Annals of Epidemiology最新文献

{"title":"COVID-19 vaccine acceptance differences among unvaccinated foreign- and united states-born persons: A cross-sectional study, 2021","authors":"Aryana Sepassi PharmD, MAS ,&nbsp;Samantha Garcia PhD, MPH, CHES ,&nbsp;Sora Tanjasiri DrPH ,&nbsp;Sunmin Lee ScD ,&nbsp;Nana Entsuah-Boateng PharmD ,&nbsp;Mark Bounthavong PharmD, PhD, MPH","doi":"10.1016/j.annepidem.2025.01.009","DOIUrl":"10.1016/j.annepidem.2025.01.009","url":null,"abstract":"<div><h3>Purpose</h3><div>To investigate the association between nativity and COVID-19 vaccine acceptance and its interaction with race/ethnicity, education, and English proficiency.</div></div><div><h3>Methods</h3><div>Differences in vaccine acceptance among propensity-score matched foreign- and US-born persons using 2021 California Health Interview Survey Data were measured using a survey-weighted multivariable logistic regression model with interaction terms and average predicted probabilities between nativity and: race/ethnicity, education, English proficiency.</div></div><div><h3>Results</h3><div>A total of 4,234,655 survey-weighted persons (8504 unweighted) met inclusion criteria; 2251,279 (53 %) were foreign-born (1,983,376 US-born), and 55 % of all persons were Hispanic/Latino, 22 % were Non-Hispanic White, 17 % were Non-Hispanic Asian/Pacific Islander, 3.6 % were Non-Hispanic Black/African American, and 2.5 % were categorized as ‘Other’. Foreign-born status was significantly associated with greater odds of acceptance (adjusted odds ratio [aOR], 2.81 [95 %CI, 1.16–6.83]). Foreign-born Hispanic persons had a significantly greater probability of acceptance compared to their US-born counterparts (average probability difference, +0.11 [95 %CI, +0.023, +0.20]). Foreign-born persons with poor English proficiency had a lower probability of acceptance versus US-born persons (APD, −0.081, [95 %CI, −0.43, 0.27]).</div></div><div><h3>Conclusions</h3><div>Nativity was significantly associated with COVID-19 vaccine acceptance, and this relationship varied by race/ethnicity and English proficiency. These findings may be used to direct future interventions aimed at improving COVID-19 vaccination rates.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"103 ","pages":"Pages 21-27"},"PeriodicalIF":3.3,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143373104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence estimates of mental illness among parents in the United States: Results from the National Survey on Drug Use and Health, 2021–2023","authors":"Paul J. Geiger ,&nbsp;Lauren Klein Warren ,&nbsp;Leyla Stambaugh ,&nbsp;Douglas Richesson ,&nbsp;Tenecia Smith ,&nbsp;Jennifer Hoenig","doi":"10.1016/j.annepidem.2025.01.007","DOIUrl":"10.1016/j.annepidem.2025.01.007","url":null,"abstract":"","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"102 ","pages":"Pages 91-93"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143029811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical harmonization of versions of measures across studies using external data: Self-rated health and self-rated memory","authors":"Yingyan Wu MS ,&nbsp;Eleanor Hayes-Larson PhD, MPH ,&nbsp;Yixuan Zhou ,&nbsp;Vincent Bouteloup PharmD ,&nbsp;Scott C. Zimmerman MPH ,&nbsp;Anna M. Pederson MPH ,&nbsp;Vincent Planche MD, PhD ,&nbsp;Marissa J. Seamans PhD, MSPH ,&nbsp;Daniel Westreich PhD ,&nbsp;M. Maria Glymour ,&nbsp;Laura E. Gibbons PhD ,&nbsp;Carole Dufouil PhD ,&nbsp;Elizabeth Rose Mayeda PhD, MPH","doi":"10.1016/j.annepidem.2025.01.002","DOIUrl":"10.1016/j.annepidem.2025.01.002","url":null,"abstract":"<div><h3>Purpose</h3><div>Harmonizing variables for constructs measured differently across studies is essential for comparing, combining, and generalizing results. We developed and fielded a brief survey to harmonize Likert and continuous versions of measures for two constructs, self-rated health and self-rated memory, for use in studies of French older adults.</div></div><div><h3>Methods</h3><div>We recruited 300 participants from a French memory clinic in 2023 to answer both the Likert and continuous versions of self-rated health and self-rated memory questions. For each construct, we predicted responses to the Likert version with multinomial and ordinal logistic models, varying specifications of continuous version responses (linear or spline) and covariate sets (question order, age, sex/gender, and interactions between the continuous version and covariates). We also implemented a percentiles-based crosswalk sensitivity analysis. We compared Cohen’s weighted kappa values to identify the best statistical harmonization approach.