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description Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2019 United KingdomPublisher:American Thoracic Society Funded by:WT | The Kadoorie Biobank stud..., WT | China Kadoorie Biobank (C..., UKRI | Assessing health risks as... +1 projectsWT| The Kadoorie Biobank study. ,WT| China Kadoorie Biobank (CKB) of 0.5 million adults. ,UKRI| Assessing health risks associated with exposure to household and ambient air pollution in rural and urban China ,WT| China Kadoorie Biobank (CKB) prospective study of 0.5 million adultsKa Hung Chan; Om P. Kurmi; Derrick A. Bennett; Ling Yang; Yiping Chen; Yunlong Tan; Pei Pei; Xunfu Zhong; Jianxin Chen; Jun Zhang; Haidong Kan; Richard Peto; Kin Bong Hubert Lam; Zhengming Chen; Junshi Chen; Zhengming Chen; Robert Clarke; Rory Collins; Yu Guo; Liming Li; Jun Lv; Richard Peto; Robin Walters; Daniel Avery; Derrick Bennett; Ruth Boxall; Yumei Chang; Yiping Chen; Zhengming Chen; Robert Clarke; Huaidong Du; Simon Gilbert; Alex Hacker; Michael Holmes; Christiana Kartsonaki; Rene Kerosi; Garry Lancaster; Kuang Lin; John McDonnell; Iona Millwood; Qunhua Nie; Jayakrishnan Radhakrishnan; Paul Ryder; Sam Sansome; Dan Schmidt; Rajani Sohoni; Becky Stevens; Iain Turnbull; Robin Walters; Jenny Wang; Lin Wang; Neil Wright; Ling Yang; Xiaoming Yang; Zheng Bian; Yu Guo; Xiao Han; Can Hou; Jun Lv; Pei Pei; Chao Liu; Biao Jing; Yunlong Tan; Canqing Yu; Zengchang Pang; Ruqin Gao; Shanpeng Li; Shaojie Wang; Yongmei Liu; Ranran Du; Yajing Zang; Liang Cheng; Xiaocao Tian; Hua Zhang; Yaoming Zhai; Feng Ning; Xiaohui Sun; Feifei Li; Silu Lv; Junzheng Wang; Wei Hou; Mingyuan Zeng; Ge Jiang; Xue Zhou; Liqiu Yang; Hui He; Bo Yu; Yanjie Li; Qinai Xu; Quan Kang; Ziyan Guo; Dan Wang; Ximin Hu; Hongmei Wang; Jinyan Chen; Yan Fu; Zhenwang Fu; Xiaohuan Wang; Min Weng; Zhendong Guo; Shukuan Wu; Yilei Li; Huimei Li; Zhifang Fu; Ming Wu; Yonglin Zhou; Jinyi Zhou; Ran Tao; Jie Yang; Jian Su; Fang Liu; Jun Zhang; Yihe Hu; Yan Lu; Liangcai Ma; Aiyu Tang; Shuo Zhang; Jianrong Jin; Jingchao Liu; Zhenzhu Tang; Naying Chen; Ying Huang; Mingqiang Li; Jinhuai Meng; Rong Pan; Qilian Jiang; Jian Lan; Yun Liu; Liuping Wei; Liyuan Zhou; Ningyu Chen; Ping Wang; Fanwen Meng; Yulu Qin; Sisi Wang; Xianping Wu; Ningmei Zhang; Xiaofang Chen; Weiwei Zhou; Guojin Luo; Jianguo Li; Xiaofang Chen; Xunfu Zhong; Jiaqiu Liu; Qiang Sun; Pengfei Ge; Xiaolan Ren; Caixia Dong; Hui Zhang; Enke Mao; Xiaoping Wang; Tao Wang; Xi Zhang; Ding Zhang; Gang Zhou; Shixian Feng; Liang Chang; Lei Fan; Yulian Gao; Tianyou He; Huarong Sun; Chen Hu; Xukui Zhang; Huifang Wu; Pan He; Min Yu; Ruying Hu; Hao Wang; Yijian Qian; Chunmei Wang; Kaixu Xie; Lingli Chen; Yidan Zhang; Dongxia Pan; Qijun Gu; Yuelong Huang; Biyun Chen; Li Yin; Huilin Liu; Zhongxi Fu; Qiaohua Xu; Xin Xu; Hao Zhang; Huajun Long; Xianzhi Li; Libo Zhang; Zhe Qiu;Little evidence from large-scale cohort studies exists about the relationship of solid fuel use with hospitalization and mortality from major respiratory diseases.To examine the associations of solid fuel use and risks of acute and chronic respiratory diseases.A cohort study of 277,838 Chinese never-smokers with no prior major chronic diseases at baseline. During 9 years of follow-up, 19,823 first hospitalization episodes or deaths from major respiratory diseases, including 10,553 chronic lower respiratory disease (CLRD), 4,398 chronic obstructive pulmonary disease (COPD), and 7,324 acute lower respiratory infection (ALRI), were recorded. Cox regression yielded adjusted hazard ratios (HRs) for disease risks associated with self-reported primary cooking fuel use.Overall, 91% of participants reported regular cooking, with 52% using solid fuels. Compared with clean fuel users, solid fuel users had an adjusted HR of 1.36 (95% confidence interval, 1.32-1.40) for major respiratory diseases, whereas those who switched from solid to clean fuels had a weaker HR (1.14, 1.10-1.17). The HRs were higher in wood (1.37, 1.33-1.41) than coal users (1.22, 1.15-1.29) and in those with prolonged use (≥40 yr, 1.54, 1.48-1.60; <20 yr, 1.32, 1.26-1.39), but lower among those who used ventilated than nonventilated cookstoves (1.22, 1.19-1.25 vs. 1.29, 1.24-1.35). For CLRD, COPD, and ALRI, the HRs associated with solid fuel use were 1.47 (1.41-1.52), 1.10 (1.03-1.18), and 1.16 (1.09-1.23), respectively.Among Chinese adults, solid fuel use for cooking was associated with higher risks of major respiratory disease admissions and death, and switching to clean fuels or use of ventilated cookstoves had lower risk than not switching.
