Annals of Epidemiology最新文献

{"title":"Misclassification of Opioid-involvement in Drug-related Overdose Deaths in the United States: A Scoping Review.","authors":"Sarah Gutkind, Megan E Marziali, Emilie Bruzelius, Zachary L Mannes, Silvia S Martins, Deborah S Hasin, Pia M Mauro","doi":"10.1016/j.annepidem.2024.12.010","DOIUrl":"https://doi.org/10.1016/j.annepidem.2024.12.010","url":null,"abstract":"<p><strong>Purpose: </strong>Most drug-related deaths in the United States (US) in 2022 involved opioids. However, methodological challenges in overdose surveillance may contribute to underestimation of opioid involvement in the overdose crisis. This scoping review aimed to synthesize existing literature to examine the breadth and contributing sources of misclassification of opioid-related overdose deaths.</p><p><strong>Methods: </strong>In October 2022, we searched PubMed, Web of Science, and Scopus for studies on overdose surveillance, death certificates, and medicolegal death investigation (MDI) systems in the US published in 2013-2022. Two reviewers independently screened abstracts, reviewed full-texts, and performed data extraction of study characteristics.</p><p><strong>Results: </strong>We identified 17 studies examining misclassification in drug-related deaths. Across studies, opioid involvement in drug-related deaths was underestimated nationally by 20-35%. Unspecified drug-related deaths differed by geographic areas and MDI systems and decreased over time. States/counties with coroner MDI systems were more likely to report unspecified overdose deaths than those with medical examiners. Integrating toxicology testing, death scene investigations, and other data with death certificates identified additional opioid-related overdose deaths, particularly those involving heroin.</p><p><strong>Conclusions: </strong>Findings highlight the need for additional resources for surveillance efforts, training for coroners, and data integration to improve reporting of opioid involvement in overdose deaths to inform interventions.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142883191","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":"Gut microbiome and obesity in late adolescence: a case-control study in \"Children of 1997\" birth cohort.","authors":"Baoting He, Sheng Xu, C Mary Schooling, Gabriel M Leung, Joshua W K Ho, Shiu Lun Au Yeung","doi":"10.1016/j.annepidem.2024.12.009","DOIUrl":"https://doi.org/10.1016/j.annepidem.2024.12.009","url":null,"abstract":"<p><strong>Purpose: </strong>Although the gut microbiome is important in human health, its relation to adolescent obesity remains unclear. Here we assessed the associations of the gut microbiome with adolescent obesity in a case-control study.</p><p><strong>Methods: </strong>In the \"Children of 1997\" birth cohort, participants with and without obesity at ~17.4 years were 1:1 matched on sex, physical activity, parental education and occupation (n=312). Fecal gut microbiome composition and pathways were assessed via shotgun metagenomic sequencing. The association of microbiota species with obesity was evaluated using conditional logistic regression. We explored the association of the obesity-relevant species with adolescent metabolomics using multivariable linear regression, and causal relationships with type 2 diabetes using Mendelian randomization analysis.</p><p><strong>Results: </strong>Gut microbiota in the adolescents with obesity exhibited lower richness (p=0.031) and evenness (p=0.014) compared to controls. Beta diversity revealed differences in the microbiome composition in two groups (p=0.034). Lower relative abundance of Clostridium spiroforme, Clostridium phoceensis and Bacteroides uniformis were associated with higher obesity risk (q<0.15). Lower Bacteroides uniformis was associated with higher branched-chain amino acid, potentially contributing to higher type 2 diabetes risk.</p><p><strong>Conclusion: </strong>Adolescents with obesity had a distinct gut microbiota profile compared to the controls, possibly linked to metabolic pertubation and related diseases.