Identifying High-Risk Clusters of Gastric Cancer Incidence in Iran, 2004 - 2009

  • Kavousi, Amir (Department of Basic Sciences, School of Health, Safety and Environment, Shahid Beheshti University of Medical Sciences) ;
  • Bashiri, Yousef (Department of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences) ;
  • Mehrabi, Yadollah (Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences) ;
  • Etemad, Korosh (Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences) ;
  • Teymourpour, Amir (Department of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences)
  • Published : 2015.01.06


Background: Gastric cancer is considered as the second most prevalent cancer in Iran. The present research sought to identify high risk clusters of gastric cancer with mapping using space-time scan statistics. Materials and Methods: The present research is of descriptive type. The required data were gathered from the registered cancer reports of Cancer Control Office in the Center for Non Communicable Disease of the Ministry of Health (MOH). The data were extracted at province level in the time span of 2004-9. Sat-Scan software was used to analyse the data and to identify high risk clusters. ArcGIS10 was utilized to map the distribution of gastric cancer and to demonstrate high risk clusters. Results: The most likely clusters were found in Ardabil, Gilan, Zanjan, East-Azerbaijan, Qazvin, West-Azerbaijan, Kurdistan, Hamadan, Tehran and Mazandaran between 2007 and 2009. It was statistically significant at the p-value below 0.05. Conclusions: High risk regions included Northern, West-North and central provinces, particularly Ardabil, Kurdistan, Mazandaran and Gilan. More screening tests are suggested to be conducted in high risk regions along with more frequent epidemiological studies to enact gastric cancer prevention programs.


Gastric cancer;space-time scan statistics;cluster identification;mapping


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