American Journal of ... arrow_drop_down American Journal of Respiratory and Critical Care MedicineArticleLicense: CC BYData sources: UnpayWallOxford University Research ArchiveArticle . 2018License: CC BYData sources: Oxford University Research ArchiveAmerican Journal of Respiratory and Critical Care MedicineArticle . 2019 . Peer-reviewedData sources: CrossrefAmerican Journal of Respiratory and Critical Care MedicineArticle . 2019Data sources: Europe PubMed CentralAmerican Journal of Respiratory and Critical Care MedicineJournalData sources: Microsoft Academic Graphadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 63 citations 63 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert American Journal of ... arrow_drop_down American Journal of Respiratory and Critical Care MedicineArticleLicense: CC BYData sources: UnpayWallOxford University Research ArchiveArticle . 2018License: CC BYData sources: Oxford University Research ArchiveAmerican Journal of Respiratory and Critical Care MedicineArticle . 2019 . Peer-reviewedData sources: CrossrefAmerican Journal of Respiratory and Critical Care MedicineArticle . 2019Data sources: Europe PubMed CentralAmerican Journal of Respiratory and Critical Care MedicineJournalData sources: Microsoft Academic Graphadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2018 United KingdomPublisher:American Medical Association (AMA) Canqing Yu; Yiping Chen; Tangchun Wu; Derrick A Bennett; Om P Kurmi; An Pan; Jun Lv; Gaokun Qiu; Liming Li; Liming Li; Frank B. Hu; Kuai Yu; Kin Bong Hubert Lam; Yu Guo; Zheng Bian; Zhengming Chen; Ling Yang; Ka Hung Chan;When combusted indoors, solid fuels generate a large amount of pollutants such as fine particulate matter.To assess the associations of solid fuel use for cooking and heating with cardiovascular and all-cause mortality.This nationwide prospective cohort study recruited participants from 5 rural areas across China between June 2004 and July 2008; mortality follow-up was until January 1, 2014. A total of 271 217 adults without a self-reported history of physician-diagnosed cardiovascular disease at baseline were included, with a random subset (n = 10 892) participating in a resurvey after a mean interval of 2.7 years.Self-reported primary cooking and heating fuels (solid: coal, wood, or charcoal; clean: gas, electricity, or central heating), switching of fuel type before baseline, and use of ventilated cookstoves.Death from cardiovascular and all causes, collected through established death registries.Among the 271 217 participants, the mean (SD) age was 51.0 (10.2) years, and 59% (n = 158 914) were women. A total of 66% (n = 179 952) of the participants reported regular cooking (at least weekly) and 60% (n = 163 882) reported winter heating, of whom 84% (n = 150 992) and 90% (n = 147 272) used solid fuels, respectively. There were 15 468 deaths, including 5519 from cardiovascular causes, documented during a mean (SD) of 7.2 (1.4) years of follow-up. Use of solid fuels for cooking was associated with greater risk of cardiovascular mortality (absolute rate difference [ARD] per 100 000 person-years, 135 [95% CI, 77-193]; hazard ratio [HR], 1.20 [95% CI, 1.02-1.41]) and all-cause mortality (ARD, 338 [95% CI, 249-427]; HR, 1.11 [95% CI, 1.03-1.20]). Use of solid fuels for heating was also associated with greater risk of cardiovascular mortality (ARD, 175 [95% CI, 118-231]; HR, 1.29 [95% CI, 1.06-1.55]) and all-cause mortality (ARD, 392 [95% CI, 297-487]; HR, 1.14 [95% CI, 1.03-1.26]). Compared with persistent solid fuel users, participants who reported having previously switched from solid to clean fuels for cooking had a lower risk of cardiovascular mortality (ARD, 138 [95% CI, 71-205]; HR, 0.83 [95% CI, 0.69-0.99]) and all-cause mortality (ARD, 407 [95% CI, 317-497]; HR, 0.87 [95% CI, 0.79-0.95]), while for heating, the ARDs were 193 (95% CI, 128-258) and 492 (95% CI, 383-601), and the HRs were 0.57 (95% CI, 0.42-0.77) and 0.67 (95% CI, 0.57-0.79), respectively. Among solid fuel users, use of ventilated cookstoves was also associated with lower risk of cardiovascular mortality (ARD, 33 [95% CI, -9 to 75]; HR, 0.89 [95% CI, 0.80-0.99]) and all-cause mortality (ARD, 87 [95% CI, 20-153]; HR, 0.91 [95% CI, 0.85-0.96]).In rural China, solid fuel use for cooking and heating was associated with higher risks of cardiovascular and all-cause mortality. These risks may be lower among those who had previously switched to clean fuels and those who used ventilation.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 233 citations 233 popularity Top 0.1% influence Top 1% impulse Top 1% Powered by BIP!
