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Article ; Online: Establishing a cohort in a developing country

Fatima Mukhtar / Zahid A. Butt

Journal of Epidemiology and Global Health, Vol 7, Iss

Experiences of the diabetes-tuberculosis treatment outcome cohort study

2019 Volume 4

Abstract: Background: Prospective cohort studies are instrumental in generating valid scientific evidence based on identifying temporal associations between cause and effect. Researchers in a developing country like Pakistan seldom undertake cohort studies hence ... ...

Abstract	Background: Prospective cohort studies are instrumental in generating valid scientific evidence based on identifying temporal associations between cause and effect. Researchers in a developing country like Pakistan seldom undertake cohort studies hence little is known about the challenges encountered while conducting them. We describe the retention rates among tuberculosis patients with and without diabetes, look at factors associated with loss to follow up among the cohort and assess operational factors that contributed to retention of cohort. Methods: A prospective cohort study was initiated in October 2013 at the Gulab Devi Chest Hospital, Lahore, Pakistan. We recruited 614 new adult cases of pulmonary tuberculosis, whose diabetic status was ascertained by conducting random and fasting blood glucose tests. The cohort was followed up at the 2nd, 5th and 6th month while on anti-tuberculosis therapy (ATT) and 6 months after ATT completion to determine treatment outcomes among the two groups i.e. patients with diabetes and patients without diabetes. Results: The overall retention rate was 81.9% (n = 503), with 82.3% (93/113) among patients with diabetes and 81.8% (410/501) among patients without diabetes (p = 0.91). Age (p = 0.001), area of residence (p = 0.029), marital status (p = 0.001), educational qualification (p = <0.001) and smoking (p = 0.026) were significantly associated with loss to follow up. Respondents were lost to follow up due to inability of research team to contact them as either contact numbers provided were incorrect or switched off (44/111, 39.6%). Conclusion: We were able to retain 81.9% of PTB patients in the diabetes tuberculosis treatment outcome (DITTO) study for 12 months. Retention rates among people with and without diabetes were similar. Older age, rural residence, illiteracy and smoking were associated with loss to follow up. The study employed gender matched data collectors, had a 24-h helpline for patients and sent follow up reminders through telephone calls rather than short messaging service, which might have contributed to retention of cohort.
Keywords	Cohort study ; Pakistan ; Diabetes ; Tuberculosis ; Public aspects of medicine ; RA1-1270
Subject code	616
Language	English
Publishing date	2019-04-01T00:00:00Z
Publisher	Springer
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Prevalence of Neonatal Mortality and its Associated Factors

Md. Akhtarul Islam / Zahid A. Butt / Nusrat Jahan Sathi

Dr. Sulaiman Al Habib Medical Journal, Vol 4, Iss 3, Pp 145-

A Meta-analysis of Demographic and Health Survey Data from 21 Developing Countries

2022 Volume 152

Abstract: Abstract Neonatal mortality is high in developing countries, and reducing neonatal mortality is an indispensable part of the third Sustainable Development Goal. This study estimated the prevalence of neonatal mortality and the impact of maternal ... ...

Abstract	Abstract Neonatal mortality is high in developing countries, and reducing neonatal mortality is an indispensable part of the third Sustainable Development Goal. This study estimated the prevalence of neonatal mortality and the impact of maternal education, economic status, and utilization of antenatal care (ANC) services on neonatal mortality in developing countries. We used a cross-sectional study design to integrate data from 21 developing countries to acquire a wider perspective on neonatal mortality. A meta-analysis was conducted using the latest Demographic and Health Survey data from 21 developing countries. In addition, sensitivity analysis was adopted to assess the stability of the meta-analysis. The random-effects model indicated that women with higher education were less likely to experience neonatal death than mothers with up to primary education (odds ratio [OR] 0.820, 95% confidence interval [CI] 0.740–0.910). Women with higher socioeconomic status were less likely to experience neonatal death than mothers with lower socioeconomic status (OR 0.823, 95% CI 0.747–0.908). Mothers with ANC were less likely to experience neonatal death than those with no ANC (OR 0.374, 95% CI 0.323–0.433). Subgroup analysis showed that maternal education and ANC were more effective in Asian countries. In this study, mothers’ lower educational level, poor economic status, and lack of ANC were statistically significant factors associated with neonatal death in developing countries. The effect of these factors on neonatal death differed in different regions.
Keywords	Neonatal mortality ; Maternal education ; Antenatal care ; Sustainable development goals ; Meta-analysis ; Medicine (General) ; R5-920
Subject code	310
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	Springer
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Risk of adverse treatment outcomes among new pulmonary TB patients co-infected with diabetes in Pakistan

Fatima Mukhtar / Zahid A Butt

PLoS ONE, Vol 13, Iss 11, p e

A prospective cohort study.

