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http://dx.doi.org/10.7314/APJCP.2015.16.14.5787

Application of Bayesian Multilevel Space-Time Models to Study Relative Risk of Esophageal Cancer in Iran 2005-2007 at a County Level  

Rastaghi, Sedigheh (Department of Biostatistics, School of Public Health, Isfahan University of Medical Sciences)
Jafari-Koshki, Tohid (Department of Biostatistics, School of Public Health, Sabzevar University of Medical Sciences)
Mahaki, Behzad (Department of Biostatistics, School of Public Health, Isfahan University of Medical Sciences)
Publication Information
Asian Pacific Journal of Cancer Prevention / v.16, no.14, 2015 , pp. 5787-5792 More about this Journal
Abstract
Background: Reported age standardized incidence rates for esophageal cancer in Iran are 0.88 and 6.15 for females and males, at fifth and the eighth ranks, respectively, of cancers overall. The present study aimed to map relative risk using more realistic and less problematic methods than common estimators. Materials and Methods: In this ecological investigation, the studied population consisted of all esophageal cancer patients in Iran from 2005 to 2007. The Bayesian multilevel space-time model with three levels of county, province, and time was used to measure the relative risk of esophageal cancer. Analyses were conducted using R package INLA. Results: The total number of registered patients was 7,160. According to the results, the three-level model with adjustment for risk factors of physical activity and smoking had the best fit among all models. The overall temporal trend was significantly increasing. At county level, Ahar, Marand, Salmas, Bojnoord, Saghez, Sarakhs, Shahroud and Torbatejam had the highest relative risks. Physical activity was found to have significant direct association with risk of developing esophageal cancer. Conclusions: Given to great variation across geographical areas, many different factors affect the incidence of esophageal cancer. Conducting further studies at the individual level in areas with high incidence could provide more detailed information on risk factors of esophageal cancer.
Keywords
Disease mapping; esophageal cancer; Bayesian multilevel space-time model; Iran;
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