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142878469","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":"Gender differences in physical activity and sport participation in adults across 28 European countries between 2005 and 2022.","authors":"Katherine B Owen, Lucy Corbett, Ding Ding, Rochelle Eime, Adrian Bauman","doi":"10.1016/j.annepidem.2024.12.011","DOIUrl":"https://doi.org/10.1016/j.annepidem.2024.12.011","url":null,"abstract":"<p><strong>Objective: </strong>There is a lack of understanding of the specific types and intensities of physical activity driving the gender gap in overall levels of physical activity, and how these activities are changing over time. We examined the gender gap in specific types and intensities of physical activities in European adults from 2005-2022.</p><p><strong>Study design and methods: </strong>This repeated cross-sectional study included data from adults from the Eurobarometer (2005-2022) from 28 European countries. Gender differences in meeting physical activity guidelines, sport, walking, moderate, and vigorous activity were examined using prevalence ratios (PR, relative inequalities) and mean differences (MD, absolute differences).</p><p><strong>Results: </strong>Among 123,809 participants, there was no change in the gender gap in meeting physical activity guidelines from 2005 to 2022 (PR=1.10; 95% CIs 1.07, 1.14, PR=1.04; 95% CIs 1.01, 1.08, respectively). The gender gap in vigorous intensity activity decreased from 2005 to 2022 (MD=589; 95% CIs 545.7, 631.5, MD=399; 95% CIs 354.5, 444.3, respectively). The gender gap in moderate activity increased from 2005 to 2022 (MD=10.9; 95% CIs -14.2, 35.9, MD=104; 95% CIs 77.8, 130.1, respectively). The gender gap in sport and exercise increased from 2009 to 2022 (PR=1.14; 95% CIs 1.10, 1.19; PR=1.22; 95% CIs 1.17, 1.27, respectively). There was no gender gap in walking between 2005 and 2022 (MD=-1.4; 95% CIs -21.2, 18.4, MD=12.5; 95% CIs -4.9, 29.9, respectively).</p><p><strong>Conclusions: </strong>Sport remains an underutilized contributor to overall physical activity levels and could be promoted among women to reduce the overall gender gap in physical activity.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142878464","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":"National trends in drug overdose mortality among Asian American, Native Hawaiian, and Pacific Islander populations.","authors":"David T Zhu, Andrew Park","doi":"10.1016/j.annepidem.2024.12.005","DOIUrl":"10.1016/j.annepidem.2024.12.005","url":null,"abstract":"<p><strong>Purpose: </strong>To analyze drug overdose mortality trends among Asian American and Native Hawaiian/Pacific Islander (AANHPI) populations.</p><p><strong>Methods: </strong>We obtained data on drug overdose deaths and population totals from CDC WONDER and the American Community Survey (2018-2022). Crude mortality rates per 100,000 were calculated overall and by sex, U.S. Census Division, and drug type. Disaggregated analyses included six Asian American subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, and Vietnamese) and three NHPI subgroups (Native Hawaiian, Guamanian, and Samoan).</p><p><strong>Results: </strong>In 2022, Asian Americans had 1226 drug overdose deaths and NHPI individuals had 154. The mortality rate for NHPI individuals (17.52 [95 % CI: 14.76-20.29] per 100,000) tripled that of Asian Americans (5.85 [95 % CI: 5.52-6.18] per 100,000). Fentanyl was the leading drug-related death among Asian Americans (3.17 [95 % CI: 2.93-3.41] per 100,000), while methamphetamine led for NHPI individuals (11.38 [95 % CI: 9.15-13.61] per 100,000). Disaggregated mortality rates were highest for Korean Americans (9.06 [95 % CI: 8.88-9.24] per 100,000) and Guamanians (43.16 [95 % CI: 39.05-48.24] per 100,000) among the Asian American and NHPI subgroups, respectively.</p><p><strong>Conclusions: </strong>AANHPI populations experience distinct overdose mortality patterns, with NHPI individuals and specific ethnic subgroups disproportionately affected, warranting targeted public health interventions.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"36-41"},"PeriodicalIF":3.3,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873372","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 Misclassification of Depression and Anxiety Disorders in the Multiple Sclerosis Prodrome: A Probabilistic Bias Analysis.","authors":"Fardowsa L A Yusuf, Mohammad Ehsanul Karim, Paul Gustafson, Jason M Sutherland, Feng Zhu, Yinshan Zhao, Ruth Ann Marrie, Helen Tremlett","doi":"10.1016/j.annepidem.2024.12.006","DOIUrl":"https://doi.org/10.1016/j.annepidem.2024.12.006","url":null,"abstract":"<p><strong>Background: </strong>Studies suggest that depression/anxiety form part of the multiple sclerosis (MS) prodrome. However, several biases have not been addressed. We re-examined this association after correcting for: (i) misclassification of individuals not seeking healthcare, (ii) differential surveillance of depression/anxiety in the health system, and (iii) misclassified person-time from using the date of the first MS-related diagnostic claim (i.e., a demyelinating event) as a proxy for MS onset.