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Int J Prev Med. 2019 Mar 15;10:39. doi: 10.4103/ijpvm.IJPVM_31_17. eCollection 2019.

Bivariate Spatio-Temporal Shared Component Modeling: Mapping of Relative Death Risk due to Colorectal and Stomach Cancers in Iran Provinces.

Author information

1
Department of Biostatistics and Epidemiology, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran.
2
Department of Biostatistics, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran.
3
Department of Biostatistics, School of Public Health, Kermanshah University of Medical Sciences, Isfahan, Iran.

Abstract

Background:

Gastrointestinal cancers make for nearly half fatal cancers with colorectal and stomach cancers' being listed among the ten most common in Iran. This research aims to determine the spatial pattern and temporal trend of death risk due to colorectal and stomach cancers among provinces of Iran and estimate the effect of shared and specific components as surrogates of risk factors for the aforementioned cancers on changes of death due to the cancers over time and place.

Methods:

In this ecological study, the data regarding death causes in colorectal and stomach cancers during 2006-2011 were obtained from the death registration system of the Iranian Ministry of Health. The estimation of relative risk (RR) of death due to the target cancers was performed applying Bayesian spatiotemporal shared component (SC) model in OpenBUGS software.

Results:

North-Western provinces ranked first regarding stomach cancer RR of death (RR >1.75). Furthermore, some North-Western and central provinces had the highest RR of death due to colorectal cancer (RR >1.5). The SC surrogating the risk factor shared between both cancers had the most effect in Northern, North-Western and western provinces, and the least effect in Southern and South-Eastern ones.

Conclusions:

North and North-West of Iran found to be the high-risk area for death due to both stomach and colorectal cancers and South-East and South provinces shown to have the lowest RR. The obtained results can be illuminating to health resource allocation to the health policymakers.

KEYWORDS:

Bayesian model; colorectal cancer; disease mapping; model; shared component; stomach cancer

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