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}
Pub Date : 2026-01-12DOI: 10.1007/s10654-025-01337-3
Catherine Zhou,Antien L Mooyaart,Nikita Hulscher,Thamila Kerkour,Jasper Ouwerkerk,Marieke W J Louwman,Marlies Wakkee,Yunlei Li,Quirinus J M Voorham,Annette Bruggink,Tamar E C Nijsten,Loes M Hollestein
There is a high need for accurate prognostic models among stage II melanoma to determine who may benefit from (neo)adjuvant systemic therapy. The Dutch Early- Stage Melanoma (D-ESMEL) study was designed to identify new prognostic features in a population-based sample of stage I/II melanoma patients in addition to American Joint Committee of Cancer (AJCC) staging. The validation cohort of the D-ESMEL study employs a nested case-control design. Initially, controls were randomly sampled to develop prognostic that included both known and new prognostic factors to assess the additive value of new prognostic factors. As a consequence, most controls had a very thin melanoma (<1.0 mm) while most cases had a thicker melanoma (>2.0 mm). This resulted in insufficient variability and high weights for stage II controls when applying weighted analyses in absolute risk prediction models. Therefore, randomly sampled controls were re-matched on AJCC stage (stage IA, IB, IIA, IIB, IIC), and new stage-matched controls were collected for cases who could not be rematched. The original D-ESMEL validation cohort included 5,815 stage I/II melanoma patients, of whom 154 developed distant metastasis (cases). 98/154 Cases were stage II and only 24 stage II controls were included, while the stage-matched design now includes 153 stage-matched case-control sets of which 97 stage II cases and 97 stage II controls derived from a population-based cohort of 5,785 stage I/II patients. The updated design increased the biological variability among stage II controls, balanced weights in weighted analyses and thereby facilitating reliable subgroup analyses in this clinically important subgroup.
{"title":"An extension of the validation cohort of the Dutch Early-Stage Melanoma (D-ESMEL) study for stage-specific analyses.","authors":"Catherine Zhou,Antien L Mooyaart,Nikita Hulscher,Thamila Kerkour,Jasper Ouwerkerk,Marieke W J Louwman,Marlies Wakkee,Yunlei Li,Quirinus J M Voorham,Annette Bruggink,Tamar E C Nijsten,Loes M Hollestein","doi":"10.1007/s10654-025-01337-3","DOIUrl":"https://doi.org/10.1007/s10654-025-01337-3","url":null,"abstract":"There is a high need for accurate prognostic models among stage II melanoma to determine who may benefit from (neo)adjuvant systemic therapy. The Dutch Early- Stage Melanoma (D-ESMEL) study was designed to identify new prognostic features in a population-based sample of stage I/II melanoma patients in addition to American Joint Committee of Cancer (AJCC) staging. The validation cohort of the D-ESMEL study employs a nested case-control design. Initially, controls were randomly sampled to develop prognostic that included both known and new prognostic factors to assess the additive value of new prognostic factors. As a consequence, most controls had a very thin melanoma (<1.0 mm) while most cases had a thicker melanoma (>2.0 mm). This resulted in insufficient variability and high weights for stage II controls when applying weighted analyses in absolute risk prediction models. Therefore, randomly sampled controls were re-matched on AJCC stage (stage IA, IB, IIA, IIB, IIC), and new stage-matched controls were collected for cases who could not be rematched. The original D-ESMEL validation cohort included 5,815 stage I/II melanoma patients, of whom 154 developed distant metastasis (cases). 98/154 Cases were stage II and only 24 stage II controls were included, while the stage-matched design now includes 153 stage-matched case-control sets of which 97 stage II cases and 97 stage II controls derived from a population-based cohort of 5,785 stage I/II patients. The updated design increased the biological variability among stage II controls, balanced weights in weighted analyses and thereby facilitating reliable subgroup analyses in this clinically important subgroup.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"94 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145949746","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 : 2026-01-12DOI: 10.1007/s10654-025-01336-4
Amalie Helme Simoni,Kathrine Hald,Thure Filskov Overvad,Mette Søgaard,Anne Gulbech Ording
The Danish National Patient Registry (DNPR) and the Danish Cancer Registry (DCR) are central to registry-based cancer research. This systematic review evaluates studies assessing the quality of cancer-related data in these registries under their current data structures. PubMed and Embase were systematically searched on January 24, 2025 (PROSPERO: CRD420251005952). Studies validating cancer-related data in the DNPR or DCR against a gold standard were included. Findings were synthesized narratively and categorized by DNPR data, DCR data, or multi-source algorithms. The literature search generated 915 records, of which 50 were included: 23 validated DNPR data, 9 DCR data, and 18 algorithm performance. The quality of DNPR cancer diagnoses and treatment showed positive predictive values (PPVs) of 57-100%, highest for common malignancies and treatments. The quality of DNPR comorbidities and complications varied substantially (PPVs 0-98%). The PPV of a melanoma diagnosis in the DCR was 97%. The DCR staging completeness varied considerably (34-95%). Algorithms presented PPVs of 60-96% for recurrence, active cancer, and recognized metastases, and 28% for unrecognized metastases. The DNPR and DCR provide high-quality data for many cancer diagnoses, treatments, and outcomes, supporting their use in register-based research. While some data elements, including data on complications, exhibit lower quality, algorithmic approaches can enhance utility for less robust data. However, several aspects of cancer-related data remain unvalidated.
