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3 "Nader Esmailnasab"
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Original Articles
Predictors of tuberculosis and human immunodeficiency virus co-infection: a case-control study
Leila Molaeipoor, Jalal Poorolajal, Minoo Mohraz, Nader Esmailnasab
Epidemiol Health. 2014;36:e2014024.   Published online October 30, 2014
DOI: https://doi.org/10.4178/epih/e2014024
  • 20,261 View
  • 184 Download
  • 25 Web of Science
  • 17 Crossref
AbstractAbstract PDF
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.
Summary

Citations

Citations to this article as recorded by  
  • Joint Modeling of Longitudinal Outcome and Competing Risks: Application to HIV/AIDS Data
    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
    Rengga Rusfa Gumilang, Dwi Wahyu Indriati, Diyantoro Diyantoro, Aliyah Siti Sundari
    Open Access Macedonian Journal of Medical Sciences.2022; 10(A): 893.     CrossRef
  • Effect of Isoniazid Prophylaxis Therapy on the Prevention of Tuberculosis Incidence and Associated Factors Among HIV Infected Individuals in Northwest Ethiopia: Retrospective Cohort Study
    Mulat Addis Beshaw, Shitaye Alemu Balcha, Ayenew Molla Lakew
    HIV/AIDS - Research and Palliative Care.2021; Volume 13: 617.     CrossRef
  • EFFICIENCY OF TREATMENT OF THE FIRST DETECTED TUBERCULOSIS DEPENDING ON THE HIV STATUS IN THE TUBERCULOSIS INSTITUTION OF THE FEDERAL PENITENTIARY SERVICE
    V. S. Borovitsky
    HIV Infection and Immunosuppressive Disorders.2020; 12(1): 83.     CrossRef
  • Determinants of Active Tuberculosis Occurrences after ART Initiation among Adult HIV-Positive Clients in West Showa Zone Public Hospitals, Ethiopia: A Case-Control Study
    Gerbaba Guta Nugus, Mergitu Eliyas Irena
    Advances in Public Health.2020; 2020: 1.     CrossRef
  • Predictors of tuberculosis infection among adults visiting anti-retroviral treatment center at east and west Gojjam, northwest, Ethiopia, 2017
    Habtamu Belew, Moges Wubie, Getaye Tizazu, Abebaw Bitew, Tesfa Birlew
    BMC Infectious Diseases.2020;[Epub]     CrossRef
  • Bayesian Spatial Survival Analysis of Duration to Cure among New Smear-Positive Pulmonary Tuberculosis (PTB) Patients in Iran, during 2011–2018
    Eisa Nazar, Hossein Baghishani, Hassan Doosti, Vahid Ghavami, Ehsan Aryan, Mahshid Nasehi, Saeid Sharafi, Habibollah Esmaily, Jamshid Yazdani Charati
    International Journal of Environmental Research and Public Health.2020; 18(1): 54.     CrossRef
  • Correlation Between Clinical Manifestation and Radiological Findings In Pulmonary Tuberculosis-Human Immunodeficiency Virus Coinfection Patients In Sanglah Hospital, Bali, Indonesia
    Putu Satyakumara Upadhana, Haikal Hamas Putra Iqra, I Gusti Agung Ayu Chintya Cahyarini, I Ketut Agus Somia, Pande Putu Yuli Anandasari
    Current HIV Research.2020; 18(6): 426.     CrossRef
  • THE EFFECTIVENESS OF THE TREATMENT OF TUBERCULOSIS, COMBINED WITH HIV INFECTION IN THE TB FACILITY OF THE FEDERAL PENITENTIARY SERVICE, DEPENDING ON THE TYPE OF DRUG RESISTANCE OF THE PATHOGEN
    V. S. Borovitsky
    HIV Infection and Immunosuppressive Disorders.2019; 11(3): 64.     CrossRef
  • Multistate recursively imputed survival trees for time-to-event data analysis: an application to AIDS and mortality post-HIV infection data
    Leili Tapak, Michael R. Kosorok, Majid Sadeghifar, Omid Hamidi
    BMC Medical Research Methodology.2018;[Epub]     CrossRef
  • Identifying risk factors for progression to AIDS and mortality post-HIV infection using illness-death multistate model
    Omid Hamidi, Leili Tapak, Jalal Poorolajal, Payam Amini
    Clinical Epidemiology and Global Health.2017; 5(4): 163.     CrossRef
  • Treatment outcome of new smear positive pulmonary tuberculosis patients in Hamadan, Iran: A registry-based cross-sectional study
    Salman Khazaei, Jafar Hassanzadeh, Shahab Rezaeian, Ebrahim Ghaderi, Somayeh Khazaei, Abdollah Mohammadian Hafshejani, Hamid Salehiniya, Ali Zahiri
    Egyptian Journal of Chest Diseases and Tuberculosis.2016; 65(4): 825.     CrossRef
  • Survival rate of AIDS disease and mortality in HIV-infected patients: a meta-analysis
    J. Poorolajal, E. Hooshmand, H. Mahjub, N. Esmailnasab, E. Jenabi
    Public Health.2016; 139: 3.     CrossRef
  • Predictors of Tuberculosis in HIV/AIDS Patients Referred to Behavioral Diseases Consultation Center: A Registry-Based Study in Abadan, Southwest of Iran
    Salman Khazaei, Leila Molaeipoor, Shahab Rezaeian, Erfan Ayubi, Mehran Yari, Ali Asghar Valipour, Somayeh Khazaei
    Shiraz E-Medical Journal.2016;[Epub]     CrossRef
  • Prisoners co‐infected with tuberculosis and HIV: a systematic review
    Chantal L Edge, Emma J King, Kate Dolan, Martin McKee
    Journal of the International AIDS Society.2016;[Epub]     CrossRef
  • Predictors of human immunodeficiency virus and tuberculosis co-infection
    Venkataramana Kandi
    Epidemiology and Health.2015; 37: e2015007.     CrossRef
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
  • 16,654 View
  • 104 Download
  • 6 Crossref
AbstractAbstract PDF
Abstract
<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>
Summary

