Annals of Epidemiology最新文献

{"title":"Spatiotemporal trends of birth defects in North Carolina, 2003–2015","authors":"Haidong Lu ,&nbsp;Andrew F. Olshan ,&nbsp;Marc L. Serre ,&nbsp;Kurtis M. Anthony ,&nbsp;Rebecca C. Fry ,&nbsp;Nina E. Forestieri ,&nbsp;Alexander P. Keil","doi":"10.1016/j.annepidem.2026.01.012","DOIUrl":"10.1016/j.annepidem.2026.01.012","url":null,"abstract":"<div><div>Birth defects are a leading cause of infant mortality in the United States, but little is known about causes of many types of birth defects. Spatiotemporal disease mapping to identify high-prevalence areas is a potential strategy to narrow the search for potential environmental and other causes that aggregate over space and time. We described the spatial and temporal trends of the prevalence of birth defects in North Carolina during 2003–2015, using data on live births obtained from the North Carolina Birth Defects Monitoring Program. By employing a Bayesian space-time Poisson model, we estimated spatial and temporal trends of non-chromosomal and chromosomal birth defects. During 2003–2015, 52,524 (3.3 %) of 1598,807 live births had at least one recorded birth defect. The prevalence of non-chromosomal birth defects decreased from 3.8 % in 2003–2.9 % in 2015. Spatial modeling suggested a large geographic variation in non-chromosomal birth defects at census-tract level, with the highest prevalence in southeastern North Carolina. The strong spatial heterogeneity revealed in this work allowed us to identify geographic areas with higher prevalence of non-chromosomal birth defects in North Carolina. This variation will help inform future research focused on epidemiologic studies of birth defects to identify etiologic factors.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 85-90"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146208305","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":"Public health monitoring of diabetes in the era of electronic health records: Insights from the Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network","authors":"Angela D. Liese PhD, MPH ,&nbsp;Brian E. Dixon PhD ,&nbsp;Tessa Crume PhD,MSPH ,&nbsp;Jasmin Divers PhD ,&nbsp;Yi Guo PhD ,&nbsp;Annemarie G. Hirsch PhD, MPH ,&nbsp;Kristi Reynolds PhD ,&nbsp;Levon Utidjian MD ,&nbsp;Ibrahim Zaganjor PhD ,&nbsp;Marc Rosenman MD ,&nbsp;for the DiCAYA Study Group","doi":"10.1016/j.annepidem.2026.01.016","DOIUrl":"10.1016/j.annepidem.2026.01.016","url":null,"abstract":"<div><h3>Purpose</h3><div>A critical function of public health is to monitor diseases that impede quality of life and burden affected communities. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network aims to advance disease monitoring for diabetes using multi-site electronic health record (EHR) data.</div></div><div><h3>Methods</h3><div>This work involved validating and refining case definitions for accurate identification of type 1 and type 2 diabetes cases to estimate incidence and prevalence of diabetes in children, adolescents, and young adults through age 44 years.</div></div><div><h3>Results</h3><div>In this essay, we describe the challenges experienced by the Network and lessons learned. Challenges included accessing EHR data, harmonizing EHR data from heterogeneous health systems to a common data model, and developing methods to account for bias introduced by the non-representativeness of health care utilization data. Lessons learned included approaches for data quality assessment, bias correction, and scalability.</div></div><div><h3>Conclusions</h3><div>As the US continues to evolve its public health data systems and its approach to chronic disease monitoring, the DiCAYA Network offers guidance on factors for success as well as pitfalls to avoid.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 45-49"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146108212","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":"Effect of World Trade Center Health Program on mortality among 9/11 responders","authors":"Afroza Parvin ,&nbsp;Rebecca D. Kehm ,&nbsp;Baozhen Qiao ,&nbsp;James E. Cone ,&nbsp;Mark R. Farfel ,&nbsp;Rachel Zeig-Owens ,&nbsp;David G. Goldfarb ,&nbsp;Moshe Z. Shapiro ,&nbsp;Andrew C. Todd ,&nbsp;Tabassum Insaf ,&nbsp;Charles B. Hall ,&nbsp;Paolo Boffetta ,&nbsp;Jiehui Li","doi":"10.1016/j.annepidem.2026.01.014","DOIUrl":"10.1016/j.annepidem.2026.01.014","url":null,"abstract":"<div><h3>Purpose</h3><div>The World Trade Center Health Program (WTCHP) plays a critical role in medical monitoring and treatment to those exposed to the terrorist attacks of September 11, 2001 (9/11). We investigated the association of WTCHP membership with mortality risk among 9/11 responders while controlling for comorbidities using inverse probability weighting.</div></div><div><h3>Methods</h3><div>We prospectively analyzed 28,430 9/11 responders, followed from the time of their enrollment into the WTCHP or the WTC Health Registry, through 2020. NDI linkage provided death data. Non-cancer comorbidities were self-reported physician-diagnosis and cancer was identified through cancer registry linkage. We estimated the adjusted hazard ratio (aHR) with 95 % confidence interval (CI) for the association between WTCHP membership and all-cause and cause-specific mortality using Cox proportional hazards models and cause-specific hazard regression models, respectively.</div></div><div><h3>Results</h3><div>A total of 1657 deaths were identified over 444,425 person-years of follow-up. Compared to non-members, WTCHP members had a lower risk of all-cause mortality (aHR=0.87; 95 % CI=0.77–0.98) and smoking-related mortality (aHR=0.83; 0.69–0.99) after adjusting for demographics, WTC exposure, and weights of comorbidities. With the membership-sex interaction included, reduced risk of all-cause mortality remained statistically significant among males only (aHR=0.85; 0.75–0.96). Cancer- and heart-related mortality risk were not significantly different between WTCHP members and non-members.