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2019 United KingdomPublisher:Oxford University Press (OUP) Funded by:UKRI | Assessing health risks as..., WT, WT | China Kadoorie Biobank (C... +2 projectsUKRI| Assessing health risks associated with exposure to household and ambient air pollution in rural and urban China ,WT ,WT| China Kadoorie Biobank (CKB) prospective study of 0.5 million adults ,WT| The Kadoorie Biobank study. ,WT| China Kadoorie Biobank (CKB) of 0.5 million adults.Jun Lv; Derrick A Bennett; Om P Kurmi; Lin Li; Xiaofang Chen; Yu Guo; Lam Kbh.; Yiping Chen; Yiping Chen; C Dong; Zheng Bian; Ka Hung Chan; Chuanhua Yu; Ling Yang; Ling Yang; Zhengming Chen; Zhengming Chen;Abstract Background Harmful substances in solid fuel and tobacco smoke are believed to enter the bloodstream via inhalation and to be metabolized in the liver, leading to chronic liver damage. However, little is known about the independent and joint effects of solid fuel use and smoking on risks of chronic liver disease (CLD) mortality. Methods During 2004–08, ∼0.5 million adults aged 30–79 years were recruited from 10 areas across China. During a 10-year median follow-up, 2461 CLD deaths were recorded. Multivariable Cox regression yielded adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for the individual associations of self-reported long-term cooking fuel and tobacco use with major CLD death. Results Overall, 49% reported solid fuel use and 26% smoked regularly. Long-term solid fuel use for cooking and current smoking were associated with higher risks of CLD deaths, with adjusted HRs of 1.26 (95% CI, 1.02–1.56) and 1.28 (1.13–1.44), respectively. Compared with never-smoking clean fuel users, the HRs were 1.41 (1.10–1.82) in never-smoking solid fuel users, 1.55 (1.17–2.06) in regular-smoking clean fuel users and 1.71 (1.32–2.20) in regular-smoking solid fuels users. Individuals who had switched from solid to clean fuels (1.07, 0.90–1.29; for median 14 years) and ex-regular smokers who stopped for non-medical reasons (1.16, 0.95–1.43; for median 10 years) had no evidence of excess risk of CLD deaths compared with clean fuel users and never-regular smokers, respectively. Conclusions Among Chinese adults, long-term solid fuel use for cooking and smoking were each independently associated with higher risks of CLD deaths. Individuals who had stopped using solid fuels or smoking had lower risks.
International Journa... arrow_drop_down International Journal of EpidemiologyArticle . 2019 . Peer-reviewedLicense: CC BYData sources: CrossrefOxford University Research ArchiveArticle . 2019License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/ije/dyz216&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 21 citations 21 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert International Journa... arrow_drop_down International Journal of EpidemiologyArticle . 2019 . Peer-reviewedLicense: CC BYData sources: CrossrefOxford University Research ArchiveArticle . 2019License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/ije/dyz216&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2024Publisher:Springer Science and Business Media LLC Funded by:UKRI | China Kadoorie Biobank (C..., UKRI | Assessing health risks as..., UKRI | China Kadoorie Biobank of... +5 projectsUKRI| China Kadoorie Biobank (CKB) prospective study of 0.5 million adults ,UKRI| Assessing health risks associated with exposure to household and ambient air pollution in rural and urban China ,UKRI| China Kadoorie Biobank of 500,000 people aged 30-79 ,WT| China Kadoorie Biobank of 0.5 million adults ,WT| China Kadoorie Biobank (CKB) prospective study of 0.5 million adults ,WT| The Kadoorie Biobank study. ,WT| China Kadoorie Biobank (CKB) of 0.5 million adults. ,UKRI| China Kadoorie Biobank (CKB)Xi Xia; Ka Hung Chan; Yue Niu; Cong Liu; Yitong Guo; Kin-Fai Ho; Steve Hung-Lam Yim; Baihan Wang; Aiden Doherty; Daniel Avery; Pei Pei; Canqing Yu; Dianjianyi Sun; Jun Lv; Junshi Chen; Liming Li; Peng Wen; Shaowei Wu; Kin Bong Hubert Lam*; Haidong Kan*; Zhengming Chen*;Abstract The reliance of outdoor exposure data in epidemiological studies on temperature entails important uncertainties from personal exposure misclassification. We analysed ~88,000 concurrent person-hours of measured personal, household (kitchen and living room), and outdoor temperatures collected in the summer (MAY-SEP 2017) and winter (NOV 2017-JAN 2018) in rural and urban China. The temperatures across microenvironments were strongly correlated (Spearman’s ρ: 0.86-0.92) in summer. In winter, personal temperature was strongly related to household temperatures (ρ: 0.74-0.79) but poorly related to outdoor temperature (ρ: 0.30). Random forest (RF) algorithm identified household and outdoor temperatures and study date as top predictors of personal temperature exposure for both seasons, and heating-related factors were important in winter. Multivariable linear regression and RF models incorporating questionnaire and device data performed satisfactorily in predicting personal exposure in both seasons (R2summer: 0.92; R2winter: 0.68-0.70). Using generalised additive mixed effect models, we found consistent U-shaped associations between measured and predicted personal temperature exposures and heart rate (lowest at ~14.5ºC), but a weak positive linear association with outdoor temperature. Personal and outdoor temperatures differ substantially in winter, but prediction models incorporating household and outdoor temperatures and questionnaire data performed satisfactorily. Exposure misclassification from using outdoor temperature may produce inappropriate epidemiological findings.
https://doi.org/10.2... arrow_drop_down https://doi.org/10.21203/rs.3....Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefhttps://doi.org/10.21203/rs.3....Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21203/rs.3.rs-4547455/v2&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!