2018 Volume 0207148

Abstract: PURPOSE:The escalating burden of diabetes in countries tackling high burden of tuberculosis (TB) has adverse implications for co-infected individuals and National TB control efforts. We aimed to study whether there was a difference in treatment outcome ... ...

Abstract	PURPOSE:The escalating burden of diabetes in countries tackling high burden of tuberculosis (TB) has adverse implications for co-infected individuals and National TB control efforts. We aimed to study whether there was a difference in treatment outcome among diabetic and non-diabetic pulmonary TB patients and identify the determinants of treatment outcome among the two groups. MATERIALS AND METHODS:This prospective cohort study recruited new patients of pulmonary tuberculosis (PTB) aged 15 years and above who were diagnosed at and registered with Gulab Devi Chest Hospital, Lahore, Pakistan for anti-tuberculosis treatment (ATT). PTB patients were screened for diabetes using random and fasting blood glucose tests. Diabetic and non-diabetic PTB patients were followed up at second, fifth and sixth month of ATT and 6 months after ATT completion to determine treatment outcome. Multivariate logistic regression analysis was conducted to assess association between various factors and treatment outcome. RESULTS:Of 614 PTB patients, (n = 113 [18%]) were diabetic and (n = 501 [82%]) non-diabetic. Final model showed that diabetics were more likely to experience an unfavorable outcome as compared to non-diabetics (adjusted odds ratio [aOR] = 2.70, 95% Confidence Interval [CI] = 1.30 to 5.59). Other predictors of unfavorable outcome included rural residence (aOR = 1.98, 95% CI = 1.14 to 3.47), body mass index less than 18.50 (aOR = 1.89, 95% CI = 1.03 to 3.47) and being a smoker (aOR = 2.03, 95%CI = 1.04 to 3.94). CONCLUSION:Our study shows unfavorable treatment outcome among diabetic PTB patients. Integrated models of care with screening/testing and management for diabetes and TB could improve TB treatment outcomes.
Keywords	Medicine ; R ; Science ; Q
Subject code	616
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Pattern discovery and disentanglement on relational datasets

Andrew K. C. Wong / Pei-Yuan Zhou / Zahid A. Butt

Scientific Reports, Vol 11, Iss 1, Pp 1-

2021 Volume 11

Abstract: Abstract Machine Learning has made impressive advances in many applications akin to human cognition for discernment. However, success has been limited in the areas of relational datasets, particularly for data with low volume, imbalanced groups, and ... ...

Abstract	Abstract Machine Learning has made impressive advances in many applications akin to human cognition for discernment. However, success has been limited in the areas of relational datasets, particularly for data with low volume, imbalanced groups, and mislabeled cases, with outputs that typically lack transparency and interpretability. The difficulties arise from the subtle overlapping and entanglement of functional and statistical relations at the source level. Hence, we have developed Pattern Discovery and Disentanglement System (PDD), which is able to discover explicit patterns from the data with various sizes, imbalanced groups, and screen out anomalies. We present herein four case studies on biomedical datasets to substantiate the efficacy of PDD. It improves prediction accuracy and facilitates transparent interpretation of discovered knowledge in an explicit representation framework PDD Knowledge Base that links the sources, the patterns, and individual patients. Hence, PDD promises broad and ground-breaking applications in genomic and biomedical machine learning.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Factors Affecting the Utilization of Antenatal Care Services During Pregnancy in Bangladesh and 28 Other Low- and Middle-income Countries

Md. Akhtarul Islam / Nusrat Jahan Sathi / Hossain Mohammad Abdullah / Jannatul Naime / Zahid A. Butt

Dr. Sulaiman Al Habib Medical Journal, Vol 4, Iss 1, Pp 19-

A Meta-analysis of Demographic and Health Survey Data

2022 Volume 31

Abstract: Abstract The study aimed to identify the factors influencing the utilization of antenatal care (ANC) services among pregnant women to fulfill the Sustainable Development Goals (SDG) for maternal mortality ratio (MMR) by 2030; we also investigated the ... ...