</div></div><div><h3>Conclusions</h3><div>This study found that WTCHP membership may reduce risks of all-cause and smoking-related mortality among 9/11 responders, even after accounting for underlying medical conditions, underscoring the importance of comprehensive health monitoring and treatment services for disaster-relief workers.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 8-14"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146097507","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":"Careless and inconsistent reporting inflates suicidality prevalence and biases sex differences","authors":"Romain Brisson","doi":"10.1016/j.annepidem.2026.01.013","DOIUrl":"10.1016/j.annepidem.2026.01.013","url":null,"abstract":"<div><h3>Purpose</h3><div>This study examined how careless and inconsistent reporting affects adolescent suicidality prevalence and sex differences, a methodological issue often overlooked in self-report epidemiological research.</div></div><div><h3>Methods</h3><div>I used data from two nationally representative surveys of secondary-school students conducted in 2010 (<em>n</em> = 7640; 49.3 % female) and 2014 (<em>n</em> = 5592; 52.6 % female). Both surveys assessed depressive symptoms, suicidal ideation, suicide plans, suicide attempts, attempt recognition, and attempt disclosure. Three methods of prevalence computation were used: unadjusted estimates (M1); excluding fictitious drug endorsers and treating inconsistencies as missing (M2); and excluding all careless and inconsistent reporters (M3).</div></div><div><h3>Results</h3><div>About 19 % of respondents were identified as careless or inconsistent. Compared to M1, M2 and M3 yielded lower prevalence estimates for most indicators. The largest reductions involved, on average, reports of unnoticed suicide attempts (-73.8 %), talking to no one about an attempt (-73.3 %), and reporting six or more suicide attempts (-35.9 %). Most sex differences were unaffected, except for the ‘six or more suicide attempts’ category and attempt recognition and disclosure items.</div></div><div><h3>Conclusions</h3><div>Overlooking misreporting may inflate adolescent suicidality prevalence and distort sex-difference estimates. Incorporating validity checks and data-cleaning procedures can improve the accuracy of epidemiological findings and the effectiveness of prevention programs.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 23-27"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146094875","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":"Epidemiology beyond averages: Reflections on civic responsibility and contextually structured individual heterogeneity","authors":"Juan Merlo","doi":"10.1016/j.annepidem.2026.01.010","DOIUrl":"10.1016/j.annepidem.2026.01.010","url":null,"abstract":"<div><div>Epidemiology has achieved substantial methodological refinement in recent decades, yet its social resonance has not always kept pace. This essay reflects on tendencies within influential sectors of the field toward methodological sophistication that, while yielding genuine intellectual advances, can unintentionally distance epidemiology from its civic and historical roots. By privileging what is analytically tractable, such developments may render broader contextual forces and socially patterned differences between individuals around population averages less visible. Drawing on traditions in social epidemiology, the essay advances a central argument: a substantial share of individual heterogeneity is intrinsically contextual. Differences between individuals are not pre-social deviations to be averaged away, but structured expressions of social, spatial, institutional, and historical contexts. From this perspective, the central challenge facing contemporary epidemiology is not primarily statistical but metaethical. It concerns how analytical choices shape interpretation, how values are embedded in measurement practices, and how these practices delimit the social purposes epidemiology is understood to serve. Crucially, epidemiology is not only a science of causal explanation, but also a discipline concerned with mapping, monitoring, and documenting how health and harm are distributed within populations over time. Even when major determinants of ill health are well established, epidemiology retains a core role in tracking how inequalities persist, change, or respond to policy. Rather than rejecting modern tools, the essay calls for a pluralistic and contextually grounded epidemiology that reconnects analytical rigor with social meaning. By treating individual heterogeneity as contextual rather than residual, epidemiology can reconcile population health and precision approaches and more fully realize its dual role as a scientific enterprise and a civic practice oriented toward equity.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 78-84"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146208294","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":"Midlife and late-life neighborhood socioeconomic status and cognitive function in later life: Differences by race","authors":"Greta Jianjia Cheng PhD ,&nbsp;Christina F. Mair PhD ,&nbsp;Jeanine M. Buchanich PhD ,&nbsp;Tiffany L. Gary-Webb PhD ,&nbsp;C. Elizabeth Shaaban PhD ,&nbsp;Andrea L. Rosso PhD","doi":"10.1016/j.annepidem.2026.01.017","DOIUrl":"10.1016/j.annepidem.2026.01.017","url":null,"abstract":"<div><h3>Purpose</h3><div>Evidence regarding neighborhood socioeconomic status (nSES) as an upstream determinant of cognitive outcomes has largely lacked a life-course perspective. We examined racial differences in the associations between midlife and late-life nSES and cognitive function in a cohort of 330 Black and White older Americans aged 70 + .