Pub Date : 2026-01-24DOI: 10.1007/s10654-025-01349-z
Emilio A L Gianicolo,Maria Blettner,Andreas Stang
{"title":"Indirect standardization: time to eliminate misleading terminology.","authors":"Emilio A L Gianicolo,Maria Blettner,Andreas Stang","doi":"10.1007/s10654-025-01349-z","DOIUrl":"https://doi.org/10.1007/s10654-025-01349-z","url":null,"abstract":"","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"66 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-24DOI: 10.1007/s10654-025-01347-1
Marta Pineda-Moncusí,Maria Rahman,Eleanor L Axson,Susan Hodgson,Antonella Delmestri
Since its establishment in the late 1980s, the UK Clinical Practice Research Datalink (CPRD) has become one of the most widely utilised data resources in both national and international research. Its value lies in the richness, scale and quality of its routinely collected primary care data, as well as the availability of numerous linkable datasets. This study provides comprehensive scientometric analyses of CPRD-related research output, impact, and data usage from 1988 to 2024. A total of 3779 peer-reviewed publications were identified, and for 98.78% of them, enriched bibliometric metadata were retrieved through Scopus and Web of Science. The UK emerged as the leading contributing country, with the United States and Canada ranking second and third. 'McGill University' was the most frequently affiliated institution, followed by the 'University of Manchester' and the 'University of Oxford', with seven UK universities among the top ten. The three journals most frequently publishing CPRD-based research overall, and since 2020, were 'BMJ Open', 'Pharmacoepidemiology and Drug Safety' and 'British Journal of General Practice'. Analyses of primary care data sources utilisation revealed that overall, 86.35% of manuscripts used CPRD GOLD exclusively, 8.39% used both CPRD GOLD and CPRD Aurum, and 4.76% used CPRD Aurum alone, although recent years showed an increased use of CPRD Aurum. Between 2016 and 2024, most articles (80.26%) were associated with CPRD research applications that referenced linked or CPRD algorithm-derived datasets. The three most frequently used were 'Hospital Episode Statistics' (69.77%), 'Small Area Linkages' (62.27%) and 'Office for National Statistics' mortality data (53.28%).
自20世纪80年代末建立以来，英国临床实践研究数据链（CPRD）已成为国内和国际研究中使用最广泛的数据资源之一。它的价值在于其常规收集的初级保健数据的丰富性、规模和质量，以及大量可链接数据集的可用性。本研究对1988 - 2024年cprd相关研究产出、影响和数据使用情况进行了全面的科学计量分析。共发现3779篇同行评议出版物，其中98.78%通过Scopus和Web of Science检索到丰富的文献计量元数据。英国成为贡献最多的国家，美国和加拿大分列第二和第三位。麦吉尔大学（McGill University）是排名最靠前的大学，其次是曼彻斯特大学（University of Manchester）和牛津大学（University of Oxford），共有7所英国大学跻身前十。总体而言，自2020年以来最常发表基于cpr的研究的三个期刊是“BMJ Open”、“Pharmacoepidemiology and Drug Safety”和“British Journal of General Practice”。对初级保健数据来源利用情况的分析显示，总体而言，86.35%的手稿只使用CPRD GOLD， 8.39%同时使用CPRD GOLD和CPRD Aurum， 4.76%单独使用CPRD Aurum，尽管近年来CPRD Aurum的使用有所增加。2016年至2024年间，大多数文章（80.26%）与引用链接或CPRD算法衍生数据集的CPRD研究应用相关。最常用的三个词是“医院事件统计”（69.77%）、“小区域联系”（62.27%）和“国家统计局死亡率数据”（53.28%）。
{"title":"Academic impact and research data utilisation of the clinical practice research datalink: scientometric analyses.","authors":"Marta Pineda-Moncusí,Maria Rahman,Eleanor L Axson,Susan Hodgson,Antonella Delmestri","doi":"10.1007/s10654-025-01347-1","DOIUrl":"https://doi.org/10.1007/s10654-025-01347-1","url":null,"abstract":"Since its establishment in the late 1980s, the UK Clinical Practice Research Datalink (CPRD) has become one of the most widely utilised data resources in both national and international research. Its value lies in the richness, scale and quality of its routinely collected primary care data, as well as the availability of numerous linkable datasets. This study provides comprehensive scientometric analyses of CPRD-related research output, impact, and data usage from 1988 to 2024. A total of 3779 peer-reviewed publications were identified, and for 98.78% of them, enriched bibliometric metadata were retrieved through Scopus and Web of Science. The UK emerged as the leading contributing country, with the United States and Canada ranking second and third. 'McGill University' was the most frequently affiliated institution, followed by the 'University of Manchester' and the 'University of Oxford', with seven UK universities among the top ten. The three journals most frequently publishing CPRD-based research overall, and since 2020, were 'BMJ Open', 'Pharmacoepidemiology and Drug Safety' and 'British Journal of General Practice'. Analyses of primary care data sources utilisation revealed that overall, 86.35% of manuscripts used CPRD GOLD exclusively, 8.39% used both CPRD GOLD and CPRD Aurum, and 4.76% used CPRD Aurum alone, although recent years showed an increased use of CPRD Aurum. Between 2016 and 2024, most articles (80.26%) were associated with CPRD research applications that referenced linked or CPRD algorithm-derived datasets. The three most frequently used were 'Hospital Episode Statistics' (69.77%), 'Small Area Linkages' (62.27%) and 'Office for National Statistics' mortality data (53.28%).","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"284 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-24DOI: 10.1007/s10654-025-01356-0
