Epidemiology最新文献

{"title":"Re: Ambient Air Pollution Exposures and Subsequent Children's Executive Function.","authors":"Tomoyuki Kawada","doi":"10.1097/EDE.0000000000001849","DOIUrl":"10.1097/EDE.0000000000001849","url":null,"abstract":"","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"e14"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143604468","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":"The Impact of Power Outages on Cardiovascular Hospitalizations Among Medicare Fee-for-service Enrollees in New York State, 2017-2018.","authors":"Vivian Do, Heather Kathleen McBrien, Donald Edmondson, Marianthi-Anna Kioumourtzoglou, Joan Allison Casey","doi":"10.1097/EDE.0000000000001853","DOIUrl":"10.1097/EDE.0000000000001853","url":null,"abstract":"<p><strong>Background: </strong>Power outages are common. They can result in exposure to extreme temperatures by shutting off temperature-controlling devices, and thereby also cause stress. Consequently, outages may precipitate cardiovascular disease (CVD)-related hospitalizations. We assessed this relationship among older adults.</p><p><strong>Methods: </strong>We leveraged 2017-2018 data from 245,452 New York State Medicare Fee-for-Service beneficiaries (65+ years) with 390,530 CVD hospitalizations. Using NY Department of Public Services data, we calculated total hours without power 1 day, 1-2 days, and 1-3 days before case and control periods, with an outage ZIP Code Tabulation Area (ZCTA)-hour defined based on ≥10% of customers in a ZCTA-hour without power in primary analyses. We used a case-crossover study design and ran conditional logistic regression to assess associations separately within each urbanicity level: New York City (NYC), non-NYC urban, and rural areas. We additionally stratified models by warm versus cool season, individual-level age and sex, and ZCTA-level socioeconomic factors. Secondarily, we considered emergency (n = 298,910) and nonemergency hospitalizations separately.</p><p><strong>Results: </strong>We generally observed null associations between power outages and all CVD hospitalizations across New York State and within subgroups. For example, in NYC, we observed a rate ratio of 1.05 (95% confidence interval: 0.85, 1.30) for each additional power outage hour 1 day prior.</p><p><strong>Conclusions: </strong>The case-crossover design we used eliminated time-fixed confounding, but there were a limited number of exposed cases, limiting statistical power. Future studies should investigate co-occurring severe weather, span additional years, and evaluate other and broader geographic areas.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"458-466"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12122235/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143691416","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":"Erratum: Exposure to Ambient Heat and Risk of Spontaneous Abortion: A Case-Crossover Study.","authors":"Amelia K Wesselink, Emma L Gause, Keith D Spangler, Perry Hystad, Kipruto Kirwa, Mary D Willis, Gregory A Wellenius, Lauren A Wise","doi":"10.1097/EDE.0000000000001871","DOIUrl":"10.1097/EDE.0000000000001871","url":null,"abstract":"","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"e19"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157425","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":"The Authors Respond.","authors":"Lindsey Schader, David Benkeser, Allison Codi","doi":"10.1097/EDE.0000000000001861","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001861","url":null,"abstract":"","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":"36 4","pages":"e13-e14"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144173133","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":"Vaccine effects on in-hospital COVID-19 outcomes.","authors":"Bronner P Gonçalves, Piero L Olliaro, Peter Horby, Benjamin J Cowling","doi":"10.1097/EDE.0000000000001877","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001877","url":null,"abstract":"<p><p>Here, we posit that studies comparing outcomes of patients hospitalized with COVID-19 by vaccination status are important descriptive epidemiologic studies, but contrast two groups that are not comparable with regard to causal analyses. We use the principal stratification framework to show that these studies can estimate a causal vaccine effect only for the subgroup of individuals who would be hospitalized with or without vaccination. Further, we describe the methodology for, and present sensitivity analyses of, this effect. Using this approach can change the interpretation of studies only reporting the standard analyses that condition on observed hospital admission status - that is, analyses comparing outcomes for all hospitalised COVID-19 patients by vaccination status.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144316241","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":"Computing True Parameter Values in Simulation Studies Using Monte Carlo Integration.","authors":"Ashley I Naimi, David Benkeser, Jacqueline E Rudolph","doi":"10.1097/EDE.0000000000001873","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001873","url":null,"abstract":"<p><p>Simulation studies are used to evaluate and compare the properties of statistical methods in controlled experimental settings. In most cases, performing a simulation study requires knowledge of the true value of the parameter, or estimand, of interest. However, in many simulation designs, the true value of the estimand is difficult to compute analytically. Here, we illustrate the use of Monte Carlo integration to compute true estimand values in simple and more complex simulation designs. We provide general pseudocode that can be replicated in any software program of choice to demonstrate key principles in using Monte Carlo integration in two scenarios: a simple three-variable simulation where interest lies in the marginally adjusted odds ratio and a more complex causal mediation analysis where interest lies in the controlled direct effect in the presence of mediator-outcome confounders affected by the exposure. We discuss general strategies that can be used to minimize Monte Carlo error and to serve as checks on the simulation program to avoid coding errors. R programming code is provided illustrating the application of our pseudocode in these settings.