Annals of Epidemiology最新文献

Prenatal cannabis use disorder and postpartum psychiatric emergency department visits: A retrospective cohort study of trends and associations in California, 2016-2021. 产前大麻使用障碍和产后精神科急诊就诊：2016-2021年加州趋势和关联的回顾性队列研究

IF 3.6 3区医学

Annals of Epidemiology Pub Date : 2026-08-31 DOI: 10.1016/j.annepidem.2026.110271

LaMecia De Alba, Claire E Margerison, Alison Gemmill, Sidra Goldman-Mellor

{"title":"Prenatal cannabis use disorder and postpartum psychiatric emergency department visits: A retrospective cohort study of trends and associations in California, 2016-2021.","authors":"LaMecia De Alba, Claire E Margerison, Alison Gemmill, Sidra Goldman-Mellor","doi":"10.1016/j.annepidem.2026.110271","DOIUrl":"10.1016/j.annepidem.2026.110271","url":null,"abstract":"<p><strong>Purpose: </strong>Cannabis is the most-used substance during pregnancy and has known associations with psychiatric disorders (e.g., psychosis, depression). No prospective studies, however, have investigated associations between prenatal cannabis use disorder (CUD) and psychiatric outcomes in perinatal populations.</p><p><strong>Methods: </strong>Annual cohorts of women with a live infant delivery in California from 2016 to 2021 were constructed using statewide linked hospital and emergency department (ED) discharge data. We examined temporal trends in prenatal CUD prevalence and compared risk of postpartum psychiatric ED visits between delivering women with prenatal CUD, prenatal alcohol use disorder (AUD; included as a benchmark exposure), and neither disorder.</p><p><strong>Results: </strong>The study sample included 2,036,016 delivering women. Between 2016 and 2021, prenatal CUD prevalence increased 1.0-1.4%. Postpartum psychiatric ED visits occurred in 10.4% of women diagnosed with CUD, 15.6% with AUD, and 2.7% with neither diagnosis. Relative to women with neither, those with CUD had ∼40% higher risk of any postpartum psychiatric ED visit (RR<sub>adj</sub> = 1.39, 95% CI: 1.32-1.47), while AUD was associated with 80% increased risk (RR<sub>adj</sub> = 1.80, 95% CI: 1.56-2.09).</p><p><strong>Conclusion: </strong>Elevated risk of adverse psychiatric outcomes associated with CUD underscore the need for consistent screening, diagnosis, and treatment among perinatal women with CUD diagnoses.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"110271"},"PeriodicalIF":3.6,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867682","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}

引用次数: 0

Do quantitative bias analyses accurately characterize bias due to uncontrolled confounding? 定量偏倚分析是否准确地描述了由非受控混杂引起的偏倚？

IF 3.6 3区医学

Annals of Epidemiology Pub Date : 2026-08-31 DOI: 10.1016/j.annepidem.2026.110270

Tsion A Armidie, Lindsay J Collin, Richard F MacLehose, Thomas P Ahern, Timothy L Lash

{"title":"Do quantitative bias analyses accurately characterize bias due to uncontrolled confounding?","authors":"Tsion A Armidie, Lindsay J Collin, Richard F MacLehose, Thomas P Ahern, Timothy L Lash","doi":"10.1016/j.annepidem.2026.110270","DOIUrl":"10.1016/j.annepidem.2026.110270","url":null,"abstract":"<p><strong>Purpose: </strong>Adjustment for a sufficient set of confounders removes bias. When a confounder is unmeasured, approaches exist to estimate bias. Confounders are often correlated, so analyses that ignore correlations overstate bias.</p><p><strong>Methods: </strong>Using NHANES III, we examined the association between Healthy Eating Index (HEI) and all-cause mortality (n = 2417). A fully adjusted model included tobacco use, sex, age, hypertension, BMI, education, and physical activity. Hazard ratios (HR) that would have been observed-had one of hypertension, BMI, education, or physical activity been \"unmeasured\"-were estimated by leaving them out. We then performed bias analysis for the unmeasured confounders using uncorrelated bias parameter estimates.</p><p><strong>Results: </strong>The fully adjusted HR comparing HEI Quintile 1 vs. 5 was 1.72 (95% CI 1.24-2.40). After treating variables as \"unmeasured\" confounders, HRs changed little (range: 1.73-1.98). Bias-adjusted hazard ratios ranged from 1.72 to 1.98 suggesting that substantial unmeasured confounding would be required to explain the associations.</p><p><strong>Conclusions: </strong>Due to correlations between covariates, the additional bias attributable to unmeasured variables was minimal. QBA produced estimates that often overestimated the impact of the unmeasured confounders. Although QBA is useful for evaluating unmeasured confounding, it may not precisely quantify the strength of bias.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"110270"},"PeriodicalIF":3.6,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867685","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}