more_vert https://doi.org/10.2... arrow_drop_down https://doi.org/10.21203/rs.3....Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefhttps://doi.org/10.21203/rs.3....Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21203/rs.3.rs-4547455/v2&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2023 United KingdomPublisher:Springer Science and Business Media LLC Funded by:UKRI | China Kadoorie Biobank of..., WT | China Kadoorie Biobank of..., WT | China Kadoorie Biobank (C... +5 projectsUKRI| China Kadoorie Biobank of 500,000 people aged 30-79 ,WT| China Kadoorie Biobank of 0.5 million adults ,WT| China Kadoorie Biobank (CKB) prospective study of 0.5 million adults ,UKRI| A Real-time Digital Platform for Industry 4.0 Manufacturer Insurance ,UKRI| China Kadoorie Biobank (CKB) prospective study of 0.5 million adults ,WT| The Kadoorie Biobank study. ,WT| China Kadoorie Biobank (CKB) of 0.5 million adults. ,UKRI| China Kadoorie Biobank (CKB)Pek Kei Im; Neil Wright; Ling Yang; Ka Hung Chan; Yiping Chen; Yu Guo; Huaidong Du; Xiaoming Yang; Daniel Avery; Shaojie Wang; Canqing Yu; Jun Lv; Robert Clarke; Junshi Chen; Rory Collins; Robin G. Walters; Richard Peto; Liming Li; Zhengming Chen; Iona Y. Millwood; Chen Wang; Maxim Barnard; Derrick Bennett; Ruth Boxall; Johnathan Clarke; Ahmed Edris Mohamed; Hannah Fry; Simon Gilbert; Andri Iona; Maria Kakkoura; Christiana Kartsonaki; Hubert Lam; Kuang Lin; James Liu; Mohsen Mazidi; Sam Morris; Qunhua Nie; Alfred Pozarickij; Paul Ryder; Saredo Said; Dan Schmidt; Becky Stevens; Iain Turnbull; Baihan Wang; Lin Wang; Pang Yao; Xiao Han; Can Hou; Qingmei Xia; Chao Liu; Pei Pei; Dianjianyi Sun; Naying Chen; Duo Liu; Zhenzhu Tang; Ningyu Chen; Qilian Jiang; Jian Lan; Mingqiang Li; Yun Liu; Fanwen Meng; Jinhuai Meng; Rong Pan; Yulu Qin; Ping Wang; Sisi Wang; Liuping Wei; Liyuan Zhou; Caixia Dong; Pengfei Ge; Xiaolan Ren; Zhongxiao Li; Enke Mao; Tao Wang; Hui Zhang; Xi Zhang; Jinyan Chen; Ximin Hu; Xiaohuan Wang; Zhendong Guo; Huimei Li; Yilei Li; Min Weng; Shukuan Wu; Shichun Yan; Mingyuan Zou; Xue Zhou; Ziyan Guo; Quan Kang; Yanjie Li; Bo Yu; Qinai Xu; Liang Chang; Lei Fan; Shixian Feng; Ding Zhang; Gang Zhou; Yulian Gao; Tianyou He; Pan He; Chen Hu; Huarong Sun; Xukui Zhang; Biyun Chen; Zhongxi Fu; Yuelong Huang; Huilin Liu; Qiaohua Xu; Li Yin; Huajun Long; Xin Xu; Hao Zhang; Libo Zhang; Jian Su; Ran Tao; Ming Wu; Jie Yang; Jinyi Zhou; Yonglin Zhou; Yihe Hu; Yujie Hua; Jianrong Jin; Fang Liu; Jingchao Liu; Yan Lu; Liangcai Ma; Aiyu Tang; Jun Zhang; Liang Cheng; Ranran Du; Ruqin Gao; Feifei Li; Shanpeng Li; Yongmei Liu; Feng Ning; Zengchang Pang; Xiaohui Sun; Xiaocao Tian; Yaoming Zhai; Hua Zhang; Wei Hou; Silu Lv; Junzheng Wang; Xiaofang Chen; Xianping Wu; Ningmei Zhang; Xiaoyu Chang; Xiaofang Chen; Jianguo Li; Jiaqiu Liu; Guojin Luo; Qiang Sun; Xunfu Zhong; Weiwei Gong; Ruying Hu; Hao Wang; Meng Wang; Min Yu; Lingli Chen; Qijun Gu; Dongxia Pan; Chunmei Wang; Kaixu Xie; Xiaoyi Zhang;AbstractAlcohol consumption accounts for ~3 million annual deaths worldwide, but uncertainty persists about its relationships with many diseases. We investigated the associations of alcohol consumption with 207 diseases in the 12-year China Kadoorie Biobank of >512,000 adults (41% men), including 168,050 genotyped forALDH2-rs671andADH1B-rs1229984, with >1.1 million ICD-10 coded hospitalized events. At baseline, 33% of men drank alcohol regularly. Among men, alcohol intake was positively associated with 61 diseases, including 33 not defined by the World Health Organization as alcohol-related, such as cataract (n = 2,028; hazard ratio 1.21; 95% confidence interval 1.09–1.33, per 280 g per week) and gout (n = 402; 1.57, 1.33–1.86). Genotype-predicted mean alcohol intake was positively associated with established (n = 28,564; 1.14, 1.09–1.20) and new alcohol-associated (n = 16,138; 1.06, 1.01–1.12) diseases, and with specific diseases such as liver cirrhosis (n = 499; 2.30, 1.58–3.35), stroke (n = 12,176; 1.38, 1.27–1.49) and gout (n = 338; 2.33, 1.49–3.62), but not ischemic heart disease (n = 8,408; 1.04, 0.94–1.14). Among women, 2% drank alcohol resulting in low power to assess associations of self-reported alcohol intake with disease risks, but genetic findings in women suggested the excess male risks were not due to pleiotropic genotypic effects. Among Chinese men, alcohol consumption increased multiple disease risks, highlighting the need to strengthen preventive measures to reduce alcohol intake.
