International journal of epidemiology最新文献

{"title":"Cohort profile: The Ma'anshan birth cohort (MABC) study.","authors":"Kun Huang, Juan Tong, Shuman Tao, Xiaoyan Wu, Shuangqin Yan, Guopeng Gao, Hui Cao, Liangliang Xie, Hui Gao, Menglong Geng, Chunmei Liang, Hong Gan, Yan Han, Mengjuan Lu, Yuzhu Teng, Shilu Tong, Fangbiao Tao","doi":"10.1093/ije/dyae142","DOIUrl":"https://doi.org/10.1093/ije/dyae142","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"53 6","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142564028","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":"Measurement error and information bias in causal diagrams: mapping epidemiological concepts and graphical structures.","authors":"Melissa T Wardle, Kelly M Reavis, Jonathan M Snowden","doi":"10.1093/ije/dyae141","DOIUrl":"https://doi.org/10.1093/ije/dyae141","url":null,"abstract":"<p><p>Measurement error and information bias are ubiquitous in epidemiology, yet directed acyclic graphs (DAGs) are infrequently used to represent them, in contrast with confounding and selection bias. This represents a missed opportunity to leverage the full utility of DAGs to depict associations between the variables we actually analyse in practice: empirically measured variables, which are necessarily measured with error. In this article, we focus on applying causal diagrams to depict the data-generating mechanisms that give rise to the data we analyse, including measurement error. We begin by considering empirical data considerations using a general example, and then build up to a specific worked example from the clinical epidemiology of hearing health. Throughout, our goal is to highlight both the challenges and the benefits of using DAGs to depict measurement error. In addition to the application of DAGs to conceptual causal questions (which pertain to unmeasured constructs free from measurement error), which is common, we highlight the advantages associated with applying DAGs to also include empirically measured variables and-potentially-information bias. We also highlight the implications implied by this use of DAGs, particularly regarding the unblocked backdoor path causal structure. Ultimately, we seek to help increase the clarity with which epidemiologists can map traditional epidemiological concepts (such as information bias and confounding) onto causal graphical structures.</p>","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"53 6","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142500022","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":"Data Resource Profile: The School Health Research Network (SHRN) Student Health and Well-being (SHW) survey of 11-16-year-olds (2017-2023).","authors":"Nicholas Page, Shujun Liu, Kelly Morgan, Lianna Angel, Edna Ogada, Chris Roberts, Honor Young, Simon Murphy","doi":"10.1093/ije/dyae161","DOIUrl":"10.1093/ije/dyae161","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"53 6","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11645470/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142828358","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":"Correction to: Cohort Profile Update: The Neuroscience in Psychiatry Network (NSPN) 2400 cohort during the COVID-19 pandemic.","authors":"","doi":"10.1093/ije/dyae157","DOIUrl":"10.1093/ije/dyae157","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"53 6","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11558059/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142619853","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":"Spatial targeting and integration across vaccination, vitamin A and deworming programs throughout India 2019-21.","authors":"Francois Rerolle, Arnab K Dey, Tarik Benmarhnia, Benjamin F Arnold","doi":"10.1093/ije/dyae160","DOIUrl":"10.1093/ije/dyae160","url":null,"abstract":"<p><strong>Background: </strong>Currently, most large-scale public health programs, such as immunization or anti-parasitic deworming, work in relative isolation. Integrating efforts across programs could potentially improve their efficiency, but identifying populations that could benefit from multiple programs has been an operational challenge.</p><p><strong>Methods: </strong>We analyzed a nationally representative survey conducted in India between 2019 and 2021 to assess and map coverage of seven vaccines [Bacillus Calmette-Guérin (BCG), hepatitis B, polio, diphtheria-tetanus-pertussis (DTP), haemophilus influenza type b (Hib), rotavirus and measles-containing vaccine (MCV)], plus Vitamin A supplementation and anti-parasitic deworming treatment among 86 761 children aged 1-3 years old.</p><p><strong>Results: </strong>National coverage varied widely by program, from 42% (rotavirus) to 95% (BCG). There was high correlation between district-level coverage estimates (r ≥ 0.7) and extensive spatial overlap in low-coverage populations. In simulated implementation strategies, we show that an integrated strategy that targets full immunization coverage for four core vaccines (BCG, polio, DTP, MCV) would achieve similar coverage to an optimal (but unrealistic) implementation strategy and far better coverage than multiple efforts focused on individual vaccines. Targeting the most under-vaccinated districts within states based on spatial clustering or coverage thresholds led to further improvements in full coverage per child targeted. Integration of anti-parasitic deworming or rotavirus vaccination into a core vaccine delivery mission could nearly double their coverage (from ∼45% to ∼85%).</p><p><strong>Conclusions: </strong>Integrated delivery and geographic targeting across core vaccines could accelerate India's progress toward full immunization coverage. An integrated platform could greatly expand coverage of non-core vaccines and other child health interventions.