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Mapping the Obesity in Iran by Bayesian Spatial Model
BACKGROUND: One of the methods used in the analysis of data related to diseases, and their underlying reasons is drawing geographical map. Mapping diseases is a valuable tool to determine the regions of high rate of infliction requiring therapeutic interventions. The objective of this study was to i...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Tehran University of Medical Sciences
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3744254/ https://www.ncbi.nlm.nih.gov/pubmed/23967425 |
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author | FARHADIAN, Maryam MOGHIMBEIGI, Abbas ALIABADI, Mohsen |
author_facet | FARHADIAN, Maryam MOGHIMBEIGI, Abbas ALIABADI, Mohsen |
author_sort | FARHADIAN, Maryam |
collection | PubMed |
description | BACKGROUND: One of the methods used in the analysis of data related to diseases, and their underlying reasons is drawing geographical map. Mapping diseases is a valuable tool to determine the regions of high rate of infliction requiring therapeutic interventions. The objective of this study was to investigate obesity pattern in Iran by drawing geographical maps based on Bayesian spatial model to recognize the pattern of the understudy symptom more carefully. METHODS: The data of this study consisted of the number of obese people in provinces of Iran in terms of sex based on the reports of non-contagious disease’s risks in 30 provinces by the Iran MSRT disease center in 2007. The analysis of data was carried out by software R and Open BUGS. In addition, the data required for the adjacency matrix were produced by Geo bugs software. RESULTS: The greatest percentage of obese people in all age ranges (15–64) is 17.8 for men in Mazandaran and the lowest is 4.9 in Sistan and Baluchestan. For women the highest and lowest are 29.9 and 11.9 in Mazandaran and Hormozgan, respectively. Mazandaran was considered the province of the greatest odds ratio of obesity for men and women. CONCLUSION: Recognizing the geographical distribution and the regions of high risk of obesity is the prerequisite of decision making in management and planning for health system of the country. The results can be applied in allocating correct resources between different regions of Iran. |
format | Online Article Text |
id | pubmed-3744254 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Tehran University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-37442542013-08-21 Mapping the Obesity in Iran by Bayesian Spatial Model FARHADIAN, Maryam MOGHIMBEIGI, Abbas ALIABADI, Mohsen Iran J Public Health Original Article BACKGROUND: One of the methods used in the analysis of data related to diseases, and their underlying reasons is drawing geographical map. Mapping diseases is a valuable tool to determine the regions of high rate of infliction requiring therapeutic interventions. The objective of this study was to investigate obesity pattern in Iran by drawing geographical maps based on Bayesian spatial model to recognize the pattern of the understudy symptom more carefully. METHODS: The data of this study consisted of the number of obese people in provinces of Iran in terms of sex based on the reports of non-contagious disease’s risks in 30 provinces by the Iran MSRT disease center in 2007. The analysis of data was carried out by software R and Open BUGS. In addition, the data required for the adjacency matrix were produced by Geo bugs software. RESULTS: The greatest percentage of obese people in all age ranges (15–64) is 17.8 for men in Mazandaran and the lowest is 4.9 in Sistan and Baluchestan. For women the highest and lowest are 29.9 and 11.9 in Mazandaran and Hormozgan, respectively. Mazandaran was considered the province of the greatest odds ratio of obesity for men and women. CONCLUSION: Recognizing the geographical distribution and the regions of high risk of obesity is the prerequisite of decision making in management and planning for health system of the country. The results can be applied in allocating correct resources between different regions of Iran. Tehran University of Medical Sciences 2013-06-01 /pmc/articles/PMC3744254/ /pubmed/23967425 Text en Copyright © Iranian Public Health Association & Tehran University of Medical Sciences http://creativecommons.org/licenses/by-nc/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0), which allows users to read, copy, distribute and make derivative works for non-commercial purposes from the material, as long as the author of the original work is cited properly. |
spellingShingle | Original Article FARHADIAN, Maryam MOGHIMBEIGI, Abbas ALIABADI, Mohsen Mapping the Obesity in Iran by Bayesian Spatial Model |
title | Mapping the Obesity in Iran by Bayesian Spatial Model |
title_full | Mapping the Obesity in Iran by Bayesian Spatial Model |
title_fullStr | Mapping the Obesity in Iran by Bayesian Spatial Model |
title_full_unstemmed | Mapping the Obesity in Iran by Bayesian Spatial Model |
title_short | Mapping the Obesity in Iran by Bayesian Spatial Model |
title_sort | mapping the obesity in iran by bayesian spatial model |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3744254/ https://www.ncbi.nlm.nih.gov/pubmed/23967425 |
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