引用次数: 0

Polysubstance use and risk of infectious diseases: Evidence from a national cohort, 2018-2023. 多物质使用和传染病风险：来自国家队列的证据，2018-2023。

IF 3.6 3区医学

Annals of Epidemiology Pub Date : 2026-08-26 DOI: 10.1016/j.annepidem.2026.110266

Saadiah I Khan, Sijin Wen, Melanie Fisher, Toni M Rudisill, Ruchi Bhandari

{"title":"Polysubstance use and risk of infectious diseases: Evidence from a national cohort, 2018-2023.","authors":"Saadiah I Khan, Sijin Wen, Melanie Fisher, Toni M Rudisill, Ruchi Bhandari","doi":"10.1016/j.annepidem.2026.110266","DOIUrl":"10.1016/j.annepidem.2026.110266","url":null,"abstract":"<p><strong>Purpose: </strong>National surveillance data indicate increasing complexity in substance use patterns, with rising polysubstance use among United States (U.S.) adults. This study quantifies and compares subsequent infectious disease diagnoses, hospitalizations, and emergency department (ED) visits measured using International Classification of Diseases, 10th Revision codes (ICD-10 codes) among U.S. adults with prior single substance versus polysubstance use.</p><p><strong>Methods: </strong>A retrospective cohort study of 42,576 demographically and geographically diverse participants was conducted using 2018-2023 data from the All of Us Research Program (AoURP). This study evaluated the risk of infectious disease outcomes, (using ICD-10 codes) associated with single substance and polysubstance use among U.S. adults. Descriptive statistics and log-binomial regression models were used to estimate relative risks (RR), adjusting for demographic and socioeconomic confounders.</p><p><strong>Results: </strong>We analyzed 7480 individuals who reported infectious disease outcomes in their electronic health records (EHR). Individuals with polysubstance use had significantly higher risk of infectious disease compared to those who use single substance (Adjusted Relative Risk [ARR] = 4.48; 95% CI: 4.29-4.68, p < 0.001).</p><p><strong>Conclusions: </strong>This study offers evidence that the growing polysubstance use crises poses a serious public health threat of increased infectious disease risk, especially to the populations historically underrepresented in biomedical research.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"110266"},"PeriodicalIF":3.6,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148833554","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}

引用次数: 0

Declining gonorrhea case rates in the United States, 2021-2023: A spatial analysis. 美国淋病发病率下降，2021-2023：一个空间分析。

IF 3.6 3区医学

Annals of Epidemiology Pub Date : 2026-08-25 DOI: 10.1016/j.annepidem.2026.110268

Brittany Liebhard, David M Kline, Elizabeth A Torrone, William C Miller, Abigail Norris Turner

