- Volume 16 Issue 14
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Investigating the Incidence of Prostate Cancer in Iran 2005-2008 using Bayesian Spatial Ecological Regression Models
- Haddad-Khoshkar, Ahmad (Department of Biostatistics, School of Public Health, Isfahan University of Medical Sciences) ;
- Koshki, TohidJafari (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)
- Published : 2015.09.02
Background: Prostate cancer is the most commonly diagnosed form of cancer and the sixth leading cause of cancer-related deaths among men in the entire world. Reported standardized incidence rates are 12.6, 61.7, 11.9 and 27.9 in Iran, developed countries, developing countries and the entire world, respectively. The present study investigated the relative risk of PC in Iran at the province level and also explored the impact of some factors by the use of Bayesian models. Materials and Methods: Our study population was all men with PC in Iran from 2005 to 2008. Considered risk factors were smoking, fruit and vegetable intake, physical activity, obesity and human development index. We used empirical and full Bayesian models to study the relative risk in Iran at province level to estimate the risk of PC more accurately. Results: In Iran from 2005 to 2008 the total number of known PC cases was 10,361 with most cases found in Fars and Tehran and the least in Ilam. In all models just human development index was found to be significantly related to PC risk Conclusions: In the unadjusted model, Fars, Semnam, Isfahan and Tehran provinces have the highest and Sistan-and-Baluchestan has the least risk of PC. In general, central provinces have high risk. After adjusting for covariates, Fars and Zanjan provinces have the highest relative risk and Kerman, Northern Khorasan, Kohgiluyeh Boyer Ahmad, Ghazvin and Kermanshah have the lowest relative risk. According to the results, the incidence of PC in provinces with higher human development index is higher.
- Afar D, Henshall S, Hiller J, et al (2006). Methods of prognosis of prostate cancer. (Google Patents).
- Akbari M, Abachizadeh K, Khayamzadeh M, et al (2008). Iran cancer report. cancer research center shahid beheshti university of medical sciences Tehran, Qom: Darolfekr.
- Allen NE, Sauvaget C, Roddam AW, et al (2004). A prospective study of diet and prostate cancer in Japanese men. Cancer Causes Control, 15, 911-20. https://doi.org/10.1007/s10552-004-1683-y
- Asmarian NS, Kavousi A, Salehi M, et al (2013). Comparison of point poisson kriging and empirical bayesian methods in mapping of gastrointestinal cancer incidence rate in Iran. J Health Syst Res, 9, 277-85.
- Bashir MN, Ahmad MR, Malik A (2014). Risk factors of prostate cancer: a case-control study in Faisalabad, Pakistan. Asian Pac J Cancer [Epub ahead of print].
- Bray F, Jemal A, Grey N, et al (2012). Global cancer transitions according to the Human Development Index (2008?2030): a population-based study. Lancet Oncol, 13, 790-801. https://doi.org/10.1016/S1470-2045(12)70211-5
- Clayton D, Kaldor J (1987). Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics J, 43, 671-81. https://doi.org/10.2307/2532003
- Cheung MR, Kang J, Ouyang D, et al (2014). Association between urinary cadmium and all cause, all cancer and prostate cancer specific mortalities for men: an analysis of National Health and Nutrition Examination Survey (NHANES III) Data. Asian Pac J Cancer Prev, 15, 483. https://doi.org/10.7314/APJCP.2014.15.1.483
- Jin JK, Dayyani F, Gallick GE (2011). Steps in prostate cancer progression that lead to bone metastasis. Int J Cancer, 128, 2545-61. https://doi.org/10.1002/ijc.26024
- Lawson A, Biggeri A, Bohning D, et al (1999). Disease mapping and risk assessment for public health (John Wiley & Sons).
- Lawson AB, Browne WJ, Rodeiro CLV (2003). Disease mapping with WinBUGS and MLwiN (11: John Wiley & Sons).
- Mahaki B, Mehrabi Y, Kavousi A, et al (2011). Multivariate disease mapping of seven prevalent cancers in Iran using a shared component model. Asian Pac J Cancer Prev, 12, 2353-8.
- Mahaki B, Mehrabi Y, Kavousi A, et al (2013). Applying gammapoisson, lognormal, and BYM models in comparing relative risk of suicide among provinces of Ilam, Iran. J Health Syst Res, 9, 86-95.
- McGrowder DA, Jackson LA, Crawford TV (2012). prostate cancer and metabolic syndrome: is there a link. Asian Pac J Cancer Prev, 13, 1-13. https://doi.org/10.7314/APJCP.2012.13.1.001
- Nilsen TIL, Johnsen, R, Vatten LJ (2000). Socio-economic and lifestyle factors associated with the risk of prostate cancer. British Journal of Cancer, 82, 1358. https://doi.org/10.1054/bjoc.1999.1105
- Pelucchi C, Talamini R, Galeone C, et al (2004). Fibre intake and prostate cancer risk. Int J Cancer, 109, 278-80. https://doi.org/10.1002/ijc.11688
- Rodriguez C, Freedland SJ, Deka A, et al (2007). Body mass index, weight change, and risk of prostate cancer in the cancer prevention study II nutrition cohort. Cancer Epidemiol Biomarkers Prev, 16, 63-69. https://doi.org/10.1158/1055-9965.EPI-06-0754
- Snowdon DA, PHILLIPS RL, Choi W (1984). Diet, obesity, and risk of fatal prostate cancer. Am J Epidemiol, 120, 244-50.
- Tewari R, Chhabra M, Natu SM, et al. (2014). Significant association of metabolic indices, lipid profile, and androgen levels with prostate cancer. Asian Pac J Cancer Prev, 15, 9841-46. https://doi.org/10.7314/APJCP.2014.15.22.9841
- Thune I, Lund E (1994). Physical activity and the risk of prostate and testicular cancer: a cohort study of 53,000 Norwegian men. Cancer Causes Control, 5, 549-56. https://doi.org/10.1007/BF01831383