Citations

Citations to this article as recorded by  
  • The prevalence of opioid use disorder in Kentucky’s counties: A two-year multi-sample capture-recapture analysis
    Katherine Thompson, Joshua A. Barocas, Chris Delcher, Jungjun Bae, Lindsey Hammerslag, Jianing Wang, Redonna Chandler, Jennifer Villani, Sharon Walsh, Jeffery Talbert
    Drug and Alcohol Dependence.2023; 242: 109710.     CrossRef
  • Estimating the Population Size of Female Sex Worker Population in Tehran, Iran: Application of Direct Capture–Recapture Method
    Manoochehr Karami, Salman Khazaei, Jalal Poorolajal, Alireza Soltanian, Mansour Sajadipoor
    AIDS and Behavior.2017; 21(8): 2394.     CrossRef
  • Using the capture-recapture method to estimate the human immunodeficiency virus-positive population
    Jalal Poorolajal, Younes Mohammadi, Farzad Farzinara
    Epidemiology and Health.2017; 39: e2017042.     CrossRef
  • Estimation of perinatal mortality rate for institutional births in Rajasthan state, India, using capture–recapture technique
    Prem K Mony, Beena Varghese, Tinku Thomas
    BMJ Open.2015; 5(3): e005966.     CrossRef
  • Estimating the size of the population of persons who inject drugs in the island of Montréal, Canada, using a six-source capture–recapture model
    Pascale Leclerc, Alain C. Vandal, Aïssatou Fall, Julie Bruneau, Élise Roy, Suzanne Brissette, Chris Archibald, Nelson Arruda, Carole Morissette
    Drug and Alcohol Dependence.2014; 142: 174.     CrossRef
  • Heterogeneity and behavioral response in continuous time capture–recapture, with application to street cannabis use in Italy
    Alessio Farcomeni, Daria Scacciatelli
    The Annals of Applied Statistics.2013;[Epub]     CrossRef
The Burden of Premature Mortality in Hamadan Province in 2006 and 2010 Using Standard Expected Years of Potential Life Lost: A Population-based Study
Jalal Poorolajal, Nader Esmailnasab, Jamal Ahmadzadeh, Tahereh Azizi Motlagh
Epidemiol Health. 2012;34:e2012005.   Published online August 31, 2012
DOI: https://doi.org/10.4178/epih/e2012005
  • 17,043 View
  • 126 Download
  • 12 Crossref
AbstractAbstract PDF
Abstract
<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>
Summary