</p><p><strong>Methods: </strong>In this cohort study, we applied a validated algorithm to health administrative ('claims') data in British Columbia, Canada (1991-2020) to identify MS cases, and matched to general population controls. The neurologist-recorded date of MS symptom onset was available for a subset of MS cases. We identified depression/anxiety in the 5-years preceding the first demyelinating claim using a validated algorithm. We compared the prevalence of depression/anxiety using modified Poisson regression. To account for misclassification and differential surveillance, we applied probabilistic bias analyses; for misclassified person-time, we applied time-distribution matching to the MS symptom onset date.</p><p><strong>Results: </strong>Our cohort included 9,929 MS cases and 49,574 controls. The prevalence ratio for depression/anxiety was 1.74 (95%CI: 1.66-1.81). Following correction for misclassification, differential surveillance using a detection ratio of 1.11, and misclassified person-time, the prevalence ratio increased to 3.25 (95%CI: 1.98-40.54). When the same correction was conducted, but a detection ratio of 1.16 was applied, the prevalence ratio increased to 3.13 (95%CI: 1.97-33.52).</p><p><strong>Conclusions: </strong>Previous conventional analyses were biased towards the null, leading to an under-estimation of the association between depression/anxiety and MS in the prodromal period. This first application of probabilistic quantitative bias analysis within MS research demonstrates both its feasibility and utility.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865880","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":"Considerations for using participatory systems modeling as a tool for implementation mapping in chronic disease prevention.","authors":"Travis R Moore, Erin Hennessy, Yuilyn Chang Chusan, Laura Ellen Ashcraft, Christina D Economos","doi":"10.1016/j.annepidem.2024.12.002","DOIUrl":"10.1016/j.annepidem.2024.12.002","url":null,"abstract":"<p><p>Effective chronic disease prevention requires a systems approach to the design, implementation, and refinement of interventions that account for the complexity and interdependence of factors influencing health outcomes. This paper proposes the Participatory Implementation Systems Mapping (PISM) process, which combines participatory systems modeling with implementation strategy development to enhance intervention design and implementation planning. PISM leverages the collaborative efforts of researchers and community partners to analyze complex health systems, identify key determinants, and develop tailored interventions and strategies that are both adaptive and contextually relevant. The phases of the PISM process include strategize, innovate, operationalize, and assess. We describe and demonstrate how each phase contributes to the overall goal of effective and sustainable intervention implementation. We also address the challenges of data availability, model complexity, and resource constraints. We offer solutions such as innovative data collection methods and participatory model development to enhance the robustness and applicability of systems models. Through a case study on the development of a chronic disease prevention intervention, the paper illustrates the practical application of PISM and highlights its potential to guide epidemiologists and implementation scientists in developing interventions that are responsive to the complexities of real-world health systems. The conclusion calls for further research to refine participatory systems modeling techniques, overcome existing challenges in data availability, and expand the use of PISM in diverse public health contexts.