Pub Date : 2024-12-01Epub Date: 2024-09-29DOI: 10.1016/j.gloepi.2024.100165
Matthew Strand , Surya Bhatt , Matthew Moll , David Baraghoshi
Objectives
To separate estimates of mean change in a health outcome into components of aging and disease progression for different severity groups of chronic obstructive pulmonary disease (COPD).
Study design and methods
A longitudinal model can be used to estimate mean change in a health outcome over time. Methods to separate this change into portions due to aging and disease progression are discussed, including conditions that allow for accurate estimation. Linear mixed models were used to estimate these changes for forced expiratory volume in 1s (FEV1) for various COPD severity and smoking groups using a large cohort (COPDGene) followed for over 10 years.
Results
Based on an analysis of 4967 subjects, age-related loss in FEV1 was found to be about 1 % per year, consistent with published work. Excess average losses (those beyond natural aging) were significant for all severity groups (except nonsmokers), including those with smoking history but normal lung function. Subjects in higher severity groups tended to have less loss in FEV1, but more relative loss, compared to baseline averages. Losses in FEV1 that included both aging and disease progression ranged from 1 to 3 % over severity groups, with current smokers generally exhibiting greater mean losses in FEV1 than former smokers.
Discussion
Effects of disease progression separate from aging can be estimated in observational studies, although care should be taken in order to make sure assumptions involving this separation are reasonable for a given study. This article demonstrates methods to estimate such effects using temporal changes in lung function for subjects in the COPDGene study.
{"title":"Estimating effects of aging and disease progression in current and former smokers using longitudinal models","authors":"Matthew Strand , Surya Bhatt , Matthew Moll , David Baraghoshi","doi":"10.1016/j.gloepi.2024.100165","DOIUrl":"10.1016/j.gloepi.2024.100165","url":null,"abstract":"<div><h3>Objectives</h3><div>To separate estimates of mean change in a health outcome into components of aging and disease progression for different severity groups of chronic obstructive pulmonary disease (COPD).</div></div><div><h3>Study design and methods</h3><div>A longitudinal model can be used to estimate mean change in a health outcome over time. Methods to separate this change into portions due to aging and disease progression are discussed, including conditions that allow for accurate estimation. Linear mixed models were used to estimate these changes for <em>forced expiratory volume in 1</em> <em>s</em> (FEV<sub>1</sub>) for various COPD severity and smoking groups using a large cohort (COPDGene) followed for over 10 years.</div></div><div><h3>Results</h3><div>Based on an analysis of 4967 subjects, age-related loss in FEV<sub>1</sub> was found to be about 1 % per year, consistent with published work. Excess average losses (those beyond natural aging) were significant for all severity groups (except nonsmokers), including those with smoking history but normal lung function. Subjects in higher severity groups tended to have less loss in FEV<sub>1</sub>, but more relative loss, compared to baseline averages. Losses in FEV<sub>1</sub> that included both aging and disease progression ranged from 1 to 3 % over severity groups, with current smokers generally exhibiting greater mean losses in FEV<sub>1</sub> than former smokers.</div></div><div><h3>Discussion</h3><div>Effects of disease progression separate from aging can be estimated in observational studies, although care should be taken in order to make sure assumptions involving this separation are reasonable for a given study. This article demonstrates methods to estimate such effects using temporal changes in lung function for subjects in the COPDGene study.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"8 ","pages":"Article 100165"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01Epub Date: 2024-10-21DOI: 10.1016/j.gloepi.2024.100173
Louis Anthony Cox Jr.
{"title":"What constitutes valid evidence of causation? Gas stoves and childhood asthma revisited","authors":"Louis Anthony Cox Jr.","doi":"10.1016/j.gloepi.2024.100173","DOIUrl":"10.1016/j.gloepi.2024.100173","url":null,"abstract":"","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"8 ","pages":"Article 100173"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01Epub Date: 2024-10-22DOI: 10.1016/j.gloepi.2024.100174
Fausto Ciccacci , Benjamin Welu , Harrison Ndoi , Claudia Mosconi , Carolina De Santo , Mariachiara Carestia , Anna Maria Doro Altan , Joseph Murungi , Koome Muthuri , Mariagrazia Cicala , Giovanni Guidotti , Stefano Orlando
Background
Africa is the epicenter of the HIV epidemic, with over two-thirds of the global population living with HIV. It is also facing a dramatic increase in non-communicable diseases (NCDs) amidst its aging population. This necessitates a healthcare approach that addresses both infectious diseases and NCDs in HIV-positive individuals. In Kenya, with 1.4 million HIV-positive people, efforts include widespread ART access and integrating HIV services into the health system. Challenges remain in healthcare infrastructure, particularly in rural areas. The Comorbidities in HIV/AIDS Outpatients (CHAO) Project, funded by the Italian Cooperation Agency, aims to improve understanding and management of comorbidities in HIV patients, highlighting the need for cost-effective healthcare strategies to address this dual burden.