Citations

Citations to this article as recorded by  
  • Suicidal behaviors among intravenous drug users: a meta-analysis
    Bahram Armoon, Marie-Josée Fleury, Azadeh Bayani, Rasool Mohammadi, Elaheh Ahounbar, Mark D. Griffiths
    Journal of Substance Use.2024; 29(1): 10.     CrossRef
  • The Role of Social Support in Preventing Suicidal Ideations and Behaviors: A Systematic Review and Meta-Analysis
    Nahid Darvishi, Jalal Poorolajal, Bita Azmi-Naei, Mehran Farhadi
    Journal of Research in Health Sciences.2024; 24(2): e00609.     CrossRef
  • Anticipating influential factors on suicide outcomes through machine learning techniques: Insights from a suicide registration program in western Iran
    Nasrin Matinnia, Behnaz Alafchi, Arya Haddadi, Ali Ghaleiha, Hasan Davari, Manochehr Karami, Zahra Taslimi, Mohammad Reza Afkhami, Saeid Yazdi-Ravandi
    Asian Journal of Psychiatry.2024; 100: 104183.     CrossRef
  • Diabetes in southern Iran: a 16-year follow-up of mortality and years of life lost
    Habibollah Azarbakhsh, Mohammad Hossein Sharifi, Jafar Hassanzadeh, Rebecca Susan Dewey, Maryam Janfada, Alireza Mirahmadizadeh
    International Journal of Diabetes in Developing Countries.2023; 43(4): 574.     CrossRef
  • Premature Death, Underlying Reasons, and Preventive Experiences in Iran: A Narrative Review
    Iman Razeghian-Jahromi, Yasin Ghasemi Mianrood, Mahintaj Dara, Pouria Azami
    Archives of Iranian Medicine.2023; 26(7): 403.     CrossRef
  • Prevalence, sociodemographic variables, mental health condition, and type of drug use associated with suicide behaviors among people with substance use disorders: a systematic review and meta-analysis
    Bahram Armoon, Neda SoleimanvandiAzar, Marie-Josée Fleury, Alireza Noroozi, Amir-Hossein Bayat, Rasool Mohammadi, Elahe Ahounbar, Ladan Fattah Moghaddam
    Journal of Addictive Diseases.2021; 39(4): 550.     CrossRef
  • The Burden of Premature Mortality Related to Suicide in West Azerbaijan From 2014 to 2016
    Javad Aghazadeh-Attari, Rasool EntezarMahdi, Jamal Ahmadzadeh, Kazhal Mobaraki, Behnam Mansorian, Hasan Karimi, Shamsi Mirghaffarzadeh, Mahnaz Hajimohammadian, Iraj Mohebbi
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    BMC Public Health.2019;[Epub]     CrossRef
  • Substance use disorder and risk of suicidal ideation, suicide attempt and suicide death: a meta-analysis
    Jalal Poorolajal, Tahereh Haghtalab, Mehran Farhadi, Nahid Darvishi
    Journal of Public Health.2016; 38(3): e282.     CrossRef
  • Smoking and Suicide: A Meta-Analysis
    Jalal Poorolajal, Nahid Darvishi, Osama Ali Abulseoud
    PLOS ONE.2016; 11(7): e0156348.     CrossRef
  • Alcohol-Related Risk of Suicidal Ideation, Suicide Attempt, and Completed Suicide: A Meta-Analysis
    Nahid Darvishi, Mehran Farhadi, Tahereh Haghtalab, Jalal Poorolajal, Martin Voracek
    PLOS ONE.2015; 10(5): e0126870.     CrossRef
  • ESTIMATION OF ECONOMIC LOSS DUE TO MORTALITY EXTERNAL CAUSES AS ELEMENT OF POPULATION VITAL ACTIVITY SAFETY IN ARKHANGELSK REGION
    Zh L Varakina, A M Vyazmin, A L Sannikov
    Ekologiya cheloveka (Human Ecology).2014; 21(11): 31.     CrossRef
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