</p>","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"53 6","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11631194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142806797","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":"A Global South epidemiological heritage: the Pelotas (Brazil) Birth Cohort Studies.","authors":"Pedro C Hallal, Michael Reichenheim","doi":"10.1093/ije/dyae149","DOIUrl":"https://doi.org/10.1093/ije/dyae149","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"53 6","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142590867","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":"Cohort Profile Update: Project Viva Offspring.","authors":"Sheryl L Rifas-Shiman, Izzuddin M Aris, Karen M Switkowski, Jessica Young, Abby F Fleisch, Wei Perng, Jorge E Chavarro, Andres Cardenas, Diane R Gold, Mingyu Zhang, Peter James, Rachel C Whooten, Ken P Kleinman, Emily Oken, Marie-France Hivert","doi":"10.1093/ije/dyae162","DOIUrl":"10.1093/ije/dyae162","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"53 6","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11630542/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142828354","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":"Ambient temperature exposure and rapid infant weight gain.","authors":"Neora Alterman,Daniel Nevo,Ronit Calderon-Margalit,Iaroslav Youssim,Bar Weinstein,Itai Kloog,Michael Hauzer,Raanan Raz","doi":"10.1093/ije/dyae134","DOIUrl":"https://doi.org/10.1093/ije/dyae134","url":null,"abstract":"BACKGROUNDChildhood obesity is a major public health concern, and the global rate is rising. Rapid infant weight gain is a risk factor for later overweight. Studies have linked prenatal ambient temperature exposure to fetal growth, and preliminary evidence suggests postnatal exposure may be associated with infant weight gain.METHODSUsing a population-based historical cohort study including 1 100 576 infants born 2011-2019, we assessed the relationship between prenatal and one-month postnatal ambient temperature exposure and rapid infant weight gain. We used a hybrid spatiotemporal model to assess temperatures at the family's recorded residence at birth. Repeated weight measurements between birth and 15 months were used to model the outcome using the SuperImposition by Translation and Rotation (SITAR) method. We employed generalized linear models and distributed lag models to estimate the association between prenatal and postnatal exposure and rapid infant weight gain, defined as the upper tertile of the SITAR growth velocity.RESULTSOverall, higher ambient temperatures were associated with rapid infant weight gain. The cumulative adjusted relative risk for the highest exposure quintile during pregnancy compared with the lowest quintile was 1.33 [95% confidence interval (CI): 1.25, 1.40], and the corresponding association for the first postnatal month was 1.19 (95% CI: 1.15, 1.23). Exposure to high ambient temperature during early and mid-pregnancy, as well as the first postnatal month, was associated with rapid weight gain, while during late pregnancy, exposure to low temperatures was associated with this outcome.CONCLUSIONSPrenatal and postnatal ambient temperatures are associated with rapid infant weight gain.","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"13 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439483","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":"Staggered interventions with no control groups.","authors":"Brice Batomen,Tarik Benmarhnia","doi":"10.1093/ije/dyae137","DOIUrl":"https://doi.org/10.1093/ije/dyae137","url":null,"abstract":"The limitations of the two-way fixed effects for the impact evaluation of interventions that occur at different times for each group have meant that 'staggered interventions' have been highlighted in recent years in the econometric literature and, more recently, in epidemiology. Although many alternative strategies (such as staggered difference-in-differences) have been proposed, the focus has predominantly been on scenarios in which one or more control groups are available. However, control groups are often unavailable, due to limitations in the available data or because all units eventually receive the intervention. In this context, interrupted time series (ITS) designs can constitute an appropriate alternative. The extent to which common model specifications for ITS analyses are limited in the case of staggered interventions remains an underexplored area in the methodological literature. In this work, we aim to demonstrate that standard ITS model specifications typically yield biased results for staggered interventions and we propose alternative model specifications that were inspired by recent developments in the difference-in-differences literature to propose adapted analytical strategies.","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"25 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439510","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":"Probabilistic bias analysis for exposure misclassification of household income by neighbourhood in a cohort of individuals with colorectal cancer.","authors":"Laura E Davis,Hailey R Banack,Renzo Calderon-Anyosa,Erin C Strumpf,Alyson L Mahar","doi":"10.1093/ije/dyae135","DOIUrl":"https://doi.org/10.1093/ije/dyae135","url":null,"abstract":"INTRODUCTIONDespite poor agreement, neighbourhood income is used as a proxy for household income, due to a lack of data availability. We quantified misclassification between household and neighbourhood income and demonstrate quantitative bias analysis (QBA) in scenarios where only neighbourhood income is available in assessing income inequalities on colorectal cancer mortality.METHODSThis was a retrospective study of adults with colorectal cancer diagnosed 2006-14 from Statistics Canada's Canadian Census Health and Environment Cohort. Neighbourhood income quintiles from Statistics Canada were used. Census household income quintiles were used to determine bias parameters and confirm results of the QBA. We calculated positive and negative predictive values using multinomial models, adjusting for age, sex and rural residence. Probabilistic QBA was conducted to explore the implication of exposure misclassification when estimating the effect of income on 5-year mortality.RESULTSWe found poor agreement between neighbourhood and household income: positive predictive values ranged from 21% to 37%. The bias-adjusted risk of neighbourhood income on 5-year mortality was similar to the risk of mortality by household income. The bias-adjusted relative risk of the lowest income quintile compared with the highest was 1.42 [95% simulation interval (SI) 1.32-1.53] compared with 1.46 [95% confidence interval (CI) 1.39-1.54] for household income and 1.18 (95% CI 1.12-1.24) for neighbourhood income.CONCLUSIONQBA can be used to estimate adjusted effects of neighbourhood income on mortality which represent household income. The predictive values from our study can be applied to similar cohorts with only neighbourhood income to estimate the effects of household income on cancer mortality.","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"55 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142436159","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}