Pub Date : 2026-01-13DOI: 10.1016/j.annepidem.2026.01.004
Peter M. Socha , Maryam Oskoui , Jennifer A. Hutcheon , Sam Harper
Purpose
To improve the identification of cerebral palsy cases in administrative health data.
Methods
We included all children in a population-based cerebral palsy registry in Quebec, Canada, born from 1999 through 2002, and a sample of children without cerebral palsy. Population-based hospitalization and physician billing records through 2012 were obtained for all children. We used logistic regression to model the probability of cerebral palsy, using International Classification of Diseases codes for related diseases. We reported receiver operating characteristic (ROC) and precision-recall (PR) curves, and compared the accuracy to that of existing algorithms. We also reported the accuracy of cerebral palsy codes by age, data source, and gestational age at birth.
Results
The area under the ROC and PR curves of our model were 0.98 (95 % CI: 0.97–0.99) and 0.73 (95 % CI: 0.63–0.79), respectively. Cut-offs with a similar specificity to existing algorithms yielded sensitivities that were 1–14 %age-points higher. The sensitivity of cerebral palsy codes was higher (and the specificity was lower) with longer follow-up times since birth, when using both hospitalization and billing records, and among children born preterm.
Conclusions
Our model improved identification of cerebral palsy cases in administrative data, but residual misclassification remained.
{"title":"A multivariable model for improving the identification of cerebral palsy cases in administrative health data","authors":"Peter M. Socha , Maryam Oskoui , Jennifer A. Hutcheon , Sam Harper","doi":"10.1016/j.annepidem.2026.01.004","DOIUrl":"10.1016/j.annepidem.2026.01.004","url":null,"abstract":"<div><h3>Purpose</h3><div>To improve the identification of cerebral palsy cases in administrative health data.</div></div><div><h3>Methods</h3><div>We included all children in a population-based cerebral palsy registry in Quebec, Canada, born from 1999 through 2002, and a sample of children without cerebral palsy. Population-based hospitalization and physician billing records through 2012 were obtained for all children. We used logistic regression to model the probability of cerebral palsy, using International Classification of Diseases codes for related diseases. We reported receiver operating characteristic (ROC) and precision-recall (PR) curves, and compared the accuracy to that of existing algorithms. We also reported the accuracy of cerebral palsy codes by age, data source, and gestational age at birth.</div></div><div><h3>Results</h3><div>The area under the ROC and PR curves of our model were 0.98 (95 % CI: 0.97–0.99) and 0.73 (95 % CI: 0.63–0.79), respectively. Cut-offs with a similar specificity to existing algorithms yielded sensitivities that were 1–14 %age-points higher. The sensitivity of cerebral palsy codes was higher (and the specificity was lower) with longer follow-up times since birth, when using both hospitalization and billing records, and among children born preterm.</div></div><div><h3>Conclusions</h3><div>Our model improved identification of cerebral palsy cases in administrative data, but residual misclassification remained.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"114 ","pages":"Pages 26-31"},"PeriodicalIF":3.0,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978004","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}
Pub Date : 2026-01-12DOI: 10.1016/j.annepidem.2026.01.003
Emaan Rashidi, Madeline Brooks, Ahmed Hassoon, Shruti Mehta, Keri Althoff, G Caleb Alexander
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.
{"title":"is Artificial Intelligence a friend or foe to epidemiology?","authors":"Emaan Rashidi, Madeline Brooks, Ahmed Hassoon, Shruti Mehta, Keri Althoff, G Caleb Alexander","doi":"10.1016/j.annepidem.2026.01.003","DOIUrl":"https://doi.org/10.1016/j.annepidem.2026.01.003","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-01-12","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}
Pub Date : 2026-01-07DOI: 10.1016/j.annepidem.2026.01.002
Omobola O. Oluwafemi , Laura E. Mitchell , Jenil R. Patel , Wendy N. Nembhard , Gary M. Shaw , Andrew F. Olshan , Han Chen , A.J. Agopian
Purpose
To estimate associations between paternal race and ethnicity and a spectrum of birth defects.
