International journal of epidemiology最新文献

{"title":"Why epidemiology should not be automated: the case for slow epidemiology.","authors":"Peter W G Tennant, Haidong Lu, Daniel Westreich","doi":"10.1093/ije/dyag181","DOIUrl":"https://doi.org/10.1093/ije/dyag181","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"55 5","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148944745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Redefining the public health problem in epidemiology: Clarifying operational boundaries for a post‑pandemic discipline.","authors":"Jose Leopoldo Ferreira Antunes, Marco A Peres","doi":"10.1093/ije/dyag193","DOIUrl":"https://doi.org/10.1093/ije/dyag193","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"55 5","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148874039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A population-based study of obstructive sleep apnea: using probabilistic case ascertainment through health administrative databases.","authors":"Robert Talarico, Marcus Povitz, Sachin R Pendharkar, William Reisman, Daniel I McIsaac, Tetyana Kendzerska","doi":"10.1093/ije/dyag176","DOIUrl":"10.1093/ije/dyag176","url":null,"abstract":"<p><strong>Background: </strong>Although polysomnography (PSG) is the diagnostic gold standard, PSG data on obstructive sleep apnea (OSA) presence and severity are rarely available at the population level. Health administrative databases offer broad coverage for OSA case ascertainment but require methods that address inherent misclassification. We utilized a previously validated probabilistic case ascertainment model of OSA to estimate population-level prevalence and correlates of OSA.</p><p><strong>Methods: </strong>We conducted a population-based retrospective cohort study in Ontario, Canada. First, using a clinical cohort with PSG-confirmed OSA severity (measurement cohort; n = 18 581), we quantified misclassification in probabilistic OSA case definitions. We then applied the externally validated probability models to all adults 18 years and older in Ontario who underwent in-laboratory overnight PSG between 2010 and 2018 (provincial PSG cohort; n = 834 361). OSA prevalence and correlates were estimated using multiple probability thresholds and a threshold-free bootstrap imputation approach (BIA).</p><p><strong>Results: </strong>Compared to the PSG-based gold standard, the BIA surrogate definition had the lowest average relative bias in OSA prevalence estimation (BIA: 5% versus >38% probability threshold: 11.4%). Using BIA, we estimate a 44.3% prevalence of moderate-severe OSA in the provincial PSG cohort, which in scenario-based projections yields a 3.4%-17.1% general population prevalence dependent on an assumed OSA underdiagnosis rate. OSA prevalence was higher in men, older ages, and previous comorbidity and was stable annually.</p><p><strong>Conclusion: </strong>Probabilistic case ascertainment using health administrative data enables robust population-level estimation of OSA epidemiology despite the absence of clinical diagnostic data and provides a framework for studying OSA prevalence, correlates, and outcomes over time.</p>","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"55 5","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13493051/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148792661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adiposity and infection-related mortality: Mendelian randomization study of 126 000 Mexican adults.","authors":"Lukman Lawal, Eirini Trichia, Jesus Alegre-Díaz, Paulina Baca, Elizabeth Barerra, Carlos González-Carballo, Raúl Ramirez-Reyes, Fernando Rivas, Diego Aguilar-Ramirez, Fiona Bragg, William G Herrington, Michael Hill, Tianshu Liu, Michael Turner, Jason Torres, Alejandra Vergara-Lope, Rachel Wade, Rory Collins, Pablo Kuri-Morales, Jaime Berumen, Jonathan R Emberson, Roberto Tapia-Conyer, Louisa Gnatiuc Friedrichs","doi":"10.1093/ije/dyag197","DOIUrl":"10.1093/ije/dyag197","url":null,"abstract":"<p><strong>Background: </strong>The causal relevance of different adiposity markers to infection-related death remains uncertain. We estimated the lifelong associations of genetically predicted adiposity traits with infection-related mortality among 126 491 Mexican adults.</p><p><strong>Methods: </strong>Mendelian randomization (MR) using trans-ancestry instruments for body mass index (BMI), fat-mass percentage (FM%), and waist and hip circumference was used to estimate causal effects on infection-related mortality at ages 35-74 years, overall and across six infection subtypes. Multivariable MR was used to assess independent associations.</p><p><strong>Results: </strong>Genetic instruments explained 1.6%-3.5% of the variance in adiposity markers and the strengths of their associations with the markers were similar in men and women. Over 20 years, 2592 infection-related deaths occurred at ages 35-74 years. Genetically predicted adiposity was strongly associated with infection mortality, with the strongest association for FM% [hazard ratio (HR) per 1-SD higher level: 2.54; 95% confidence interval (CI) 1.91-3.38] and the weakest for hip circumference (HR 1.61; 95% CI 1.30-2.01). Associations were consistent across six subtypes: respiratory; urinary tract; gastrointestinal; sepsis; skin, bone, and connective tissue; and other infections. For BMI and FM%, mutual adjustment for waist and hip circumference reduced the associations by nearly one-third. For waist circumference, adjustment for BMI and hip circumference reduced the association by more than half, while, for hip circumference, mutual adjustment for BMI and waist circumference almost eliminated its association. Sensitivity analyses supported the main conclusions.