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"42-51"},"PeriodicalIF":3.3,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142840115","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":"A web-based tool for cancer risk prediction for middle-aged and elderly adults using machine learning algorithms and self-reported questions.","authors":"Xingjian Xiao, Xiaohan Yi, Nyi Nyi Soe, Phyu Mon Latt, Luotao Lin, Xuefen Chen, Hualing Song, Bo Sun, Hailei Zhao, Xianglong Xu","doi":"10.1016/j.annepidem.2024.12.003","DOIUrl":"10.1016/j.annepidem.2024.12.003","url":null,"abstract":"<p><strong>Background: </strong>From a global perspective, China is one of the countries with higher incidence and mortality rates for cancer.</p><p><strong>Objective: </strong>Our objective is to create an online cancer risk prediction tool for middle-aged and elderly Chinese adults by leveraging machine learning algorithms and self-reported data.</p><p><strong>Method: </strong>Drawing from a cohort of 19,798 participants aged 45 and above from the China Health and Retirement Longitudinal Study (2011 - 2018), we employed nine machine learning algorithms (LR: Logistic Regression, Adaboost: Adaptive Boosting, SVM: Support Vector Machine, RF: Random Forest, GNB: Gaussian Naive Bayes, GBM: Gradient Boosting Machine, LGBM: Light Gradient Boosting Machine, XGBoost: eXtreme Gradient Boosting, KNN: K - Nearest Neighbors), which are mainly used for classification and regression tasks, to construct predictive models for various cancers. Utilizing non-invasive self-reported predictors encompassing demographic, educational, marital, lifestyle, health history, and other factors, we focused on predicting \"Cancer or Malignant Tumour\" outcomes. The types of cancers that can be predicted mainly include lung cancer, breast cancer, cervical cancer, colorectal cancer, gastric cancer, esophageal cancer, and other rare cancers.</p><p><strong>Results: </strong>The developed tool, MyCancerRisk, demonstrated significant performance, with the Random Forest algorithm achieving an AUC of 0.75 and ACC of 0.99 using self-reported variables. Key predictors identified include age, self-rated health, sleep patterns, household heating sources, childhood health status, living conditions, and smoking habits.</p><p><strong>Conclusion: </strong>MyCancerRisk aims to serve as a preventative screening tool, encouraging individuals to undergo testing and adopt healthier behaviours to mitigate the public health impact of cancer. Our study also sheds light on unconventional predictors, such as housing conditions, offering valuable insights for refining cancer prediction models.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"27-35"},"PeriodicalIF":3.3,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142830711","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":"An exploration of potential risk factors for gastroschisis using decision tree learning.","authors":"Julie M Petersen, Jaimie L Gradus, Martha M Werler, Samantha E Parker","doi":"10.1016/j.annepidem.2024.12.004","DOIUrl":"10.1016/j.annepidem.2024.12.004","url":null,"abstract":"<p><strong>Purpose: </strong>Despite a wealth of research, the etiology of the abdominal wall defect gastroschisis remains largely unknown. The strongest known risk factor is young maternal age. Our objective was to conduct a hypothesis-generating analysis regarding gastroschisis etiology using random forests.</p><p><strong>Methods: </strong>Data were from the Slone Birth Defects Study (case-control, United States and Canada, 1998-2015). Cases were gastroschisis-affected pregnancies (n = 273); controls were live-born infants, frequency-matched by center (n = 2591). Potential risk factor data were ascertained via standardized interviews. We calculated adjusted odds ratios (aOR) and 95 % confidence intervals (CIs) using targeted maximum likelihood estimation.</p><p><strong>Results: </strong>The strongest associations were observed with young maternal age (aOR 3.4, 95 % CI 2.9, 4.0) and prepregnancy body-mass-index < 30 kg/m² (aOR 3.3, 95 % CI 2.4, 4.5). More moderate increased odds were observed for parents not in a relationship, non-Black maternal race, young paternal age, marijuana use, cigarette smoking, alcohol intake, lower parity, oral contraceptive use, nonsteroidal anti-inflammatory drug use, daily fast food/processed foods intake, lower poly- or monounsaturated fat, higher total fat, and lower parental education.</p><p><strong>Conclusions: </strong>Our research provides support for established risk factors and suggested novel factors (e.g., certain aspects of diet), which warrant further investigation.