Methods
We analyzed data from the National Birth Defects Prevention Study for infants with birth defects and controls delivered between 1997–2011. Using unconditional logistic regression, we assessed associations between paternal race and ethnicity and 32 birth defects, before and after adjusting for maternal race and ethnicity and 14 other factors.
Results
Data from 33,455 fathers were analyzed (889 Asian/Pacific Islander [A/PI], 8394 Hispanic, 4139 non-Hispanic Black [NHB], and 20,033 non-Hispanic White [NHW]). Compared with NHW fathers, A/PI paternal race and ethnicity was significantly associated with 6/32 defects, Hispanic paternal ethnicity with 6/32 defects, and NHB paternal race and ethnicity with 7/32 defects, after adjustment. The strongest associations included A/PI and pulmonary valve stenosis (adjusted odds ratio [aOR] 0.36, 95 % CI 0.18–0.71), Hispanic and heterotaxy (aOR 2.53, 95 % CI 1.57–4.06), and NHB and gastroschisis (aOR 2.25, 95 % CI 1.62–3.12).
Conclusions
Paternal race and ethnicity were associated with heterotaxy, cleft lip with or without cleft palate, and spina bifida, independent of maternal race and ethnicity. These findings warrant replication and further investigation into biological, environmental, and social mechanisms that may underlie these associations.
目的：估计父亲种族和民族与出生缺陷谱之间的关系。方法：我们分析了1997-2011年出生缺陷和对照婴儿的国家出生缺陷预防研究数据。使用无条件逻辑回归，我们评估了父亲种族和民族与32个出生缺陷之间的关系，在调整母亲种族和民族以及14个其他因素之前和之后。结果：分析了33,455名父亲的数据（889名亚洲/太平洋岛民[A/PI]， 8,394名西班牙裔，4,139名非西班牙裔黑人[NHB]和20,033名非西班牙裔白人[NHW]）。与NHW父亲比较，A/PI父亲种族与6/32缺陷显著相关，西班牙裔父亲种族与6/32缺陷显著相关，NHB父亲种族与7/32缺陷显著相关。最强的相关性包括A/PI和肺动脉瓣狭窄（校正优势比[aOR] 0.36, 95% CI 0.18-0.71），西班牙裔和异位（aOR 2.53, 95% CI 1.57-4.06），以及NHB和胃裂（aOR 2.25, 95% CI 1.62-3.12）。结论：父亲的种族和民族与异位、唇裂伴或不伴腭裂、脊柱裂相关，与母亲的种族和民族无关。这些发现值得重复，并进一步研究这些关联背后的生物、环境和社会机制。
{"title":"The association between paternal race and ethnicity and a spectrum of birth defects in a national case-control study","authors":"Omobola O. Oluwafemi , Laura E. Mitchell , Jenil R. Patel , Wendy N. Nembhard , Gary M. Shaw , Andrew F. Olshan , Han Chen , A.J. Agopian","doi":"10.1016/j.annepidem.2026.01.002","DOIUrl":"10.1016/j.annepidem.2026.01.002","url":null,"abstract":"<div><h3>Purpose</h3><div>To estimate associations between paternal race and ethnicity and a spectrum of birth defects.</div></div><div><h3>Methods</h3><div>We analyzed data from the National Birth Defects Prevention Study for infants with birth defects and controls delivered between 1997–2011. Using unconditional logistic regression, we assessed associations between paternal race and ethnicity and 32 birth defects, before and after adjusting for maternal race and ethnicity and 14 other factors.</div></div><div><h3>Results</h3><div>Data from 33,455 fathers were analyzed (889 Asian/Pacific Islander [A/PI], 8394 Hispanic, 4139 non-Hispanic Black [NHB], and 20,033 non-Hispanic White [NHW]). Compared with NHW fathers, A/PI paternal race and ethnicity was significantly associated with 6/32 defects, Hispanic paternal ethnicity with 6/32 defects, and NHB paternal race and ethnicity with 7/32 defects, after adjustment. The strongest associations included A/PI and pulmonary valve stenosis (adjusted odds ratio [aOR] 0.36, 95 % CI 0.18–0.71), Hispanic and heterotaxy (aOR 2.53, 95 % CI 1.57–4.06), and NHB and gastroschisis (aOR 2.25, 95 % CI 1.62–3.12).</div></div><div><h3>Conclusions</h3><div>Paternal race and ethnicity were associated with heterotaxy, cleft lip with or without cleft palate, and spina bifida, independent of maternal race and ethnicity. These findings warrant replication and further investigation into biological, environmental, and social mechanisms that may underlie these associations.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"114 ","pages":"Pages 12-21"},"PeriodicalIF":3.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145946494","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}
