Epidemiology最新文献

{"title":"Handling Multivariable Missing Data in Causal Mediation Analysis Estimating Interventional Effects.","authors":"S Ghazaleh Dashti, Katherine J Lee, Julie A Simpson, John B Carlin, Margarita Moreno-Betancur","doi":"10.1097/EDE.0000000000001866","DOIUrl":"10.1097/EDE.0000000000001866","url":null,"abstract":"<p><p>The interventional effects approach to causal mediation analysis is increasingly common in epidemiologic research given its potential to address policy-relevant questions about hypothetical mediator interventions. Multiple imputation is widely used for handling multivariable missing data in epidemiologic studies. However, guidance is lacking on best practices for using multiple imputation when estimating interventional mediation effects, specifically regarding the role of missingness mechanism in the performance of the method, how to appropriately specify the multiple imputation model when g-computation is used for effect estimation, and appropriate variance estimation. To address this gap, we conducted simulations based on the Victorian Adolescent Health Cohort Study. We considered seven missingness mechanisms, involving varying assumptions regarding the influence of an intermediate confounder, a mediator, and/or the outcome on missingness in key variables. We compared the performance of complete case analysis, six multiple imputation approaches by fully conditional specification, differing in how the imputation model was tailored, and a \"substantive model compatible\" multiple imputation-fully conditional specification approach. We evaluated MIBoot (multiple imputation, then bootstrap) and BootMI (bootstrap, then multiple imputation) approaches for variance estimation. All multiple imputation approaches, apart from those clearly diverging from best practice, yielded approximately unbiased estimates when none of the intermediate confounder, mediator, and outcome variables influenced missingness in any of these variables and nonnegligible bias otherwise. We observed the largest bias for interventional effects when each of the intermediate confounders, mediators, and outcomes influenced their own missingness. BootMI returned variance estimates with a smaller bias than MIBoot.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"487-499"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751725","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":"Right Censoring and Mortality in the Multicenter AIDS Cohort Study and Women's Interagency HIV Study.","authors":"Jessie K Edwards, Tiffany L Breger, Stephen R Cole, Paul N Zivich, Bonnie E Shook-Sa, Leah M Sadinski, Daniel Westreich, Andrew Edmonds, Catalina Ramirez, Igho Ofotokun, Seble G Kassaye, Todd T Brown, Deborah Konkle-Parker, Valentina Stosor, Robert Bolan, Sarah Krier, Deborah L Jones, Gypsyamber D'Souza, Mardge Cohen, Phyllis C Tien, Tonya Taylor, Kathryn Anastos, M Bradley Drummond, Michelle Floris-Moore","doi":"10.1097/EDE.0000000000001852","DOIUrl":"10.1097/EDE.0000000000001852","url":null,"abstract":"<p><strong>Background: </strong>Epidemiologists frequently employ right censoring to handle missing outcome, covariate, or exposure data incurred when participants have large gaps between study visits or stop attending study visits entirely. But, if participants who are censored are more or less likely to experience outcomes of interest than those not censored, such censoring could introduce bias in estimated measures.</p><p><strong>Methods: </strong>We examined how censoring after two consecutive missed visits may affect mortality results from the Multicenter AIDS Cohort Study (MACS) and Women's Interagency HIV Study (WIHS). MACS and WIHS provide linkages to vital statistics registries, such that mortality data were available for all participants, regardless of whether they attended study visits.</p><p><strong>Results: </strong>In a gold standard analysis that did not censor after two consecutive missed visits, 10-year mortality was 23% (95% CI: 22, 24) in MACS and 21% (95% CI: 20, 23) in WIHS. Estimated mortality was modestly reduced by 0%-5% across subgroups when censoring at missed visits. Applying inverse probability of censoring weights partially removed this attenuation.</p><p><strong>Conclusions: </strong>While mortality was slightly elevated after two consecutive missed visits in MACS and WIHS, censoring at two consecutive missed visits did not substantially alter estimated mortality, particularly after applying inverse probability of censoring weights.