</div></div><div><h3>Results</h3><div>In the final models [multinomial models with continuous version spline, question order (self-rated memory model only), age, sex/gender, and interactions between the continuous version and covariates], weighted kappa values were 0.61 for self-rated health and 0.60 for self-rated memory, reflecting moderate agreement.</div></div><div><h3>Conclusions</h3><div>Primary data collection feasibly facilitates statistical harmonization of variables for constructs measured differently across studies.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"102 ","pages":"Pages 86-90"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142973142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conceptualizing patient-level adverse effects in implementation trials","authors":"Charles W. Goss ,&nbsp;Lindsey M. Filiatreau ,&nbsp;Lisa R. Hirschhorn ,&nbsp;Mark D. Huffman ,&nbsp;Aaloke Mody ,&nbsp;Byron J. Powell ,&nbsp;Emmanuel Tetteh ,&nbsp;Elvin H. Geng ,&nbsp;Mosepele Mosepele","doi":"10.1016/j.annepidem.2024.12.012","DOIUrl":"10.1016/j.annepidem.2024.12.012","url":null,"abstract":"<div><h3>Background</h3><div>Identifying and monitoring adverse effects (AEs) are integral to ensuring patient safety in clinical trials. Research sponsors and regulatory bodies have put into place a variety of policies and procedures to guide researchers in protecting patient safety during clinical trials. However, it remains unclear how these policies and procedures should be adapted for trials in implementation science. As a starting point, we develop a conceptual model that traces causal pathways leading from implementation strategies to AEs, propose a definition and classification of such effects, and provide recommendations for monitoring and oversight.</div></div><div><h3>Main text</h3><div>We propose four major types of adverse effects for implementation trials. First, we characterize implementation strategies that lead to “proper use” of an intervention that align with AEs as conceptualized and reported in clinical trials. Second, we characterize a strategy’s AEs mediated through “misuse” which involves inappropriate utilization of an evidence-based intervention (EBI). Third, we characterize a strategy which focuses on one EBI and may inadvertently cause the inappropriate discontinuation or “disuse” of other EBIs already in place, thus inducing AEs. Finally, we characterize strategies that may cause AEs by reducing the use of an EBI in the target population (i.e., “nonuse”). Based on these considerations, we propose an extended definition of adverse effects that includes harms that are causally related to implementation strategies, termed Implementation strategy Adverse Effects (IAEs). We recommend researchers, oversight committees, sponsors, and other stakeholders work together prior to trials to determine the best approaches for identifying, monitoring, and reporting IAEs.</div></div><div><h3>Conclusions</h3><div>In this paper, we develop a conceptual model to identify four types of AEs in implementation trials clarifying the mechanisms linking implementation strategies to patterns of use of the EBI and potential patient-level harms. We propose a new definition that links implementation strategies to AEs that can be used to guide conceptualization, monitoring, and oversight of potential harms in future implementation trials. Our work represents an important step towards understanding adverse effects in implementation trials and lays the groundwork for future advancement in the conceptualization of other types of adverse effects (e.g., harms to providers) encountered in implementation trials.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"102 ","pages":"Pages 55-61"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142900185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of ICD-10 diagnostic coding for influenza in the Danish National Patient Registry","authors":"Bo Langhoff Hønge ,&nbsp;Kristoffer Skaalum Hansen ,&nbsp;Marianne Kragh Thomsen ,&nbsp;Lars Østergaard ,&nbsp;Trine Hyrup Mogensen ,&nbsp;Merete Storgaard ,&nbsp;Christian Erikstrup ,&nbsp;Signe Sørup","doi":"10.1016/j.annepidem.2024.12.017","DOIUrl":"10.1016/j.annepidem.2024.12.017","url":null,"abstract":"<div><h3>Background</h3><div>The accuracy of recorded diagnosis codes for hospital admissions due to influenza in the Danish national registries is uncertain. We evaluated positive predictive value (PPV) and sensitivity of ICD-10 codes for influenza by comparing to the reference standard of influenza test results.