Pub Date : 2026-01-06DOI: 10.1016/j.annepidem.2026.01.001
Michelle A. Williams ScD
{"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":"2026-01-06","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}
Pub Date : 2026-01-01DOI: 10.1016/j.annepidem.2025.10.021
Jeb Jones PhD, MPH, MS
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 the use of mediation in a study exploring whether breast density mediates the relationship between early life characteristics and postmenopausal breast cancer: Pedersen DC, Hameiri-Bowen D, Aarestrup J, Jensen BW, Tjønneland A, Mellemkjær L, von Euler-Chelpin M, Vejborg I, Andersen ZJ, Baker JL. Associations of early life body size and pubertal timing with breast density and postmenopausal breast cancer risk: A mediation analysis. Ann Epidemiol. 2025 Feb;102:68–74. doi: 10.1016/j.annepidem.2025.01.004. Epub 2025 Jan 10. PMID: 39798680 [1].
教育参与模块（EEMs）是为教育工作者和学生提供的教材，有助于更深入地理解关键的流行病学方法和概念。每个EEM提出一系列问题，使用最近发表在《年鉴》上的一篇论文，以进一步理解特定的研究设计，并鼓励批判性思维和仔细评估。乳腺密度是否在早期生活特征与绝经后乳腺癌之间起中介作用的研究：Pedersen DC， Hameiri-Bowen D, Aarestrup J, Jensen BW, Tjønneland a, Mellemkjær L, von Euler-Chelpin M, Vejborg I, Andersen ZJ, Baker JL。早期生活体型和青春期时间与乳腺密度和绝经后乳腺癌风险的关联：一个中介分析。流行病学杂志。2025;102:68-74。doi: 10.1016 / j.annepidem.2025.01.004。Epub 2025年1月10日中国经济：39798680[1]。
{"title":"Mediation learning module: Pedersen et al (2025), Associations of early life body size and pubertal timing with breast density and postmenopausal breast cancer risk: A mediation analysis","authors":"Jeb Jones PhD, MPH, MS","doi":"10.1016/j.annepidem.2025.10.021","DOIUrl":"10.1016/j.annepidem.2025.10.021","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 the use of mediation in a study exploring whether breast density mediates the relationship between early life characteristics and postmenopausal breast cancer: Pedersen DC, Hameiri-Bowen D, Aarestrup J, Jensen BW, Tjønneland A, Mellemkjær L, von Euler-Chelpin M, Vejborg I, Andersen ZJ, Baker JL. Associations of early life body size and pubertal timing with breast density and postmenopausal breast cancer risk: A mediation analysis. Ann Epidemiol. 2025 Feb;102:68–74. doi: 10.1016/j.annepidem.2025.01.004. Epub 2025 Jan 10. PMID: 39798680 <span><span>[1]</span></span>.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"113 ","pages":"Pages 86-88"},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938917","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}
Pub Date : 2025-12-23DOI: 10.1016/j.annepidem.2025.12.010
Kaitlyn Stanhope PhD , Quiana Lewis PhD, MPH , Laura Brugger PhD , Leah Hamilton PhD, MSW , Stephen Roll PhD , Latrice Rollins PhD, MSW , Naomi Zewde PhD
Objective
To estimate differences in mental distress, sleep quality, and sleep duration following twelve and twenty-four months of receipt of guaranteed income (GI) between program participants and a comparison group.
Methods
We conducted a community-engaged intervention study (In Her Hands) between 2022 and 2024 in Georgia, United States. Participants included self-identified Black women with income ≤ 200 % of the federal poverty level who participated in follow-up surveys (12-month participation rates: intervention: 40.8 %; control: 11.9 %). GI recipients were selected via lottery; comparison participants were those not selected at baseline who completed follow-up surveys. We measured mental distress using the Kessler-10 and sleep quality and duration via the Pittsburgh Sleep Quality Index at 12- and 24-months following enrollment. We fit linear regression models using generalized estimating equations, accounting for site, age, and wave to estimate differences and 95 % confidence intervals.