Methods
The CHAO (Comorbidities in HIV/AIDS Outpatients) project conducted a cross-sectional epidemiological study across 25 clinics in Meru County, Kenya. The study included comprehensive surveys and screenings for various comorbidities among HIV-positive patients receiving treatment, utilizing both clinical evaluations and laboratory tests to assess the prevalence of infectious diseases and NCDs.
Results
A total of 1051 HIV-positive individuals were included in the study: 75 % females, 25 % males, median age 47 years, the majority (96 %) on long-term ART, mostly Dolutegravir-based (95 %). 55.4 % had at least one comorbidity, with NCDs such as dyslipidemia (21.22 %) and hypertension (20.17 %) being the most prevalent. The study also noted significant occurrences of communicable diseases, including syphilis (5.23 %), hepatitis B (2.19 %), and hepatitis C (0.29 %). The prevalence of comorbidities varied with age, highlighting the impact of aging on disease burden.
Discussion
The high prevalence of comorbidities among HIV-positive patients in Meru County underscores the need for integrated healthcare strategies that address both infectious diseases and NCDs. The findings advocate for systematic screening and management of comorbidities within HIV care programs, emphasizing the need for holistic health approaches to improve outcomes for this population.
{"title":"Exploring diseases burden in HIV population: Results from the CHAO (Comorbidities in HIV/AIDS outpatients) cross-sectional study in Kenya","authors":"Fausto Ciccacci , Benjamin Welu , Harrison Ndoi , Claudia Mosconi , Carolina De Santo , Mariachiara Carestia , Anna Maria Doro Altan , Joseph Murungi , Koome Muthuri , Mariagrazia Cicala , Giovanni Guidotti , Stefano Orlando","doi":"10.1016/j.gloepi.2024.100174","DOIUrl":"10.1016/j.gloepi.2024.100174","url":null,"abstract":"<div><h3>Background</h3><div>Africa is the epicenter of the HIV epidemic, with over two-thirds of the global population living with HIV. It is also facing a dramatic increase in non-communicable diseases (NCDs) amidst its aging population. This necessitates a healthcare approach that addresses both infectious diseases and NCDs in HIV-positive individuals. In Kenya, with 1.4 million HIV-positive people, efforts include widespread ART access and integrating HIV services into the health system. Challenges remain in healthcare infrastructure, particularly in rural areas. The Comorbidities in HIV/AIDS Outpatients (CHAO) Project, funded by the Italian Cooperation Agency, aims to improve understanding and management of comorbidities in HIV patients, highlighting the need for cost-effective healthcare strategies to address this dual burden.</div></div><div><h3>Methods</h3><div>The CHAO (Comorbidities in HIV/AIDS Outpatients) project conducted a cross-sectional epidemiological study across 25 clinics in Meru County, Kenya. The study included comprehensive surveys and screenings for various comorbidities among HIV-positive patients receiving treatment, utilizing both clinical evaluations and laboratory tests to assess the prevalence of infectious diseases and NCDs.</div></div><div><h3>Results</h3><div>A total of 1051 HIV-positive individuals were included in the study: 75 % females, 25 % males, median age 47 years, the majority (96 %) on long-term ART, mostly Dolutegravir-based (95 %). 55.4 % had at least one comorbidity, with NCDs such as dyslipidemia (21.22 %) and hypertension (20.17 %) being the most prevalent. The study also noted significant occurrences of communicable diseases, including syphilis (5.23 %), hepatitis B (2.19 %), and hepatitis C (0.29 %). The prevalence of comorbidities varied with age, highlighting the impact of aging on disease burden.</div></div><div><h3>Discussion</h3><div>The high prevalence of comorbidities among HIV-positive patients in Meru County underscores the need for integrated healthcare strategies that address both infectious diseases and NCDs. The findings advocate for systematic screening and management of comorbidities within HIV care programs, emphasizing the need for holistic health approaches to improve outcomes for this population.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"8 ","pages":"Article 100174"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01Epub Date: 2024-09-21DOI: 10.1016/j.gloepi.2024.100163
R. Gal , R. Kessels , K. Luijken , L.A. Daamen , D.R. Mink van der Molen , S.A.M. Gernaat , A.M. May , H.M. Verkooijen , P.M. van de Ven
Objective: The estimand framework offers a structured approach to define the treatment effect to be estimated in a clinical study. Defining the estimand upfront helps formulating the research question and informs study design, data collection and statistical analysis methods. Since the Trials within Cohorts (TwiCs) design has unique characteristics, the objective of this study is to describe considerations and provide guidance for formulating estimands for TwiCs studies.