Abstract	Abstract The study aimed to identify the factors influencing the utilization of antenatal care (ANC) services among pregnant women to fulfill the Sustainable Development Goals (SDG) for maternal mortality ratio (MMR) by 2030; we also investigated the consistency of these factors. We have used the Demographic and Health Survey (DHS) data from 29 developing countries for analysis. A binary logistic regression model was run using Demographic and Health Survey data from Bangladesh to determine the factors influencing ANC utilization in Bangladesh. In addition, a random-effects model estimation for meta-analysis was performed using DHS data from 29 developing to investigate the overall effects and consistency between covariates and the utilization of ANC services. Logistic regression revealed that residence (odds ratio [OR] 1.436; 95% confidence interval [CI] 1.238, 1.666), respondent’s education (OR 3.153; 95% CI 2.204, 4.509), husband’s education (OR 2.507; 95% CI 1.922, 3.271) wealth index (OR 1.485; 95% CI 1.256, 1.756), birth order (OR 0.786; 95% CI 0.684, 0.904), working status (OR 1.292; 95% CI 1.136, 1.470), and media access (OR 1.649; 95% CI 1.434, 1.896) were the main significant factors for Bangladesh. Meta-analysis showed that residence (OR 2.041; 95% CI 1.621, 2.570), respondent’s age (OR 1.260; 95% CI 1.106, 1.435), respondent’s education level (OR 2.808; 95% CI 2.353, 3.351), husband’s education (OR 2.267; 95% CI 1.911, 2.690), wealth index (OR 2.715; 95% CI 2.199, 3.352), birth order (OR 1.722; 95% CI 1.388, 2.137), and media access (OR 2.474; 95% CI 2.102, 2.913) were the most conclusive factors in a subjects decision to attend ANC. Our results support the augmentation of maternal education and media access in rural areas with ANC services. Particular focus is needed for women from Afghanistan since they have a lower level of ANC services.
Keywords	Antenatal care ; Developing countries ; DHS ; Meta-analysis ; Ethiopia ; Logistic ; Medicine (General) ; R5-920
Subject code	310
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	Springer
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Understanding the Differential Impact of Vegetation Measures on Modeling the Association between Vegetation and Psychotic and Non-Psychotic Disorders in Toronto, Canada

Abu Yousuf Md Abdullah / Jane Law / Zahid A. Butt / Christopher M. Perlman

International Journal of Environmental Research and Public Health, Vol 18, Iss 4713, p

2021 Volume 4713

Abstract: Considerable debate exists on whether exposure to vegetation cover is associated with better mental health outcomes. Past studies could not accurately capture people’s exposure to surrounding vegetation and heavily relied on non-spatial models, where the ...

Abstract	Considerable debate exists on whether exposure to vegetation cover is associated with better mental health outcomes. Past studies could not accurately capture people’s exposure to surrounding vegetation and heavily relied on non-spatial models, where the spatial autocorrelation and latent covariates could not be adjusted. Therefore, a suite of five different vegetation measures was used to separately analyze the association between vegetation cover and the number of psychotic and non-psychotic disorder cases in the neighborhoods of Toronto, Canada. Three satellite-based and two area-based vegetation measures were used to analyze these associations using Poisson lognormal models under a Bayesian framework. Healthy vegetation cover was found to be negatively associated with both psychotic and non-psychotic disorders. Results suggest that the satellite-based indices, which can measure both the density and health of vegetation cover and are also adjusted for urban and environmental perturbations, could be better alternatives to simple ratio- and area-based measures for understanding the effect of vegetation on mental health. A strong dominance of spatially structured latent covariates was found in the models, highlighting the importance of adopting a spatial approach. This study can provide critical guidelines for selecting appropriate vegetation measures and developing spatial models for future population-based epidemiological research.
Keywords	vegetation ; mental health ; spatial modeling ; psychotic ; non-psychotic ; enhanced vegetation index ; Medicine ; R
Subject code	910
Language	English
Publishing date	2021-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Exploring the dynamic transitions of polysubstance use patterns among Canadian youth using Latent Markov Models on COMPASS dataResearch in context

Yang Yang / Zahid A. Butt / Scott T. Leatherdale / Plinio P. Morita / Alexander Wong / Laura Rosella / Helen H. Chen

The Lancet Regional Health. Americas, Vol 16, Iss , Pp 100389- (2022)

2022

Abstract: Summary: Background: Understanding what factors lead to youth polysubstance use (PSU) patterns and how the transitions between use patterns can inform the design and implementation of PSU prevention programs. We explore the dynamics of PSU patterns from ... ...