Viktor H Ahlqvist, Hugo Sjöqvist, Arvid Sjölander, Daniel Berglind, Paul C Lambert, Brian K Lee, Paul Madley-Dowd
Findings from family-based analyses, such as sibling comparisons, are often reported using only odds ratios or hazard ratios. We demonstrate how this can be improved upon by applying the marginalized between-within framework. We provide an overview of sibling comparison methods and the marginalized between-within framework, which enables estimation of absolute risks and clinically relevant metrics while accounting for shared familial confounding. We illustrate the approach using Swedish registry data to examine the association between maternal smoking and infant mortality, estimating absolute quantities (e.g., cumulative risks), average treatment effects, attributable fractions, and numbers needed to harm (or treat). The marginalized between-within model decomposes effects into within- and between-family components while applying a global baseline across all families. Although it typically yields similar relative estimates to conditional logistic or stratified Cox regression, the model's specification of a baseline enables the estimation of absolute measures. In the applied example, absolute measures provided more interpretable and policy-relevant insights than relative estimates alone. Code for implementation in Stata and R is provided. The marginalized between-within framework may strengthen the interpretability of family-based analysis by enabling absolute and policy-relevant estimates for both binary and time-to-event outcomes, moving beyond the limitations of solely relying on relative effect measures.
{"title":"Moving beyond risk ratios in sibling analysis: estimating clinically useful measures from family-based analysis.","authors":"Viktor H Ahlqvist, Hugo Sjöqvist, Arvid Sjölander, Daniel Berglind, Paul C Lambert, Brian K Lee, Paul Madley-Dowd","doi":"10.1007/s10654-025-01356-0","DOIUrl":"10.1007/s10654-025-01356-0","url":null,"abstract":"<p><p>Findings from family-based analyses, such as sibling comparisons, are often reported using only odds ratios or hazard ratios. We demonstrate how this can be improved upon by applying the marginalized between-within framework. We provide an overview of sibling comparison methods and the marginalized between-within framework, which enables estimation of absolute risks and clinically relevant metrics while accounting for shared familial confounding. We illustrate the approach using Swedish registry data to examine the association between maternal smoking and infant mortality, estimating absolute quantities (e.g., cumulative risks), average treatment effects, attributable fractions, and numbers needed to harm (or treat). The marginalized between-within model decomposes effects into within- and between-family components while applying a global baseline across all families. Although it typically yields similar relative estimates to conditional logistic or stratified Cox regression, the model's specification of a baseline enables the estimation of absolute measures. In the applied example, absolute measures provided more interpretable and policy-relevant insights than relative estimates alone. Code for implementation in Stata and R is provided. The marginalized between-within framework may strengthen the interpretability of family-based analysis by enabling absolute and policy-relevant estimates for both binary and time-to-event outcomes, moving beyond the limitations of solely relying on relative effect measures.</p>","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":" ","pages":""},"PeriodicalIF":5.9,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146040523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amyotrophic lateral sclerosis (ALS) is a multifactorial neurodegenerative disease whose incidence increases with age. According to the gene-time-environment hypothesis, ALS onset occurs through the interaction between genes and environmental exposures during ageing, which may involve a continuous accumulation process. Alternatively, the multistep pathogenic hypothesis, based on the Armitage-Doll multistep model from cancer research, posits that a discrete number of specific sequential "hits" are necessary to trigger ALS. Here we analyzed three large population-based epidemiological datasets of ALS to formally test whether the ALS age-incidence curve is better described by a power law, as predicted by the Armitage-Doll model, or by an exponential function, which is generally associated to continuous accumulation of damage and is incompatible with the Armitage-Doll model. We obtained moderate-to-extreme Bayesian evidence in favor of the exponential function compared to the power law. Cancer data were instead better aligned, as expected, with the power law. These results suggest that the multistep pathogenesis hypothesis based on the Armitage-Doll model cannot be extended from cancer to ALS, because it is incompatible with the epidemiological data. This calls for a re-consideration of the current understanding of ALS pathogenesis. Our work also warns against extending the Armitage-Doll multistep model from cancer to other aging-related diseases solely based on age-incidence curves.