</div></div><div><h3>Methods</h3><div>Hospital admissions were assessed in the Danish National Patient Registry (DNPR), and influenza test results in the Danish Microbiology Database (MiBa). First, we report the proportion of positive influenza virus tests within seven days of admission among hospital admissions with a discharge influenza ICD-10 code (PPV). Second, we report the proportion with ICD-10 codes for influenza among patients with an admission registered with seven days of a positive influenza virus test (sensitivity).</div></div><div><h3>Results</h3><div>From January 2012 – November 2022 a total of 18,761 admissions were registered with one of the 22 influenza ICD-10 codes in DNPR. Overall, there was a positive influenza test in 16,754 of the admissions (87.9 % = overall PPV, 95 % CI: 87.4–88.3). The PPV was highest for older patient groups (93.7 % in patients &gt;80 years vs. 78.0 % in patients &lt; 11 years), and for admissions that occurred in recent years (95.8 % in 2022 vs. 52.4 % in 2012). Among 33,834 hospitals admissions with a positive influenza test, less than half (n = 16,421, 48.5 % = sensitivity (95 % CI: 48.0 – 49.1 %)) were registered with an influenza ICD-10 code.</div></div><div><h3>Conclusions</h3><div>ICD-10 diagnoses codes have relatively high positive predictive value, but the sensitivity is low. Furthermore, the PPV depend on age and calendar year.</div></div><div><h3>What is new</h3><div><ul><li><span>•</span><span><div>Danish national registries have reasonable positive predictive value for influenza ICD-10 codes.</div></span></li></ul><ul><li><span>•</span><span><div>Positive predictive value varies with time of hospital admission and age of the patient.</div></span></li></ul></div><div><ul><li><span>•</span><span><div>Studies based on ICD-10 codes alone underestimates the number of patients with influenza due to low sensitivity.</div></span></li></ul></div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"102 ","pages":"Pages 62-67"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142967122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecologic study learning module: Gordon et al. (2023), Disparities in preterm birth following the July 1995 Chicago heat wave","authors":"Jeb Jones","doi":"10.1016/j.annepidem.2024.06.010","DOIUrl":"10.1016/j.annepidem.2024.06.010","url":null,"abstract":"<div><div>Educational Engagement Modules (EEMs) are teaching materials for educators and students that facilitate a deeper understanding of key epidemiological methods and concepts. Each EEM poses a series of questions using a recently published paper in <em>Annals of Epidemiology</em> to further understanding of a specific study design and to encourage critical thinking and careful evaluation. This EEM focuses on ecological study designs and references the following article: Gordon M, Casey JA, McBrien H, Gemmill A, Hernández D, Catalano R, Chakrabarti S, Bruckner T. Disparities in preterm birth following the July 1995 Chicago heat wave <span><span>[1]</span></span>.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"102 ","pages":"Pages 122-124"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143334228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cohort and co-sibling study learning module: Crump et al (2023), Preterm or early term birth and risk of attention-deficit/hyperactivity disorder","authors":"Jeb Jones","doi":"10.1016/j.annepidem.2024.06.004","DOIUrl":"10.1016/j.annepidem.2024.06.004","url":null,"abstract":"<div><div>Educational Engagement Modules (EEMs) are teaching materials for educators and students that facilitate a deeper understanding of key epidemiological methods and concepts. Each EEM poses a series of questions using a recently published paper in <em>Annals of Epidemiology</em> to further understanding of a specific study design and to encourage critical thinking and careful evaluation. This EEM focuses on sibling study designs and references the following article: Crump C, Sundquist J, Sundquist K. Preterm or early term birth and risk of attention-deficit/hyperactivity disorder: a national cohort and co-sibling study <span><span>[1]</span></span>.