Volume 13, Issue 3 (Vol.13, No.3, Atumn 2017)
irje 2017, 13(3): 199-209 |
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Seyedagha S, Kavousi A, Baghestani A, Nasehi M. Evaluation of Effect of Geographical Pattern on Improvement of Patients with Pulmonary Tuberculosis Based on A Parametric Accelerated Failure Time Model. irje 2017; 13 (3) :199-209
URL: http://irje.tums.ac.ir/article-1-5817-en.html
URL: http://irje.tums.ac.ir/article-1-5817-en.html
1- School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2- Associate Professor, School of Health, Safety and Environment, Shahid Beheshti University of Medical Sciences, Tehran, Iran , kavousi@sbmu.ac.ir
3- Assistant Professor, Department of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
4- Associate Professor, Department of Epidemiology, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
2- Associate Professor, School of Health, Safety and Environment, Shahid Beheshti University of Medical Sciences, Tehran, Iran , kavousi@sbmu.ac.ir
3- Assistant Professor, Department of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
4- Associate Professor, Department of Epidemiology, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
Abstract: (6033 Views)
Background and Objectives: Tuberculosis is the most common cause of death among single-factor infectious diseases and is the tenth cause of death among all diseases in the world. The disease is spread mainly from an infected person through close contact with other people living in one place. The aim of this study was to investigate the relationship between the spatial correlation structure and the recovery time of patients with pulmonary tuberculosis in Iran.
Methods: In this applied study, the data of 20554 patients with sputum smear-positive pulmonary tuberculosis in Iran from 1389 to 1393 were used. A parametric accelerated failure time model with spatial frailty and batesian approach was used to analyze the data. The OpenBUGS 1.4 was used for programming and the ArcGIS 9.2 was used for mapping the environmental impact on tuberculosis.
Results: The mean age of the patients was 50.35 years with a standard deviation of 21.6 years. The results showed that the geographical environment, gender, prison condition, degree of smear positivity at diagnosis and location (urban-rural) had a significant impact on the recovery time of pulmonary tuberculosis patients. The recovery time of patients with smear grade 1-9 bacilli, 1+ and 2+ who were treated was significantly shorter than the others.
Conclusion: According to the study, geographical environment and the location have a significant impact on smear positive patients’ recovery time. This impact depends on the degree of smear positivity in some provinces and is independent of it in some other provinces.
Methods: In this applied study, the data of 20554 patients with sputum smear-positive pulmonary tuberculosis in Iran from 1389 to 1393 were used. A parametric accelerated failure time model with spatial frailty and batesian approach was used to analyze the data. The OpenBUGS 1.4 was used for programming and the ArcGIS 9.2 was used for mapping the environmental impact on tuberculosis.
Results: The mean age of the patients was 50.35 years with a standard deviation of 21.6 years. The results showed that the geographical environment, gender, prison condition, degree of smear positivity at diagnosis and location (urban-rural) had a significant impact on the recovery time of pulmonary tuberculosis patients. The recovery time of patients with smear grade 1-9 bacilli, 1+ and 2+ who were treated was significantly shorter than the others.
Conclusion: According to the study, geographical environment and the location have a significant impact on smear positive patients’ recovery time. This impact depends on the degree of smear positivity in some provinces and is independent of it in some other provinces.
Keywords: Parametric accelerated failure time model, Spatial statistics, Bayesian analysis, Parametric survival analysis, Pulmonary tuberculosis
Type of Study: Research |
Subject:
General
Received: 2017/11/29 | Accepted: 2017/11/29 | Published: 2017/11/29
Received: 2017/11/29 | Accepted: 2017/11/29 | Published: 2017/11/29
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