{"title":"The multistep pathogenic hypothesis of amyotrophic lateral sclerosis is incompatible with the epidemiological data.","authors":"Guglielmo Foffani,Daniele Urso,Josh Hiller,Marco Piccininni,Benoît Marin,Giancarlo Logroscino","doi":"10.1007/s10654-025-01289-8","DOIUrl":"https://doi.org/10.1007/s10654-025-01289-8","url":null,"abstract":"Amyotrophic lateral sclerosis (ALS) is a multifactorial neurodegenerative disease whose incidence increases with age. According to the gene-time-environment hypothesis, ALS onset occurs through the interaction between genes and environmental exposures during ageing, which may involve a continuous accumulation process. Alternatively, the multistep pathogenic hypothesis, based on the Armitage-Doll multistep model from cancer research, posits that a discrete number of specific sequential \"hits\" are necessary to trigger ALS. Here we analyzed three large population-based epidemiological datasets of ALS to formally test whether the ALS age-incidence curve is better described by a power law, as predicted by the Armitage-Doll model, or by an exponential function, which is generally associated to continuous accumulation of damage and is incompatible with the Armitage-Doll model. We obtained moderate-to-extreme Bayesian evidence in favor of the exponential function compared to the power law. Cancer data were instead better aligned, as expected, with the power law. These results suggest that the multistep pathogenesis hypothesis based on the Armitage-Doll model cannot be extended from cancer to ALS, because it is incompatible with the epidemiological data. This calls for a re-consideration of the current understanding of ALS pathogenesis. Our work also warns against extending the Armitage-Doll multistep model from cancer to other aging-related diseases solely based on age-incidence curves.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"39 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-24DOI: 10.1007/s10654-025-01350-6
Chunsu Zhu,Melissa S Y Thong,Daniela Doege,Lena Koch-Gallenkamp,Heike Bertram,Andrea Eberle,Bernd Holleczek,Alice Nennecke,Annika Waldmann,Sylke Ruth Zeißig,Ron Pritzkuleit,Hermann Brenner,Volker Arndt
The association between healthy lifestyles and mortality in cancer survivors remains inconclusive with few evidence among long-term cancer survivors (LTCS, survived ≥ 5 years post-diagnosis). Our study aims to investigate the association between individual and combined healthy lifestyle factors and mortality in LTCS. We included 6,057 LTCS of breast, colorectal or prostate cancer from a multiple regions study in Germany. A healthy lifestyle score (HLS) comprising alcohol consumption, body mass index (BMI), physical activity and smoking was created and was classified into tertiles with higher tertile indicating healthier lifestyle. We used Cox proportional hazards regression to examine the associations of individual lifestyle factors and HLS with all-cause mortality among LTCS. A total of 2,015 death events occurred over a maximum follow-up period of 12.3 years. Compared with the lowest tertile, participants in the middle and highest tertile experienced a 27% and 32% lower mortality (middle [hazard ratio (HR), 0.73; 95% CI 0.65-0.83]; highest [HR, 0.68, 95% CI 0.61-0.76]). A significant dose-response relationship was observed (p- trend < 0.001). These associations were consistent across different demographic and clinical characteristics. In addition, full adherence to lifestyle recommendations for smoking (HR, 0.51, 95% CI 0.44-0.59), physical activity (HR, 0.78, 95% CI 0.70-0.86) and BMI (HR, 0.87, 95% CI 0.77-0.99) were significantly related to a lower mortality, after full adjustment. Adherence to an overall healthy lifestyle was associated with significantly lower all-cause mortality in LTCS, emphasizing the importance of maintaining and promoting a healthier lifestyle among LTCS.