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"511-519"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12122228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143691415","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":"Alcohol Policy in Adolescence and Subsequent Alcohol-attributable Hospitalizations and Mortality at Ages 21-54 Years: A Register-based Cohort Study.","authors":"Juha Luukkonen, Elina Einiö, Lasse Tarkiainen, Pekka Martikainen, Hanna Remes","doi":"10.1097/EDE.0000000000001857","DOIUrl":"10.1097/EDE.0000000000001857","url":null,"abstract":"<p><strong>Background: </strong>Little is known about how alcohol policies experienced in adolescence are associated with later health. We assess whether the age of exposure to stricter alcohol policies is associated with later alcohol-attributable hospitalizations and mortality. We take advantage of an alcohol advertising ban and alcohol tax increases introduced in 1975-1977 with relatively stable alcohol policies before and after.</p><p><strong>Methods: </strong>We used Finnish register data on birth cohorts 1950-1964 (1,175,878 individuals) to assess cohort-wise hazard ratios for the first incidence of alcohol-attributable hospitalization and mortality, and mortality due to external and other causes at ages 21-54 years.</p><p><strong>Results: </strong>Men who were aged 19-25 at the time of the restrictive reform had similar risks for alcohol-attributable hospitalization and mortality to the reference group of those aged 18-legal drinking age-at the time of reform. For those underage at the time, hospitalization and mortality rates were incrementally smaller cohort by cohort. For example, men who were 17 at the time of the reform had lower hazard ratios of alcohol-attributable hospitalization: 0.91 (95% confidence interval: 0.87, 0.95) as did those who were 13 (0.85; 95% confidence interval: 0.81, 0.89). The findings were similar for external-cause mortality, and similar yet more uncertain for women. In contrast, mortality from other causes declined continuously from cohort to cohort.</p><p><strong>Conclusions: </strong>Our findings are consistent with the hypothesis that stricter alcohol policies in adolescence reduce harmful alcohol consumption patterns extending into adulthood and manifesting as lower alcohol-related harm to health.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"580-589"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12118618/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788096","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":"Five Facts About Influence Functions.","authors":"Stephen R Cole, Alexander Breskin, Bonnie E Shook-Sa, Paul N Zivich, Michael G Hudgens, Jessie K Edwards","doi":"10.1097/EDE.0000000000001858","DOIUrl":"10.1097/EDE.0000000000001858","url":null,"abstract":"","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"467-472"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751719","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":"Health Predictors of Neighborhood Selection: A Prospective Cohort Study of Residential Mobility in Ontario, Canada.","authors":"Emmalin Buajitti, Laura C Rosella","doi":"10.1097/EDE.0000000000001862","DOIUrl":"10.1097/EDE.0000000000001862","url":null,"abstract":"<p><strong>Background: </strong>Health selection into neighborhoods describes unhealthy people moving disproportionately to lower-income neighborhoods, producing observable socioeconomic gradients sometimes falsely attributed to neighborhood effects on health. We investigated residential mobility outcomes and their relationship to baseline health using population-level data linkages in Ontario, Canada.</p><p><strong>Methods: </strong>We included Canadian Community Health Survey respondents ages 25 to 64 between 2005 and 2014 (n = 93,235). We assessed baseline health using self-reported health and multimorbidity. We captured moves using health administrative data and the Canadian census. We fit multinomial logistic regression models with a six-category residential mobility outcome: (1) nonmovers from low-income neighborhoods; (2) nonmovers from high-income neighborhoods; (3) movers from low-income to low-income; (4) movers from low-income to high-income; (5) movers from high-income to low-income; and (6) movers from high-income to high-income. We adjusted models for the Canadian Community Health Survey cycle, age, sex, household income, immigrant status, and residential instability.</p><p><strong>Results: </strong>Compared with those with very good or excellent health, respondents reporting fair or poor health at baseline had higher odds of moving from low- to low-income neighborhoods (Adjusted odds ratios [aOR] = 1.73; 95% confidence interval [CI] = 1.46, 2.05), moving from high- to low-income (aOR = 1.64; 95% CI = 1.35, 1.98), moving from low- to high-income (aOR = 1.26; 95% CI = 1.04, 1.54), and not moving within low-income (aOR = 1.36; 1.23, 1.51) relative to not moving within high-income. Results were consistent for objective health measures, comparing respondents with at least four chronic conditions to those with one or none.</p><p><strong>Conclusions: </strong>In a large, population-based study, both subjective and objective measures of health had a strong relationship with residential mobility outcomes.