Results
We include 468 GI recipients and 374 controls (99.93 % Black; mean age 37.0 years, median annual income: $11,400). Following 12 and 24 months of GI receipt, GI recipients reported better sleep quality (24 month difference in PSQI score, −1.33 (-1.83, −0.82)) and lower mental distress (24 month K10 difference: −3.99 (-5.45, −2.52)) but not significant differences in sleep duration (24 month difference: 0.22 (-0.15, 0.60) compared to non-recipients.
Conclusions
At 12 and 24 months of GI, intervention participants reported higher sleep quality and lower mental distress compared to a comparison group.
目的：评估项目参与者和对照组在获得保证收入（GI） 12个月和24个月后的精神痛苦、睡眠质量和睡眠时间的差异。方法：我们于2022-2024年间在美国乔治亚州进行了一项社区参与的干预研究（In Her Hands）。参与者包括收入≤联邦贫困水平200%的自我认定的黑人妇女，她们参加了随访调查（12个月参与率：干预：40.8%；对照组：11.9%）。GI受助人以抽签方式选出；比较参与者是那些在基线时未被选中完成随访调查的人。在入组后的12个月和24个月，我们用凯斯勒-10量表测量了精神压力，用匹兹堡睡眠质量指数测量了睡眠质量和持续时间。我们使用广义估计方程拟合线性回归模型，考虑到地点、年龄和波浪来估计差异和95%置信区间。结果：我们纳入了468名GI受者和374名对照组（99.93%为黑人；平均年龄37.0岁，年收入中位数：11,400美元）。在接受GI治疗12个月和24个月后，GI接受者报告睡眠质量更好（PSQI评分24个月差异，-1.33(-1.83,-0.82)），精神压力更低（24个月K10差异：-3.99(-5.45,-2.52)），但睡眠时间差异不显著（24个月差异：0.22(-0.15,0.60)）。结论：在GI的12个月和24个月，与对照组相比，干预参与者报告了更高的睡眠质量和更低的精神困扰。
{"title":"Improvements in stress and sleep following 24-months of Guaranteed Income, results from a randomized trial among Black women in Georgia","authors":"Kaitlyn Stanhope PhD , Quiana Lewis PhD, MPH , Laura Brugger PhD , Leah Hamilton PhD, MSW , Stephen Roll PhD , Latrice Rollins PhD, MSW , Naomi Zewde PhD","doi":"10.1016/j.annepidem.2025.12.010","DOIUrl":"10.1016/j.annepidem.2025.12.010","url":null,"abstract":"<div><h3>Objective</h3><div>To estimate differences in mental distress, sleep quality, and sleep duration following twelve and twenty-four months of receipt of guaranteed income (GI) between program participants and a comparison group.</div></div><div><h3>Methods</h3><div>We conducted a community-engaged intervention study (In Her Hands) between 2022 and 2024 in Georgia, United States. Participants included self-identified Black women with income ≤ 200 % of the federal poverty level who participated in follow-up surveys (12-month participation rates: intervention: 40.8 %; control: 11.9 %). GI recipients were selected via lottery; comparison participants were those not selected at baseline who completed follow-up surveys. We measured mental distress using the Kessler-10 and sleep quality and duration via the Pittsburgh Sleep Quality Index at 12- and 24-months following enrollment. We fit linear regression models using generalized estimating equations, accounting for site, age, and wave to estimate differences and 95 % confidence intervals.</div></div><div><h3>Results</h3><div>We include 468 GI recipients and 374 controls (99.93 % Black; mean age 37.0 years, median annual income: $11,400). Following 12 and 24 months of GI receipt, GI recipients reported better sleep quality (24 month difference in PSQI score, −1.33 (-1.83, −0.82)) and lower mental distress (24 month K10 difference: −3.99 (-5.45, −2.52)) but not significant differences in sleep duration (24 month difference: 0.22 (-0.15, 0.60) compared to non-recipients.</div></div><div><h3>Conclusions</h3><div>At 12 and 24 months of GI, intervention participants reported higher sleep quality and lower mental distress compared to a comparison group.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"114 ","pages":"Pages 1-6"},"PeriodicalIF":3.0,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145834976","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}
Pub Date : 2025-12-19DOI: 10.1016/j.annepidem.2025.12.008
Ingvild M. Rosenlund MD, PhD , Ellisiv B. Mathiesen Professor, MD, PhD , Unni Ringberg MD, PhD , Liv-Hege Johnsen MD, PhD , Tom Wilsgaard Professor, PhD , Jørgen Isaksen MD, PhD , Tor Ingebrigtsen Professor, MD, PhD
Purpose
Widespread use of diagnostic testing in asymptomatic individuals raises ethical concerns. We aimed to investigate whether participation in an extensive health examination survey is associated with psychosocial outcomes, healthcare use, and mortality.