癌症幸存者中健康生活方式与死亡率之间的关系仍然不确定，在长期癌症幸存者（LTCS，诊断后存活≥5年）中几乎没有证据。本研究旨在探讨LTCS个体及综合健康生活方式因素与死亡率的关系。我们纳入了6057例来自德国多地区研究的乳腺癌、结直肠癌或前列腺癌LTCS。建立了一个健康生活方式评分（HLS），包括饮酒、身体质量指数（BMI）、体育活动和吸烟，并将其分为三类，分值越高表明生活方式越健康。我们使用Cox比例风险回归来检验LTCS中个人生活方式因素和HLS与全因死亡率的关系。在12.3年的最长随访期内，总共发生了2,015起死亡事件。与最低分位数的参与者相比，中等和最高分位数的参与者死亡率分别降低27%和32%(中[危险比（HR）， 0.73；95% ci 0.65-0.83]；最高[HR， 0.68, 95% CI 0.61-0.76])。观察到显著的剂量-反应关系（p趋势< 0.001）。这些关联在不同的人口统计学和临床特征中是一致的。此外，在完全调整后，完全遵守吸烟（HR, 0.51, 95% CI 0.44-0.59）、体育活动（HR, 0.78, 95% CI 0.70-0.86）和BMI （HR, 0.87, 95% CI 0.77-0.99）等生活方式建议与较低的死亡率显著相关。在LTCS中，坚持整体健康的生活方式与全因死亡率显著降低相关，这强调了在LTCS中维持和促进更健康的生活方式的重要性。
{"title":"Lifestyle factors and all-cause mortality in long-term cancer survivors: a population-based prospective cohort study.","authors":"Chunsu Zhu,Melissa S Y Thong,Daniela Doege,Lena Koch-Gallenkamp,Heike Bertram,Andrea Eberle,Bernd Holleczek,Alice Nennecke,Annika Waldmann,Sylke Ruth Zeißig,Ron Pritzkuleit,Hermann Brenner,Volker Arndt","doi":"10.1007/s10654-025-01350-6","DOIUrl":"https://doi.org/10.1007/s10654-025-01350-6","url":null,"abstract":"The association between healthy lifestyles and mortality in cancer survivors remains inconclusive with few evidence among long-term cancer survivors (LTCS, survived ≥ 5 years post-diagnosis). Our study aims to investigate the association between individual and combined healthy lifestyle factors and mortality in LTCS. We included 6,057 LTCS of breast, colorectal or prostate cancer from a multiple regions study in Germany. A healthy lifestyle score (HLS) comprising alcohol consumption, body mass index (BMI), physical activity and smoking was created and was classified into tertiles with higher tertile indicating healthier lifestyle. We used Cox proportional hazards regression to examine the associations of individual lifestyle factors and HLS with all-cause mortality among LTCS. A total of 2,015 death events occurred over a maximum follow-up period of 12.3 years. Compared with the lowest tertile, participants in the middle and highest tertile experienced a 27% and 32% lower mortality (middle [hazard ratio (HR), 0.73; 95% CI 0.65-0.83]; highest [HR, 0.68, 95% CI 0.61-0.76]). A significant dose-response relationship was observed (p- trend < 0.001). These associations were consistent across different demographic and clinical characteristics. In addition, full adherence to lifestyle recommendations for smoking (HR, 0.51, 95% CI 0.44-0.59), physical activity (HR, 0.78, 95% CI 0.70-0.86) and BMI (HR, 0.87, 95% CI 0.77-0.99) were significantly related to a lower mortality, after full adjustment. Adherence to an overall healthy lifestyle was associated with significantly lower all-cause mortality in LTCS, emphasizing the importance of maintaining and promoting a healthier lifestyle among LTCS.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"18 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Individuals with mental disorders face a substantially higher risk of mortality and are more likely to be lonely, socially isolated, and with low social support compared to those without mental disorders. We aimed to quantify the extent to which the observed mortality gap associated with mental disorders could be explained by these social factors. This cohort study included 162,483 participants from the Danish National Health Survey in 2013 and 2017 who were followed for six years after survey participation. Survey data on social disconnection (loneliness, social isolation, social support in the form of perceived emotional support, and a composite measure) was linked with register data on hospital-diagnosed mental disorders and mortality. We applied G-computation-based causal decomposition to compare the sex-specific relative risk of mortality associated with mental disorders under a natural course to a counterfactual scenario in which all individuals had a distribution of social disconnection similar to individuals without mental disorders. We found that social disconnection and the distribution of loneliness, social isolation, and social support accounted for 10-34% of the mortality gap associated with mental disorders among men and 2-20% among women, assuming a causal effect of social disconnection on mortality. The largest contributions were found for social isolation and loneliness, whereas the smallest were found for social support. Our results highlight the possibility that different aspects of social disconnection, especially social isolation and loneliness, could explain part of the mortality gap associated with mental disorders, with larger contributions among men than women.