Methods: The key attributes of an estimand are the target population, treatments that are compared, the endpoint, intercurrent events and their handling, and the population-level summary measure. The estimand framework was applied retrospectively to two TwiCs studies: the SPONGE and UMBRELLA Fit trial. The aim is to demonstrate how the estimand framework can be implemented in TwiCs studies, thereby focusing on considerations relevant for defining the estimand. Three estimands were defined for both studies. For the SPONGE trial, estimators were derived.
Results: Intercurrent events considered to occur exclusively or more frequently in TwiCs studies compared to conventional randomized trials included intervention refusal after randomization, misalignment of timing of routine cohort measurements and the intervention period, and participants in the control arm initiating treatments similar to the studied intervention. Considerations for handling refusal after randomization related to decisions on whether the target population should include all eligible participants or the subpopulation that would accept (or undergo) the intervention when offered. Considerations for handling treatment initiation in the control arm and misalignments of timing related to decisions on whether such events should be considered part of treatment policy or whether interest is in a hypothetical scenario where such events do not occur.
Conclusion: The TwiCs study design has unique features that pose specific considerations when formulating an estimand. The examples in this study can provide guidance in the definition of estimands in future TwiCs studies.
{"title":"Tailored guidance to apply the Estimand framework to Trials within Cohorts (TwiCs) studies","authors":"R. Gal , R. Kessels , K. Luijken , L.A. Daamen , D.R. Mink van der Molen , S.A.M. Gernaat , A.M. May , H.M. Verkooijen , P.M. van de Ven","doi":"10.1016/j.gloepi.2024.100163","DOIUrl":"10.1016/j.gloepi.2024.100163","url":null,"abstract":"<div><div><strong>Objective</strong>: The estimand framework offers a structured approach to define the treatment effect to be estimated in a clinical study. Defining the estimand upfront helps formulating the research question and informs study design, data collection and statistical analysis methods. Since the Trials within Cohorts (TwiCs) design has unique characteristics, the objective of this study is to describe considerations and provide guidance for formulating estimands for TwiCs studies.</div><div><strong>Methods</strong>: The key attributes of an estimand are the target population, treatments that are compared, the endpoint, intercurrent events and their handling, and the population-level summary measure. The estimand framework was applied retrospectively to two TwiCs studies: the SPONGE and UMBRELLA Fit trial. The aim is to demonstrate how the estimand framework can be implemented in TwiCs studies, thereby focusing on considerations relevant for defining the estimand. Three estimands were defined for both studies. For the SPONGE trial, estimators were derived.</div><div><strong>Results</strong>: Intercurrent events considered to occur exclusively or more frequently in TwiCs studies compared to conventional randomized trials included intervention refusal after randomization, misalignment of timing of routine cohort measurements and the intervention period, and participants in the control arm initiating treatments similar to the studied intervention. Considerations for handling refusal after randomization related to decisions on whether the target population should include all eligible participants or the subpopulation that would accept (or undergo) the intervention when offered. Considerations for handling treatment initiation in the control arm and misalignments of timing related to decisions on whether such events should be considered part of treatment policy or whether interest is in a hypothetical scenario where such events do not occur.</div><div><strong>Conclusion</strong>: The TwiCs study design has unique features that pose specific considerations when formulating an estimand. The examples in this study can provide guidance in the definition of estimands in future TwiCs studies.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"8 ","pages":"Article 100163"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01Epub Date: 2024-07-01DOI: 10.1016/j.gloepi.2024.100153
Tyler J. VanderWeele
{"title":"Response to: Letter by Litwack and DeGruttola regarding “Moral controversies and academic public health: Notes on navigating and surviving academic freedom challenges”","authors":"Tyler J. VanderWeele","doi":"10.1016/j.gloepi.2024.100153","DOIUrl":"https://doi.org/10.1016/j.gloepi.2024.100153","url":null,"abstract":"","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"8 ","pages":"Article 100153"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590113324000191/pdfft?md5=361b89dd2baf33bf5100df18f05dec44&pid=1-s2.0-S2590113324000191-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141594042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01Epub Date: 2024-06-14DOI: 10.1016/j.gloepi.2024.100150
Rebecca J. Schmidt , Amanda J. Goodrich , Lauren Granillo , Yunru Huang , Paula Krakowiak , Adrianne Widaman , J. Erin Dienes , Deborah H. Bennett , Cheryl K. Walker , Daniel J. Tancredi
Background
Gestational nutrition can protect against adverse neurodevelopmental outcomes.
