Relationship between Urbanization and Cancer Incidence in Iran Using Quantile Regression

Momenyan, Somayeh; Sadeghifar, Majid; Sarvi, Fatemeh; Khodadost, Mahmoud; Mosavi-Jarrahi, Alireza; Ghaffari, Mohammad Ebrahim; Sekhavati, Eghbal

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자료유형: 학술저널

저자정보: Momenyan, Somayeh (Epidemiology and Biostatistics Department, Qom University of Medical Sciences) Sadeghifar, Majid (Department of Statistics, Faculty of Basic Science, Bu Ali Sina University) Sarvi, Fatemeh (Department of Biostatistics& Epidemiology, School of Public Health, Hamadan University of Medical Sciences) Khodadost, Mahmoud (Gastroenterology and Liver Research Center, Baqiyatallah University of Medical Sciences) Mosavi-Jarrahi, Alireza (Medical School, Shahid Beheshti University of Medical Sciences and Health Services, Larestan School of Medical Sciences) Ghaffari, Mohammad Ebrahim (Department of Biostatistics& Epidemiology, School of Public Health, Hamadan University of Medical Sciences) Sekhavati, Eghbal (Larestan School of Medical Sciences)

저널정보: 아시아태평양암예방학회 Asian Pacific journal of cancer prevention : APJCP Asian Pacific journal of cancer prevention : APJCP 제17권 제3호

발행연도: 2016.1

수록면: 113 - 117 (5page)

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Quantile regression is an efficient method for predicting and estimating the relationship between explanatory variables and percentile points of the response distribution, particularly for extreme percentiles of the distribution. To study the relationship between urbanization and cancer morbidity, we here applied quantile regression. This cross-sectional study was conducted for 9 cancers in 345 cities in 2007 in Iran. Data were obtained from the Ministry of Health and Medical Education and the relationship between urbanization and cancer morbidity was investigated using quantile regression and least square regression. Fitting models were compared using AIC criteria. R (3.0.1) software and the Quantreg package were used for statistical analysis. With the quantile regression model all percentiles for breast, colorectal, prostate, lung and pancreas cancers demonstrated increasing incidence rate with urbanization. The maximum increase for breast cancer was in the 90th percentile (${\beta}$=0.13, p-value<0.001), for colorectal cancer was in the 75th percentile (${\beta}$=0.048, p-value<0.001), for prostate cancer the 95th percentile (${\beta}$=0.55, p-value<0.001), for lung cancer was in 95th percentile (${\beta}$=0.52, p-value=0.006), for pancreas cancer was in 10th percentile (${\beta}$=0.011, p-value<0.001). For gastric, esophageal and skin cancers, with increasing urbanization, the incidence rate was decreased. The maximum decrease for gastric cancer was in the 90th percentile(${\beta}$=0.003, p-value<0.001), for esophageal cancer the 95th (${\beta}$=0.04, p-value=0.4) and for skin cancer also the 95th (${\beta}$=0.145, p-value=0.071). The AIC showed that for upper percentiles, the fitting of quantile regression was better than least square regression. According to the results of this study, the significant impact of urbanization on cancer morbidity requirs more effort and planning by policymakers and administrators in order to reduce risk factors such as pollution in urban areas and ensure proper nutrition recommendations are made.

#Urbanization #cancer incidence #quantile regression #Iran

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