{"title":"Quantifying the contribution of social disconnection to the mortality gap associated with mental disorders: a decomposition analysis.","authors":"Lisbeth Mølgaard Laustsen,Linda Ejlskov,Danni Chen,Mathias Lasgaard,Naja Hulvej Rod,Jaimie L Gradus,Marie Stjerne Grønkjær,Oleguer Plana-Ripoll","doi":"10.1007/s10654-025-01348-0","DOIUrl":"https://doi.org/10.1007/s10654-025-01348-0","url":null,"abstract":"Individuals with mental disorders face a substantially higher risk of mortality and are more likely to be lonely, socially isolated, and with low social support compared to those without mental disorders. We aimed to quantify the extent to which the observed mortality gap associated with mental disorders could be explained by these social factors. This cohort study included 162,483 participants from the Danish National Health Survey in 2013 and 2017 who were followed for six years after survey participation. Survey data on social disconnection (loneliness, social isolation, social support in the form of perceived emotional support, and a composite measure) was linked with register data on hospital-diagnosed mental disorders and mortality. We applied G-computation-based causal decomposition to compare the sex-specific relative risk of mortality associated with mental disorders under a natural course to a counterfactual scenario in which all individuals had a distribution of social disconnection similar to individuals without mental disorders. We found that social disconnection and the distribution of loneliness, social isolation, and social support accounted for 10-34% of the mortality gap associated with mental disorders among men and 2-20% among women, assuming a causal effect of social disconnection on mortality. The largest contributions were found for social isolation and loneliness, whereas the smallest were found for social support. Our results highlight the possibility that different aspects of social disconnection, especially social isolation and loneliness, could explain part of the mortality gap associated with mental disorders, with larger contributions among men than women.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"75 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-24DOI: 10.1007/s10654-025-01358-y
Xinyuan Zhang,Longgang Zhao,Kai Zhang,David Vlahov,Yun Chen,Ann Hsing,Mindie H Nguyen,Katherine A McGlynn,Tamar Taddei,Lifang Hou,Xuehong Zhang
Social determinants of health (SDOH) are crucial in shaping liver health outcomes, yet comprehensive assessments that span key SDOH domains are lacking. To address this knowledge gap, we developed a Social Determinants Disadvantage Score (SDDS) and examined its association with major adverse liver conditions. We conducted a cross-sectional analysis of 117,783 participants from the All of Us Research Program. The SDDS was systematically constructed using validated questionnaires covering economic stability, education, healthcare access and quality, neighborhood and built environment, and social and community context. Each question was scored on a 0 (most advantage) to 1 (most disadvantage) scale. Total SDDS was calculated as the mean of all questions, ranging from 0 to 1. We used logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations of SDDS with total and individual adverse liver conditions, including steatotic liver disease (SLD), metabolic dysfunction-associated steatohepatitis (MASH), alcoholic liver disease (ALD), cirrhosis, hepatocellular carcinoma (HCC), chronic hepatitis B virus (HBV), chronic hepatitis C virus (HCV), and hepatic failure based on the Electronic Health Record. Higher SDDS was associated with a higher risk of adverse liver conditions. The highest SDDS quintile (most disadvantaged) compared to the lowest SDDS quintile had an OR = 1.67 (95% CI: 1.55-1.79) for total adverse liver condition risk after adjusting for age, sex, race, and other covariates. Similar associations were observed for individual liver conditions. Per 10% higher SDDS, the adjusted OR (95% CI) was 1.25 (1.22-1.29) for SLD, 1.27 (1.19-1.35) for MASH, 1.15 (0.99-1.34) for ALD, 1.31 (1.25-1.39) for cirrhosis, 1.35 (1.15-1.59) for HCC, 1.24 (1.14-1.35) for HBV infection, 1.40 (1.33-1.48) for HCV infection, and 1.35 (1.21-1.50) for hepatic failure. Consistent associations were found for disadvantages in individual SDOH domains, score excluding missingness, and score with selected factors. The SDDS provides a comprehensive, validated tool for assessing SDOH and their associations with liver health. Our findings highlight significant associations between social disadvantage and the prevalence of adverse liver conditions, emphasizing the need for future longitudinal studies to inform targeted interventions.