Objectives
We developed a short tool for collecting maternal nutritional intake during pregnancy to facilitate research in this area and compared its retrospective use to prospectively-collected food frequency questionnaires (FFQ).
Methods
Maternal nutritional intake was retrospectively assessed using three versions (full interview, full self-administered online, and shortened interview) of the Early Life Exposure Assessment Tool (ELEAT) among participants of the MARBLES pregnancy cohort study of younger siblings of autistic children. Retrospective responses were compared with responses to supplement questions and the validated 2005 Block FFQ prospectively collected in MARBLES during pregnancies 2–7 years prior. ELEAT nutrient values were calculated using reported food intake frequencies and nutrient values from the USDA nutrient database. Correlations between retrospectively- and prospectively-reported intake were evaluated using Kappa coefficients, Youden's J, and Spearman Rank Correlation Coefficients (rs).
Results
MARBLES FFQ dietary intakes were compared among 54 women who completed the ELEAT full form including 12 online, and among 23 who completed the ELEAT short form. Correlations across most foods were fair to moderate. Most ELEAT quantified nutrient values were moderately correlated (rs = 0.3–0.6) with those on the Block FFQ. Supplement questions in both MARBLES and the ELEAT were completed by 114 women. Kappas were moderate for whether or not supplements were taken, but modest for timing. Correlations varied by version and child diagnosis or concerns, and were higher when mothers completed the ELEAT when their child was 4 years old or younger.
Conclusions
With recall up to several years, ELEAT dietary and supplement module responses were modestly to moderately reliable and produced nutrient values moderately correlated with prospectively-collected measures. The ELEAT dietary and vitamin supplements modules can be used to rank participants in terms of intake of several nutrients relevant for neurodevelopment.