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"102 ","pages":"Pages 119-121"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143334227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations of pregnancy timing relative to the COVID-19 pandemic, maternal SARS-CoV-2 infection, and adverse perinatal outcomes","authors":"Maria Sevoyan ,&nbsp;Jihong Liu ,&nbsp;Yi-Wen Shih ,&nbsp;Peiyin Hung ,&nbsp;Jiajia Zhang ,&nbsp;Xiaoming Li","doi":"10.1016/j.annepidem.2025.01.006","DOIUrl":"10.1016/j.annepidem.2025.01.006","url":null,"abstract":"<div><h3>Purpose</h3><div>To examine associations between pregnancy timing relative to the COVID-19 pandemic, maternal SARS-CoV-2 infection, and perinatal outcomes.</div></div><div><h3>Methods</h3><div>We conducted a retrospective cohort study of 189,097 singleton births in South Carolina (2018–2021). Pregnancy timing relative to the pandemic was classified as pre-pandemic (delivered before March 1, 2020), partial pandemic overlap (conceived before and delivered during the pandemic), or pandemic (conceived and delivered during the pandemic). We examined COVID-19 testing, severity, and timing. Modified Poisson regression models with robust variance were used.</div></div><div><h3>Results</h3><div>Compared to the pre-pandemic group, the partial overlap group had lower risks of low birthweight (LBW) (aRR=0.93, 95 % CI 0.89–0.97) and preterm birth (PTB) (aRR=0.91, 95 % CI 0.88–0.95). The pandemic group had increased risks of LBW (aRR=1.10, 95 % CI 1.06–1.14), PTB (aRR=1.10, 95 % CI 1.07–1.14), and NICU admissions (aRR=1.13, 95 % CI 1.09–1.17) but a decreased risk of breastfeeding initiation (aRR=0.98, 95 % CI 0.97–0.98). Moderate-to-severe COVID-19 symptoms increased PTB (aRR=1.34, 95 % CI 1.13–1.58). Third-trimester COVID-19 infection increased LBW (aRR=1.23, 95 % CI 1.10–1.37), PTB (aRR=1.18, 95 % CI 1.07–1.30), and NICU admissions (aRR=1.17, 95 % CI 1.05–1.30).</div></div><div><h3>Conclusions</h3><div>Our findings highlight the importance of considering both maternal COVID-19 infection and pandemic-related factors in optimizing perinatal outcomes.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"102 ","pages":"Pages 94-101"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143029810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal cohort study learning module: Judson et al (2023), Association of protective behaviors with SARS-CoV-2 infection","authors":"Jeb Jones","doi":"10.1016/j.annepidem.2024.06.009","DOIUrl":"10.1016/j.annepidem.2024.06.009","url":null,"abstract":"<div><div>Educational Engagement Modules (EEMs) are teaching materials for educators and students that facilitate a deeper understanding of key epidemiological methods and concepts. Each EEM poses a series of questions using a recently published paper in Annals to further understanding of a specific study design and to encourage critical thinking and careful evaluation. This EEM focuses on observational cohort studies and references the following article: Judson TJ, Zhang S, Lindan CP, Boothroyd D, Grumbach K, Bollyky JB, Sample HA, Huang B, Desai M, Gonzales R, Maldonado Y, Rutherford G; TrackCOVID Consortium. Association of protective behaviors with SARS-CoV-2 infection: results from a longitudinal cohort study of adults in the San Francisco Bay Area <span><span>[1]</span></span>.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"102 ","pages":"Pages 116-118"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143334772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Suveillance Learning Module: Labgold et al. (2024), Population-based denominators matter: Bias in U.S. Virgin Islands COVID-19 vaccination coverage under changing population counts","authors":"Jeb Jones","doi":"10.1016/j.annepidem.2024.06.005","DOIUrl":"10.1016/j.annepidem.2024.06.005","url":null,"abstract":"<div><div>Educational Engagement Modules (EEMs) are teaching materials for educators and students that facilitate a deeper understanding of key epidemiological methods and concepts. Each EEM poses a series of questions using a recently published paper in <em>Annals of Epidemiology</em> to further understanding of a specific study design and to encourage critical thinking and careful evaluation. This EEM focuses on surveillance study designs and references the following article: Labgold K, Cranford HM, Ekpo LL, Mac VV, Roth J Jr, Stout M, Ellis EM. Population-based denominators matter: Bias in U.S. Virgin Islands COVID-19 vaccination coverage under changing population counts <span><span>[1]</span></span>.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"102 ","pages":"Pages 125-127"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143334229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}