Annals of Epidemiology最新文献_第2页

School performance following invasive Group B Streptococcus disease in early infancy in Denmark 丹麦婴儿期侵袭性B群链球菌感染后的学习表现

IF 3 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology

Pub Date : 2026-02-03 DOI: 10.1016/j.annepidem.2026.01.009

Malene Risager Lykke MD , Henrik Toft Sørensen MD, PhD, DMsc., DSc. , Joy Elizabeth Lawn MB BS, FRCPCH., MPH, PhD , Janet L Peacock MSc, PhD , Erzsébet Horváth-Puhó MSc, PhD

Objectives

Better quantification of long-term neurodevelopmental impairments following invasive Group B Streptococcus disease (iGBS) in early infancy can inform prognostication and societal impacts, including children's educational and social care needs.

Study design

A population-based observational prevalence study.

Methods

Children born 1997–2010, who survived iGBS sepsis or meningitis within the first 89 days after birth and completed public school tests aged 8–15 years were matched 1:20 with a general population comparison group without iGBS by sex and year of birth in Denmark. IGBS was identified using the Danish National Patient Registry covering all Danish hospitals and International Classification of Diseases, Tenth Revision codes. Standardized school test scores from 2010 to 2019 were obtained from the Danish Ministry of Education. Adjusted differences (adj. diff.) in school performance and corresponding 95 % confidence intervals (CIs) were estimated by subject type, grade, sex (at birth), and preterm birth using multivariable linear regression models with robust variance estimators.

Results

Among 807 iGBS survivors (90.7 % sepsis, 9.3 % meningitis) and 16,140 comparators, iGBS-sepsis survivors' performance was comparable to children without iGBS across tests, subjects, or grades. However, iGBS-meningitis survivors performed poorer than their matched comparators (adj. diff. −2·74 [95 % CI −5·19; −0·29]). Preterm birth was associated with poorer performance, regardless of a history of iGBS. No difference in test scores was found between sexes.

Conclusion

Among Danish school children, no overall difference was observed in school performance between children with a history of iGBS and comparators. However, iGBS-meningitis and preterm birth were linked to lower standardized test scores. This association was not observed in children who had iGBS-sepsis, unless they were also preterm.

目的：更好地量化婴儿早期侵袭性B群链球菌病（iGBS）后的长期神经发育障碍，可以为预后和社会影响提供信息，包括儿童的教育和社会护理需求。研究设计：基于人群的观察性患病率研究。方法：1997-2010年出生的儿童，出生后89天内存活iGBS败血症或脑膜炎并完成8-15岁公立学校测试的儿童，按性别和出生年份与没有iGBS的一般人群对照组进行1:20匹配。IGBS是根据涵盖所有丹麦医院的丹麦国家病人登记处和《国际疾病分类第十版》代码确定的。2010年至2019年的标准化学校考试成绩来自丹麦教育部。根据受试者类型、年级、性别（出生时）和早产情况，使用具有稳健方差估计的多变量线性回归模型估计学校表现的调整差异（形容词。diff.）和相应的95%置信区间（ci）。结果：在807名iGBS幸存者（90.7%败血症，9.3%脑膜炎）和16140名比较者中，iGBS败血症幸存者在测试、受试者或年级上的表现与没有iGBS的儿童相当。然而，igbs -脑膜炎幸存者的表现比他们匹配的比较者差（adj. diff. -2·74 [95% CI - 5.19; - 0.29]）。无论是否有iGBS病史，早产与较差的表现有关。测试成绩没有发现性别之间的差异。结论：在丹麦学龄儿童中，有iGBS病史的儿童和比较者在学校表现上没有总体差异。然而，igbs -脑膜炎和早产与较低的标准化考试成绩有关。这种关联在患有igbs -败血症的儿童中没有观察到，除非他们也是早产儿。

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引用次数: 0

Midlife and late-life neighborhood socioeconomic status and cognitive function in later life: Differences by race 中老年邻里社会经济地位与晚年认知功能：种族差异。

IF 3 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology

Pub Date : 2026-02-01 DOI: 10.1016/j.annepidem.2026.01.017

Greta Jianjia Cheng PhD , Christina F. Mair PhD , Jeanine M. Buchanich PhD , Tiffany L. Gary-Webb PhD , C. Elizabeth Shaaban PhD , Andrea L. Rosso PhD

Purpose

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 + .