</p><p><strong>Conclusion: </strong>Higher adiposity is causally associated with a higher risk of infection-related mortality in Mexican adults. Strategies to reduce the population levels of adiposity in Mexico could contribute to lowering mortality from infection.</p>","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"55 5","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13568476/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148944711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cohort Profile Update: The Korean Genome and Epidemiology Study (KoGES).","authors":"Jieun Lyu, Joong-Yeon Lim, Joong Won Lee, Hye-Kyoung Kwak, Hyun-Young Park, Jae-Pil Jeon","doi":"10.1093/ije/dyag192","DOIUrl":"10.1093/ije/dyag192","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"55 5","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13585397/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148989807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sicker at all ages? Two decades of changing disease histories and mortality in the United States.","authors":"Marcus Ebeling, Neil K Mehta, Leah Abrams, Mikko Myrskylä","doi":"10.1093/ije/dyag217","DOIUrl":"10.1093/ije/dyag217","url":null,"abstract":"<p><strong>Background: </strong>Stagnating cardiovascular disease mortality and rising drug- and suicide-related deaths are key drivers of stalled US mortality improvements. However, prior research has largely overlooked disease histories preceding death, despite increasing multimorbidity. We examined changes in disease-history profiles in the US population and assessed how shifts in profile composition and within-profile mortality shaped mortality trends.</p><p><strong>Methods: </strong>We analysed adults aged ≥30 years (N = 510 372) from the IPUMS-NHIS (National Health Interview Survey) 1997-2018 linked mortality files (follow-up through 2019). Latent class analysis on the pooled sample across all ages and years identified disease-history profiles based on self-reported cancer, diabetes, cardiovascular disease, mental health, internal diseases, obesity, and physical limitations. Logistic regression was used to estimate profile-specific 5-year mortality over time, and counterfactual decomposition was used to quantify the contributions of compositional change and within-profile mortality improvement to overall mortality trends.</p><p><strong>Results: </strong>Five disease-history profiles were identified. Prevalence and 5-year death probability ranged from disease-free (62.4%; men 3.7% [95% confidence interval (CI) 3.5-3.8], women 2.4% [95% CI 2.3-2.5]) to high-burden multimorbidity (5.9%; men 17.8% [95% CI 16.8-18.8], women 12.6% [95% CI 11.9-13.3]), with substantial gradients across intermediate profiles. Profile composition varied substantially by gender, education, and race/ethnicity. The disease-free population declined by nearly 1% annually, replaced primarily by cardiometabolic and high-burden multimorbidity profiles. Most profiles experienced stagnating or increasing mortality after the mid-2000s. The decomposition shows that within-profile mortality improvement was the dominant driver of declining mortality; compositional shifts, mostly driven by the declining disease-free share, partially offset these gains.</p><p><strong>Conclusion: </strong>Stagnating US mortality reflects both the growing prevalence of high-morbidity profiles and worsening or stagnating survival within them, highlighting the limited reach of prevention and disease-management efforts.</p>","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"55 5","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13654198/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149167256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exposure misclassification of self-reported vegetarian diet and its impact on health outcomes.","authors":"Narges Ghoreishi, Tobias Kurth, Sven Knüppel, Matthew P Fox","doi":"10.1093/ije/dyag168","DOIUrl":"10.1093/ije/dyag168","url":null,"abstract":"<p><strong>Background: </strong>Literature around the health impact of a vegetarian diet is expanding, yet exposure measurement and its effect on the study results receive far less attention. The aim of our study was to show the effect of bias from exposure misclassification on the direction, amount, and uncertainty of study results.</p><p><strong>Methods: </strong>We included 11 180 participants from the National Health and Nutrition Examination Survey (2007-10). The exposure was self-reported diet type (being vegetarian). Using sensitivity, specificity, and positive and negative predictive values as bias parameters, we quantified the effect of exposure misclassification in non-differential and differential scenarios. We compared conventional analysis with bias-adjusted results.</p><p><strong>Results: </strong>Among self-reported vegetarians (2.2%), more than half (68%) reported consuming meat, poultry, or fish in the 24-hour dietary recalls. The sensitivity of self-reported diet type was 32% (95% CI, 0.26-0.38) and the specificity was 98% (95% CI, 0.98-0.99). The exposure misclassification was differential. The quantitative bias analysis of differential exposure misclassification was more informative. Using positive and negative predictive values as bias parameters was helpful to avoid negative bias-adjusted cell counts.</p><p><strong>Conclusion: </strong>Assessing the impact of exposure misclassification in the self-reported vegetarian diet on four health outcomes, our study demonstrates that quantitative bias analysis can help to make more plausible assumptions about the possible direction, strength, and uncertainty of bias and its impact on the effect estimates of conventional analysis. However, comparing different scenarios showed that the model assumptions play a key role in the informative value of quantitative bias analysis.