Epidemiology最新文献

{"title":"Method for Testing Etiologic Heterogeneity Among Noncompeting Diagnoses, Applied to Impact of Perinatal Exposures on Autism and Attention Deficit Hyperactivity Disorder.","authors":"Amy E Kalkbrenner, Cheng Zheng, Justin Yu, Tara E Jenson, Thomas Kuhlwein, Christine Ladd-Acosta, Jakob Grove, Diana Schendel","doi":"10.1097/EDE.0000000000001760","DOIUrl":"10.1097/EDE.0000000000001760","url":null,"abstract":"<p><strong>Background: </strong>Testing etiologic heterogeneity, whether a disorder subtype is more or less impacted by a risk factor, is important for understanding causal pathways and optimizing statistical power. The study of mental health disorders especially benefits from strategic subcategorization because these disorders are heterogeneous and frequently co-occur. Existing methods to quantify etiologic heterogeneity are not appropriate for noncompeting events in an open cohort of variable-length follow-up. Thus, we developed a new method.</p><p><strong>Methods: </strong>We estimated risks from urban residence, maternal smoking during pregnancy, and parental psychiatric history, with subtypes defined by the presence or absence of a codiagnosis: autism alone, attention deficit hyperactivity disorder (ADHD) alone, and joint diagnoses of autism + ADHD. To calculate the risk of a single diagnosis (e.g., autism alone), we subtracted the risk for autism + ADHD from the risk for autism overall. We tested the equivalency of average risk ratios over time, using a Wald-type test and bootstrapped standard errors.</p><p><strong>Results: </strong>Urban residence was most strongly linked with autism + ADHD and least with ADHD only; maternal smoking was associated with ADHD only but not autism only; and parental psychiatric history exhibited similar associations with all subgroups.</p><p><strong>Conclusion: </strong>Our method allowed the calculation of appropriate P values to test the strength of association, informing etiologic heterogeneity wherein two of these three risk factors exhibited different impacts across diagnostic subtypes. The method used all available data, avoided neurodevelopmental outcome misclassification, exhibited robust statistical precision, and is applicable to similar heterogeneous complex conditions using common diagnostic data with variable follow-up.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"689-700"},"PeriodicalIF":4.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11309336/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141723300","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":"Outcome of Pregnancy Oral Glucose Tolerance Test and Preterm Birth.","authors":"Richard Liang, Danielle M Panelli, David K Stevenson, David H Rehkopf, Gary M Shaw, Henrik Toft Sørensen, Lars Pedersen","doi":"10.1097/EDE.0000000000001752","DOIUrl":"10.1097/EDE.0000000000001752","url":null,"abstract":"<p><strong>Background: </strong>Gestational diabetes is associated with adverse outcomes such as preterm birth (<37 weeks). However, there is no international consensus on screening criteria or diagnostic levels for gestational diabetes, and it is unknown whether body mass index (BMI) or obesity modifies the relation between glucose level and preterm birth.</p><p><strong>Methods: </strong>We studied a pregnancy cohort restricted to two Danish regions from the linked Danish Medical Birth Register to study associations between glucose measurements from the 2-hour postload 75-g oral glucose tolerance test (one-step approach) and preterm birth from 2004 to 2018. In Denmark, gestational diabetes screening is a targeted strategy for mothers with identified risk factors. We used Poisson regression to estimate rate ratios (RR) of preterm birth with z-standardized glucose measurements. We assessed effect measure modification by stratifying analyses and testing for heterogeneity.</p><p><strong>Results: </strong>Among 11,337 pregnancies (6.2% delivered preterm), we observed an adjusted preterm birth RR of 1.2 (95% confidence interval [CI] = 1.1, 1.3) for a one-standard deviation glucose increase of 1.4 mmol/l from the mean of 6.7 mmol/l. There was evidence for effect measure modification by obesity, for example, adjusted RR for nonobese (BMI, <30): 1.2 (95% CI = 1.1, 1.3) versus obese (BMI, ≥30): 1.3 (95% CI = 1.2-1.5), P = 0.05 for heterogeneity.</p><p><strong>Conclusion: </strong>Among mothers screened for gestational diabetes, increased glucose levels, even those below the diagnostic level for gestational diabetes in Denmark, were associated with increased preterm birth risk. Obesity (BMI, ≥30) may be an effect measure modifier, not just a confounder, of the relation between blood glucose and preterm birth risk.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"701-709"},"PeriodicalIF":4.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11305920/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141075036","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":"Synthesizing Subject-matter Expertise for Variable Selection in Causal Effect Estimation: A Case Study.","authors":"Julia Debertin, Javier A Jurado Vélez, Laura Corlin, Bertha Hidalgo, Eleanor J Murray","doi":"10.1097/EDE.0000000000001758","DOIUrl":"10.1097/EDE.0000000000001758","url":null,"abstract":"<p><strong>Background: </strong>Causal graphs are an important tool for covariate selection but there is limited applied research on how best to create them. Here, we used data from the Coronary Drug Project trial to assess a range of approaches to directed acyclic graph (DAG) creation. We focused on the effect of adherence on mortality in the placebo arm, since the true causal effect is believed with a high degree of certainty.</p><p><strong>Methods: </strong>We created DAGs for the effect of placebo adherence on mortality using different approaches for identifying variables and links to include or exclude. For each DAG, we identified minimal adjustment sets of covariates for estimating our causal effect of interest and applied these to analyses of the Coronary Drug Project data.