{"title":"Declining gonorrhea case rates in the United States, 2021-2023: A spatial analysis.","authors":"Brittany Liebhard, David M Kline, Elizabeth A Torrone, William C Miller, Abigail Norris Turner","doi":"10.1016/j.annepidem.2026.110268","DOIUrl":"10.1016/j.annepidem.2026.110268","url":null,"abstract":"<p><strong>Objective: </strong>To examine the spatial distribution of the decline in gonorrhea case rates in the contiguous United States between 2021 and 2023.</p><p><strong>Methods: </strong>Using surveillance data from the Centers for Disease Control and Prevention, we computed the percent change in county-level gonorrhea case rates between 2021 and 2023 for 3076 counties. We mapped and examined the spatial distribution of changes in gonorrhea case rates to describe substate trends.</p><p><strong>Results: </strong>Nearly three-quarters (74%) of all counties had greater than 10% declines in gonorrhea case rates between 2021 and 2023. Trajectories were similar in urban compared to rural areas. Despite widespread declines, several counties within the Northeast and South regions had increasing gonorrhea case rates. Some were densely populated and had high disease burden.</p><p><strong>Conclusions: </strong>Declines in county-level gonorrhea case rates were substantial between 2021 and 2023. But the identification of a few large metropolitan counties in the Northeast and South with elevated, and persistently increasing, case rates suggest the need for further epidemiological investigation.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"110268"},"PeriodicalIF":3.6,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148820204","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}

引用次数: 0

Evolution of characteristics and outcomes for patients hospitalized for COVID-19 during successive waves of the epidemic in France 法国连续几波疫情期间COVID-19住院患者特征和结果的演变

IF 3 3区医学

Annals of Epidemiology Pub Date : 2026-04-01 Epub Date: 2026-02-06 DOI: 10.1016/j.annepidem.2026.110053

Eric Ouattara MD, PhD , Aurelie Borde MSc , Maggie Le-Bourhis MD , Amelie Bruandet MD, PhD , Delphine Gabillard MSc, PhD , Fabienne Seguret MD, PhD , Florence Binder-Foucard MD , Joris Muller MD , Xavier Lenne MSc , Sophie Tezenas du Montcel MD, PhD , Pierre Tran Ba Loc MD , Veronique Gilleron MD, PhD

{"title":"Evolution of characteristics and outcomes for patients hospitalized for COVID-19 during successive waves of the epidemic in France","authors":"Eric Ouattara MD, PhD , Aurelie Borde MSc , Maggie Le-Bourhis MD , Amelie Bruandet MD, PhD , Delphine Gabillard MSc, PhD , Fabienne Seguret MD, PhD , Florence Binder-Foucard MD , Joris Muller MD , Xavier Lenne MSc , Sophie Tezenas du Montcel MD, PhD , Pierre Tran Ba Loc MD , Veronique Gilleron MD, PhD","doi":"10.1016/j.annepidem.2026.110053","DOIUrl":"10.1016/j.annepidem.2026.110053","url":null,"abstract":"<div><h3>Purpose</h3><div>To explore changes in in-hospital mortality, admission to critical care unit (CCU) and clinical characteristics of patients hospitalized for COVID-19 in France.</div></div><div><h3>Methods</h3><div>Hospital discharge data were used to analyse outcomes during epidemic waves: W1 (January-July 2020), W2 (August 2020-June 2021), W3 (July-October 2021),W4 (November 2021-May 2022), W5 (June-September 2022). Join-point, logistic and survival regressions were used for the analyses.</div></div><div><h3>Results</h3><div>Overall, 502,532 patients were included. W3 patients were younger (median age: 61 years; interquartile-range: 44–76) and fewer than 10 % had a Charlson Comorbidity Index ≥ 3. The proportion of patients aged ≥ 75 years old was higher (59 %) during W5. Compared to W1, W3 patients had a higher risk of admission to CCU, adjusted odds ratios ranged from 1.18 (CI: 1.09–1.28) for < 45 years old to 1.30 (1.17–1.34) for ≥ 75 years old. In CCU the risk of death decreased by 47 % during W2 in < 45 years old, increased by 11 % during W4 for 45–74 years old, and increased by 13 % and 10 % during W2 and W3 respectively, for ≥ 75 years old.</div></div><div><h3>Conclusion</h3><div>This analysis confirms the age as a major risk factor for adverse outcomes of COVID-19, and highlights the importance of hospital discharge data for future pandemics.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"116 ","pages":"Article 110053"},"PeriodicalIF":3.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146144661","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}