</p>","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"55 5","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13641060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149109284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mortality in people experiencing homelessness: a systematic review and meta-analysis.","authors":"James White, Yvonne Moriarty, Mandy Lau, Rebecca Cannings-John, Abigail Palmer, Alison L Weightman, Meg Kiseleva, G David Batty","doi":"10.1093/ije/dyag129","DOIUrl":"10.1093/ije/dyag129","url":null,"abstract":"<p><strong>Background: </strong>The association between homelessness and the type of homeless experience with all-cause and cause-specific mortality is uncertain.</p><p><strong>Methods: </strong>Published studies were retrieved through a systematic search of MEDLINE, Embase PsycINFO, and Scopus from inception to December 2024. Unpublished data were identified from open-access data archives. We used random-effects meta-analysis to combine the effect estimates from published and unpublished data from 116 studies comprising 2 563 633 homeless people and 129 292 553 population controls. This review is registered at PROSPERO (CRD42023430984).</p><p><strong>Results: </strong>The risk of all-cause mortality was increased in people exposed to homelessness compared with those unexposed [relative risk (RR) 2.21, 95% confidence interval (CI) 1.91-2.57, P < .001, I2 = 99.7], with risks similar in men (RR 4.04, 95% CI 2.87-5.21) and women (RR 3.58, 95% CI 2.35-4.82). Risks were higher in people who had slept rough (RR 7.63, 95% CI 3.29-11.97) than in those who had slept in homeless hostels/shelters (RR 3.44, 95% CI 2.10-4.77) and also elevated for people staying in low-cost hotels (RR 5.18, 95% CI 1.14-9.23). Summary RR estimates were elevated for 33 of the 36 (92%) causes of death. The highest risk of death was apparent for psychoactive-substance-use disorder (RR 21.38, 95% CI 14.44-31.67), accidental injuries (RR 13.15, 95% CI 5.46-31.69), and drug overdose (RR 11.65, 95% CI 6.97-19.48). Around half of the studies (57%) were of high quality. No studies were found in low-income countries. There was no evidence of publication bias.</p><p><strong>Conclusion: </strong>Compared with the general population, homeless people experience an increased risk of premature mortality. The most extreme inequalities were from deaths through psychoactive-substance-use disorder, accidents, and drug overdose. There are evidence-based treatments for psychoactive substance use and drug overdose, suggesting that some of these deaths are avoidable.</p>","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"55 5","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13586615/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148989774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data Resource Profile: Children in Wales: The Cohort for Health and Wellbeing Inequality (CWTCH)","authors":"Sarah J Aldridge,Lateef Akanni,Stuart Bedston,Davara Bennett,Michelle Black,Yanhua Chen,Yu Wei Chua,Oluwaseun B Esan,Lucy J Griffiths,Emily Lowthian,Philip McHale,Ashley Akbari,David Taylor-Robinson","doi":"10.1093/ije/dyag180","DOIUrl":"https://doi.org/10.1093/ije/dyag180","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"17 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148922899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing interrupted time series with count outcomes using single or multiple control time series.","authors":"Xueyan Zheng, Christian Bottomley, Woojoo Lee","doi":"10.1093/ije/dyag199","DOIUrl":"https://doi.org/10.1093/ije/dyag199","url":null,"abstract":"<p><strong>Background: </strong>Interrupted time series (ITS) analysis is a widely used quasi-experimental design for evaluating the impact of population-level interventions. To control for confounding from concurrent events, researchers often incorporate control time series. However, for count outcomes, especially with control series, methodological development remains limited.</p><p><strong>Development: </strong>We introduce a likelihood-based framework for controlled ITS analysis with count data. The proposed framework is based on a conditional Poisson likelihood and naturally extends to settings with multiple control series. This analysis is straightforward when the intervention and control series share a common time-varying component, whereas more flexible modeling is required when such shared structure is not supported. We describe a data-driven method for assessing whether the intervention and control series share a common time-varying component. We also show that, with robust variance estimation, the proposed approach can provide valid statistical inference even if the assumed distribution is misspecified.</p><p><strong>Application: </strong>We demonstrate the method using two real datasets. The first example assesses the effect of Florida's Stand Your Ground (SYG) law on firearm-related homicides and illustrates how the use of multiple control series (homicide rates in other states) leads to more accurate inference. The second example evaluates rotavirus vaccine introduction in Ghana and demonstrates how the analysis proceeds when the common time-varying component assumption is not supported.</p><p><strong>Conclusions: </strong>The proposed conditional Poisson approach provides a practical likelihood-based framework for analyzing ITS with count outcomes using single or multiple control time series. When the common time-varying component assumption holds, incorporating multiple control series can lead to more precise estimation of the parameter of interest.</p>","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"55 5","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148906234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}