Methods
This longitudinal matched cohort study included 461 participants who underwent comprehensive screening examinations as part of the population-based Tromsø7 Study, including electrocardiogram, carotid artery ultrasound, echocardiography, brain magnetic resonance imaging, and spirometry. Age- and sex-matched controls (n = 461) were drawn from Tromsø7 participants who only underwent limited basic measurements. Health-related quality of life, psychological distress, and health anxiety were assessed at baseline and after 5 years. Data on healthcare utilization and mortality were obtained from national registries.
Results
No significant differences were found in psychosocial outcomes. Healthcare use was largely similar, although screening participants had slightly fewer hospital admissions, 0.23 vs. 0.31 per person-year (95 % CI 0.19, 0.28 vs. 0.25, 0.38). Screening participants also had lower, but non-significant, risk of death compared with controls, hazard ratio 0.69 (95 % CI 0.47, 1.01).
Conclusion
Extensive health examination survey screening was not associated with psychosocial harms, healthcare use or statistically significant differences in mortality. Overall, the findings suggest that participation in such screening is safe.
目的：在无症状个体中广泛使用诊断测试引起了伦理问题。我们的目的是调查参与广泛的健康检查调查是否与心理社会结局、医疗保健使用和死亡率有关。方法：这项纵向匹配队列研究纳入了461名参与者，作为基于人群的Tromsø7研究的一部分，他们接受了全面的筛查检查，包括心电图、颈动脉超声、超声心动图、脑磁共振成像和肺活量测定。年龄和性别匹配的对照组（n=461）来自仅接受有限基本测量的Tromsø7参与者。在基线和5年后评估与健康相关的生活质量、心理困扰和健康焦虑。关于医疗保健利用和死亡率的数据来自国家登记处。结果：心理社会结局无显著差异。医疗保健使用大致相似，尽管筛查参与者的住院率略低，每人年0.23比0.31 （95% CI 0.19, 0.28比0.25,0.38）。与对照组相比，筛查参与者的死亡风险也较低，但不显著，风险比为0.69 （95% CI 0.47, 1.01）。结论：广泛的健康检查调查筛查与心理社会伤害、医疗保健使用或死亡率的统计学显著差异无关。总的来说，研究结果表明，参与这种筛查是安全的。
{"title":"Impact of extensive health examination survey screening on quality of life, healthcare use, and mortality: A longitudinal matched cohort study","authors":"Ingvild M. Rosenlund MD, PhD , Ellisiv B. Mathiesen Professor, MD, PhD , Unni Ringberg MD, PhD , Liv-Hege Johnsen MD, PhD , Tom Wilsgaard Professor, PhD , Jørgen Isaksen MD, PhD , Tor Ingebrigtsen Professor, MD, PhD","doi":"10.1016/j.annepidem.2025.12.008","DOIUrl":"10.1016/j.annepidem.2025.12.008","url":null,"abstract":"<div><h3>Purpose</h3><div>Widespread use of diagnostic testing in asymptomatic individuals raises ethical concerns. We aimed to investigate whether participation in an extensive health examination survey is associated with psychosocial outcomes, healthcare use, and mortality.</div></div><div><h3>Methods</h3><div>This longitudinal matched cohort study included 461 participants who underwent comprehensive screening examinations as part of the population-based Tromsø7 Study, including electrocardiogram, carotid artery ultrasound, echocardiography, brain magnetic resonance imaging, and spirometry. Age- and sex-matched controls (n = 461) were drawn from Tromsø7 participants who only underwent limited basic measurements. Health-related quality of life, psychological distress, and health anxiety were assessed at baseline and after 5 years. Data on healthcare utilization and mortality were obtained from national registries.</div></div><div><h3>Results</h3><div>No significant differences were found in psychosocial outcomes. Healthcare use was largely similar, although screening participants had slightly fewer hospital admissions, 0.23 vs. 0.31 per person-year (95 % CI 0.19, 0.28 vs. 0.25, 0.38). Screening participants also had lower, but non-significant, risk of death compared with controls, hazard ratio 0.69 (95 % CI 0.47, 1.01).</div></div><div><h3>Conclusion</h3><div>Extensive health examination survey screening was not associated with psychosocial harms, healthcare use or statistically significant differences in mortality. Overall, the findings suggest that participation in such screening is safe.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"113 ","pages":"Pages 78-85"},"PeriodicalIF":3.0,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145806262","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}