Nature Medicine arrow_drop_down Oxford University Research ArchiveArticle . 2023License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41591-023-02383-8&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 86 citations 86 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Nature Medicine arrow_drop_down Oxford University Research ArchiveArticle . 2023License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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description Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2019 United KingdomPublisher:American Thoracic Society Funded by:WT | The Kadoorie Biobank stud..., WT | China Kadoorie Biobank (C..., UKRI | Assessing health risks as... +1 projectsWT| The Kadoorie Biobank study. ,WT| China Kadoorie Biobank (CKB) of 0.5 million adults. ,UKRI| Assessing health risks associated with exposure to household and ambient air pollution in rural and urban China ,WT| China Kadoorie Biobank (CKB) prospective study of 0.5 million adultsKa Hung Chan; Om P. Kurmi; Derrick A. Bennett; Ling Yang; Yiping Chen; Yunlong Tan; Pei Pei; Xunfu Zhong; Jianxin Chen; Jun Zhang; Haidong Kan; Richard Peto; Kin Bong Hubert Lam; Zhengming Chen; Junshi Chen; Zhengming Chen; Robert Clarke; Rory Collins; Yu Guo; Liming Li; Jun Lv; Richard Peto; Robin Walters; Daniel Avery; Derrick Bennett; Ruth Boxall; Yumei Chang; Yiping Chen; Zhengming Chen; Robert Clarke; Huaidong Du; Simon Gilbert; Alex Hacker; Michael Holmes; Christiana Kartsonaki; Rene Kerosi; Garry Lancaster; Kuang Lin; John McDonnell; Iona Millwood; Qunhua Nie; Jayakrishnan Radhakrishnan; Paul Ryder; Sam Sansome; Dan Schmidt; Rajani Sohoni; Becky Stevens; Iain Turnbull; Robin Walters; Jenny Wang; Lin Wang; Neil Wright; Ling Yang; Xiaoming Yang; Zheng Bian; Yu Guo; Xiao Han; Can Hou; Jun Lv; Pei Pei; Chao Liu; Biao Jing; Yunlong Tan; Canqing Yu; Zengchang Pang; Ruqin Gao; Shanpeng Li; Shaojie Wang; Yongmei Liu; Ranran Du; Yajing Zang; Liang Cheng; Xiaocao Tian; Hua Zhang; Yaoming Zhai; Feng Ning; Xiaohui Sun; Feifei Li; Silu Lv; Junzheng Wang; Wei Hou; Mingyuan Zeng; Ge Jiang; Xue Zhou; Liqiu Yang; Hui He; Bo Yu; Yanjie Li; Qinai Xu; Quan Kang; Ziyan Guo; Dan Wang; Ximin Hu; Hongmei Wang; Jinyan Chen; Yan Fu; Zhenwang Fu; Xiaohuan Wang; Min Weng; Zhendong Guo; Shukuan Wu; Yilei Li; Huimei Li; Zhifang Fu; Ming Wu; Yonglin Zhou; Jinyi Zhou; Ran Tao; Jie Yang; Jian Su; Fang Liu; Jun Zhang; Yihe Hu; Yan Lu; Liangcai Ma; Aiyu Tang; Shuo Zhang; Jianrong Jin; Jingchao Liu; Zhenzhu Tang; Naying Chen; Ying Huang; Mingqiang Li; Jinhuai Meng; Rong Pan; Qilian Jiang; Jian Lan; Yun Liu; Liuping Wei; Liyuan Zhou; Ningyu Chen; Ping Wang; Fanwen Meng; Yulu Qin; Sisi Wang; Xianping Wu; Ningmei Zhang; Xiaofang Chen; Weiwei Zhou; Guojin Luo; Jianguo Li; Xiaofang Chen; Xunfu Zhong; Jiaqiu Liu; Qiang Sun; Pengfei Ge; Xiaolan Ren; Caixia Dong; Hui Zhang; Enke Mao; Xiaoping Wang; Tao Wang; Xi Zhang; Ding Zhang; Gang Zhou; Shixian Feng; Liang Chang; Lei Fan; Yulian Gao; Tianyou He; Huarong Sun; Chen Hu; Xukui Zhang; Huifang Wu; Pan He; Min Yu; Ruying Hu; Hao Wang; Yijian Qian; Chunmei Wang; Kaixu Xie; Lingli Chen; Yidan Zhang; Dongxia Pan; Qijun Gu; Yuelong Huang; Biyun Chen; Li Yin; Huilin Liu; Zhongxi Fu; Qiaohua Xu; Xin Xu; Hao Zhang; Huajun Long; Xianzhi Li; Libo Zhang; Zhe Qiu;Little evidence from large-scale cohort studies exists about the relationship of solid fuel use with hospitalization and mortality from major respiratory diseases.To examine the associations of solid fuel use and risks of acute and chronic respiratory diseases.A cohort study of 277,838 Chinese never-smokers with no prior major chronic diseases at baseline. During 9 years of follow-up, 19,823 first hospitalization episodes or deaths from major respiratory diseases, including 10,553 chronic lower respiratory disease (CLRD), 4,398 chronic obstructive pulmonary disease (COPD), and 7,324 acute lower respiratory infection (ALRI), were recorded. Cox regression yielded adjusted hazard ratios (HRs) for disease risks associated with self-reported primary cooking fuel use.Overall, 91% of participants reported regular cooking, with 52% using solid fuels. Compared with clean fuel users, solid fuel users had an adjusted HR of 1.36 (95% confidence interval, 1.32-1.40) for major respiratory diseases, whereas those who switched from solid to clean fuels had a weaker HR (1.14, 1.10-1.17). The HRs were higher in wood (1.37, 1.33-1.41) than coal users (1.22, 1.15-1.29) and in those with prolonged use (≥40 yr, 1.54, 1.48-1.60; <20 yr, 1.32, 1.26-1.39), but lower among those who used ventilated than nonventilated cookstoves (1.22, 1.19-1.25 vs. 1.29, 1.24-1.35). For CLRD, COPD, and ALRI, the HRs associated with solid fuel use were 1.47 (1.41-1.52), 1.10 (1.03-1.18), and 1.16 (1.09-1.23), respectively.Among Chinese adults, solid fuel use for cooking was associated with higher risks of major respiratory disease admissions and death, and switching to clean fuels or use of ventilated cookstoves had lower risk than not switching.