{"title":"Social determinants disadvantage score and liver health in the All of Us Research Program.","authors":"Xinyuan Zhang,Longgang Zhao,Kai Zhang,David Vlahov,Yun Chen,Ann Hsing,Mindie H Nguyen,Katherine A McGlynn,Tamar Taddei,Lifang Hou,Xuehong Zhang","doi":"10.1007/s10654-025-01358-y","DOIUrl":"https://doi.org/10.1007/s10654-025-01358-y","url":null,"abstract":"Social determinants of health (SDOH) are crucial in shaping liver health outcomes, yet comprehensive assessments that span key SDOH domains are lacking. To address this knowledge gap, we developed a Social Determinants Disadvantage Score (SDDS) and examined its association with major adverse liver conditions. We conducted a cross-sectional analysis of 117,783 participants from the All of Us Research Program. The SDDS was systematically constructed using validated questionnaires covering economic stability, education, healthcare access and quality, neighborhood and built environment, and social and community context. Each question was scored on a 0 (most advantage) to 1 (most disadvantage) scale. Total SDDS was calculated as the mean of all questions, ranging from 0 to 1. We used logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations of SDDS with total and individual adverse liver conditions, including steatotic liver disease (SLD), metabolic dysfunction-associated steatohepatitis (MASH), alcoholic liver disease (ALD), cirrhosis, hepatocellular carcinoma (HCC), chronic hepatitis B virus (HBV), chronic hepatitis C virus (HCV), and hepatic failure based on the Electronic Health Record. Higher SDDS was associated with a higher risk of adverse liver conditions. The highest SDDS quintile (most disadvantaged) compared to the lowest SDDS quintile had an OR = 1.67 (95% CI: 1.55-1.79) for total adverse liver condition risk after adjusting for age, sex, race, and other covariates. Similar associations were observed for individual liver conditions. Per 10% higher SDDS, the adjusted OR (95% CI) was 1.25 (1.22-1.29) for SLD, 1.27 (1.19-1.35) for MASH, 1.15 (0.99-1.34) for ALD, 1.31 (1.25-1.39) for cirrhosis, 1.35 (1.15-1.59) for HCC, 1.24 (1.14-1.35) for HBV infection, 1.40 (1.33-1.48) for HCV infection, and 1.35 (1.21-1.50) for hepatic failure. Consistent associations were found for disadvantages in individual SDOH domains, score excluding missingness, and score with selected factors. The SDDS provides a comprehensive, validated tool for assessing SDOH and their associations with liver health. Our findings highlight significant associations between social disadvantage and the prevalence of adverse liver conditions, emphasizing the need for future longitudinal studies to inform targeted interventions.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"7 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The global rise of non-communicable diseases (NCDs) presents an urgent public health challenge, particularly in regions undergoing rapid economic and demographic transitions. Guangdong Province, China’s most populous and economically advanced region, is experiencing a substantial and accelerating burden of NCDs. However, large-scale, population-based cohorts from this region remain scarce, limiting insights into region-specific disease determinants and prevention strategies. The Guangdong Biobank Cohort (GDBC) was established in 2017, enrolling 35,081 participants aged 40–84 years from urban and rural areas of Zhongshan City in the Pearl River Delta. At baseline, comprehensive data on 346 variables—including lifestyle, environmental exposures, medical histories, physical examinations, and laboratory profiles—were collected via a cloud-based member management information system (MMIS), alongside blood and saliva samples for biobanking. A sub-cohort underwent genome-wide genotyping ( N = 2,530) and oral microbiome profiling via 16 S rRNA sequencing ( N = 2,049). During dynamic follow-up, 44.2% ( N = 15,499) completed Phase I resurvey with repeated measurements and updated biospecimens. Disease outcomes, including hypertension, diabetes, and cancer, were ascertained through active surveillance and regional registry linkage until December 2023. Baseline prevalence of hypertension, diabetes, and cancer was 25.3%, 8.0%, and 3.6%, respectively. Over follow-up, 1,767 hypertension cases, 814 diabetes cases, and 558 cancers were recorded, yielding crude incidence rates of 1,804.6, 649.7, and 423.1 per 100,000 person-years, respectively. The GDBC provides a comprehensive, dynamically updated resource to dissect gene–microbiome–environment interactions and develop precision prevention strategies to inform public health policies.
{"title":"Guangdong Biobank Cohort (GDBC) study","authors":"Yong-Qiao He, Wen-Qiong Xue, Hua Diao, Ji-Yun Zhan, Ming-Fang Ji, Da-Wei Yang, Yi Zhao, Chang-Mi Deng, Zi-Yi Wu, Ting Zhou, Ying Liao, Mei-Qi Zheng, Wen-Li Zhang, Yi-Jing Jia, Lei-Lei Yuan, Lu-Ting Luo, Dan-Hua Li, Tong-Min Wang, Xia-Ting Tong, Yan Du, Ling-Ling Tang, Jing-Wen Huang, Chang-ling Huang, Zhi-Yang Zhao, Yan-Xia Wu, Lian-Jing Cao, Si-Qi Dong, Fang Wang, Cheng-Tao Jiang, Ruo-Wen Xiao, Wen-Bin Zhang, Xue-Yin Chen, Qiao-Ling Wang, Qiao-Yun Liu, Yue-Ze Zhao, Cao-Li Tang, Lin Ma, Xiao-Hui Zheng, Pei-Fen Zhang, Xi-Zhao Li, Shao-Dan Zhang, Ye-Zhu Hu, Xia Yu, Biao-Hua Wu, Fu-Gui Li, Jian-Hua Wu, Bi-Sen Deng, Xue-Jun Liang, Wei-Hua Jia","doi":"10.1007/s10654-025-01320-y","DOIUrl":"https://doi.org/10.1007/s10654-025-01320-y","url":null,"abstract":"The global rise of non-communicable diseases (NCDs) presents an urgent public health challenge, particularly