Pub Date : 2025-12-19DOI: 10.1016/j.annepidem.2025.12.007
Bereket Kefale , Jonine Jancey , Amanuel T. Gebremedhin , Daniel Gashaneh Belay , Gavin Pereira , Gizachew A. Tessema
Purpose
This methodological systematic review aimed to identify and synthesise the existing under-five mortality (U5M) estimation methods globally.
Methods
We searched seven databases including Medline, Embase, Scopus, Web of Science, CINAHL, Global Health, and ProQuest Central, as well as grey literature sources from inception to September 25, 2025. The review protocol was prospectively registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42023465476).
Results
Fifty-six studies were included in this review. The most frequently employed child mortality estimation method was the indirect method (n = 16), followed by the Global Burden of Disease (GBD) study method (n = 12) and the direct method (n = 11). The most commonly applied models were spatiotemporal Gaussian process regression and the Bayesian B-spline bias-reduction model. Substantial variation was observed across studies in geographical scope, temporal coverage, data sources, uncertainty quantification, statistical modelling, and bias adjustment.
Conclusions
There are substantial variations in U5M estimation methods, with challenges in data availability, uncertainty estimation, and bias adjustment. These findings highlight the need to harmonise methodological approaches and refine estimation methods. Strengthening vital registration systems is essential to ensure accurate, reliable data to inform evidence-based decision-making and track progress towards U5M reduction targets.
目的：本方法学系统综述旨在确定和综合全球现有的五岁以下儿童死亡率（U5M）估计方法。方法：检索Medline、Embase、Scopus、Web of Science、CINAHL、Global Health、ProQuest Central等7个数据库，以及创立至2025年9月25日的灰色文献来源。该评价方案已在国际前瞻性系统评价登记册（PROSPERO） （CRD42023465476）前瞻性注册。结果：本综述纳入56项研究。最常用的儿童死亡率估计方法是间接方法（n= 16），其次是全球疾病负担（GBD）研究方法（n=12）和直接方法（n= 11）。最常用的模型是时空高斯过程回归模型和贝叶斯b样条偏置减少模型。在地理范围、时间覆盖范围、数据来源、不确定性量化、统计建模和偏倚调整等方面，各研究均存在显著差异。结论：U5M估计方法存在很大差异，在数据可用性、不确定性估计和偏倚调整方面存在挑战。这些发现突出了协调方法方法和改进估计方法的必要性。加强生命登记系统对于确保准确、可靠的数据，为循证决策提供信息，跟踪实现降低儿童死亡率目标的进展至关重要。
{"title":"Under-five mortality estimation methods: A methodological systematic review","authors":"Bereket Kefale , Jonine Jancey , Amanuel T. Gebremedhin , Daniel Gashaneh Belay , Gavin Pereira , Gizachew A. Tessema","doi":"10.1016/j.annepidem.2025.12.007","DOIUrl":"10.1016/j.annepidem.2025.12.007","url":null,"abstract":"<div><h3>Purpose</h3><div>This methodological systematic review aimed to identify and synthesise the existing under-five mortality (U5M) estimation methods globally.</div></div><div><h3>Methods</h3><div>We searched seven databases including Medline, Embase, Scopus, Web of Science, CINAHL, Global Health, and ProQuest Central, as well as grey literature sources from inception to September 25, 2025. The review protocol was prospectively registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42023465476).</div></div><div><h3>Results</h3><div>Fifty-six studies were included in this review. The most frequently employed child mortality estimation method was the indirect method (n = 16), followed by the Global Burden of Disease (GBD) study method (n = 12) and the direct method (n = 11). The most commonly applied models were spatiotemporal Gaussian process regression and the Bayesian B-spline bias-reduction model. Substantial variation was observed across studies in geographical scope, temporal coverage, data sources, uncertainty quantification, statistical modelling, and bias adjustment.</div></div><div><h3>Conclusions</h3><div>There are substantial variations in U5M estimation methods, with challenges in data availability, uncertainty estimation, and bias adjustment. These findings highlight the need to harmonise methodological approaches and refine estimation methods. Strengthening vital registration systems is essential to ensure accurate, reliable data to inform evidence-based decision-making and track progress towards U5M reduction targets.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"113 ","pages":"Pages 71-77"},"PeriodicalIF":3.0,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145806307","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}
