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Epidemiology and Health 2019;e2019032.
DOI: https://doi.org/10.4178/epih.e2019032    [Accepted] Published online July 9, 2019.
Factors associated with the mortality of tuberculosis in Iran: an ‎Application of the Generalized estimating equation based zero-inflated negative binomial model on the national ‎registered data
Fatemeh Sarvi1  , Abbas Moghimbeigi2  , Hossein Mahjoub3  , Mahshid Nasehi4  , Mahmoud Khodadost5 
1Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences‎, Hamadan, Iran
2Modeling of Noncommunicable Diseases Research Center, Department of Biostatistics, School of Public Health, ‎Hamadan University of Medical Sciences, Hamadan, Iran
3Research Center for Health Sciences, Department of Biostatistics, Faculty of Public Health, Hamadan University ‎of Medical Sciences, Hamadan, Iran
4Center for Communicable Diseases Control, Ministry of Health and Medical Education‎, Hamadan, Iran
5Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Correspondence  Abbas Moghimbeigi ,Tel: 0989125683772, Email: moghimb@yahoo.com
Received: May 21, 2019  Accepted after revision: July 9, 2019
Abstract
OBJECTIVES:
Tuberculosis is a global public health problem and it is one of the main reasons ‎for morbidity and mortality for millions per year. The purpose of this study was to examine the ‎relationship between potential risk factors with tuberculosis mortality in Iran.‎
METHODS:
This cross-sectional study was performed on 9151 patients with tuberculosis from ‎March 2017 to March 2018 in Iran. Data was gathered from all 429 counties of Iran by the ‎Ministry of Health and Medical Education and Statistical Center of Iran. In this study, Generalized estimating equation(GEE) based zero-inflated negative binomial(ZINB) model was used to determine the effect of related factors on mortality from ‎tuberculosis in the community level. For data analysis, R (3.4.2) software and related packages ‎were used.
RESULTS:
The results of this study showed that with the increase in unemployment (β ̂=‎‎ 0.016)‎‏ ‏‎, illiteracy (β ̂= 0.042), household density per residential unit (β ̂= 1.29), distance ‎between the center of county and province's capital (β ̂=0.034) and urbanization (β ̂= 0.81), ‎the risk of mortality due to tuberculosis increased. Among the other potential risk factors,‎‏ ‏diabetes (β ̂=0.023), HIV(β ̂=0.039), infected with TB in two recent years (β ̂=0.072) ‎injecting drug use(β ̂=0.075), long-term corticosteroid use(β ̂=0.09), malignant ‎diseases(β ̂=0.09), chronic kidney disease(β ̂=0.32), gastrectomy(β ̂=0.5), chronic ‎malnutrition (β ̂=0.38), and BMI less than 10% (β ̂=0.011), were as risk factors of TB ‎mortality, but silicosis had no effect.‎
CONCLUSIONS:
The results of this study provide useful information to improve knowledge about the risk of ‎increasing mortality from tuberculosis.‎
Keywords: Tuberculosis‎; Risk factors‎; Socio-Economic; Zero-inflated models; Generalized estimating equations (GEE)‎
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