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"440-449"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12118616/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788098","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":"Revisiting the Population Attributable Fraction.","authors":"Mark Klose, Paul N Zivich, Stephen R Cole","doi":"10.1097/EDE.0000000000001867","DOIUrl":"10.1097/EDE.0000000000001867","url":null,"abstract":"<p><strong>Background: </strong>The population attributable fraction corresponds to the reduction of the outcome had individuals (counter-to-fact) not experienced the exposure scaled by the observed incidence. Estimators proposed by Levin and Miettinen implicitly assume the study population is a random sample of the target population, which is not always the case.</p><p><strong>Methods: </strong>In our example, we estimate the reduction in AIDS or death among women diagnosed with HIV in the United States in 2008, had they not had a history of injection drug use. To transport risk estimates from 1164 women in the Women's Interagency HIV Study to the 11,282 women diagnosed with HIV in the United States in 2008, we use the inverse probability of treatment and the inverse odds of sampling weighting. We estimate the variance of the population attributable fraction with a nonparametric bootstrap and M-estimation using the sandwich variance estimator.</p><p><strong>Results: </strong>The population attributable fraction estimated in the observed sample was 0.21 (95% confidence interval: 0.13, 0.29). After transporting the population attributable fraction to the target population, it was 0.13 (95% confidence interval: 0.065, 0.19).</p><p><strong>Conclusions: </strong>Defining the target population and identification conditions allows for a clearer interpretation of the population attributable fraction.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"482-486"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12122213/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751754","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":"The Same but Different?: A Systematic Review of the Impact of Selection and Collider Bias on Internal Validity.","authors":"Natalie S Levy, Katrina L Kezios","doi":"10.1097/EDE.0000000000001864","DOIUrl":"10.1097/EDE.0000000000001864","url":null,"abstract":"<p><strong>Background: </strong>Recent work conceptually unifying selection and collider-restriction bias as threats to internal validity implies that their impact on observed associations should similarly align. We reviewed epidemiologic literature to summarize existing knowledge about the impact of selection and collider bias.</p><p><strong>Methods: </strong>We systematically searched for peer-reviewed, methodologic articles and general epidemiology textbooks published in English from 1 January 2000 to 12 July 2024. We included sources that focused on internal validity and discussed the magnitude or direction of selection or collider bias. We abstracted conclusions about the likely magnitude and direction of bias, which stratum or strata are affected when restricting analyses to a subset, and the conditions under which the consequences of bias were evaluated.</p><p><strong>Results: </strong>We retained 33 of 5508 identified articles and 12 of 205 textbooks for data abstraction. Overall, we found that collider bias articles conveyed its impact as minimal while selection bias sources described variable effects. We also observed that most collider bias sources evaluated bias under the sharp null (assuming no relationship between the exposure and outcome) and found differences between how selection and collider bias sources discussed the role of interaction and the strata affected.</p><p><strong>Conclusions: </strong>Although collider-restriction and selection bias affecting internal validity are considered theoretically equivalent, conclusions differ about their consequences for study results. Investigating collider bias not under the sharp null and considering the role of both multiplicative and additive interaction between the causes of a collider may improve our ability to predict and quantify its impact on internal validity.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"473-481"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12122217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751755","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":"State-level Payday Loan Bans and Preterm Births in the US, 2000-2019.","authors":"Samantha Gailey, Tim Bruckner, Rania Badran, Parvati Singh","doi":"10.1097/EDE.0000000000001865","DOIUrl":"10.1097/EDE.0000000000001865","url":null,"abstract":"<p><strong>Background: </strong>Payday loans refer to high-interest, short-term loans. These loans can provide immediate financial relief for individuals with limited access to traditional credit. However, the predatory nature of payday loans may portend increased financial strain and adverse public health consequences.