American Journal of ... arrow_drop_down American Journal of Respiratory and Critical Care MedicineArticleLicense: CC BYData sources: UnpayWallOxford University Research ArchiveArticle . 2018License: CC BYData sources: Oxford University Research ArchiveAmerican Journal of Respiratory and Critical Care MedicineArticle . 2019 . Peer-reviewedData sources: CrossrefAmerican Journal of Respiratory and Critical Care MedicineArticle . 2019Data sources: Europe PubMed CentralAmerican Journal of Respiratory and Critical Care MedicineJournalData sources: Microsoft Academic Graphadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1164/rccm.201803-0432oc&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 63 citations 63 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert American Journal of ... arrow_drop_down American Journal of Respiratory and Critical Care MedicineArticleLicense: CC BYData sources: UnpayWallOxford University Research ArchiveArticle . 2018License: CC BYData sources: Oxford University Research ArchiveAmerican Journal of Respiratory and Critical Care MedicineArticle . 2019 . Peer-reviewedData sources: CrossrefAmerican Journal of Respiratory and Critical Care MedicineArticle . 2019Data sources: Europe PubMed CentralAmerican Journal of Respiratory and Critical Care MedicineJournalData sources: Microsoft Academic Graphadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2018 United KingdomPublisher:American Medical Association (AMA) Canqing Yu; Yiping Chen; Tangchun Wu; Derrick A Bennett; Om P Kurmi; An Pan; Jun Lv; Gaokun Qiu; Liming Li; Liming Li; Frank B. Hu; Kuai Yu; Kin Bong Hubert Lam; Yu Guo; Zheng Bian; Zhengming Chen; Ling Yang; Ka Hung Chan;When combusted indoors, solid fuels generate a large amount of pollutants such as fine particulate matter.To assess the associations of solid fuel use for cooking and heating with cardiovascular and all-cause mortality.This nationwide prospective cohort study recruited participants from 5 rural areas across China between June 2004 and July 2008; mortality follow-up was until January 1, 2014. A total of 271 217 adults without a self-reported history of physician-diagnosed cardiovascular disease at baseline were included, with a random subset (n = 10 892) participating in a resurvey after a mean interval of 2.7 years.Self-reported primary cooking and heating fuels (solid: coal, wood, or charcoal; clean: gas, electricity, or central heating), switching of fuel type before baseline, and use of ventilated cookstoves.Death from cardiovascular and all causes, collected through established death registries.Among the 271 217 participants, the mean (SD) age was 51.0 (10.2) years, and 59% (n = 158 914) were women. A total of 66% (n = 179 952) of the participants reported regular cooking (at least weekly) and 60% (n = 163 882) reported winter heating, of whom 84% (n = 150 992) and 90% (n = 147 272) used solid fuels, respectively. There were 15 468 deaths, including 5519 from cardiovascular causes, documented during a mean (SD) of 7.2 (1.4) years of follow-up. Use of solid fuels for cooking was associated with greater risk of cardiovascular mortality (absolute rate difference [ARD] per 100 000 person-years, 135 [95% CI, 77-193]; hazard ratio [HR], 1.20 [95% CI, 1.02-1.41]) and all-cause mortality (ARD, 338 [95% CI, 249-427]; HR, 1.11 [95% CI, 1.03-1.20]). Use of solid fuels for heating was also associated with greater risk of cardiovascular mortality (ARD, 175 [95% CI, 118-231]; HR, 1.29 [95% CI, 1.06-1.55]) and all-cause mortality (ARD, 392 [95% CI, 297-487]; HR, 1.14 [95% CI, 1.03-1.26]). Compared with persistent solid fuel users, participants who reported having previously switched from solid to clean fuels for cooking had a lower risk of cardiovascular mortality (ARD, 138 [95% CI, 71-205]; HR, 0.83 [95% CI, 0.69-0.99]) and all-cause mortality (ARD, 407 [95% CI, 317-497]; HR, 0.87 [95% CI, 0.79-0.95]), while for heating, the ARDs were 193 (95% CI, 128-258) and 492 (95% CI, 383-601), and the HRs were 0.57 (95% CI, 0.42-0.77) and 0.67 (95% CI, 0.57-0.79), respectively. Among solid fuel users, use of ventilated cookstoves was also associated with lower risk of cardiovascular mortality (ARD, 33 [95% CI, -9 to 75]; HR, 0.89 [95% CI, 0.80-0.99]) and all-cause mortality (ARD, 87 [95% CI, 20-153]; HR, 0.91 [95% CI, 0.85-0.96]).In rural China, solid fuel use for cooking and heating was associated with higher risks of cardiovascular and all-cause mortality. These risks may be lower among those who had previously switched to clean fuels and those who used ventilation.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 233 citations 233 popularity Top 0.1% influence Top 1% impulse Top 1% Powered by BIP!
