Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: FARHADIAN, Maryam, MOGHIMBEIGI, Abbas, ALIABADI, Mohsen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tehran University of Medical Sciences 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3744254/
https://www.ncbi.nlm.nih.gov/pubmed/23967425
_version_ 1782280568889671680
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
work_keys_str_mv AT farhadianmaryam mappingtheobesityiniranbybayesianspatialmodel
AT moghimbeigiabbas mappingtheobesityiniranbybayesianspatialmodel
AT aliabadimohsen mappingtheobesityiniranbybayesianspatialmodel