</div></div><div><h3>Methods</h3><div>General cognitive function was measured using Modified Mini-Mental State Examination up to a 15-year follow-up. Midlife (age 49–58) and late-life (age 70–79) nSES scores were z-standardized based on five census indicators of tract-level socioeconomic characteristics. Mixed-effects linear regression examined the associations between midlife and late-life nSES and cognitive function.</div></div><div><h3>Results</h3><div>Higher midlife nSES was associated with higher baseline levels of cognitive function among Black (β: 3.10, 95 % CI: 0.85, 5.33), but not among White participants (β: 0.51, 95 % CI: −0.88, 1.90; p for interaction: 0.037). There were no observed associations between midlife nSES and changes in cognitive function in the overall sample or in either racial group. Late-life nSES was not associated with baseline levels of cognitive function or changes in the overall sample or either racial group.</div></div><div><h3>Conclusions</h3><div>Midlife may be a critical period in which neighborhood socioeconomic exposure has a greater impact on late-life cognitive health, particularly for Black individuals.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 50-56"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146108152","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":"Towards reliable feature interpretation in machine learning-based longevity prediction","authors":"Souichi Oka,&nbsp;Yoshiki Takahashi,&nbsp;Yoshiyasu Takefuji","doi":"10.1016/j.annepidem.2026.01.005","DOIUrl":"10.1016/j.annepidem.2026.01.005","url":null,"abstract":"","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 76-77"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145994713","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 considerations for sex inclusion in clinical studies","authors":"Nusrat Rabbee","doi":"10.1016/j.annepidem.2026.02.001","DOIUrl":"10.1016/j.annepidem.2026.02.001","url":null,"abstract":"<div><div>The NIH Office of Research on Women’s Health (ORWH) established the 4Cs framework—Consider, Collect, Characterize, Communicate—to promote the integration of Sex as a Biological Variable (SABV) in clinical research. Building on this foundation, we provide applied statistical guidance for implementing SABV across study design, analysis, and reporting. Using a simulated myocardial infarction example, we illustrate how sex-related bias can arise from omitted variables, underrepresentation, and unmodeled interactions. These methodological oversights can mask important sex-specific patterns in health outcomes and limit generalizability. While grounded in U.S. policy efforts, the statistical principles and approaches described are broadly applicable across epidemiologic research to improve scientific rigor and equity.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 64-73"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146133599","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":"Predicting nonresponse to sexual identity question in youth risk behavior surveillance: A machine learning analysis of complex survey data","authors":"Yu He MPH ,&nbsp;Chanapong Rojanaworarit PhD","doi":"10.1016/j.annepidem.2026.01.011","DOIUrl":"10.1016/j.annepidem.2026.01.011","url":null,"abstract":"<div><h3>Purpose</h3><div>To compare seven machine learning (ML) models developed to predict non-response to the sexual identity question in the 2023 Youth Risk Behavior Surveillance System (YRBSS) and identify the best-performing ML model, along with key attributes associated with the non-response.</div></div><div><h3>Methods</h3><div>Data of 20,103 students, with 32 predictors across domains of personal characteristics, school behavior, substance use, and sexual activity were analyzed. Supervised ML models–including random forest (RF), gradient boosting, extreme gradient boosting, decision tree, neural network, lasso, and elastic net were developed and incorporated survey weights. Performance was assessed using F1 score, area under the ROC curve (AUC), and area under the precision-recall curve (AUPRC).</div></div><div><h3>Results</h3><div>About 10 % of students didn’t respond to the sexual identity question, with higher rates among racial/ethnic minorities, including American Indian/Alaska Native and Native Hawaiian/Pacific Islander youths. RF model showed the most robust overall performance across all metrics. Attributes predicting non-response included response status to questions of school absence due to safety concerns and having ≥ 4 sexual partners.</div></div><div><h3>Conclusions</h3><div>Non-response was non-random and concentrated among vulnerable groups. Predictive performance was strong, but findings suggest that response patterns to other sensitive survey items play substantial role, with implications for survey design and non-response adjustment.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 37-44"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146100960","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":"The Abraham Lilienfeld Award of the American College of Epidemiology - From Paper to Pixels: The Digital Revolution in Women's Health Epidemiology, September 8, 2025","authors":"Michelle A. Williams ScD","doi":"10.1016/j.annepidem.2026.01.001","DOIUrl":"10.1016/j.annepidem.2026.01.001","url":null,"abstract":"","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"114 ","pages":"Pages 22-25"},"PeriodicalIF":3.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978003","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}