</p><p><strong>Methods: </strong>We examine whether state-level temporal variation in payday loan restrictions over a 20-year period (2000-2019) corresponds with a reduction in preterm births: a leading cause of infant mortality in the United States (US). Between 2000 and 2019, 10 US states and the District of Columbia imposed restrictions on payday lending at varied time points. We use data on preterm births provided by the Centers of Disease Control's WONDER database (2000-2019) and apply staggered difference-in-difference approaches to examine whether preterm births (per 100 live births) declined among states that imposed payday lending restrictions, relative to states that never imposed restrictions. We also control for state-specific time propensity of preterm births, derived through time-series analysis.</p><p><strong>Results: </strong>Results indicate a decline in the preterm births by approximately 0.22 per 100 live births (95% confidence interval: -0.31, -0.13) within the first 3 years of payday loan restrictions, which corresponds to 4512 fewer than expected preterm births.</p><p><strong>Conclusion: </strong>Our findings are consistent with the hypothesis that state-level payday lending restrictionsare associated with a reduction in preterm births.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"541-550"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12122219/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802557","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":"Time and Age as Longitudinal Timescales: Multiple Useful Models are Illuminating.","authors":"Michael E Griswold, M Maria Glymour","doi":"10.1097/EDE.0000000000001869","DOIUrl":"10.1097/EDE.0000000000001869","url":null,"abstract":"","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":"36 4","pages":"572-579"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12118613/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144173151","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":"Approaches to Timescale Choice in Cognitive Aging Research and Potential Implications for Estimated Exposure Effects: Coordinated Analyses in 10 Cohorts of Older Adults.","authors":"Eleanor Hayes-Larson, Ryan M Andrews, Katrina L Kezios, Ariane Bercu, Anaïs Rouanet, Catherine Helmer, Paul K Crane, Laura E Gibbons, Brandon S Klinedinst, Linda K McEvoy, Emma Nichols, Jennifer Weuve, Kumar B Rajan, Phillip H Hwang, Jesse Mez, Mateo Farina, Crystal Shaw, Kendra D Sims, Terry Therneau, Ronald C Petersen, Vincent Bouteloup, Alden L Gross, Marilyn Albert, John C Morris, Colin L Masters, Susan M Resnick, Paul Maruff, Jennifer J Manly, Indira C Turney, Jet M J Vonk, Justina Avila-Rieger, Alexandra Weigand, Ruijia Chen, Jingxuan Wang, Cécile Proust-Lima, Elizabeth Rose Mayeda","doi":"10.1097/EDE.0000000000001859","DOIUrl":"10.1097/EDE.0000000000001859","url":null,"abstract":"<p><strong>Background: </strong>Cognitive change is an important factor in understanding dementia. Estimating effects of exposures on cognitive change requires choosing an analytical timescale, typically time on study or current age. There is limited consensus regarding timescale choice in epidemiologic cognitive aging research.</p><p><strong>Methods: </strong>Using a coordinated analytic approach in 10 cohorts of older adults, we evaluated whether estimated effects of two exposures on memory change differed depending on timescale (time on study or current age). We modeled effects of apolipoprotein-E ( APOE ) ε4 genotype (a time-invariant exposure) and diabetes (a potentially time-varying/acquired exposure evaluated at baseline) using mixed-effects models with linear and nonlinear time specifications for both timescales.</p><p><strong>Results: </strong>Among APOE ε4 carriers, model-estimated memory scores at baseline (time on study timescale) or at each cohort's median baseline age (current age timescale) were lower, and the average rate of decline was faster than among APOE ε4 noncarriers. Model-estimated memory scores at baseline or at median baseline age were generally similar across baseline diabetes status, with variability across cohorts in the diabetes-memory change association. In some cohorts, trends in diabetes-memory change associations differed in direction across timescales.</p><p><strong>Conclusions: </strong>Timescale was largely inconsequential for estimated effects of APOE genotype, but yielded differences in estimated diabetes effects, raising questions about the appropriate scale. The current age scale may be problematic because diabetes was measured heterogeneously in age across individuals, a common issue in aging cohorts. Our work demonstrates approaches to evaluate alternative timescales, including in multicohort analyses, and highlights potential implications for estimated exposure effects on cognitive change.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"560-571"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12211680/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751717","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}