引用次数: 0

Suicide risks associated with cardiovascular disease in persons with alcohol use disorder 酒精使用障碍患者与心血管疾病相关的自杀风险

IF 3 3区医学

Annals of Epidemiology Pub Date : 2026-04-01 Epub Date: 2026-02-06 DOI: 10.1016/j.annepidem.2026.110052

Casey Crump , Jan Sundquist , Kristina Sundquist , Alexis C. Edwards

{"title":"Suicide risks associated with cardiovascular disease in persons with alcohol use disorder","authors":"Casey Crump , Jan Sundquist , Kristina Sundquist , Alexis C. Edwards","doi":"10.1016/j.annepidem.2026.110052","DOIUrl":"10.1016/j.annepidem.2026.110052","url":null,"abstract":"<div><h3>Purpose</h3><div>People with alcohol use disorder (AUD) have high risks of both cardiovascular disease (CVD) and suicide. We examined how CVD contributes to their long-term suicide risk in a large population-based cohort, which may help guide preventive interventions.</div></div><div><h3>Methods</h3><div>A national cohort study was conducted of all 537,802 people with AUD in Sweden during 1973–2017. CVD and suicide deaths were ascertained from nationwide records through 2018. Cox regression was used to determine hazard ratios (HRs) for suicide death associated with ischemic heart disease, stroke, heart failure, or atrial fibrillation, and a composite outcome (“any CVD”), adjusting for other mental disorders and sociodemographic factors.</div></div><div><h3>Results</h3><div>Any CVD was associated with a 1.4-fold risk of death by suicide (adjusted HR, 1.44; 95 % CI, 1.35–1.54). Adjusted HRs by specific comorbidities were: ischemic heart disease, 1.26 (95 % CI, 1.16–1.38); stroke, 1.45 (1.31–1.61); heart failure, 1.49 (1.31–1.69); and atrial fibrillation, 1.52 (1.36–1.70). These risks were similarly elevated in men and women.</div></div><div><h3>Conclusions</h3><div>In this large national cohort with AUD, CVD was associated with a ∼40 % higher risk of suicide death. Clinical care for persons with AUD should integrate mental health and prevention and treatment of CVD comorbidities to support their long-term health and survival.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"116 ","pages":"Article 110052"},"PeriodicalIF":3.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146144643","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}

引用次数: 0

Validity and Reliability learning module: Zubizarreta et al. (2025), Context matters: Validity and reliability of a sociopolitical concerns measure for use in population health research on discrimination and health 效度和可靠性学习模块：Zubizarreta等人（2025年），背景问题：用于人口健康歧视和健康研究的社会政治关切措施的效度和可靠性。

IF 3 3区医学

Annals of Epidemiology Pub Date : 2026-03-01 Epub Date: 2026-02-14 DOI: 10.1016/j.annepidem.2025.12.011

Jeb Jones

引用次数: 0

Is artificial intelligence a friend or foe to epidemiology? 人工智能是流行病学的朋友还是敌人？

IF 3 3区医学

Annals of Epidemiology Pub Date : 2026-03-01 Epub Date: 2026-01-12 DOI: 10.1016/j.annepidem.2026.01.003

Emaan Rashidi MHS , Madeline Brooks MPH , Ahmed Hassoon MD, MPH , Shruti Mehta PhD, MPH , Keri Althoff PhD, MPH , G. Caleb Alexander MD, MS