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289331","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":"Improving the Use of Social Contact Studies in Epidemic Modeling.","authors":"Tom Britton, Frank Ball","doi":"10.1097/EDE.0000000000001876","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001876","url":null,"abstract":"<p><p>Social contact studies are used in infectious disease epidemiology to infer a contact matrix , having the mean number of contacts between individuals of different age groups as elements. However, does not capture the (often large) variation in the number of contacts within each age group, information is also available in social contact studies. Here, we include such variation by separating each age group into two halves: the socially active (having many contacts) and the socially less active (having fewer contacts). The extended contact matrix and its associated epidemic model show that acknowledging variation in social activity within age groups has a substantial impact on the basic reproduction number, , and the final fraction getting infected if the epidemic takes off, . In fact, variation in social activity is more important for data fitting than allowing for different age groups. A difficulty with variation in social activity, however, is that social contact studies typically lack information on whether mixing with respect to social activity is assortative (when socially active mainly have contact with other socially active individuals) or not. Our analysis shows that accounting for variation in social activity improves model predictability, yielding more accurate expressions for and irrespective of whether such mixing is assortative, but different assumptions on assortativity give rather different outputs. Future social contact studies should, therefore, also try to infer the degree of assortativity (with respect to social activity) between peers and their contacts.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289332","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":"Regression-based Proximal Causal Inference for Right-censored Time-to-event Data.","authors":"Kendrick Qijun Li, George C Linderman, Xu Shi, Eric J Tchetgen Tchetgen","doi":"10.1097/EDE.0000000000001884","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001884","url":null,"abstract":"<p><p>Unmeasured confounding is a major concern in obtaining credible inferences about causal effects from observational data. Proximal causal inference is an emerging methodological framework to detect and potentially account for confounding bias by carefully leveraging a pair of negative control exposure and outcome variables, also known as treatment and outcome confounding proxies. Although regression-based proximal causal inference is well-developed for binary and continuous outcomes, analogous proximal causal inference regression methods for right-censored time-to-event outcomes are currently lacking. In this paper, we propose a novel two-stage regression proximal causal inference approach for right-censored survival data under an additive hazard structural model. We provide theoretical justification for the proposed approach tailored to different types of negative control outcomes, including continuous, count, and right-censored time-to-event variables. We illustrate the approach with an evaluation of the effectiveness of right heart catheterization among critically ill patients using data from the SUPPORT study. Our method is implemented in the open-access R package \"pci2s.\"</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289400","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":"Use of health administrative data to identify migraine in individuals with a recognized pregnancy: A validation study in Ontario, Canada.","authors":"Carmela Melina Albanese, Susan J Bondy, Christine Lay, Zhiyin Li, Jun Guan, Hilary K Brown","doi":"10.1097/EDE.0000000000001890","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001890","url":null,"abstract":"<p><strong>Background: </strong>Migraine is a common risk factor for adverse perinatal outcomes, showing the importance of studying migraine in pregnancy. Despite growing use of routinely collected administrative data in health research, the validity of such data to detect migraine in pregnant populations is unestablished. We validated algorithms to identify a history of migraine among pregnant individuals using health administrative data and population-representative self-report data.</p><p><strong>Methods: </strong>We included n=8824 females in Ontario, Canada with a documented pregnancy with an estimated conception date from 09/01/2005 to 12/31/2021 who completed the Canadian Community Health Survey (CCHS) within 5 years before conception. We created algorithms using different combinations of diagnostic codes for headache disorders and migraine-specific drug claims with varying lookback periods before conception. We compared their performance to self-reported migraine diagnosis from the CCHS. Measures of validity were sensitivity, specificity, predictive values, and agreement.</p><p><strong>Results: </strong>The prevalence of self-reported migraine from the CCHS was 18% (95%CI 16%-19%). The prevalence using administrative data depended on the definition (range: 2%-25%). All algorithms had high specificity (81.7-98.9%), while sensitivity varied (6.1-53.2%). The algorithm requiring ≥2 physician visits or ≥1 hospitalizations or emergency department visits with diagnostic codes ICD-9: 346/ICD-10: G43, with a lifetime lookback, had high specificity (94.0%; 95%CI 93.1%-94.8%) and negative predictive value (86.3%; 95%CI 85.0%-87.6%) and modest sensitivity (30.4%; 95%CI 27.3%-33.6%) and positive predictive value (51.9%; 95%CI 46.8%-57.0%). Agreement was fair (κ = 0.29; 95%CI 0.25-0.33).</p><p><strong>Conclusion: </strong>Longitudinally linked health administrative data are effective at identifying pregnant individuals with migraine, with high specificity and reasonable sensitivity.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144247052","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":"Generalizability Analyses with a Partially Nested Trial Design: The Necrotizing Enterocolitis Surgery Trial.","authors":"Sarah E Robertson, Matthew A Rysavy, Martin L Blakely, Jon A Steingrimsson, Issa J Dahabreh","doi":"10.1097/EDE.0000000000001875","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001875","url":null,"abstract":"<p><p>We discuss generalizability analyses under a partially nested trial design, where part of the trial is nested within a cohort of trial-eligible individuals, while the rest of the trial is not nested. This design arises, for example, when only some centers participating in a trial are able to collect data on nonrandomized individuals, or when data on nonrandomized individuals cannot be collected for the full duration of the trial. Our work is motivated by the Necrotizing Enterocolitis Surgery Trial, which compared initial laparotomy versus peritoneal drain for infants with necrotizing enterocolitis or spontaneous intestinal perforation. During the first phase of the study, data were collected from randomized individuals as well as consenting nonrandomized individuals; during the second phase of the study, however, data were only collected from randomized individuals, resulting in a partially nested trial design. We propose methods for generalizability analyses with partially nested trial designs. We describe identification conditions and propose estimators for causal estimands in the target population of all trial-eligible individuals, both randomized and nonrandomized, in the part of the data where the trial is nested while using trial information spanning both parts. We evaluate the estimators in a simulation study and provide an illustration using the Necrotizing Enterocolitis Surgery Trial study.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144233557","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}