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Area-to-Area Poisson Kriging Analysis of Mapping of County-Level Esophageal Cancer Incidence Rates in Iran

  • Asmarian, Naeimeh Sadat (Department of Biostatistics, School of Paramedicine, Safety and Environment, Shahid Beheshti University of medical Sciences) ;
  • Ruzitalab, Ahmad (Department of Applied Mathematics, School of mathematic Sciences, Ferdowsi University of mashhad) ;
  • Amir, Kavousi (Department of Sciences, School of Health, Safety and Environment, Shahid Beheshti University of medical Sciences) ;
  • Masoud, Salehi (Department of Statistics and Mathematics, School of Health Management and Information Sciences, Member of Health Management and Economics Research Center, Tehran University of Medical Sciences) ;
  • Mahaki, Behzad (Department of Biostatistics, School of Public Health, Isfahan University of Medical Sciences)
  • Published : 2013.01.31

Abstract

Background: Esophagus cancer, the third most common gastrointestinal cancer overall, demonstrates high incidence in parts of Iran. The counties of Iran vary in size, shape and population size. The aim of this study was to account for spatial support with Area-to-Area (ATA) Poisson Kriging to increase precision of parameter estimates and yield correct variance and create maps of disease rates. Materials and Methods: This study involved application/ecology methodology, illustrated using esophagus cancer data recorded by the Ministry of Health and Medical Education (in the Non-infectious Diseases Management Center) of Iran. The analysis focused on the 336 counties over the years 2003-2007. ATA was used for estimating the parameters of the map with SpaceStat and ArcGIS9.3 software for analysing the data and drawing maps. Results: Northern counties of Iran have high risk estimation. The ATA Poisson Kriging approach yielded variance increase in large sparsely populated counties. So, central counties had the most prediction variance. Conclusions: The ATAPoisson kriging approach is recommended for estimating parameters of disease mapping since this method accounts for spatial support and patterns in irregular spatial areas. The results demonstrate that the counties in provinces Ardebil, Mazandaran and Kordestan have higher risk than other counties.

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