
  • Los Angeles / epidemiology
  • Male
  • Melanoma / epidemiology*
  • Melanoma / etiology
  • Middle Aged
  • Occupational Exposure / adverse effects*
  • Odds Ratio
  • Registries
  • Risk Factors
  • Socioeconomic Factors
  • Sunlight / adverse effects*
  • White People