Spatial structure of breast cancer using Poisson generalized linear mixed model in Iran

Background: Breast cancer is one of the most common diseases in women and causes more deaths rather than other cancers. The increasing trend of breast cancer in Iran makes clear the need of extensive breast cancer research in this area. Some studies showed that in the variety countries and even in the different areas in one country has different risk of breast cancer incidence and this is a reason that there is a correlation between region of life and risk of breast cancer. The purpose of this study was to determine the spatial structure associated with the incidence of breast cancer based on statistical models and identification of areas with high incidence of breast cancer in Iran. Methods: This ecological study was conducted in Kermanshah University of Medical Sciences, Iran, from February to July 2018. Data on breast cancer patients in all provinces of Iran (30 provinces) were investigated since 2004 to 2009. Risk factors in this study included fruit and vegetable consumption, physical activity, overweight or obesity, and human development index. In this study, we have used routine and spatial Poisson's generalized linear mixed models for data analysis. Results: In both routine and spatial models, direct and significant correlation was found between the incidence of breast cancer and the human development index (P<0.05). In addition to human development index, overweight or obesity factors were also had direct and significant relationship to the incidence of breast cancer in the spatial Poisson's generalized linear mixed model (P<0.05). In the spatial Poisson's generalized linear mixed model with correlation structure of Besag Yorg Molie (BYM), two provinces of Gilan and East Azerbaijan had the highest risk of breast cancer incidence and province of Kohgiluyeh and Boyer Ahmad had the lowest risk of breast cancer incidence. Conclusion: The results showed that the distribution of breast cancer incidence in Iran has a spatial structure. That is, the adjacent provinces have similar incidences of this disease.