Literature DB >> 23534706

Area-to-Area Poisson Kriging analysis of mapping of county- level esophageal cancer incidence rates in Iran.

Naeimeh Sadat Asmarian1, Ahmad Ruzitalab, Kavousi Amir, Salehi Masoud, Behzad Mahaki.   

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.

Entities:  

Mesh:

Year:  2013        PMID: 23534706     DOI: 10.7314/apjcp.2013.14.1.11

Source DB:  PubMed          Journal:  Asian Pac J Cancer Prev        ISSN: 1513-7368


  15 in total

1.  POISSON COKRIGING AS A GENERALIZED LINEAR MIXED MODEL.

Authors:  Lynette M Smith; Walter W Stroup; David B Marx
Journal:  Spat Stat       Date:  2019-12-13

2.  Applying and comparing empirical and full Bayesian models in study of evaluating relative risk of suicide among counties of Ilam province.

Authors:  Behzad Mahaki; Yadollah Mehrabi; Amir Kavousi; Youkhabeh Mohammadian; Mehdi Kargar
Journal:  J Educ Health Promot       Date:  2015-08-06

3.  Variations in the spatial distribution of gall bladder cancer: a call for collaborative action.

Authors:  M Krishnatreya; A Saikia; Ac Kataki; Jd Sharma; M Baruah
Journal:  Ann Med Health Sci Res       Date:  2014-09

4.  Estimating the Esophagus Cancer Incidence Rate in Ardabil, Iran: A Capture-Recapture Method.

Authors:  Mahmoud Khodadost; Parvin Yavari; Behnam Khodadost; Masoud Babaei; Fatemeh Sarvi; Seyed Reza Khatibi; Saeed Barzegari
Journal:  Iran J Cancer Prev       Date:  2016-02-17

5.  Risk Prediction Modeling of Sequencing Data Using a Forward Random Field Method.

Authors:  Yalu Wen; Zihuai He; Ming Li; Qing Lu
Journal:  Sci Rep       Date:  2016-02-19       Impact factor: 4.379

6.  Area-to-Area Poisson Kriging and Spatial Bayesian Analysiszzm321990in Mapping of Gastric Cancer Incidence in Iran

Authors:  Naeimehossadat Asmarian; Tohid Jafari-Koshki; Ali Soleimani; Seyyed Mohammad Taghi Ayatollahi
Journal:  Asian Pac J Cancer Prev       Date:  2016-10-01

Review 7.  Incidence and Mortality of Various Cancers in Iran and Compare to Other Countries: A Review Article.

Authors:  Bagher Farhood; Ghazale Geraily; Ahad Alizadeh
Journal:  Iran J Public Health       Date:  2018-03       Impact factor: 1.429

8.  Mapping of Stomach, Colorectal, and Bladder Cancers in Iran, 2004-2009: Applying Bayesian Polytomous Logit Model.

Authors:  Marzieh Nasrazadani; Mohammad Reza Maracy; Emanuela Dreassi; Behzad Mahaki
Journal:  Int J Prev Med       Date:  2018-12-05

9.  Spatial variations of pulmonary tuberculosis prevalence co-impacted by socio-economic and geographic factors in People's Republic of China, 2010.

Authors:  Xin-Xu Li; Li-Xia Wang; Hui Zhang; Shi-Wen Jiang; Qun Fang; Jia-Xu Chen; Xiao-Nong Zhou
Journal:  BMC Public Health       Date:  2014-03-17       Impact factor: 3.295

10.  Exploring spatial patterns of sudden cardiac arrests in the city of Toronto using Poisson kriging and Hot Spot analyses.

Authors:  Raymond Przybysz; Martin Bunch
Journal:  PLoS One       Date:  2017-07-03       Impact factor: 3.240

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