Epidemiology and Health

Original Articles

Factors associated with mortality from tuberculosis in Iran: an application of a generalized estimating equation-based zero-inflated negative binomial model to national registry data: Fatemeh Sarvi, Abbas Moghimbeigi, Hossein Mahjub, Mahshid Nasehi, Mahmoud Khodadost; Epidemiol Health. 2019;41:e2019032. Published online July 9, 2019; DOI: https://doi.org/10.4178/epih.e2019032

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Abstract PDF: Abstract
OBJECTIVES
Tuberculosis (TB) is a global public health problem that causes morbidity and mortality in millions of people per year. The purpose of this study was to examine the relationship of potential risk factors with TB mortality in Iran.
METHODS
This cross-sectional study was performed on 9,151 patients with TB from March 2017 to March 2018 in Iran. Data were gathered from all 429 counties of Iran by the Ministry of Health and Medical Education and Statistical Center of Iran. In this study, a generalized estimating equation-based zero-inflated negative binomial model was used to determine the effect of related factors on TB mortality at the community level. For data analysis, R version 3.4.2 was used with the relevant packages.
RESULTS
The risk of mortality from TB was found to increase with the unemployment rate (βˆ=0.02), illiteracy (βˆ=0.04), household density per residential unit (βˆ=1.29), distance between the center of the county and the provincial capital (βˆ=0.03), and urbanization (βˆ=0.81). The following other risk factors for TB mortality were identified: diabetes (βˆ=0.02), human immunodeficiency virus infection (βˆ=0.04), infection with TB in the most recent 2 years (βˆ=0.07), injection drug use (βˆ=0.07), long-term corticosteroid use (βˆ=0.09), malignant diseases (βˆ=0.09), chronic kidney disease (βˆ=0.32), gastrectomy (βˆ=0.50), chronic malnutrition (βˆ=0.38), and a body mass index more than 10% under the ideal weight (βˆ=0.01). However, silicosis had no effect.
CONCLUSIONS
The results of this study provide useful information on risk factors for mortality from TB.; Summary

Diabetic peripheral neuropathy class prediction by multicategory support vector machine model: a cross-sectional study: Maryam Kazemi, Abbas Moghimbeigi, Javad Kiani, Hossein Mahjub, Javad Faradmal; Epidemiol Health. 2016;38:e2016011. Published online March 24, 2016; DOI: https://doi.org/10.4178/epih.e2016011

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Abstract

OBJECTIVES
Diabetes is increasing in worldwide prevalence, toward epidemic levels. Diabetic neuropathy, one of the most common complications of diabetes mellitus, is a serious condition that can lead to amputation. This study used a multicategory support vector machine (MSVM) to predict diabetic peripheral neuropathy severity classified into four categories using patients’ demographic characteristics and clinical features.

METHODS

In this study, the data were collected at the Diabetes Center of Hamadan in Iran. Patients were enrolled by the convenience sampling method. Six hundred patients were recruited. After obtaining informed consent, a questionnaire collecting general information and a neuropathy disability score (NDS) questionnaire were administered. The NDS was used to classify the severity of the disease. We used MSVM with both one-against-all and one-against-one methods and three kernel functions, radial basis function (RBF), linear, and polynomial, to predict the class of disease with an unbalanced dataset. The synthetic minority class oversampling technique algorithm was used to improve model performance. To compare the performance of the models, the mean of accuracy was used.

RESULTS

For predicting diabetic neuropathy, a classifier built from a balanced dataset and the RBF kernel function with a one-against-one strategy predicted the class to which a patient belonged with about 76% accuracy.

CONCLUSIONS

The results of this study indicate that, in terms of overall classification accuracy, the MSVM model based on a balanced dataset can be useful for predicting the severity of diabetic neuropathy, and it should be further investigated for the prediction of other diseases.

Summary

Citations

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Ya Wu, Danmeng Dong, Lijie Zhu, Zihong Luo, Yang Liu, Xiaoyun Xie
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Estimation of the Frequency of Intravenous Drug Users in Hamadan City, Iran, Using the Capture-recapture Method: Salman Khazaei, Jalal Poorolajal, Hossein Mahjub, Nader Esmailnasab, Mohammad Mirzaei; Epidemiol Health. 2012;34:e2012006. Published online October 31, 2012; DOI: https://doi.org/10.4178/epih/e2012006

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Abstract PDF

Abstract

<sec><title>OBJECTIVES</title>The number of illicit drug users is prone to underestimation. This study aimed to use the capture-recapture method as a statistical procedure for measuring the prevalence of intravenous drug users (IDUs) by estimating the number of unknown IDUs not registered by any of the registry centers.</sec><sec><title>METHODS</title>This study was conducted in Hamadan City, the west of Iran, in 2012. Three incomplete data sources of IDUs, with partial overlapping data, were assessed including: (a) Volunteer Counseling and Testing Centers (VCTCs); (b) Drop in Centers (DICs); and (c) Outreach Teams (ORTs). A log-linear model was applied for the analysis of three-sample capture-recapture results. Two information criteria were used for model selection including Akaike's Information Criterion and the Bayesian Information Criterion.</sec><sec><title>RESULTS</title>Out of 1,478 IDUs registered by three centers, 48% were identified by VCTCs, 32% by DICs, and 20% by ORTs. After exclusion of duplicates, 1,369 IDUs remained. According to our findings, there were 9,964 (95% CI, 6,088 to 17,636) IDUs not identified by any of the centers. Hence, the real number of IDUs is expected to be 11,333. Based on these findings, the overall completeness of the three data sources was around 12% (95% CI, 7% to 18%).</sec><sec><title>CONCLUSION</title>There was a considerable number of IDUs not identified by any of the centers. Although the capture-recapture method is a useful and practical approach for estimating unknown populations, due to the assumptions and limitations of the method, the results must be interpreted with caution.</sec>

Summary

Citations

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The prevalence of opioid use disorder in Kentucky’s counties: A two-year multi-sample capture-recapture analysis
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Estimating the Population Size of Female Sex Worker Population in Tehran, Iran: Application of Direct Capture–Recapture Method
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Heterogeneity and behavioral response in continuous time capture–recapture, with application to street cannabis use in Italy
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