in regions undergoing rapid economic and demographic transitions. Guangdong Province, China’s most populous and economically advanced region, is experiencing a substantial and accelerating burden of NCDs. However, large-scale, population-based cohorts from this region remain scarce, limiting insights into region-specific disease determinants and prevention strategies. The Guangdong Biobank Cohort (GDBC) was established in 2017, enrolling 35,081 participants aged 40–84 years from urban and rural areas of Zhongshan City in the Pearl River Delta. At baseline, comprehensive data on 346 variables—including lifestyle, environmental exposures, medical histories, physical examinations, and laboratory profiles—were collected via a cloud-based member management information system (MMIS), alongside blood and saliva samples for biobanking. A sub-cohort underwent genome-wide genotyping ( <jats:italic>N</jats:italic> = 2,530) and oral microbiome profiling via 16 S rRNA sequencing ( <jats:italic>N</jats:italic> = 2,049). During dynamic follow-up, 44.2% ( <jats:italic>N</jats:italic> = 15,499) completed Phase I resurvey with repeated measurements and updated biospecimens. Disease outcomes, including hypertension, diabetes, and cancer, were ascertained through active surveillance and regional registry linkage until December 2023. Baseline prevalence of hypertension, diabetes, and cancer was 25.3%, 8.0%, and 3.6%, respectively. Over follow-up, 1,767 hypertension cases, 814 diabetes cases, and 558 cancers were recorded, yielding crude incidence rates of 1,804.6, 649.7, and 423.1 per 100,000 person-years, respectively. The GDBC provides a comprehensive, dynamically updated resource to dissect gene–microbiome–environment interactions and develop precision prevention strategies to inform public health policies.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"1 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Acute lymphoblastic leukemia (ALL) is the most common childhood malignancy. While space-time clustering of ALL cases has been suggested, only one prior study has examined clustering by genetic subtype. We investigated space-time clustering of childhood ALL in Sweden, both overall and by genetic subtype. The cohort included 1,629 children age 0-18 years diagnosed with ALL between 1992 and 2017, comprising 1,446 B-cell precursor ALL (BCP-ALL) and 183 T-cell ALL (T-ALL) cases. Two BCP-ALL subgroups were analyzed: high hyperdiploidy (HeH, n = 466) and ETV6::RUNX1 (n = 225). The Unbiased Knox Test and Unbiased Combined Knox Test were used to assess space-time clustering at the municipality level, accounting for multiple testing and population shifts. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm was applied to identify significant clusters. Logistic regression was used to evaluate demographic differences between clusters, including age, sex, and birth order. Significant space-time clustering was observed in the HeH subgroup for both place and date of birth (p = 0.005) and place and date of diagnosis (p = 0.011), at space-time thresholds of 40 km/18 months and 30 km/24 months, respectively. No clustering was detected in the overall BCP-ALL group, T-ALL group, or the ETV6::RUNX1 subgroup. Space-time clustering at birth and diagnosis was observed in the HeH subgroup, suggesting potential etiologic heterogeneity in BCP-ALL. These findings support further investigation of environmental and infectious exposures across immunophenotypes and genetic subtypes in larger cohorts.
{"title":"Space-time clustering of childhood high hyperdiploid B-cell precursor acute lymphoblastic leukemia: a nationwide Swedish study.","authors":"Gleb Bychkov,Niklas Engsner,Benedicte Bang,Mats Marshall Heyman,Gisela Barbany,Anna Skarin Nordenvall,Giorgio Tettamanti,Claes Strannegård,Ann Nordgren","doi":"10.1007/s10654-025-01323-9","DOIUrl":"https://doi.org/10.1007/s10654-025-01323-9","url":null,"abstract":"Acute lymphoblastic leukemia (ALL) is the most common childhood malignancy. While space-time clustering of ALL cases has been suggested, only one prior study has examined clustering by genetic subtype. We investigated space-time clustering of childhood ALL in Sweden, both overall and by genetic subtype. The cohort included 1,629 children age 0-18 years diagnosed with ALL between 1992 and 2017, comprising 1,446 B-cell precursor ALL (BCP-ALL) and 183 T-cell ALL (T-ALL) cases. Two BCP-ALL subgroups were analyzed: high hyperdiploidy (HeH, n = 466) and ETV6::RUNX1 (n = 225). The Unbiased Knox Test and Unbiased Combined Knox Test were used to assess space-time clustering at the municipality level, accounting for multiple testing and population shifts. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm was applied to identify significant clusters. Logistic regression was used to evaluate demographic differences between clusters, including age, sex, and birth order. Significant space-time clustering was observed in the HeH subgroup for both place and date of birth (p = 0.005) and place and date of diagnosis (p = 0.011), at space-time thresholds of 40 km/18 months and 30 km/24 months, respectively. No clustering was detected in the overall BCP-ALL group, T-ALL group, or the ETV6::RUNX1 subgroup. Space-time clustering at birth and diagnosis was observed in the HeH subgroup, suggesting potential etiologic heterogeneity in BCP-ALL. These findings support further investigation of environmental and infectious exposures across immunophenotypes and genetic subtypes in larger cohorts.