{"title":"Quality of cancer-related data from the Danish National patient registry (1994-2025) and the Danish cancer registry (2004-2025): a systematic review.","authors":"Amalie Helme Simoni,Kathrine Hald,Thure Filskov Overvad,Mette Søgaard,Anne Gulbech Ording","doi":"10.1007/s10654-025-01336-4","DOIUrl":"https://doi.org/10.1007/s10654-025-01336-4","url":null,"abstract":"The Danish National Patient Registry (DNPR) and the Danish Cancer Registry (DCR) are central to registry-based cancer research. This systematic review evaluates studies assessing the quality of cancer-related data in these registries under their current data structures. PubMed and Embase were systematically searched on January 24, 2025 (PROSPERO: CRD420251005952). Studies validating cancer-related data in the DNPR or DCR against a gold standard were included. Findings were synthesized narratively and categorized by DNPR data, DCR data, or multi-source algorithms. The literature search generated 915 records, of which 50 were included: 23 validated DNPR data, 9 DCR data, and 18 algorithm performance. The quality of DNPR cancer diagnoses and treatment showed positive predictive values (PPVs) of 57-100%, highest for common malignancies and treatments. The quality of DNPR comorbidities and complications varied substantially (PPVs 0-98%). The PPV of a melanoma diagnosis in the DCR was 97%. The DCR staging completeness varied considerably (34-95%). Algorithms presented PPVs of 60-96% for recurrence, active cancer, and recognized metastases, and 28% for unrecognized metastases. The DNPR and DCR provide high-quality data for many cancer diagnoses, treatments, and outcomes, supporting their use in register-based research. While some data elements, including data on complications, exhibit lower quality, algorithmic approaches can enhance utility for less robust data. However, several aspects of cancer-related data remain unvalidated.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"82 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145949767","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 : 2026-01-12DOI: 10.1007/s10654-025-01346-2
Magdalena Muszynska-Spielauer,Paola Di Giulio,Yuka Minagawa,Vanessa Di Lego,Marc Luy
This study tests the "longevity hypothesis," which posits that women's greater number of years spent in poor health is primarily a direct consequence of their longer survival. We analyse gender differences in unhealthy life years (ULY) at age 50 across 22 European countries in 2015-2017. ULY was estimated using three approaches-the Sullivan method, the cross-sectional average length of healthy life, and multistate life tables-applied to four health indicators of varying severity: chronic diseases, functional limitations, self-rated health, and disability. Data were drawn from the Human Mortality Database and the Survey of Health, Ageing and Retirement in Europe. We decomposed the gender gap in ULY into a "mortality effect" (ME), reflecting differences in life years lived, and a "health effect" (HE), reflecting differences in morbidity prevalence. Women at age 50 lived more unhealthy years than men across almost all health indicators and countries. In most cases, more than half of the gender gap in ULY was attributable to the ME, indicating that women's longer survival primarily explains their greater number of years spent in poor health. The HE showed greater variation across indicators and countries. Results were most consistent for chronic diseases and self-rated health, while functional limitations and disability yielded smaller and less consistent differences. Findings support the longevity hypothesis: women's higher life expectancy is the main driver of their longer lifetime spent in poor health. The variation across health dimensions highlights the importance of distinguishing between them when studying gender inequalities in health.