Methods

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.

Results

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.

Conclusions

Midlife may be a critical period in which neighborhood socioeconomic exposure has a greater impact on late-life cognitive health, particularly for Black individuals.

目的：关于社区社会经济地位（nSES）作为认知结果的上游决定因素的证据在很大程度上缺乏生命历程视角。我们研究了330名70岁以上的美国黑人和白人老年人在中年和晚年nSES与认知功能之间关系的种族差异。方法：采用改良迷你精神状态检查法测量一般认知功能，随访15年。中年（49-58岁）和老年（70-79岁）的nSES评分基于5个区域水平社会经济特征的人口普查指标进行z标准化。混合效应线性回归检验了中年和晚年nSES与认知功能之间的关系。结果：黑人较高的中年nSES与较高的基线认知功能水平相关（β: 3.10, 95% CI: 0.85, 5.33），但在白人参与者中不相关（β: 0.51, 95% CI: -0.88, 1.90；相互作用p: 0.037）。在整个样本或两组种族中，没有观察到中年nSES与认知功能变化之间的联系。老年nSES与总体样本或任何种族群体的认知功能或变化的基线水平无关。结论：中年可能是社区社会经济暴露对晚年认知健康影响较大的关键时期，尤其是对黑人个体。

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引用次数: 0

Public health monitoring of diabetes in the era of electronic health records: Insights from the Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network 电子健康记录时代糖尿病的公共卫生监测：来自儿童、青少年和年轻人糖尿病（DiCAYA）网络的见解

IF 3 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology

Pub Date : 2026-01-31 DOI: 10.1016/j.annepidem.2026.01.016

Angela D. Liese PhD, MPH , Brian E. Dixon PhD , Tessa Crume PhD,MSPH , Jasmin Divers PhD , Yi Guo PhD , Annemarie G. Hirsch PhD, MPH , Kristi Reynolds PhD , Levon Utidjian MD , Ibrahim Zaganjor PhD , Marc Rosenman MD , for the DiCAYA Study Group

Purpose

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.

Methods

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.

Results

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.

Conclusions

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.

目的：公共卫生的一项关键职能是监测妨碍生活质量和给受影响社区造成负担的疾病。儿童、青少年和青年糖尿病（DiCAYA）网络旨在利用多站点电子健康记录（EHR）数据推进糖尿病疾病监测。方法：这项工作包括验证和完善病例定义，以准确识别1型和2型糖尿病病例，以估计儿童、青少年和44岁以下年轻人糖尿病的发病率和患病率。结果：在这篇文章中，我们描述了网络所经历的挑战和吸取的教训。挑战包括访问EHR数据，将来自异构卫生系统的EHR数据协调到一个共同的数据模型，以及开发方法来解释卫生保健利用数据的非代表性所带来的偏见。学到的经验包括数据质量评估、偏差校正和可伸缩性的方法。结论：随着美国公共卫生数据系统和慢性病监测方法的不断发展，DiCAYA网络为成功因素和应避免的陷阱提供了指导。

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引用次数: 0

Predicting nonresponse to sexual identity question in youth risk behavior surveillance: A machine learning analysis of complex survey data 预测青少年危险行为监测中对性别认同问题的无反应：复杂调查数据的机器学习分析。

IF 3 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology

Pub Date : 2026-01-30 DOI: 10.1016/j.annepidem.2026.01.011

Yu He MPH , Chanapong Rojanaworarit PhD

Purpose

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.