{"title":"Reliability of a short diet and vitamin supplement questionnaire for retrospective collection of maternal nutrient intake","authors":"Rebecca J. Schmidt , Amanda J. Goodrich , Lauren Granillo , Yunru Huang , Paula Krakowiak , Adrianne Widaman , J. Erin Dienes , Deborah H. Bennett , Cheryl K. Walker , Daniel J. Tancredi","doi":"10.1016/j.gloepi.2024.100150","DOIUrl":"10.1016/j.gloepi.2024.100150","url":null,"abstract":"<div><h3>Background</h3><p>Gestational nutrition can protect against adverse neurodevelopmental outcomes.</p></div><div><h3>Objectives</h3><p>We developed a short tool for collecting maternal nutritional intake during pregnancy to facilitate research in this area and compared its retrospective use to prospectively-collected food frequency questionnaires (FFQ).</p></div><div><h3>Methods</h3><p>Maternal nutritional intake was retrospectively assessed using three versions (full interview, full self-administered online, and shortened interview) of the Early Life Exposure Assessment Tool (ELEAT) among participants of the MARBLES pregnancy cohort study of younger siblings of autistic children. Retrospective responses were compared with responses to supplement questions and the validated 2005 Block FFQ prospectively collected in MARBLES during pregnancies 2–7 years prior. ELEAT nutrient values were calculated using reported food intake frequencies and nutrient values from the USDA nutrient database. Correlations between retrospectively- and prospectively-reported intake were evaluated using Kappa coefficients, Youden's J, and Spearman Rank Correlation Coefficients (r<sub>s</sub>).</p></div><div><h3>Results</h3><p>MARBLES FFQ dietary intakes were compared among 54 women who completed the ELEAT full form including 12 online, and among 23 who completed the ELEAT short form. Correlations across most foods were fair to moderate. Most ELEAT quantified nutrient values were moderately correlated (r<sub>s</sub> = 0.3–0.6) with those on the Block FFQ. Supplement questions in both MARBLES and the ELEAT were completed by 114 women. Kappas were moderate for whether or not supplements were taken, but modest for timing. Correlations varied by version and child diagnosis or concerns, and were higher when mothers completed the ELEAT when their child was 4 years old or younger.</p></div><div><h3>Conclusions</h3><p>With recall up to several years, ELEAT dietary and supplement module responses were modestly to moderately reliable and produced nutrient values moderately correlated with prospectively-collected measures. The ELEAT dietary and vitamin supplements modules can be used to rank participants in terms of intake of several nutrients relevant for neurodevelopment.</p></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"8 ","pages":"Article 100150"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590113324000166/pdfft?md5=0d583c28cdbaddd85aaf42f8850125cc&pid=1-s2.0-S2590113324000166-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141412256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01Epub Date: 2024-06-04DOI: 10.1016/j.gloepi.2024.100146
Vinay Kampalath , Ms Maia C. Tarnas , Ms Vaibhavee Patel , Mohamed Hamze , Randa Loutfi , Bachir Tajaldin , Ahmad Albik , Ayman Kassas , Anas Khashata , Aula Abbara
Background
One in six children worldwide lives in a region exposed to armed conflict. In conflicts, children are among the most vulnerable, and at risk of adverse health outcomes. We sought to describe trends in child and adolescent morbidity in northwest Syria (NWS) and understand how forced displacement affects clinical utilisation during the Syrian conflict.
Methods
Retrospective data between January 2018 and December 2022 were obtained from the Syrian American Medical Society (SAMS), a non-governmental organisation that operates health facilities in NWS. After initial descriptive analyses were completed, we performed a seasonal-trend decomposition to estimate the seasonality of clinical presentations. We subsequently employed a multivariate regression model incorporating age, gender, residency status, season, and a random district-level intercept to measure the association between the odds of clinical consultation and forced displacement.
Findings
Across 51 reporting SAMS facilities, 2,687,807 clinical consultations were studied over a five-year period. Seasonality was demonstrated for every clinical consultation category. Higher levels of forced displacement were associated with increased odds of consultations for nutrition, trauma, NCDs and mental health and decreased odds of consultation for communicable diseases. Aside from traumatic injury, internally displaced persons (IDPs) had higher AORs of clinical consultations compared to host populations.
Interpretation
Forced displacement differentially impacts clinical utilisation among children in northwest Syria, and the effects of displacement persist for at least six months. Clinical needs vary by host/IDP status, sex, age, and season. This study can assist policymakers in forecasting the health needs of children in northwest Syria.
