• Title, Summary, Keyword: BYM model

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Comparison of Bayesian Spatial Ecological Regression Models for Investigating the Incidence of Breast Cancer in Iran, 2005- 2008

  • Khoshkar, Ahmad Haddad;Koshki, Tohid Jafari;Mahaki, Behzad
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.14
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    • pp.5669-5673
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    • 2015
  • Background: Breast cancer is the most prevalent kind of cancer among women in Iran. Regarding the importance of cancer prevention and considerable variation of breast cancer incidence in different parts of the country, it is necessary to recognize regions with high incidence of breast cancer and evaluate the role of potential risk factors by use of advanced statistical models. The present study focussed on incidence of breast cancer in Iran 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 in the 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, log normal and BYM models were used to estimate the relative risk of breast cancer in this ecological investigation with and without adjustment for the covariates. Results: The unadjusted BYM model had the best fit among applied 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, Lorestan and Hamedan had the highest and Ardebil and Kohgiluyeh-Boyerahmad the lowest incidences. A significantly direct 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.

Area-to-Area Poisson Kriging and Spatial Bayesian Analysis in Mapping of Gastric Cancer Incidence in Iran

  • Asmarian, Naeimehossadat;Jafari-Koshki, Tohid;Soleimani, Ali;Ayatollahi, Seyyed Mohammad Taghi
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.10
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    • pp.4587-4590
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    • 2016
  • Background: In many countries gastric cancer has the highest incidence among the gastrointestinal cancers and is the second most common cancer in Iran. The aim of this study was to identify and map high risk gastric cancer regions at the county-level in Iran. Methods: In this study we analyzed gastric cancer data for Iran in the years 2003-2010. Area-to-area Poisson kriging and Besag, York and Mollie (BYM) spatial models were applied to smoothing the standardized incidence ratios of gastric cancer for the 373 counties surveyed in this study. The two methods were compared in term of accuracy and precision in identifying high risk regions. Result: The highest smoothed standardized incidence rate (SIR) according to area-to-area Poisson kriging was in Meshkinshahr county in Ardabil province in north-western Iran (2.4,SD=0.05), while the highest smoothed standardized incidence rate (SIR) according to the BYM model was in Ardabil, the capital of that province (2.9,SD=0.09). Conclusion: Both methods of mapping, ATA Poisson kriging and BYM, showed the gastric cancer incidence rate to be highest in north and north-west Iran. However, area-to-area Poisson kriging was more precise than the BYM model and required less smoothing. According to the results obtained, preventive measures and treatment programs should be focused on particular counties of Iran.

Spatial Inequalities in the Incidence of Colorectal Cancer and Associated Factors in the Neighborhoods of Tehran, Iran: Bayesian Spatial Models

  • Mansori, Kamyar;Solaymani-Dodaran, Masoud;Mosavi-Jarrahi, Alireza;Motlagh, Ali Ganbary;Salehi, Masoud;Delavari, Alireza;Asadi-Lari, Mohsen
    • Journal of Preventive Medicine and Public Health
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    • v.51 no.1
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    • pp.33-40
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    • 2018
  • Objectives: The aim of this study was to determine the factors associated with the spatial distribution of the incidence of colorectal cancer (CRC) in the neighborhoods of Tehran, Iran using Bayesian spatial models. Methods: This ecological study was implemented in Tehran on the neighborhood level. Socioeconomic variables, risk factors, and health costs were extracted from the Equity Assessment Study conducted in Tehran. The data on CRC incidence were extracted from the Iranian population-based cancer registry. The $Besag-York-Molli{\acute{e}}$ (BYM) model was used to identify factors associated with the spatial distribution of CRC incidence. The software programs OpenBUGS version 3.2.3, ArcGIS 10.3, and GeoDa were used for the analysis. Results: The Moran index was statistically significant for all the variables studied (p<0.05). The BYM model showed that having a women head of household (median standardized incidence ratio [SIR], 1.63; 95% confidence interval [CI], 1.06 to 2.53), living in a rental house (median SIR, 0.82; 95% CI, 0.71 to 0.96), not consuming milk daily (median SIR, 0.71; 95% CI, 0.55 to 0.94) and having greater household health expenditures (median SIR, 1.34; 95% CI, 1.06 to 1.68) were associated with a statistically significant elevation in the SIR of CRC. The median (interquartile range) and mean (standard deviation) values of the SIR of CRC, with the inclusion of all the variables studied in the model, were 0.57 (1.01) and 1.05 (1.31), respectively. Conclusions: Inequality was found in the spatial distribution of CRC incidence in Tehran on the neighborhood level. Paying attention to this inequality and the factors associated with it may be useful for resource allocation and developing preventive strategies in at-risk areas.