</p><p><strong>Results: </strong>When we used only baseline covariate values to estimate the cumulative effect of placebo adherence on mortality, all adjustment sets performed similarly. The specific choice of covariates had minimal effect on these (biased) point estimates, but including nonconfounding prognostic factors resulted in smaller variance estimates. When we additionally adjusted for time-varying covariates of adherence using inverse probability weighting, covariates identified from the DAG created by focusing on prognostic factors performed best.</p><p><strong>Conclusion: </strong>Theoretical advice on covariate selection suggests that including prognostic factors that are not exposure predictors can reduce variance without increasing bias. In contrast, for exposure predictors that are not prognostic factors, inclusion may result in less bias control. Our results empirically confirm this advice. We recommend that hand-creating DAGs begin with the identification of all potential outcome prognostic factors.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"642-653"},"PeriodicalIF":4.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11309331/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141300384","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":"Understanding the Intergenerational Impact of Migration: An Adult Mortality Advantage for the Children of Forced Migrants?","authors":"Ben Wilson, Matthew Wallace, Jan Saarela","doi":"10.1097/EDE.0000000000001763","DOIUrl":"10.1097/EDE.0000000000001763","url":null,"abstract":"<p><strong>Background: </strong>Children of immigrants often have excess mortality rates, in contrast to the low mortality typically exhibited by their parents' generation. However, prior research has studied children of immigrants who were selected for migration, thereby rendering it difficult to isolate the intergenerational impact of migration on adult mortality.</p><p><strong>Methods: </strong>We use semiparametric survival analysis to carry out a total population cohort study estimating all-cause and cause-specific mortality among all adult men and women from age of 17 years among all men and women born in 1953-1972 and resident in Finland in 1970-2020. We compare children of forced migrants from ceded Karelia, an area of Finland that was ceded to Russia during the Second World War, with the children of parents born in present-day Finland.</p><p><strong>Results: </strong>Children with two parents who were forced migrants have higher mortality than children with two parents born in Northern, Southern, and Western Finland, but similar or lower mortality than the subpopulation of children whose parents were born in the more comparable areas of Eastern Finland. For women and men, a mortality advantage is largest for external causes and persists after controlling for socioeconomic factors.</p><p><strong>Conclusion: </strong>Our findings suggest that forced migration can have a beneficial impact on the mortality of later generations, at least in the case where forced migrants are able to move to contextually similar locations that offer opportunities for rapid integration and social mobility. The findings also highlight the importance of making appropriate comparisons when evaluating the impact of forced migration.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"589-596"},"PeriodicalIF":4.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11309332/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141579273","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":"Interpreting Violations of Falsification Tests in the Context of Multiple Proposed Instrumental Variables.","authors":"Elizabeth W Diemer","doi":"10.1097/EDE.0000000000001751","DOIUrl":"10.1097/EDE.0000000000001751","url":null,"abstract":"","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"638-641"},"PeriodicalIF":4.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141075032","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":"Migration and Health: Chasing Causality in a Complex World.","authors":"Danielle M Crookes, Jacqueline M Torres","doi":"10.1097/EDE.0000000000001762","DOIUrl":"10.1097/EDE.0000000000001762","url":null,"abstract":"","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"597-601"},"PeriodicalIF":4.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141317183","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":"Natural effects with a recanting witness: non-identifiability or meaningless estimand?","authors":"Ian Shrier","doi":"10.1097/EDE.0000000000001768","DOIUrl":"10.1097/EDE.0000000000001768","url":null,"abstract":"","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"e18-e19"},"PeriodicalIF":4.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141317184","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":"Ambient Air Pollution Exposures and Child Executive Function: A US Multicohort Study.","authors":"Yu Ni, Alexis Sullivan, Adam A Szpiro, James Peng, Christine T Loftus, Marnie F Hazlehurst, Allison Sherris, Erin R Wallace, Laura E Murphy, Ruby H N Nguyen, Shanna H Swan, Sheela Sathyanarayana, Emily S Barrett, W Alex Mason, Nicole R Bush, Catherine J Karr, Kaja Z LeWinn","doi":"10.1097/EDE.0000000000001754","DOIUrl":"10.1097/EDE.0000000000001754","url":null,"abstract":"<p><strong>Background: </strong>Executive function, which develops rapidly in childhood, enables problem-solving, focused attention, and planning. Animal models describe executive function decrements associated with ambient air pollution exposure, but epidemiologic studies are limited.