{"title":"An analysis of paediatric clinical presentations in Northwest Syria and the effect of forced displacement, 2018–2022","authors":"Vinay Kampalath , Ms Maia C. Tarnas , Ms Vaibhavee Patel , Mohamed Hamze , Randa Loutfi , Bachir Tajaldin , Ahmad Albik , Ayman Kassas , Anas Khashata , Aula Abbara","doi":"10.1016/j.gloepi.2024.100146","DOIUrl":"10.1016/j.gloepi.2024.100146","url":null,"abstract":"<div><h3>Background</h3><p>One in six children worldwide lives in a region exposed to armed conflict. In conflicts, children are among the most vulnerable, and at risk of adverse health outcomes. We sought to describe trends in child and adolescent morbidity in northwest Syria (NWS) and understand how forced displacement affects clinical utilisation during the Syrian conflict.</p></div><div><h3>Methods</h3><p>Retrospective data between January 2018 and December 2022 were obtained from the Syrian American Medical Society (SAMS), a non-governmental organisation that operates health facilities in NWS. After initial descriptive analyses were completed, we performed a seasonal-trend decomposition to estimate the seasonality of clinical presentations. We subsequently employed a multivariate regression model incorporating age, gender, residency status, season, and a random district-level intercept to measure the association between the odds of clinical consultation and forced displacement.</p></div><div><h3>Findings</h3><p>Across 51 reporting SAMS facilities, 2,687,807 clinical consultations were studied over a five-year period. Seasonality was demonstrated for every clinical consultation category. Higher levels of forced displacement were associated with increased odds of consultations for nutrition, trauma, NCDs and mental health and decreased odds of consultation for communicable diseases. Aside from traumatic injury, internally displaced persons (IDPs) had higher AORs of clinical consultations compared to host populations.</p></div><div><h3>Interpretation</h3><p>Forced displacement differentially impacts clinical utilisation among children in northwest Syria, and the effects of displacement persist for at least six months. Clinical needs vary by host/IDP status, sex, age, and season. This study can assist policymakers in forecasting the health needs of children in northwest Syria.</p></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"8 ","pages":"Article 100146"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590113324000129/pdfft?md5=b2d42f6ebc1c79281f0f8ae3397e2798&pid=1-s2.0-S2590113324000129-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141276215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Education serves as a vital instrument for empowering citizens to engage fully in the development process. However, various factors can impact the quality and competency of female students in higher education. In Ethiopian institutions, the proportion of female students is significantly lower than that of their male counterparts, highlighting the unique challenges faced by females that can hinder their academic success. Understanding these challenges and the factors influencing female academic performance is essential for enhancing educational outcomes and promoting greater equity in higher education.
Methods
An institutional-based cross-sectional study was conducted involving 633 female university students, supplemented by a qualitative approach. Participants were selected using a multistage sampling technique. Data were collected via a self-administered questionnaire, while qualitative data were gathered through key informant and in-depth interviews. Qualitative data were transcribed, labeled, and analyzed narratively through content analysis. Logistic regression analysis was employed to identify factors associated with academic performance.
Results
The study revealed that 11.85 % of female students (95 % CI: 9.43–14.62) experienced poor academic performance. Key factors influencing academic performance included alcohol consumption (AOR = 2.3, 95 % CI: 1.8–4.0), smoking (AOR = 2.9, 95 % CI: 1.1–7.4), working after school (AOR = 1.6, 95 % CI: 1.1–2.8), choice in preferred departments (AOR = 0.6, 95 % CI: 0.3–0.8), poor prior knowledge in English and basic science (AOR = 2.1, 95 % CI: 1.4–4.1), and insufficient parental support (AOR = 2.1, 95 % CI: 1.3–3.7).
Conclusion
The abstract effectively summarizes the key findings and offers relevant insights into the academic challenges faced by female students. More than one in ten female students encounters significant academic obstacles influenced by factors such as substance use, after-school employment, limited department choice, and inadequate foundational knowledge. Addressing these issues is crucial for improving academic performance and reinforcing support systems for female students, thereby providing a solid foundation for future studies in this area.