Methods

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).

Results

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.

Conclusions

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.

目的：比较2023年青少年风险行为监测系统（YRBSS）中用于预测对性别认同问题无反应的七种机器学习（ML）模型，并确定表现最佳的ML模型，以及与无反应相关的关键属性。方法：对20,103名学生的数据进行分析，包括个人特征、学校行为、物质使用和性活动等32个预测因素。开发了有监督的机器学习模型，包括随机森林（RF）、梯度增强、极端梯度增强、决策树、神经网络、lasso和弹性网，并纳入了调查权重。使用F1评分、ROC曲线下面积（AUC）和precision-recall曲线下面积（AUPRC）来评估绩效。结果：约有10%的学生没有回答性别认同问题，其中少数族裔的比例更高，包括美国印第安人/阿拉斯加原住民和夏威夷原住民/太平洋岛民青年。RF模型在所有指标中显示出最稳健的总体性能。预测无反应的属性包括因安全考虑而缺课和拥有≥4个性伴侣的问题的反应状态。结论：无反应是非随机的，集中在弱势群体中。预测性能很强，但研究结果表明，对其他敏感调查项目的反应模式也起着实质性的作用，对调查设计和非反应调整有影响。

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引用次数: 0

Effect of World Trade Center Health Program on mortality among 9/11 responders 世贸中心健康计划对9/11响应者死亡率的影响

IF 3 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology

Pub Date : 2026-01-29 DOI: 10.1016/j.annepidem.2026.01.014

Afroza Parvin , Rebecca D. Kehm , Baozhen Qiao , James E. Cone , Mark R. Farfel , Rachel Zeig-Owens , David G. Goldfarb , Moshe Z. Shapiro , Andrew C. Todd , Tabassum Insaf , Charles B. Hall , Paolo Boffetta , Jiehui Li

Purpose

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.

Methods

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.

Results

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.

Conclusions

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.

目的：世界贸易中心健康计划（WTCHP）在2001年9月11日（9/11）遭受恐怖袭击的人群的医疗监测和治疗中发挥着关键作用。我们调查了WTCHP成员与9/11响应者死亡风险的关系，同时使用逆概率加权控制合并症。方法：我们前瞻性地分析了28,430名9/11响应者，从他们入组WTCHP或WTC健康登记处的时间到2020年。NDI链接提供死亡数据。非癌症合并症是自我报告的医生诊断，癌症是通过癌症登记联系确定的。我们分别使用Cox比例风险模型和原因特异性风险回归模型估计WTCHP成员与全因和原因特异性死亡率之间的校正风险比（aHR）和95%置信区间（CI）。结果：在444425人-年的随访中，共有1657人死亡。与非会员相比，在调整了人口统计学、WTC暴露和合共病权重后，WTCHP会员的全因死亡率（aHR=0.87; 95% CI=0.77-0.98）和吸烟相关死亡率（aHR=0.83; 0.69-0.99）的风险较低。包括成员-性别相互作用在内，全因死亡率的降低仅在男性中具有统计学意义（aHR=0.85; 0.75-0.96）。癌症和心脏相关的死亡风险在WTCHP成员和非成员之间没有显著差异。结论：本研究发现，即使考虑到潜在的医疗条件，WTCHP成员资格也可能降低9/11响应者的全因死亡率和吸烟相关死亡率，强调了对救灾人员进行全面健康监测和治疗服务的重要性。

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引用次数: 0

Careless and inconsistent reporting inflates suicidality prevalence and biases sex differences 不小心和不一致的报告夸大了自杀率，并偏见了性别差异。

IF 3 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology

Pub Date : 2026-01-29 DOI: 10.1016/j.annepidem.2026.01.013

Romain Brisson

Purpose

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.

Methods

I used data from two nationally representative surveys of secondary-school students conducted in 2010 (n = 7640; 49.3 % female) and 2014 (n = 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).

Results

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.