Pub Date : 2025-12-19DOI: 10.1016/j.annepidem.2025.12.009
Hongjie Liu PhD., MS
Purpose
This paper illustrates the application of multilevel modeling to egocentric network data, where network alters are nested within their respective egos. The nested structure and intra-ego dependencies in such data violate the independence assumptions of traditional regression models.
Methods
Multilevel modeling addresses this dependency by accommodating hierarchical data structures, allowing for more accurate estimation of ego–alter associations. It also distinguishes the effects of variables measured at the alter, ego, and dyadic (ego–alter) levels on outcome variable. We describe model specifications involving random intercepts and slopes, cross-level interactions, and assumptions related to residuals and variance structures. An illustrative example is provided to demonstrate how to estimate fixed and random effects for both continuous and binary outcome variables, assess intraclass correlation, test cross-level interactions, and interpret model results.
Results
This paper serves as a practical guide for applying multilevel models to egocentric network data, outlining key conceptual foundations, methodological considerations, and step-by-step implementation using SAS and R.
Conclusions
The guide aims to support researchers in the social and health sciences in rigorously applying multilevel modeling to egocentric network data, fostering deeper insights into how individual, relational, and structural factors influence health-related outcomes.
{"title":"Multilevel modeling in egocentric network analysis: A practical guide with SAS and R","authors":"Hongjie Liu PhD., MS","doi":"10.1016/j.annepidem.2025.12.009","DOIUrl":"10.1016/j.annepidem.2025.12.009","url":null,"abstract":"<div><h3>Purpose</h3><div>This paper illustrates the application of multilevel modeling to egocentric network data, where network alters are nested within their respective egos. The nested structure and intra-ego dependencies in such data violate the independence assumptions of traditional regression models.</div></div><div><h3>Methods</h3><div>Multilevel modeling addresses this dependency by accommodating hierarchical data structures, allowing for more accurate estimation of ego–alter associations. It also distinguishes the effects of variables measured at the alter, ego, and dyadic (ego–alter) levels on outcome variable. We describe model specifications involving random intercepts and slopes, cross-level interactions, and assumptions related to residuals and variance structures. An illustrative example is provided to demonstrate how to estimate fixed and random effects for both continuous and binary outcome variables, assess intraclass correlation, test cross-level interactions, and interpret model results.</div></div><div><h3>Results</h3><div>This paper serves as a practical guide for applying multilevel models to egocentric network data, outlining key conceptual foundations, methodological considerations, and step-by-step implementation using SAS and R.</div></div><div><h3>Conclusions</h3><div>The guide aims to support researchers in the social and health sciences in rigorously applying multilevel modeling to egocentric network data, fostering deeper insights into how individual, relational, and structural factors influence health-related outcomes.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"113 ","pages":"Pages 64-70"},"PeriodicalIF":3.0,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145806257","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}
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