{"title":"Academic performance and associated factors among female university students","authors":"Tsiyon Birhanu Wube , Solomon Gebremichael Asgedom , Zelalem Mohammed Jemal , Lielt Gebreselassie Gebrekirstos","doi":"10.1016/j.gloepi.2024.100175","DOIUrl":"10.1016/j.gloepi.2024.100175","url":null,"abstract":"<div><h3>Background</h3><div>Education serves as a vital instrument for empowering citizens to engage fully in the development process. However, various factors can impact the quality and competency of female students in higher education. In Ethiopian institutions, the proportion of female students is significantly lower than that of their male counterparts, highlighting the unique challenges faced by females that can hinder their academic success. Understanding these challenges and the factors influencing female academic performance is essential for enhancing educational outcomes and promoting greater equity in higher education.</div></div><div><h3>Methods</h3><div>An institutional-based cross-sectional study was conducted involving 633 female university students, supplemented by a qualitative approach. Participants were selected using a multistage sampling technique. Data were collected via a self-administered questionnaire, while qualitative data were gathered through key informant and in-depth interviews. Qualitative data were transcribed, labeled, and analyzed narratively through content analysis. Logistic regression analysis was employed to identify factors associated with academic performance.</div></div><div><h3>Results</h3><div>The study revealed that 11.85 % of female students (95 % CI: 9.43–14.62) experienced poor academic performance. Key factors influencing academic performance included alcohol consumption (AOR = 2.3, 95 % CI: 1.8–4.0), smoking (AOR = 2.9, 95 % CI: 1.1–7.4), working after school (AOR = 1.6, 95 % CI: 1.1–2.8), choice in preferred departments (AOR = 0.6, 95 % CI: 0.3–0.8), poor prior knowledge in English and basic science (AOR = 2.1, 95 % CI: 1.4–4.1), and insufficient parental support (AOR = 2.1, 95 % CI: 1.3–3.7).</div></div><div><h3>Conclusion</h3><div>The abstract effectively summarizes the key findings and offers relevant insights into the academic challenges faced by female students. More than one in ten female students encounters significant academic obstacles influenced by factors such as substance use, after-school employment, limited department choice, and inadequate foundational knowledge. Addressing these issues is crucial for improving academic performance and reinforcing support systems for female students, thereby providing a solid foundation for future studies in this area.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"8 ","pages":"Article 100175"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142654778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01Epub Date: 2024-09-28DOI: 10.1016/j.gloepi.2024.100167
Carl V. Phillips , Igor Burstyn , David J. Miller , Ali K. Hamade , Raghavendhran Avanasi , Denali Boon , Saumitra V. Rege , Sandrine E. Déglin
One of the practical contributions of epidemiology studies is to inform risk assessment and management to protect public health. However, there is a perception among some that environmental and occupational epidemiology is falling short of satisfying the needs of risk assessors. The specific reasons for this are not clearly understood. To help identify the points of dissatisfaction and possible areas for mutual learning, we conducted a survey of risk assessors, seeking their opinions of epidemiology research. We present a few quantitative measures and a thematic analysis of responses to open-ended questions. Survey results suggest that some risk assessors (with some adamant exceptions) believe that epidemiology has great potential to contribute to risk assessment but can be deficient in many ways. For example, respondents identified the lack of full disclosure of methods, deficiencies in exposure assessment, the absence of comprehensive uncertainty analyses, and the failure to investigate or explore thresholds of effects as some of the common shortcomings. These could be straightforward to address. Respondents also brought up a wide collection of more complicated and subtle concerns that could lead to further improvement of useful results. We identify areas where mutually-educating interdisciplinary dialogue seems particularly promising. Epidemiology research is expensive, and risk management decisions even more so; therefore, it is desirable for the risk assessment and epidemiologic communities to work toward making epidemiologic research more useful for informing decisions.
{"title":"Improving the integration of epidemiological data into human health risk assessment: What risk assessors told us they want","authors":"Carl V. Phillips , Igor Burstyn , David J. Miller , Ali K. Hamade , Raghavendhran Avanasi , Denali Boon , Saumitra V. Rege , Sandrine E. Déglin","doi":"10.1016/j.gloepi.2024.100167","DOIUrl":"10.1016/j.gloepi.2024.100167","url":null,"abstract":"<div><div>One of the practical contributions of epidemiology studies is to inform risk assessment and management to protect public health. However, there is a perception among some that environmental and occupational epidemiology is falling short of satisfying the needs of risk assessors. The specific reasons for this are not clearly understood. To help identify the points of dissatisfaction and possible areas for mutual learning, we conducted a survey of risk assessors, seeking their opinions of epidemiology research. We present a few quantitative measures and a thematic analysis of responses to open-ended questions. Survey results suggest that some risk assessors (with some adamant exceptions) believe that epidemiology has great potential to contribute to risk assessment but can be deficient in many ways. For example, respondents identified the lack of full disclosure of methods, deficiencies in exposure assessment, the absence of comprehensive uncertainty analyses, and the failure to investigate or explore thresholds of effects as some of the common shortcomings. These could be straightforward to address. Respondents also brought up a wide collection of more complicated and subtle concerns that could lead to further improvement of useful results. We identify areas where mutually-educating interdisciplinary dialogue seems particularly promising. Epidemiology research is expensive, and risk management decisions even more so; therefore, it is desirable for the risk assessment and epidemiologic communities to work toward making epidemiologic research more useful for informing decisions.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"8 ","pages":"Article 100167"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01Epub Date: 2024-10-04DOI: 10.1016/j.gloepi.2024.100168
Lise M. Bjerre , Cayden Peixoto , Rawan Alkurd , Robert Talarico , Rami Abielmona
Background
Research comparing artificial intelligence and machine learning (AI/ML) methods with classical statistical methods applied to large population health databases is limited.