Conclusions

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.

目的：本研究考察了粗心和不一致的报告如何影响青少年自杀率和性别差异，这是一个在自我报告流行病学研究中经常被忽视的方法学问题。方法：我使用了2010年（n = 7640，女性49.3%）和2014年（n = 5592，女性52.6%）两次具有全国代表性的中学生调查数据。两项调查都评估了抑郁症状、自杀意念、自杀计划、自杀企图、企图识别和企图披露。使用了三种患病率计算方法：未经调整的估计（M1）；排除虚构的药物代言人并将不一致视为缺失（M2）；排除所有粗心和不一致的记者（M3）。结果：约19%的受访者被认为是粗心大意或前后不一致。与M1相比，M2和M3对大多数指标的患病率估计较低。平均而言，减少最多的是未被注意到的自杀企图（-73.8%），没有向任何人谈论自杀企图（-73.3%），以及报告六次或更多自杀企图（-35.9%）。除了“六次或以上自杀企图”类别和企图识别和披露项目外，大多数性别差异未受影响。结论：忽视误报可能会夸大青少年自杀率并扭曲性别差异估计。结合有效性检查和数据清理程序可以提高流行病学调查结果的准确性和预防方案的有效性。

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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 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology

Pub Date : 2026-01-23 DOI: 10.1016/j.annepidem.2026.01.007

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

Purpose

We aimed to identify key midlife dementia predictors and develop a novel machine learning (ML) -enabled risk prediction model.

Methods

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.

Results

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.

Conclusions

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.

目的：我们旨在确定关键的中年痴呆预测因素，并开发一种新的机器学习（ML）支持的风险预测模型。方法：使用9266名社区动脉粥样硬化风险研究参与者（基线年龄45-64岁，1987-1989）的数据。到2019年12月确定了偶发性痴呆。采用基于ml的LASSO-Cox模型建立风险预测模型。结果：在25年的平均随访中，2010名参与者患上了痴呆症。LASSO-Cox模型确定了12个关键预测因子，在训练集（n = 6,182）和测试集（n = 3,084）中，c指数（95%CI）分别为0.77（0.75-0.79）和0.78（0.76-0.81）。预测因子包括年龄、数字符号替代试验、载脂蛋白E ε4、HbA1c、臂压、因子VIII、延迟单词回忆试验、高血压、卒中史、c反应蛋白、白细胞计数、载脂蛋白b。所得nomogram鉴别能力强（AUC 0.77 ~ 0.86），校正效果好。LASSO-Cox风险评分四分位数有效地将参与者分为低、中、高和非常高痴呆风险组。结论：研究结果表明，新开发的基于机器学习的LASSO-Cox模型为预测痴呆症高危人群提供了一种强大的方法。

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引用次数: 0

Residential mobility during pregnancy and birth outcomes in the United States: The environmental influences on Child Health Outcomes (ECHO) Cohort (2010–2019) 美国怀孕期间的居住流动性和分娩结果：环境对儿童健康结果（ECHO）队列的影响（2010-2019）。

IF 3 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology

Pub Date : 2026-01-17 DOI: 10.1016/j.annepidem.2026.01.008

Angela D’Adamo , Amii M. Kress , Rima Habre , Nissa Towe-Goodman , Michael R. Desjardins , Akram Alshawabkeh , Izzuddin M. Aris , Carlos A. Camargo Jr. , Kecia N. Carroll , Andrea E. Cassidy-Bushrow , Su H. Chu , Yolaine Civil , Alexandrea L. Craft , Lisa A. Croen , Sean Deoni , Viren Dsa , Anne L. Dunlop , Amy J. Elliott , Assiamira Ferrara , Jody M. Ganiban , Emily A. Knapp

Purpose

To examine factors associated with moving during pregnancy and impacts of assigning nSES at enrollment, delivery, or a time-weighted average on birth outcomes (birthweight, birthweight-for-gestational-age z-score, low birthweight, gestational age, small-for-gestational age, preterm birth).

