Comparison of Bayesian Spatial Ecological Regression Models or Investigating the Incidence of Breast Cancer in Iran, 2005-008


Background: Breast cancer is the most prevalent kind of cancer among women in Iran. Regarding theimportance of cancer prevention and considerable variation of breast cancer incidence in different parts of thecountry, it is necessary to recognize regions with high incidence of breast cancer and evaluate the role of potentialrisk factors by use of advanced statistical models. The present study focussed on incidence of breast cancer inIran at the province level and also explored the impact of some prominent covariates using Bayesian models.Materials and
Methods: All patients diagnosed with breast cancer in Iran from 2005 to 2008 were included inthe study. Smoking, fruit and vegetable intake, physical activity, obesity and the Human Development Index(HDI), measured at the province level, were considered as potential modulating factors. Gamma-Poisson, lognormal and BYM models were used to estimate the relative risk of breast cancer in this ecological investigationwith and without adjustment for the covariates.
Results: The unadjusted BYM model had the best fit amongapplied models. Without adjustment, Isfahan, Yazd, and Tehran had the highest incidences and Sistan-Baluchestan and Chaharmahal-Bakhtiari had the lowest. With the adjusted model, Khorasan-Razavi, Lorestanand Hamedan had the highest and Ardebil and Kohgiluyeh-Boyerahmad the lowest incidences. A significantlydirect association was found between breast cancer incidence and HDI.
Conclusions: BYM model has better fit,because it contains parameters that allow including effects from neighbors. Since HDI is a significant variable,it is also recommended that HDI should be considered in future investigations. This study showed that Yazd,Isfahan and Tehran provinces feature the highest crude incidences of breast cancer.