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"48 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145949747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss worldwide. However, evidence regarding the relationship between air pollution and AMD is limited, and the modifying effect of genetic susceptibility on this association remains unknown. A total of 445,237 participants without AMD at baseline were included from the UK Biobank. The concentrations of nitrogen dioxide (NO2), nitrogen oxides (NOx), particulate matter (PM2.5, PM10, PM2.5-10) were collected by using land-use regression models. Air pollution score (APS) was constructed through summing each pollutant weighted by the regression coefficients with AMD from single-pollutant model. Cox proportional hazard models were used to evaluate hazard rations (HRs) and 95% confidence intervals (95%CIs) of associations between air pollutants and polygenic risk score (PRS) with incident AMD. During a median follow-up of 13.83 years, we observed 9,635 incident AMD events. The HR (95%CI) of incident AMD for each standard deviation increase in NO2, NOx, PM2.5, PM10, and APS were 1.04(1.02, 1.06), 1.03(1.01, 1.05). 1.04(1.02, 1.07), 1.02(1.00, 1.04), and 1.04(1.02, 1.06), respectively. Significant additive interaction effects of NO2, NOx, PM2.5-10, APS and PRS with incident risk of AMD were observed, with the relative excess risk due to the interaction (RERI), attributable proportion (AP), and their 95% CIs of 0.10(0.01, 0.18) and 0.05(0.01, 0.11) for NO2, 0.11(0.01, 0.19) and 0.05(0.02, 0.10) for NOx, 0.15(0.06, 0.23) and 0.08(0.03, 0.13) for PM2.5-10, and 0.12(0.03, 0.20) and 0.06(0.01, 0.11) for APS, respectively. Compared with participants exposed to low level of above air pollutants and low PRS, those exposed to high air pollution and high PRS had almost double incident risk of AMD [HR(95%CI) ranged from 1.83(1.68, 1.99) to 2.03(1.86, 2.21)]. Long-term exposure to air pollutants NO2, NOx, PM2.5, and PM10 showed positive associations with increased risk of AMD, which could be further enhanced by genetic susceptibility.
{"title":"Air pollutants, genetic susceptibility, and the risk of age-related macular degeneration: a large prospective cohort study.","authors":"Shengli Chen,Gongyue Wang,Xin Guan,Chenming Wang,Yang Xiao,Xingdi Li,Shiru Hong,Yuhan Zhou,Yingqian You,Ye Fu,Yuxi Wang,Yichi Zhang,Hui Zhao,Yingchen Zhang,Yang Cheng,Huan Guo,Huatao Xie","doi":"10.1007/s10654-025-01340-8","DOIUrl":"https://doi.org/10.1007/s10654-025-01340-8","url":null,"abstract":"Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss worldwide. However, evidence regarding the relationship between air pollution and AMD is limited, and the modifying effect of genetic susceptibility on this association remains unknown. A total of 445,237 participants without AMD at baseline were included from the UK Biobank. The concentrations of nitrogen dioxide (NO2), nitrogen oxides (NOx), particulate matter (PM2.5, PM10, PM2.5-10) were collected by using land-use regression models. Air pollution score (APS) was constructed through summing each pollutant weighted by the regression coefficients with AMD from single-pollutant model. Cox proportional hazard models were used to evaluate hazard rations (HRs) and 95% confidence intervals (95%CIs) of associations between air pollutants and polygenic risk score (PRS) with incident AMD. During a median follow-up of 13.83 years, we observed 9,635 incident AMD events. The HR (95%CI) of incident AMD for each standard deviation increase in NO2, NOx, PM2.5, PM10, and APS were 1.04(1.02, 1.06), 1.03(1.01, 1.05). 1.04(1.02, 1.07), 1.02(1.00, 1.04), and 1.04(1.02, 1.06), respectively. Significant additive interaction effects of NO2, NOx, PM2.5-10, APS and PRS with incident risk of AMD were observed, with the relative excess risk due to the interaction (RERI), attributable proportion (AP), and their 95% CIs of 0.10(0.01, 0.18) and 0.05(0.01, 0.11) for NO2, 0.11(0.01, 0.19) and 0.05(0.02, 0.10) for NOx, 0.15(0.06, 0.23) and 0.08(0.03, 0.13) for PM2.5-10, and 0.12(0.03, 0.20) and 0.06(0.01, 0.11) for APS, respectively. Compared with participants exposed to low level of above air pollutants and low PRS, those exposed to high air pollution and high PRS had almost double incident risk of AMD [HR(95%CI) ranged from 1.83(1.68, 1.99) to 2.03(1.86, 2.21)]. Long-term exposure to air pollutants NO2, NOx, PM2.5, and PM10 showed positive associations with increased risk of AMD, which could be further enhanced by genetic susceptibility.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"48 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145949743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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