{"title":"Why do women live longer than men, but spend more time in poor health? A decomposition analysis of the gender gap in unhealthy life years across Europe.","authors":"Magdalena Muszynska-Spielauer,Paola Di Giulio,Yuka Minagawa,Vanessa Di Lego,Marc Luy","doi":"10.1007/s10654-025-01346-2","DOIUrl":"https://doi.org/10.1007/s10654-025-01346-2","url":null,"abstract":"This study tests the \"longevity hypothesis,\" which posits that women's greater number of years spent in poor health is primarily a direct consequence of their longer survival. We analyse gender differences in unhealthy life years (ULY) at age 50 across 22 European countries in 2015-2017. ULY was estimated using three approaches-the Sullivan method, the cross-sectional average length of healthy life, and multistate life tables-applied to four health indicators of varying severity: chronic diseases, functional limitations, self-rated health, and disability. Data were drawn from the Human Mortality Database and the Survey of Health, Ageing and Retirement in Europe. We decomposed the gender gap in ULY into a \"mortality effect\" (ME), reflecting differences in life years lived, and a \"health effect\" (HE), reflecting differences in morbidity prevalence. Women at age 50 lived more unhealthy years than men across almost all health indicators and countries. In most cases, more than half of the gender gap in ULY was attributable to the ME, indicating that women's longer survival primarily explains their greater number of years spent in poor health. The HE showed greater variation across indicators and countries. Results were most consistent for chronic diseases and self-rated health, while functional limitations and disability yielded smaller and less consistent differences. Findings support the longevity hypothesis: women's higher life expectancy is the main driver of their longer lifetime spent in poor health. The variation across health dimensions highlights the importance of distinguishing between them when studying gender inequalities in health.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"30 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145949744","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 : 2026-01-12DOI: 10.1007/s10654-025-01338-2
Marius Johansen,Tone Kristin Omsland,Katariina Laine,Siri Eldevik Håberg,Maria Christine Magnus
Women with endometriosis have a higher burden of anxiety and depression. Whether they are at increased risk of postpartum depression (PPD) remains unclear. We aimed to compare the risk of PPD between women with and without endometriosis and to explore mediation by previous history of major depression and infertility. In a population-based cohort study, we compared 1,159 singleton pregnancies to women with self-reported endometriosis and 74,590 pregnancies to women without endometriosis. We calculated a djusted risk ratios (aRR) with 95% confidence intervals (CI) using multivariable log-binomial regression, adjusting for age, body mass index, education and income. Mediation analyses assessed the indirect effect of any history of major depression or infertility. Women with endometriosis had a higher risk of PPD (aRR: 1.34, 95% CI: 1.15-1.55). Mediation analyses indicated that a large part of this association was explained by a higher lifetime prevalence of major depression among women with endometriosis (natural direct effect of endometriosis: aRR: 1.17, 95% CI: 1.00-1.36; natural indirect effect of any history of major depression: aRR: 1.14, 95% CI: 1.08-1.20), with 49.3% proportion mediated. Infertility demonstrated a negative natural indirect effect on the association between endometriosis and PPD (aRR: 0.87, 95% CI: 0.81-0.94). Women with endometriosis had an elevated risk of PPD which was largely explained by a higher lifetime prevalence of major depression. Our findings suggest that they constitute a high-risk group and could benefit from closer follow-up to facilitate early identification and intervention.
{"title":"Risk of postpartum depression among women with endometriosis: the Norwegian mother, father and child cohort study (MoBa).","authors":"Marius Johansen,Tone Kristin Omsland,Katariina Laine,Siri Eldevik Håberg,Maria Christine Magnus","doi":"10.1007/s10654-025-01338-2","DOIUrl":"https://doi.org/10.1007/s10654-025-01338-2","url":null,"abstract":"Women with endometriosis have a higher burden of anxiety and depression. Whether they are at increased risk of postpartum depression (PPD) remains unclear. We aimed to compare the risk of PPD between women with and without endometriosis and to explore mediation by previous history of major depression and infertility. In a population-based cohort study, we compared 1,159 singleton pregnancies to women with self-reported endometriosis and 74,590 pregnancies to women without endometriosis. We calculated a djusted risk ratios (aRR) with 95% confidence intervals (CI) using multivariable log-binomial regression, adjusting for age, body mass index, education and income. Mediation analyses assessed the indirect effect of any history of major depression or infertility. Women with endometriosis had a higher risk of PPD (aRR: 1.34, 95% CI: 1.15-1.55). Mediation analyses indicated that a large part of this association was explained by a higher lifetime prevalence of major depression among women with endometriosis (natural direct effect of endometriosis: aRR: 1.17, 95% CI: 1.00-1.36; natural indirect effect of any history of major depression: aRR: 1.14, 95% CI: 1.08-1.20), with 49.3% proportion mediated. Infertility demonstrated a negative natural indirect effect on the association between endometriosis and PPD (aRR: 0.87, 95% CI: 0.81-0.94). Women with endometriosis had an elevated risk of PPD which was largely explained by a higher lifetime prevalence of major depression. Our findings suggest that they constitute a high-risk group and could benefit from closer follow-up to facilitate early identification and intervention.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"24 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145949750","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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