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The examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in Iran 2010-2011
Background: Poverty and low socioeconomic status are the most important reasons of increasing the global burden of tuberculosis, not only in developing countries but also in developed countries for particular groups. The purpose of this study was to assess the association between socioeconomic facto...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Iran University of Medical Sciences
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5004564/ https://www.ncbi.nlm.nih.gov/pubmed/27579289 |
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author | Sarvi, Fatemeh Momenian, Somayeh Khodadost, Mahmoud Pahlavanzadeh, Bagher Nasehi, Mahshid Sekhavati, Eghbal |
author_facet | Sarvi, Fatemeh Momenian, Somayeh Khodadost, Mahmoud Pahlavanzadeh, Bagher Nasehi, Mahshid Sekhavati, Eghbal |
author_sort | Sarvi, Fatemeh |
collection | PubMed |
description | Background: Poverty and low socioeconomic status are the most important reasons of increasing the global burden of tuberculosis, not only in developing countries but also in developed countries for particular groups. The purpose of this study was to assess the association between socioeconomic factors and the number of tuberculosis patients using quantile regression for count data. Methods: This cross-sectional study was conducted on 11,320 tuberculosis patients from March 2010 to March 201 in Iran. Data was gathered from the 345 sections of Iran by Ministry of Health and Medical Education and Statistical Center of Iran. The jittering method was applied for smoothing, and then, the quantile regression for count data was fitted. The AIC was used to compare the fitness of quantile regression for count data model and Poisson log-linear model. The R (3.0.1) software and Quantreg and AER packages were used for all analysis and modeling of the data. Results: The results of fitting the quantile regression for count data showed that in all percentiles, the more increase in immigration rate, illiteracy rate, unemployment and urbanization rates, the more tuberculosis morbidity rate was increased. The maximum increase of tuberculosis due to immigration rate, urbanization rate, unemployment rate, and illiteracy rate was in 95th percentile (β^=0.315), 85'Th percentile (β^=0.162), 75'Th percentile (β^=0.114 ), and 95'Th percentile (β^=0.304), respectively. For 50th percentiles and higher percentiles, with increasing the sum of physicians to the number of population, the tuberculosis morbidity rate was decreased, and the maximum decrease was in 95'Th percentile ( β^=-0.1). For all percentiles, the AIC showed that quantile regression for count data had been a better fit to data. Conclusion: With respect to the relationship between socioeconomic factors and TB rate, health care observers should pay close attention to improving these factors in Iran to reduce the TB mortality and morbidity. |
format | Online Article Text |
id | pubmed-5004564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Iran University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-50045642016-08-30 The examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in Iran 2010-2011 Sarvi, Fatemeh Momenian, Somayeh Khodadost, Mahmoud Pahlavanzadeh, Bagher Nasehi, Mahshid Sekhavati, Eghbal Med J Islam Repub Iran Original Article Background: Poverty and low socioeconomic status are the most important reasons of increasing the global burden of tuberculosis, not only in developing countries but also in developed countries for particular groups. The purpose of this study was to assess the association between socioeconomic factors and the number of tuberculosis patients using quantile regression for count data. Methods: This cross-sectional study was conducted on 11,320 tuberculosis patients from March 2010 to March 201 in Iran. Data was gathered from the 345 sections of Iran by Ministry of Health and Medical Education and Statistical Center of Iran. The jittering method was applied for smoothing, and then, the quantile regression for count data was fitted. The AIC was used to compare the fitness of quantile regression for count data model and Poisson log-linear model. The R (3.0.1) software and Quantreg and AER packages were used for all analysis and modeling of the data. Results: The results of fitting the quantile regression for count data showed that in all percentiles, the more increase in immigration rate, illiteracy rate, unemployment and urbanization rates, the more tuberculosis morbidity rate was increased. The maximum increase of tuberculosis due to immigration rate, urbanization rate, unemployment rate, and illiteracy rate was in 95th percentile (β^=0.315), 85'Th percentile (β^=0.162), 75'Th percentile (β^=0.114 ), and 95'Th percentile (β^=0.304), respectively. For 50th percentiles and higher percentiles, with increasing the sum of physicians to the number of population, the tuberculosis morbidity rate was decreased, and the maximum decrease was in 95'Th percentile ( β^=-0.1). For all percentiles, the AIC showed that quantile regression for count data had been a better fit to data. Conclusion: With respect to the relationship between socioeconomic factors and TB rate, health care observers should pay close attention to improving these factors in Iran to reduce the TB mortality and morbidity. Iran University of Medical Sciences 2016-07-17 /pmc/articles/PMC5004564/ /pubmed/27579289 Text en © 2016 Iran 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 Sarvi, Fatemeh Momenian, Somayeh Khodadost, Mahmoud Pahlavanzadeh, Bagher Nasehi, Mahshid Sekhavati, Eghbal The examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in Iran 2010-2011 |
title | The examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in Iran 2010-2011 |
title_full | The examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in Iran 2010-2011 |
title_fullStr | The examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in Iran 2010-2011 |
title_full_unstemmed | The examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in Iran 2010-2011 |
title_short | The examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in Iran 2010-2011 |
title_sort | examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in iran 2010-2011 |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5004564/ https://www.ncbi.nlm.nih.gov/pubmed/27579289 |
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