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2019 United KingdomPublisher:Oxford University Press (OUP) Funded by:UKRI | Assessing health risks as..., WT, WT | China Kadoorie Biobank (C... +2 projectsUKRI| Assessing health risks associated with exposure to household and ambient air pollution in rural and urban China ,WT ,WT| China Kadoorie Biobank (CKB) prospective study of 0.5 million adults ,WT| The Kadoorie Biobank study. ,WT| China Kadoorie Biobank (CKB) of 0.5 million adults.Jun Lv; Derrick A Bennett; Om P Kurmi; Lin Li; Xiaofang Chen; Yu Guo; Lam Kbh.; Yiping Chen; Yiping Chen; C Dong; Zheng Bian; Ka Hung Chan; Chuanhua Yu; Ling Yang; Ling Yang; Zhengming Chen; Zhengming Chen;Abstract Background Harmful substances in solid fuel and tobacco smoke are believed to enter the bloodstream via inhalation and to be metabolized in the liver, leading to chronic liver damage. However, little is known about the independent and joint effects of solid fuel use and smoking on risks of chronic liver disease (CLD) mortality. Methods During 2004–08, ∼0.5 million adults aged 30–79 years were recruited from 10 areas across China. During a 10-year median follow-up, 2461 CLD deaths were recorded. Multivariable Cox regression yielded adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for the individual associations of self-reported long-term cooking fuel and tobacco use with major CLD death. Results Overall, 49% reported solid fuel use and 26% smoked regularly. Long-term solid fuel use for cooking and current smoking were associated with higher risks of CLD deaths, with adjusted HRs of 1.26 (95% CI, 1.02–1.56) and 1.28 (1.13–1.44), respectively. Compared with never-smoking clean fuel users, the HRs were 1.41 (1.10–1.82) in never-smoking solid fuel users, 1.55 (1.17–2.06) in regular-smoking clean fuel users and 1.71 (1.32–2.20) in regular-smoking solid fuels users. Individuals who had switched from solid to clean fuels (1.07, 0.90–1.29; for median 14 years) and ex-regular smokers who stopped for non-medical reasons (1.16, 0.95–1.43; for median 10 years) had no evidence of excess risk of CLD deaths compared with clean fuel users and never-regular smokers, respectively. Conclusions Among Chinese adults, long-term solid fuel use for cooking and smoking were each independently associated with higher risks of CLD deaths. Individuals who had stopped using solid fuels or smoking had lower risks.
International Journa... arrow_drop_down International Journal of EpidemiologyArticle . 2019 . Peer-reviewedLicense: CC BYData sources: CrossrefOxford University Research ArchiveArticle . 2019License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 21 citations 21 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert International Journa... arrow_drop_down International Journal of EpidemiologyArticle . 2019 . Peer-reviewedLicense: CC BYData sources: CrossrefOxford University Research ArchiveArticle . 2019License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2024Publisher:Springer Science and Business Media LLC Funded by:UKRI | China Kadoorie Biobank (C..., UKRI | Assessing health risks as..., UKRI | China Kadoorie Biobank of... +5 projectsUKRI| China Kadoorie Biobank (CKB) prospective study of 0.5 million adults ,UKRI| Assessing health risks associated with exposure to household and ambient air pollution in rural and urban China ,UKRI| China Kadoorie Biobank of 500,000 people aged 30-79 ,WT| China Kadoorie Biobank of 0.5 million adults ,WT| China Kadoorie Biobank (CKB) prospective study of 0.5 million adults ,WT| The Kadoorie Biobank study. ,WT| China Kadoorie Biobank (CKB) of 0.5 million adults. ,UKRI| China Kadoorie Biobank (CKB)Xi Xia; Ka Hung Chan; Yue Niu; Cong Liu; Yitong Guo; Kin-Fai Ho; Steve Hung-Lam Yim; Baihan Wang; Aiden Doherty; Daniel Avery; Pei Pei; Canqing Yu; Dianjianyi Sun; Jun Lv; Junshi Chen; Liming Li; Peng Wen; Shaowei Wu; Kin Bong Hubert Lam*; Haidong Kan*; Zhengming Chen*;Abstract The reliance of outdoor exposure data in epidemiological studies on temperature entails important uncertainties from personal exposure misclassification. We analysed ~88,000 concurrent person-hours of measured personal, household (kitchen and living room), and outdoor temperatures collected in the summer (MAY-SEP 2017) and winter (NOV 2017-JAN 2018) in rural and urban China. The temperatures across microenvironments were strongly correlated (Spearman’s ρ: 0.86-0.92) in summer. In winter, personal temperature was strongly related to household temperatures (ρ: 0.74-0.79) but poorly related to outdoor temperature (ρ: 0.30). Random forest (RF) algorithm identified household and outdoor temperatures and study date as top predictors of personal temperature exposure for both seasons, and heating-related factors were important in winter. Multivariable linear regression and RF models incorporating questionnaire and device data performed satisfactorily in predicting personal exposure in both seasons (R2summer: 0.92; R2winter: 0.68-0.70). Using generalised additive mixed effect models, we found consistent U-shaped associations between measured and predicted personal temperature exposures and heart rate (lowest at ~14.5ºC), but a weak positive linear association with outdoor temperature. Personal and outdoor temperatures differ substantially in winter, but prediction models incorporating household and outdoor temperatures and questionnaire data performed satisfactorily. Exposure misclassification from using outdoor temperature may produce inappropriate epidemiological findings.
https://doi.org/10.2... arrow_drop_down https://doi.org/10.21203/rs.3....Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefhttps://doi.org/10.21203/rs.3....Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21203/rs.3.rs-4547455/v2&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!