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"19-26"},"PeriodicalIF":3.3,"publicationDate":"2024-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142808596","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 impact of COVID-19 on breast cancer mortality trends in Brazil: A time-series study.","authors":"Adriano Hyeda, Élide Sbardellotto Mariano da Costa, Sérgio Cândido Kowalski","doi":"10.1016/j.annepidem.2024.12.001","DOIUrl":"10.1016/j.annepidem.2024.12.001","url":null,"abstract":"<p><strong>Background: </strong>There is a lack of research on whether COVID-19 disruptions in breast cancer screening, diagnosis, and treatment affected mortality rates over time.</p><p><strong>Method: </strong>This ecological time series study, covering the period between 2013 and 2023, utilizes the inflection point regression model and calculates the Annual Percentage Change (APC). The study used open-access data from the Brazilian Mortality Information System. The dependent variables measured were mortality rates due to breast cancer as an underlying cause and contributing cause in women aged 20 and over. The double exponential smoothing method was applied to predict mortality rates for 2020-2023.</p><p><strong>Results: </strong>During the study period, the mortality rate due to breast cancer as a contributing cause increased approximately tenfold compared to mortality as an underlying cause (APC 6.9 % vs. 0.7 %). On average, 12 % of breast cancer-related deaths were attributed to the disease as a contributing cause. Breast cancer deaths as an underlying cause declined in 2020 and 2021, remaining below the 95 % predicted interval (95 % PI), but showed recovery until 2023. Mortality due to breast cancer as a contributing cause increased early in the pandemic, with deaths related to COVID-19 as an underlying cause comprising 39.6 % of cases in 2021. Breast cancer-related deaths, both as an underlying and contributing cause, showed an upward trend until 2021 and remained within the 95 % PI until 2023.</p><p><strong>Conclusion: </strong>During the pandemic, deaths due to breast cancer as an underlying cause decreased while contributing deaths increased, with total mortality remaining within the predicted range.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"7-13"},"PeriodicalIF":3.3,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792722","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":"Gender diversity and daily steps: Findings from the Adolescent Brain Cognitive Development Study.","authors":"Jason M Nagata, Shirley Sui, Angela E Kim, Iris Yuefan Shao, Christopher D Otmar, Kyle T Ganson, Alexander Testa, Erin E Dooley, Holly C Gooding, Fiona C Baker, Kelley Pettee Gabriel","doi":"10.1016/j.annepidem.2024.11.004","DOIUrl":"10.1016/j.annepidem.2024.11.004","url":null,"abstract":"<p><strong>Purpose: </strong>To examine the association between multiple dimensions of gender diversity and physical activity (daily steps) in a diverse national sample of early adolescents in the United States.</p><p><strong>Methods: </strong>This study analyzed Year 2 data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 6038, M_age=12.0 years). Linear regression models were used to estimate the associations of gender diversity across multiple measures (transgender identity, felt gender, gender expression, gender non-contentedness) with daily step count measured by wrist-worn Fitbit devices.</p><p><strong>Results: </strong>In this sample of early adolescents, 49.7 % were assigned female at birth, 39.4 % were from racial/ethnic minority groups, and 1 % to 16.9 % identified as gender diverse, depending on the measure used. Transgender identity was associated with 1394 (95 % confidence interval 284-2504) fewer steps per day compared to cisgender identity after adjusting for all covariates. Greater gender diversity, as measured by felt gender and gender non-contentedness, was also associated with lower daily steps.</p><p><strong>Conclusions: </strong>Transgender and gender-diverse adolescents engage in less physical activity than their cisgender peers. This research has important implications for public health and policies focused on supporting physical activity among transgender and gender-diverse early adolescents.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"1-6"},"PeriodicalIF":3.3,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142787656","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}