Objectives
This retrospective cohort study aimed to compare the predictive performance of AI/ML algorithms against conventional multivariate logistic regression models using linked health administrative data.
Methods
Using Ontario's population health databases, we created a cohort of residents of the city of Ottawa, Ontario, who underwent a PCR test for COVID-19 between March 10, 2020, and May 13, 2021. Using demographic, socio-economic and health data (including COVID-19 PCR test results and available, symptom data), we developed predictive models for the purpose of COVID-19 case identification using the following approaches: classical multivariate logistic regression (LR); deep neural network (DNN); random forest (RF); and gradient boosting trees (GBT). Model performance comparisons were made using the area under the curve (AUC) swarm plot for 10-fold cross-validation.
Results
The cohort consisted of n = 351,248 Ottawa residents tested for COVID-19 during the study period. Among whom, a total of n = 883,879 unique COVID-19 tests were performed (2.6 % positive test results). Inclusion of COVID-19 symptoms data in the analysis improved model performance and variable predictive value across all tested models (p < 0.0001), with the 10-fold cross-validation AUC increasing to near or over 0.7 in all models when symptoms data were included. In various pairwise comparisons, the GBT method had the highest predictive ability (AUC = 0.796 ± 0.017), significantly outperforming multivariate logistic regression and the other AI/ML approaches.
Conclusions
Conventional multivariate regression-based models are better than some and worse than other machine learning algorithms to provide good predictive accuracy in a moderate dataset with a reasonable number of features. However, whenever possible, the AI/ML GBT approach should be considered.
{"title":"Comparing AI/ML approaches and classical regression for predictive modeling using large population health databases: Applications to COVID-19 case prediction","authors":"Lise M. Bjerre , Cayden Peixoto , Rawan Alkurd , Robert Talarico , Rami Abielmona","doi":"10.1016/j.gloepi.2024.100168","DOIUrl":"10.1016/j.gloepi.2024.100168","url":null,"abstract":"<div><h3>Background</h3><div>Research comparing artificial intelligence and machine learning (AI/ML) methods with classical statistical methods applied to large population health databases is limited.</div></div><div><h3>Objectives</h3><div>This retrospective cohort study aimed to compare the predictive performance of AI/ML algorithms against conventional multivariate logistic regression models using linked health administrative data.</div></div><div><h3>Methods</h3><div>Using Ontario's population health databases, we created a cohort of residents of the city of Ottawa, Ontario, who underwent a PCR test for COVID-19 between March 10, 2020, and May 13, 2021. Using demographic, socio-economic and health data (including COVID-19 PCR test results and available, symptom data), we developed predictive models for the purpose of COVID-19 case identification using the following approaches: classical multivariate logistic regression (LR); deep neural network (DNN); random forest (RF); and gradient boosting trees (GBT). Model performance comparisons were made using the area under the curve (AUC) swarm plot for 10-fold cross-validation.</div></div><div><h3>Results</h3><div>The cohort consisted of <em>n</em> = 351,248 Ottawa residents tested for COVID-19 during the study period. Among whom, a total of <em>n</em> = 883,879 unique COVID-19 tests were performed (2.6 % positive test results). Inclusion of COVID-19 symptoms data in the analysis improved model performance and variable predictive value across all tested models (<em>p</em> < 0.0001), with the 10-fold cross-validation AUC increasing to near or over 0.7 in all models when symptoms data were included. In various pairwise comparisons, the GBT method had the highest predictive ability (AUC = 0.796 ± 0.017), significantly outperforming multivariate logistic regression and the other AI/ML approaches.</div></div><div><h3>Conclusions</h3><div>Conventional multivariate regression-based models are better than some and worse than other machine learning algorithms to provide good predictive accuracy in a moderate dataset with a reasonable number of features. However, whenever possible, the AI/ML GBT approach should be considered.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"8 ","pages":"Article 100168"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号