Pub Date : 2026-03-01Epub Date: 2026-02-04DOI: 10.1016/j.annepidem.2026.02.001
Nusrat Rabbee
The NIH Office of Research on Women’s Health (ORWH) established the 4Cs framework—Consider, Collect, Characterize, Communicate—to promote the integration of Sex as a Biological Variable (SABV) in clinical research. Building on this foundation, we provide applied statistical guidance for implementing SABV across study design, analysis, and reporting. Using a simulated myocardial infarction example, we illustrate how sex-related bias can arise from omitted variables, underrepresentation, and unmodeled interactions. These methodological oversights can mask important sex-specific patterns in health outcomes and limit generalizability. While grounded in U.S. policy efforts, the statistical principles and approaches described are broadly applicable across epidemiologic research to improve scientific rigor and equity.
{"title":"Statistical considerations for sex inclusion in clinical studies","authors":"Nusrat Rabbee","doi":"10.1016/j.annepidem.2026.02.001","DOIUrl":"10.1016/j.annepidem.2026.02.001","url":null,"abstract":"<div><div>The NIH Office of Research on Women’s Health (ORWH) established the 4Cs framework—Consider, Collect, Characterize, Communicate—to promote the integration of Sex as a Biological Variable (SABV) in clinical research. Building on this foundation, we provide applied statistical guidance for implementing SABV across study design, analysis, and reporting. Using a simulated myocardial infarction example, we illustrate how sex-related bias can arise from omitted variables, underrepresentation, and unmodeled interactions. These methodological oversights can mask important sex-specific patterns in health outcomes and limit generalizability. While grounded in U.S. policy efforts, the statistical principles and approaches described are broadly applicable across epidemiologic research to improve scientific rigor and equity.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 64-73"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146133599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-30DOI: 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.
{"title":"Predicting nonresponse to sexual identity question in youth risk behavior surveillance: A machine learning analysis of complex survey data","authors":"Yu He MPH , Chanapong Rojanaworarit PhD","doi":"10.1016/j.annepidem.2026.01.011","DOIUrl":"10.1016/j.annepidem.2026.01.011","url":null,"abstract":"<div><h3>Purpose</h3><div>To compare seven machine learning (ML) models developed to predict non-response to the sexual identity question in the 2023 Youth Risk Behavior Surveillance System (YRBSS) and identify the best-performing ML model, along with key attributes associated with the non-response.</div></div><div><h3>Methods</h3><div>Data of 20,103 students, with 32 predictors across domains of personal characteristics, school behavior, substance use, and sexual activity were analyzed. Supervised ML models–including random forest (RF), gradient boosting, extreme gradient boosting, decision tree, neural network, lasso, and elastic net were developed and incorporated survey weights. Performance was assessed using F1 score, area under the ROC curve (AUC), and area under the precision-recall curve (AUPRC).</div></div><div><h3>Results</h3><div>About 10 % of students didn’t respond to the sexual identity question, with higher rates among racial/ethnic minorities, including American Indian/Alaska Native and Native Hawaiian/Pacific Islander youths. RF model showed the most robust overall performance across all metrics. Attributes predicting non-response included response status to questions of school absence due to safety concerns and having ≥ 4 sexual partners.</div></div><div><h3>Conclusions</h3><div>Non-response was non-random and concentrated among vulnerable groups. Predictive performance was strong, but findings suggest that response patterns to other sensitive survey items play substantial role, with implications for survey design and non-response adjustment.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"115 ","pages":"Pages 37-44"},"PeriodicalIF":3.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146100960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-27DOI: 10.1016/j.annepidem.2026.110057
Bronner P Gonçalves
{"title":"Commentary on causes of death and death reporting during the pandemic.","authors":"Bronner P Gonçalves","doi":"10.1016/j.annepidem.2026.110057","DOIUrl":"10.1016/j.annepidem.2026.110057","url":null,"abstract":"","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"110057"},"PeriodicalIF":3.0,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147327347","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 : 2026-02-26DOI: 10.1016/j.annepidem.2026.110058
D Durán N, J S Kaufman, C Carmeli
{"title":"Response to commentary on causes of death and death reporting during the pandemic.","authors":"D Durán N, J S Kaufman, C Carmeli","doi":"10.1016/j.annepidem.2026.110058","DOIUrl":"https://doi.org/10.1016/j.annepidem.2026.110058","url":null,"abstract":"","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"110058"},"PeriodicalIF":3.0,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147322506","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 : 2026-02-01Epub 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":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub 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":"2026-02-01","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 : 2026-02-01Epub 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":"2026-02-01","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 : 2026-02-01Epub 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":"2026-02-01","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}
Early-onset cancer (EOC), occurring in individuals aged 15–49 years, is a growing global health concern. High body mass index (BMI) is an established modifiable risk factor contributing to cancer morbidity and mortality.