more_vert https://doi.org/10.2... arrow_drop_down https://doi.org/10.21203/rs.3....Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefhttps://doi.org/10.21203/rs.3....Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21203/rs.3.rs-4547455/v2&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2023 United KingdomPublisher:Springer Science and Business Media LLC Funded by:UKRI | China Kadoorie Biobank of..., WT | China Kadoorie Biobank of..., WT | China Kadoorie Biobank (C... +5 projectsUKRI| China Kadoorie Biobank of 500,000 people aged 30-79 ,WT| China Kadoorie Biobank of 0.5 million adults ,WT| China Kadoorie Biobank (CKB) prospective study of 0.5 million adults ,UKRI| A Real-time Digital Platform for Industry 4.0 Manufacturer Insurance ,UKRI| China Kadoorie Biobank (CKB) prospective study of 0.5 million adults ,WT| The Kadoorie Biobank study. ,WT| China Kadoorie Biobank (CKB) of 0.5 million adults. ,UKRI| China Kadoorie Biobank (CKB)Pek Kei Im; Neil Wright; Ling Yang; Ka Hung Chan; Yiping Chen; Yu Guo; Huaidong Du; Xiaoming Yang; Daniel Avery; Shaojie Wang; Canqing Yu; Jun Lv; Robert Clarke; Junshi Chen; Rory Collins; Robin G. Walters; Richard Peto; Liming Li; Zhengming Chen; Iona Y. Millwood; Chen Wang; Maxim Barnard; Derrick Bennett; Ruth Boxall; Johnathan Clarke; Ahmed Edris Mohamed; Hannah Fry; Simon Gilbert; Andri Iona; Maria Kakkoura; Christiana Kartsonaki; Hubert Lam; Kuang Lin; James Liu; Mohsen Mazidi; Sam Morris; Qunhua Nie; Alfred Pozarickij; Paul Ryder; Saredo Said; Dan Schmidt; Becky Stevens; Iain Turnbull; Baihan Wang; Lin Wang; Pang Yao; Xiao Han; Can Hou; Qingmei Xia; Chao Liu; Pei Pei; Dianjianyi Sun; Naying Chen; Duo Liu; Zhenzhu Tang; Ningyu Chen; Qilian Jiang; Jian Lan; Mingqiang Li; Yun Liu; Fanwen Meng; Jinhuai Meng; Rong Pan; Yulu Qin; Ping Wang; Sisi Wang; Liuping Wei; Liyuan Zhou; Caixia Dong; Pengfei Ge; Xiaolan Ren; Zhongxiao Li; Enke Mao; Tao Wang; Hui Zhang; Xi Zhang; Jinyan Chen; Ximin Hu; Xiaohuan Wang; Zhendong Guo; Huimei Li; Yilei Li; Min Weng; Shukuan Wu; Shichun Yan; Mingyuan Zou; Xue Zhou; Ziyan Guo; Quan Kang; Yanjie Li; Bo Yu; Qinai Xu; Liang Chang; Lei Fan; Shixian Feng; Ding Zhang; Gang Zhou; Yulian Gao; Tianyou He; Pan He; Chen Hu; Huarong Sun; Xukui Zhang; Biyun Chen; Zhongxi Fu; Yuelong Huang; Huilin Liu; Qiaohua Xu; Li Yin; Huajun Long; Xin Xu; Hao Zhang; Libo Zhang; Jian Su; Ran Tao; Ming Wu; Jie Yang; Jinyi Zhou; Yonglin Zhou; Yihe Hu; Yujie Hua; Jianrong Jin; Fang Liu; Jingchao Liu; Yan Lu; Liangcai Ma; Aiyu Tang; Jun Zhang; Liang Cheng; Ranran Du; Ruqin Gao; Feifei Li; Shanpeng Li; Yongmei Liu; Feng Ning; Zengchang Pang; Xiaohui Sun; Xiaocao Tian; Yaoming Zhai; Hua Zhang; Wei Hou; Silu Lv; Junzheng Wang; Xiaofang Chen; Xianping Wu; Ningmei Zhang; Xiaoyu Chang; Xiaofang Chen; Jianguo Li; Jiaqiu Liu; Guojin Luo; Qiang Sun; Xunfu Zhong; Weiwei Gong; Ruying Hu; Hao Wang; Meng Wang; Min Yu; Lingli Chen; Qijun Gu; Dongxia Pan; Chunmei Wang; Kaixu Xie; Xiaoyi Zhang;AbstractAlcohol consumption accounts for ~3 million annual deaths worldwide, but uncertainty persists about its relationships with many diseases. We investigated the associations of alcohol consumption with 207 diseases in the 12-year China Kadoorie Biobank of >512,000 adults (41% men), including 168,050 genotyped forALDH2-rs671andADH1B-rs1229984, with >1.1 million ICD-10 coded hospitalized events. At baseline, 33% of men drank alcohol regularly. Among men, alcohol intake was positively associated with 61 diseases, including 33 not defined by the World Health Organization as alcohol-related, such as cataract (n = 2,028; hazard ratio 1.21; 95% confidence interval 1.09–1.33, per 280 g per week) and gout (n = 402; 1.57, 1.33–1.86). Genotype-predicted mean alcohol intake was positively associated with established (n = 28,564; 1.14, 1.09–1.20) and new alcohol-associated (n = 16,138; 1.06, 1.01–1.12) diseases, and with specific diseases such as liver cirrhosis (n = 499; 2.30, 1.58–3.35), stroke (n = 12,176; 1.38, 1.27–1.49) and gout (n = 338; 2.33, 1.49–3.62), but not ischemic heart disease (n = 8,408; 1.04, 0.94–1.14). Among women, 2% drank alcohol resulting in low power to assess associations of self-reported alcohol intake with disease risks, but genetic findings in women suggested the excess male risks were not due to pleiotropic genotypic effects. Among Chinese men, alcohol consumption increased multiple disease risks, highlighting the need to strengthen preventive measures to reduce alcohol intake.
Nature Medicine arrow_drop_down Oxford University Research ArchiveArticle . 2023License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41591-023-02383-8&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 86 citations 86 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Nature Medicine arrow_drop_down Oxford University Research ArchiveArticle . 2023License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41591-023-02383-8&type=result"></script>'); --> </script>
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