Abstract	Summary: Background: Understanding what factors lead to youth polysubstance use (PSU) patterns and how the transitions between use patterns can inform the design and implementation of PSU prevention programs. We explore the dynamics of PSU patterns from a large cohort of Canadian secondary school students using machine learning techniques. Methods: We employed a multivariate latent Markov model (LMM) on COMPASS data, with a linked sample (N = 8824) of three-annual waves, Wave I (WI, 2016–17, as baseline), Wave II (WII, 2017–18), and Wave III (WIII, 2018–19). Substance use indicators, i.e., cigarette, e-cigarette, alcohol and marijuana, were self-reported and were categorized into never/occasional/current use. Outcomes: Four distinct use patterns were identified: no-use (S1), single-use of alcohol (S2), dual-use of e-cigarettes and alcohol (S3), and multi-use (S4). S1 had the highest prevalence (60.5%) at WI, however, S3 became the prominent use pattern (32.5%) by WIII. Most students remained in the same subgroup over time, particularly S4 had the highest transition probability (0.87) across the three-wave. With time, those who transitioned typically moved towards a higher use pattern, with the most and least likely transition occurring S2→S3 (0.45) and S3→S2 (<0.01), respectively. Among all covariates being examined, truancy, being measured by the # of classes skipped, significantly affected transition probabilities from any low→high (e.g., ORS2→S4 = 2.41, 95% CI [2.11, 2.72], p < 0.00001) and high→low (e.g., ORS3→S1 = 0.38, 95% CI [0.33, 0.44], p < 0.00001) use directions over time. Older students, blacks (vs. whites), and breakfast eaters were less likely to transition from low→high use direction. Students with more weekly allowance, with more friends that smoked, longer sedentary time, and attended attended school unsupportive to resist or quit drug/alcohol were more likely to transition from low→high use direction. Except for truancy, all other covariates had inconsistent effects on the transition ...
Keywords	Polysubstance use ; Use pattern ; Dynamic transition ; Risk factor ; Canadian adolescents ; Latent Markov model ; Public aspects of medicine ; RA1-1270
Subject code	360
Language	English
Publishing date	2022-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: National burden of rheumatoid arthritis in Canada, 1990–2019

Om P Kurmi / Lin Yang / Nizal Sarrafzadegan / Sanni Yaya / Zulfiqar A Bhutta / Zahid A Butt / Barthelemy Kuate Defo / Justin J Lang / Andrew T Olagunju / Jacek A Kopec / Ranjani Somayaji / Christopher J L Murray / Dilaram Acharya / Seyed-Mohammad Fereshtehnejad / Al Artaman / Ata Rafiee / Diane Lacaille / Daniel Adedayo Adeyinka / Jeffrey J Hebert /

Marjan Mansourian / Thirunavukkarasu Sathish / Juwel Rana / Amin Adibi / Alice Xu / Nejat Hassen / Amani Alandejani / Sophia Sidi / Leah E Cahill / Ihoghosa Osamuyi Iyamu / Samiah Alam / Promit Ananyo Chakraborty / John Dube / Ademola Joshua Itiola / Negar Mousavi

RMD Open, Vol 10, Iss

findings from the Global Burden of Disease Study 2019 – a GBD collaborator-led study

2024 Volume 1

Abstract: Objective The objectives of this study were: (1) to describe burden of rheumatoid arthritis (RA) and trends from 1990 to 2019 using the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) data, (2) to describe age and sex differences in RA ... ...

Abstract	Objective The objectives of this study were: (1) to describe burden of rheumatoid arthritis (RA) and trends from 1990 to 2019 using the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) data, (2) to describe age and sex differences in RA and (3) to compare Canada’s RA burden to that of other countries.Methods Disease burden indicators included prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs) and disability-adjusted life-years (DALYs). GBD estimated fatal and non-fatal outcomes using published literature, survey data and health insurance claims. Data were analysed by Bayesian meta-regression, cause of death ensemble model and other statistical methods. DALYs for Canada were compared with DALYs of countries with similarly high Socio-Demographic Index values.Results In Canada, the RA prevalence rate increased by 27% between 1990 and 2019, mortality rate decreased by 27%, YLL rate decreased by 30%, YLD increased by 27% and DALY rate increased by 13%, all age standardised. The decline in RA mortality and YLL rates was especially pronounced after 2002. The disease burden was higher in females for all indicators, and DALY rates were higher among older age groups, peaking at age 75–79 years. Prevalence and DALYs were higher in Canada compared with global rates.Conclusion Trends in RA burden indicators over time and differences by age and sex have important implications for Canadian policy-makers, researchers and care providers. Early identification and management of RA in women may help reduce the overall burden of RA in Canada.
Keywords	Medicine ; R
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	BMJ Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Computable Phenotype Model for Classification of Men Who Have Sex With Men Within a Large Linked Database of Laboratory, Surveillance, and Administrative Healthcare Records

Travis Salway / Zahid A. Butt / Stanley Wong / Younathan Abdia / Robert Balshaw / Ashleigh J. Rich / Aidan Ablona / Jason Wong / Troy Grennan / Amanda Yu / Maria Alvarez / Carmine Rossi / Mark Gilbert / Mel Krajden / Naveed Z. Janjua

Frontiers in Digital Health, Vol

2020 Volume 2

Abstract: Background: Most public health datasets do not include sexual orientation measures, thereby limiting the availability of data to monitor health disparities, and evaluate tailored interventions. We therefore developed, validated, and applied a novel ... ...

