Spatial analysis of Relative Risks for skin cancer morbidity and mortality in Iran, 2008-2010

Asian Pac J Cancer Prev. 2015;16(13):5225-31. doi: 10.7314/apjcp.2015.16.13.5225.

Abstract

Background: One of the most prevalent cancers in whole world is skin cancer and its prevalence is growing. The present research sought to estimate relative risk of morbidity and mortality due to skin cancer.

Materials and methods: In this cross-sectional study. The required data were gathered from the registered cancer reports of Cancer Control Office in the Center for Non Communicable Disease of the Iranian Ministry of Health (MOH). The data were extracted at province level in the time span of 2008-10. WINBUGS software was used to analyze the data and to identify high risk regions. ArcGIS10 was utilized to map the distribution of skin cancer and to demonstrate high risk provinces by using classic and fully Bayesian models taking into account spatial correlations of adjacent regions separately for men and women.

Results: Relative risk of morbidity for women in Yazd and for men in Kurdistan and relative risk of mortality for women in Bushehr and for men in Kohgiluyeh were found to be the highest. Bayesian model due to regarding adjacent regions correlation, have precise estimation in comparing to classical model. More frequent epidemiological studies to enact skin cancer prevention programs.

Conclusions: High risk regions in Iran include central and highland regions. Therefore it is suggested that health decision makers enact public education, using anti UV creams and sunglasses for those parts as a short preventing program.

MeSH terms

  • Bayes Theorem
  • Cross-Sectional Studies
  • Female
  • Follow-Up Studies
  • Humans
  • Iran / epidemiology
  • Male
  • Morbidity
  • Mortality / trends*
  • Neoplasm Staging
  • Prevalence
  • Prognosis
  • Registries
  • Risk Factors
  • Skin Neoplasms / epidemiology
  • Skin Neoplasms / mortality*
  • Skin Neoplasms / pathology*
  • Spatial Analysis*
  • Survival Rate
  • Time Factors