Methods
Age-specific death percents and estimated annual percentage changes (APC) were calculated to assess mortality trends associated with high BMI using GBD 2021 data. Global and regional (5 socio-demographic (SDI) regions, 21 GBD regions and 204 countries) trends were analyzed. Statistical modeling, including 2 sample t-test were performed to estimate the standard deviations among each group which is plugged in the denominator to compute the statistic.
Results
In 2021, 23,078 EOC deaths related to high BMI occurred, accounting for 2.33 % of global EOC mortality, representing a 92.78 % increase since 1990. Males (2.96 %) exhibited a higher proportion of high BMI-attributable EOC deaths compared to females (1.72 %). High-income regions recorded the highest EOC deaths (3.78 %) associated with high BMI, with increasing trends observed across all SDI levels. At the national level, Tonga (8.38 %) and the UAE (8.09 %) had the highest high BMI-associated EOC mortality rates. Among cancer types, kidney and uterine cancers exhibited the highest mortality. Notably, high BMI demonstrated a protective effect against early-onset breast cancer in females.
Discussion
The rising burden of EOC mortality attributed to high BMI underscores the need for urgent interventions in young adult population. Addressing obesity through lifestyle changes, pharmacotherapy, and bariatric surgery is crucial for reducing cancer burden. Future research should refine risk estimates and inform targeted interventions.
{"title":"A global health crisis in young adults: 30-Year trends in high BMI-related early-onset cancer mortality","authors":"Rupayan Kundu MD , Rishabh Kundu MSc , Sudipto Mukherjee MD, PhD","doi":"10.1016/j.annepidem.2025.12.006","DOIUrl":"10.1016/j.annepidem.2025.12.006","url":null,"abstract":"<div><h3>Introduction</h3><div>Early-onset cancer (EOC), occurring in individuals aged 15–49 years, is a growing global health concern. High body mass index (BMI) is an established modifiable risk factor contributing to cancer morbidity and mortality.</div></div><div><h3>Methods</h3><div>Age-specific death percents and estimated annual percentage changes (APC) were calculated to assess mortality trends associated with high BMI using GBD 2021 data. Global and regional (5 socio-demographic (SDI) regions, 21 GBD regions and 204 countries) trends were analyzed. Statistical modeling, including 2 sample t-test were performed to estimate the standard deviations among each group which is plugged in the denominator to compute the statistic.</div></div><div><h3>Results</h3><div>In 2021, 23,078 EOC deaths related to high BMI occurred, accounting for 2.33 % of global EOC mortality, representing a 92.78 % increase since 1990. Males (2.96 %) exhibited a higher proportion of high BMI-attributable EOC deaths compared to females (1.72 %). High-income regions recorded the highest EOC deaths (3.78 %) associated with high BMI, with increasing trends observed across all SDI levels. At the national level, Tonga (8.38 %) and the UAE (8.09 %) had the highest high BMI-associated EOC mortality rates. Among cancer types, kidney and uterine cancers exhibited the highest mortality. Notably, high BMI demonstrated a protective effect against early-onset breast cancer in females.</div></div><div><h3>Discussion</h3><div>The rising burden of EOC mortality attributed to high BMI underscores the need for urgent interventions in young adult population. Addressing obesity through lifestyle changes, pharmacotherapy, and bariatric surgery is crucial for reducing cancer burden. Future research should refine risk estimates and inform targeted interventions.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"114 ","pages":"Pages 7-11"},"PeriodicalIF":3.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145806237","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号