Methods

We used data from the Environmental influences on Child Health Outcomes (ECHO) Cohort Study (2010–2019) with nSES data from the American Community Survey (ACS) matched by time and location to monthly residential histories. We used multivariable logistic models with Generalized Estimating Equations to identify factors associated with moving and quantify exposure misclassification in model estimates.

Results

Approximately 7 % of 15,376 participants moved at least once during pregnancy. Maternal age (OR: 0.97, 95 % CI: 0.95, 0.98) and other race vs. White (OR: 0.39, 95 % CI: 0.20, 0.80) were associated with lower odds of moving; lower neighborhood-level education (OR: 1.34, 95 % CI: 1.11, 1.62) and living in urban neighborhoods (OR: 3.03, 95 % CI: 1.39, 6.59) were associated with higher odds. Among movers, estimates between nSES and birth outcomes changed ≥ 16 % by address assignment; birthweight-for-gestational-age z-score was significant only when using nSES at delivery.

Conclusion

Sociodemographic and nSES characteristics are associated with moving during pregnancy; movers may experience exposure misclassification and underestimated effects on birth outcomes.

目的：研究与怀孕期间运动相关的因素，以及在入组、分娩或时间加权平均时分配nSES对出生结局（出生体重、出生体重/胎龄z得分、低出生体重、胎龄、小胎龄、早产）的影响。方法：我们使用来自2010-2019年环境对儿童健康结局（ECHO）队列研究的数据，以及来自美国社区调查（ACS）的nSES数据，这些数据按时间和地点与每月居住历史相匹配。我们使用具有广义估计方程的多变量逻辑模型来识别与移动相关的因素，并量化模型估计中的暴露误分类。结果：15,376名参与者中约有7%在怀孕期间至少搬家一次。母亲年龄（OR: 0.97, 95% CI: 0.95, 0.98）和其他种族（OR: 0.39, 95% CI: 0.20, 0.80）与较低的搬家几率相关；较低的社区教育水平（OR: 1.34, 95% CI: 1.11, 1.62）和居住在城市社区（OR: 3.03, 95% CI: 1.39, 6.59）与较高的几率相关。在迁居者中，nSES与出生结局之间的估计值因住址分配而变化≥16%；只有在分娩时使用nSES时，出生体重/胎龄z-score才有显著性。结论：社会人口学和nSES特征与妊娠期运动有关；搬运工可能会经历暴露错误分类和低估对出生结果的影响。

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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 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology

Pub 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

A multivariable model for improving the identification of cerebral palsy cases in administrative health data 提高行政卫生资料中脑瘫病例识别的多变量模型

IF 3 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology

Pub Date : 2026-01-13 DOI: 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.

目的提高行政卫生资料中脑瘫病例的识别水平。方法：我们纳入了加拿大魁北克省以人口为基础的脑瘫儿童登记处的所有儿童，这些儿童出生在1999年至2002年，并以非脑瘫儿童为样本。获得了截至2012年所有儿童的基于人口的住院和医生账单记录。我们使用逻辑回归对脑瘫的概率进行建模，使用国际疾病分类代码对相关疾病进行编码。我们报告了受试者工作特征（ROC）和精确召回率（PR）曲线，并与现有算法的准确性进行了比较。我们还报道了年龄、数据来源和出生时胎龄对脑瘫编码的准确性。结果模型的ROC曲线下面积为0.98(95 % CI: 0.97-0.99)， PR曲线下面积为0.73（95 % CI: 0.63-0.79）。与现有算法具有相似特异性的截断值产生的敏感性高出1 - 14%的年龄点。脑瘫编码的敏感性较高（特异性较低），自出生以来随访时间较长，当使用住院和计费记录时，以及在早产儿童中。结论sour模型提高了行政资料对脑瘫病例的识别，但仍存在误分类现象。

{"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}

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