{"title":"Is artificial intelligence a friend or foe to epidemiology?","authors":"Emaan Rashidi MHS , Madeline Brooks MPH , Ahmed Hassoon MD, MPH , Shruti Mehta PhD, MPH , Keri Althoff PhD, MPH , G. Caleb Alexander MD, MS","doi":"10.1016/j.annepidem.2026.01.003","DOIUrl":"10.1016/j.annepidem.2026.01.003","url":null,"abstract":"<div><div>Epidemiology has long been central to public health, guiding our understanding of the distribution and determinants of disease. As the field has evolved—from John Snow’s cholera investigations to large-scale cohort studies and causal inference frameworks—it now faces a transformative juncture with the advent of artificial intelligence/machine learning (AI/ML). These technologies offer unprecedented opportunities to improve data measurement, inference, and population health insights, yet also pose methodological and ethical challenges. Anchored by the core epidemiologic domains of study population, measurement, and inference, we examine how epidemiologists can use AI/ML effectively. We consider the importance of careful population definition, informed sampling, and external validation to ensure generalizability and minimize bias when AI/ML is used. We also explore the need for rigorous assessment of data quality and model reliability, which strengthens the case for conceptual frameworks in guiding interpretation of scientific investigations. To realize AI/ML’s potential, epidemiology must adapt its training, invest in infrastructure, and promote interdisciplinary collaboration. Doing so will ensure that epidemiologic science remains robust, reproducible, and relevant in a rapidly evolving informational landscape. This moment calls for a strategic integration of AI/ML into the fabric of epidemiologic practice and training to advance both science and public health.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 2-7"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145985862","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}

引用次数: 0

Machine learning-based LASSO-Cox model for dementia prediction: The role of midlife cardiometabolic, inflammatory, and genetic risk factors in a US cohort 基于机器学习的LASSO-Cox模型预测痴呆：在美国队列中中年人心脏代谢、炎症和遗传风险因素的作用

IF 3 3区医学

Annals of Epidemiology Pub Date : 2026-03-01 Epub Date: 2026-01-23 DOI: 10.1016/j.annepidem.2026.01.007

Longjian Liu MD, PhD, MSc, Jintong Hou, PhD

{"title":"Machine learning-based LASSO-Cox model for dementia prediction: The role of midlife cardiometabolic, inflammatory, and genetic risk factors in a US cohort","authors":"Longjian Liu MD, PhD, MSc, Jintong Hou, PhD","doi":"10.1016/j.annepidem.2026.01.007","DOIUrl":"10.1016/j.annepidem.2026.01.007","url":null,"abstract":"<div><h3>Purpose</h3><div>We aimed to identify key midlife dementia predictors and develop a novel machine learning (ML) -enabled risk prediction model.</div></div><div><h3>Methods</h3><div>Using data from 9266 Atherosclerosis Risk in Communities study participants (aged 45–64 years at baseline, 1987–1989). Incident dementia was ascertained through December 2019. A ML-based LASSO-Cox model was applied to develop the risk prediction model.</div></div><div><h3>Results</h3><div>Over a 25-year mean follow-up, 2010 participants developed dementia. The LASSO-Cox model identified 12 key predictors and achieved C-indices (95 %CI) of 0.77 (0.75–0.79) in the training set (n = 6182) and 0.78 (0.76–0.81) in the test set (n = 3084). Predictors included age, Digit Symbol Substitution Test, apolipoprotein E ε4, HbA1c, brachial blood pressure, Factor VIII, Delayed Word Recall Test, hypertension, stroke history, C-reactive protein, white blood cell count, and apolipoprotein B. The resulting nomogram demonstrated strong discrimination (AUC 0.77–0.86) and good calibration. LASSO-Cox risk score quartiles effectively stratified participants into low, moderate, high, and very high dementia risk groups.</div></div><div><h3>Conclusions</h3><div>The findings demonstrate that the newly developed machine learning-based LASSO-Cox model provides a robust method to predict individuals at high risk of dementia.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 28-36"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146046999","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}

引用次数: 0

Response to “Towards reliable feature interpretation in machine learning-based longevity prediction” 对“基于机器学习的寿命预测中可靠的特征解释”的回应

IF 3 3区医学

Annals of Epidemiology Pub Date : 2026-03-01 Epub Date: 2026-01-14 DOI: 10.1016/j.annepidem.2026.01.006

Dor Atias MD, MPH, Saar Ashri Bsc, Uri Goldbourt PhD, Yariv Gerber PhD, Uri Obolski PhD

引用次数: 0