Abstract	Background: Most public health datasets do not include sexual orientation measures, thereby limiting the availability of data to monitor health disparities, and evaluate tailored interventions. We therefore developed, validated, and applied a novel computable phenotype model to classify men who have sex with men (MSM) using multiple health datasets from British Columbia, Canada, 1990–2015.Methods: Three case surveillance databases, a public health laboratory database, and five administrative health databases were linked and deidentified (BC Hepatitis Testers Cohort), resulting in a retrospective cohort of 727,091 adult men. Known MSM status from the three disease case surveillance databases was used to develop a multivariable model for classifying MSM in the full cohort. Models were selected using “elastic-net” (GLMNet package) in R, and a final model optimized area under the receiver operating characteristics curve. We compared characteristics of known MSM, classified MSM, and classified heterosexual men.Findings: History of gonorrhea and syphilis diagnoses, HIV tests in the past year, history of visit to an identified gay and bisexual men's clinic, and residence in MSM-dense neighborhoods were all positively associated with being MSM. The selected model had sensitivity of 72%, specificity of 94%. Excluding those with known MSM status, a total of 85,521 men (12% of cohort) were classified as MSM.Interpretation: Computable phenotyping is a promising approach for classification of sexual minorities and investigation of health outcomes in the absence of routinely available self-report data.
Keywords	sexual and gender minorities ; computable phenotypes ; big data ; HIV ; administrative data ; Medicine ; R ; Public aspects of medicine ; RA1-1270 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	360
Language	English
Publishing date	2020-10-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Syndemic Characterization of HCV, HBV, and HIV Co-infections in a Large Population Based Cohort Study

Geoffrey McKee / Zahid A. Butt / Stanley Wong / Travis Salway / Mark Gilbert / Jason Wong / Maria Alvarez / Nuria Chapinal / Maryam Darvishian / Mark W. Tyndall / Mel Krajden / Naveed Z. Janjua

EClinicalMedicine, Vol 4, Iss , Pp 99-

2018 Volume 108

Abstract: Background: Limited data are available on HBV, HCV, and HIV co-infections and triple infection. We characterized co-occurrence of HIV, HBV, and HCV infections at the population level in British Columbia (BC) to identify patterns of predisposing factors ... ...

Abstract	Background: Limited data are available on HBV, HCV, and HIV co-infections and triple infection. We characterized co-occurrence of HIV, HBV, and HCV infections at the population level in British Columbia (BC) to identify patterns of predisposing factors unique to co-infection subgroups. Methods: We analyzed data from the BC Hepatitis Testers Cohort, which includes all individuals tested for HCV or HIV in BC between 1992 and 2013, or included in provincial public health registries of HIV, HCV, HBV, and active tuberculosis. Individuals were classified as negative, mono-, and co-infection groups based on HIV, HBV, and HCV status. We evaluated associations between risk factors (injection drug use, sexual orientation etc.) and co-infection groups using multivariate multinomial logistic regression. Findings: Of a total of 1,376,989 individuals included in the analysis, 1,276,290 were negative and 100,699 were positive for HIV, HBV, and/or HCV. Most cases (91,399, 90.8%) were mono-infected, while 3991 (4.0%) had HBV/HCV, 670 HBV/HIV (0.7%), 3459 HCV/HIV (3.4%), and 1180 HBV/HCV/HIV (1.2%) co-infection. Risk factor and demographic distribution varied across co-infection categories. MSM classification was associated with higher odds of all HIV co-infection groups, particularly HBV/HIV (OR 6.8; 95% CI: 5.6, 8.27), while injection drug use was most strongly associated with triple infection (OR 64.19; 95% CI: 55.11, 74.77) and HIV/HCV (OR 23.23; 95% CI: 21.32, 25.31). Interpretation: Syndemics of substance use, sexual practices, mental illness, socioeconomic marginalization, and co-infections differ among population groups, highlighting avenues for optimal composition and context for health services to meet each population's unique needs. Funding: BC Centre for Disease Control and Canadian Institutes of Health Research. Keywords: Hepatitis B, Hepatitis C, HIV, Substance use, Syndemics, Co-infection
Keywords	Medicine (General) ; R5-920
Language	English
Publishing date	2018-10-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
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