</p><p><strong>Methods: </strong>We examined associations between early childhood air pollution exposure and school-aged executive function in 1235 children from three US pregnancy cohorts in the ECHO-PATHWAYS Consortium. We derived point-based residential exposures to ambient particulate matter ≤2.5 µm in aerodynamic diameter (PM 2.5 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) at ages 0-4 years from spatiotemporal models with a 2-week resolution. We assessed executive function across three domains, cognitive flexibility, working memory, and inhibitory control, using performance-based measures and calculated a composite score quantifying overall performance. We fitted linear regressions to assess air pollution and child executive function associations, adjusting for sociodemographic characteristics, maternal mental health, and health behaviors, and examined modification by child sex, maternal education, and neighborhood educational opportunity.</p><p><strong>Results: </strong>In the overall sample, we found hypothesized inverse associations in crude but not adjusted models. Modified associations between NO 2 exposure and working memory by neighborhood education opportunity were present ( Pinteraction = 0.05), with inverse associations more pronounced in the \"high\" and \"very high\" categories. Associations of interest did not differ by child sex or maternal education.</p><p><strong>Conclusion: </strong>This work contributes to the evolving science regarding early-life environmental exposures and child development. There remains a need for continued exploration in future research endeavors, to elucidate the complex interplay between natural environment and social determinants influencing child neurodevelopment.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"676-688"},"PeriodicalIF":4.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11305919/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141317182","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":"Studying Continuous, Time-varying, and/or Complex Exposures Using Longitudinal Modified Treatment Policies.","authors":"Katherine L Hoffman, Diego Salazar-Barreto, Nicholas T Williams, Kara E Rudolph, Iván Díaz","doi":"10.1097/EDE.0000000000001764","DOIUrl":"10.1097/EDE.0000000000001764","url":null,"abstract":"<p><p>This tutorial discusses a methodology for causal inference using longitudinal modified treatment policies. This method facilitates the mathematical formalization, identification, and estimation of many novel parameters and mathematically generalizes many commonly used parameters, such as the average treatment effect. Longitudinal modified treatment policies apply to a wide variety of exposures, including binary, multivariate, and continuous, and can accommodate time-varying treatments and confounders, competing risks, loss to follow-up, as well as survival, binary, or continuous outcomes. Longitudinal modified treatment policies can be seen as an extension of static and dynamic interventions to involve the natural value of treatment and, like dynamic interventions, can be used to define alternative estimands with a positivity assumption that is more likely to be satisfied than estimands corresponding to static interventions. This tutorial aims to illustrate several practical uses of the longitudinal modified treatment policy methodology, including describing different estimation strategies and their corresponding advantages and disadvantages. We provide numerous examples of types of research questions that can be answered using longitudinal modified treatment policies. We go into more depth with one of these examples, specifically, estimating the effect of delaying intubation on critically ill COVID-19 patients' mortality. We demonstrate the use of the open-source R package lmtp to estimate the effects, and we provide code on https://github.com/kathoffman/lmtp-tutorial.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":"35 5","pages":"667-675"},"PeriodicalIF":4.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141897142","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":"Overcoming Data Gaps in Life Course Epidemiology by Matching Across Cohorts.","authors":"Katrina L Kezios, Scott C Zimmerman, Peter T Buto, Kara E Rudolph, Sebastian Calonico, Adina Zeki Al Hazzouri, M Maria Glymour","doi":"10.1097/EDE.0000000000001761","DOIUrl":"10.1097/EDE.0000000000001761","url":null,"abstract":"<p><p>Life course epidemiology is hampered by the absence of large studies with exposures and outcomes measured at different life stages in the same individuals. We describe when the effect of an exposure ( A ) on an outcome ( Y ) in a target population is identifiable in a combined (\"synthetic\") cohort created by pooling an early-life cohort including measures of A with a late-life cohort including measures of Y . We enumerate causal assumptions needed for unbiased effect estimation in the synthetic cohort and illustrate by simulating target populations under four causal models. From each target population, we randomly sampled early- and late-life cohorts and created a synthetic cohort by matching individuals from the two cohorts based on mediators and confounders. We estimated the effect of A on Y in the synthetic cohort, varying matching variables, the match ratio, and the strength of association between matching variables and A . Finally, we compared bias in the synthetic cohort estimates when matching variables did not d-separate A and Y to the bias expected in the original cohort. When the set of matching variables includes all variables d-connecting exposure and outcome (i.e., variables blocking all backdoor and front-door pathways), the synthetic cohort yields unbiased effect estimates. Even when matching variables did not fully account for confounders, the synthetic cohort estimate was sometimes less biased than comparable estimates in the original cohort. Methods based on merging cohorts may hasten the evaluation of early- and mid-life determinants of late-life health but rely on available measures of both confounders and mediators.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"610-617"},"PeriodicalIF":4.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11305898/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141537702","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}