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Predictors of tuberculosis and human immunodeficiency virus co-infection: a case-control study
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Leila Molaeipoor, Jalal Poorolajal, Minoo Mohraz, Nader Esmailnasab
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Epidemiol Health. 2014;36:e2014024. Published online October 30, 2014
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DOI: https://doi.org/10.4178/epih/e2014024
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Abstract
OBJECTIVES The human immunodeficiency virus (HIV) and Mycobacterium tuberculosis co-infection is a major global challenge. It is not clear why some HIV-positive people are co-infected with tuberculosis (TB) while others are not. This study addressed that question.
METHODS This case-control study was conducted in Tehran, Iran in June 2004, enrolling 2,388 HIV-positive people. Cases were selected from those who were co-infected with TB and controls from those without TB. Multiple logistic regression analysis was performed to assess the association between M. tuberculosis/HIV co-infection and several predictors. Odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated.
RESULTS In this study, 241 cases were compared with 2,147 controls. Sex, age, marital status, educational level, imprisonment, smoking, narcotic use, route of HIV transmission, previous TB infection, isoniazid preventive therapy (IPT), antiretroviral therapy (ART), and low CD4 count (<350 cells/mm3) were independently associated with M. tuberculosis/HIV co-infection (p<0.001). However, after adjusting for all other variables in the model, only the association between M. tuberculosis/HIV co-infection and the following predictors remained statistically significant: imprisonment (odds ratio [OR], 3.82; 95% confidence interval [CI], 2.11-6.90), previous TB infection (OR, 5.54; 95% CI, 1.99-15.39), IPT (OR, 0.13; 95% CI, 0.06-0.31), ART (OR, 1.81; 95% CI, 1.26-2.61), and CD4 count <350 cells/mm3 (OR, 2.34; 95% CI, 1.36-4.02).
CONCLUSIONS Several predictors are associated with M. tuberculosis/HIV co-infection, but only a few indicators were significantly associated with M. tuberculosis/HIV co-infection. It is estimated that a number of predictors of M. tuberculosis/HIV co-infection remain unknown and require further investigation.
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Khadijeh Najafi Ghobadi, Hossein Mahjub, Jalal Poorolajal, Ebrahim Shakiba, Kaivan Khassi, Ghodratollah Roshanaei Journal of Research in Health Sciences.2023; 23(1): e00571. CrossRef - Clinico-epidemiological Determinants of Tuberculosis Co-infection among Adults Attending an Antiretroviral Centre at a Tertiary Care Hospital in Madhya Pradesh
Preeti Gupta, Akanksha Tomar, Manoj Bansal, Rajesh Kumar Gupta Journal of Medical Evidence.2023; 4(3): 220. CrossRef - The Occurrence of Tuberculosis Infection among Newly HIV Diagnosed Patient in Indonesia
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The Burden of Premature Mortality in Hamadan Province in 2006 and 2010 Using Standard Expected Years of Potential Life Lost: A Population-based Study
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Jalal Poorolajal, Nader Esmailnasab, Jamal Ahmadzadeh, Tahereh Azizi Motlagh
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Epidemiol Health. 2012;34:e2012005. Published online August 31, 2012
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DOI: https://doi.org/10.4178/epih/e2012005
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17,250
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<sec><title>OBJECTIVES</title><p>Examining the premature death rate represents the first step in estimating the overall burden of disease, reflecting a full picture of how different causes affect population health and providing a way of monitoring and evaluating population health. The present study was conducted to assess the burden of premature mortality in Hamadan Province, Iran in 2006 and 2010.</p></sec><sec><title>METHODS</title><p>To calculate years of potential life lost (YPLL), the dataset was categorized into 5-year age groups based on each person's age at death. Then the age groups were subtracted from the relevant age-based life table produced by the World Health Organization in 2009. The YPLL for each individual were then added together to yield the total YPLL for all individuals in the population who died in a particular year. Finally, we calculated the YPLL for all sex-, age-, and cause-specific mortality rates and reported them as percentages.</p></sec><sec><title>RESULTS</title><p>We analyzed 18,786 deaths, 9,127 of which occurred in 2006 and 9,659 in 2010. Mortality rates were higher in men than women for all age groups both in 2006 and 2010. In addition, age-specific mortality rates in both genders for all age groups were higher in 2010 than in 2006. The percentage of YPLL from ischemic heart diseases, cerebrovascular diseases, transport accidents, and intentional self-harm were among the greatest sources of premature death.</p></sec><sec><title>CONCLUSION</title><p>The results of the present survey indicate that the eight major causes of premature death in both 2006 and 2010 were non-communicable diseases, especially ischemic heart diseases, cerebrovascular diseases, transport accidents, and intentional self-harm. Furthermore, our findings indicate a change in the role of non-communicable diseases in premature mortality in recent years.</p></sec>
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Estimation of the Frequency of Intravenous Drug Users in Hamadan City, Iran, Using the Capture-recapture Method
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Salman Khazaei, Jalal Poorolajal, Hossein Mahjub, Nader Esmailnasab, Mohammad Mirzaei
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Epidemiol Health. 2012;34:e2012006. Published online October 31, 2012
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DOI: https://doi.org/10.4178/epih/e2012006
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16,832
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<sec><title>OBJECTIVES</title><p>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.</p></sec><sec><title>METHODS</title><p>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.</p></sec><sec><title>RESULTS</title><p>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%).</p></sec><sec><title>CONCLUSION</title><p>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.</p></sec>
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