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Meat consumption and incident type 2 diabetes: an individual-participant federated meta-analysis of 1·97 million adults with 100 000 incident cases from 31 cohorts in 20 countries
The Lancet Diabetes & Endocrinology ( IF 44.0 ) Pub Date : 2024-08-20 , DOI: 10.1016/s2213-8587(24)00179-7 Chunxiao Li 1 , Tom R P Bishop 1 , Fumiaki Imamura 1 , Stephen J Sharp 1 , Matthew Pearce 1 , Soren Brage 1 , Ken K Ong 1 , Habibul Ahsan 2 , Maira Bes-Rastrollo 3 , Joline W J Beulens 4 , Nicole den Braver 4 , Liisa Byberg 5 , Scheine Canhada 6 , Zhengming Chen 7 , Hsin-Fang Chung 8 , Adrian Cortés-Valencia 9 , Luc Djousse 10 , Jean-Philippe Drouin-Chartier 11 , Huaidong Du 7 , Shufa Du 12 , Bruce B Duncan 6 , J Michael Gaziano 13 , Penny Gordon-Larsen 12 , Atsushi Goto 14 , Fahimeh Haghighatdoost 15 , Tommi Härkänen 16 , Maryam Hashemian 17 , Frank B Hu 18 , Till Ittermann 19 , Ritva Järvinen 20 , Maria G Kakkoura 7 , Nithya Neelakantan 21 , Paul Knekt 16 , Martin Lajous 22 , Yanping Li 23 , Dianna J Magliano 24 , Reza Malekzadeh 25 , Loic Le Marchand 26 , Pedro Marques-Vidal 27 , Miguel A Martinez-Gonzalez 3 , Gertraud Maskarinec 26 , Gita D Mishra 8 , Noushin Mohammadifard 15 , Gráinne O'Donoghue 28 , Donal O'Gorman 29 , Barry Popkin 12 , Hossein Poustchi 25 , Nizal Sarrafzadegan 30 , Norie Sawada 31 , Maria Inês Schmidt 6 , Jonathan E Shaw 24 , Sabita Soedamah-Muthu 32 , Dalia Stern 33 , Lin Tong 2 , Rob M van Dam 34 , Henry Völzke 19 , Walter C Willett 18 , Alicja Wolk 35 , Canqing Yu 36 , , Nita G Forouhi 1 , Nicholas J Wareham 1
The Lancet Diabetes & Endocrinology ( IF 44.0 ) Pub Date : 2024-08-20 , DOI: 10.1016/s2213-8587(24)00179-7 Chunxiao Li 1 , Tom R P Bishop 1 , Fumiaki Imamura 1 , Stephen J Sharp 1 , Matthew Pearce 1 , Soren Brage 1 , Ken K Ong 1 , Habibul Ahsan 2 , Maira Bes-Rastrollo 3 , Joline W J Beulens 4 , Nicole den Braver 4 , Liisa Byberg 5 , Scheine Canhada 6 , Zhengming Chen 7 , Hsin-Fang Chung 8 , Adrian Cortés-Valencia 9 , Luc Djousse 10 , Jean-Philippe Drouin-Chartier 11 , Huaidong Du 7 , Shufa Du 12 , Bruce B Duncan 6 , J Michael Gaziano 13 , Penny Gordon-Larsen 12 , Atsushi Goto 14 , Fahimeh Haghighatdoost 15 , Tommi Härkänen 16 , Maryam Hashemian 17 , Frank B Hu 18 , Till Ittermann 19 , Ritva Järvinen 20 , Maria G Kakkoura 7 , Nithya Neelakantan 21 , Paul Knekt 16 , Martin Lajous 22 , Yanping Li 23 , Dianna J Magliano 24 , Reza Malekzadeh 25 , Loic Le Marchand 26 , Pedro Marques-Vidal 27 , Miguel A Martinez-Gonzalez 3 , Gertraud Maskarinec 26 , Gita D Mishra 8 , Noushin Mohammadifard 15 , Gráinne O'Donoghue 28 , Donal O'Gorman 29 , Barry Popkin 12 , Hossein Poustchi 25 , Nizal Sarrafzadegan 30 , Norie Sawada 31 , Maria Inês Schmidt 6 , Jonathan E Shaw 24 , Sabita Soedamah-Muthu 32 , Dalia Stern 33 , Lin Tong 2 , Rob M van Dam 34 , Henry Völzke 19 , Walter C Willett 18 , Alicja Wolk 35 , Canqing Yu 36 , , Nita G Forouhi 1 , Nicholas J Wareham 1
Affiliation
Meat consumption could increase the risk of type 2 diabetes. However, evidence is largely based on studies of European and North American populations, with heterogeneous analysis strategies and a greater focus on red meat than on poultry. We aimed to investigate the associations of unprocessed red meat, processed meat, and poultry consumption with type 2 diabetes using data from worldwide cohorts and harmonised analytical approaches. This individual-participant federated meta-analysis involved data from 31 cohorts participating in the InterConnect project. Cohorts were from the region of the Americas (n=12) and the Eastern Mediterranean (n=2), European (n=9), South-East Asia (n=1), and Western Pacific (n=7) regions. Access to individual-participant data was provided by each cohort; participants were eligible for inclusion if they were aged 18 years or older and had available data on dietary consumption and incident type 2 diabetes and were excluded if they had a diagnosis of any type of diabetes at baseline or missing data. Cohort-specific hazard ratios (HRs) and 95% CIs were estimated for each meat type, adjusted for potential confounders (including BMI), and pooled using a random-effects meta-analysis, with meta-regression to investigate potential sources of heterogeneity. Among 1 966 444 adults eligible for participation, 107 271 incident cases of type 2 diabetes were identified during a median follow-up of 10 (IQR 7–15) years. Median meat consumption across cohorts was 0–110 g/day for unprocessed red meat, 0–49 g/day for processed meat, and 0–72 g/day for poultry. Greater consumption of each of the three types of meat was associated with increased incidence of type 2 diabetes, with HRs of 1·10 (95% CI 1·06–1·15) per 100 g/day of unprocessed red meat (=61%), 1·15 (1·11–1·20) per 50 g/day of processed meat (=59%), and 1·08 (1·02–1·14) per 100 g/day of poultry (=68%). Positive associations between meat consumption and type 2 diabetes were observed in North America and in the European and Western Pacific regions; the CIs were wide in other regions. We found no evidence that the heterogeneity was explained by age, sex, or BMI. The findings for poultry consumption were weaker under alternative modelling assumptions. Replacing processed meat with unprocessed red meat or poultry was associated with a lower incidence of type 2 diabetes. The consumption of meat, particularly processed meat and unprocessed red meat, is a risk factor for developing type 2 diabetes across populations. These findings highlight the importance of reducing meat consumption for public health and should inform dietary guidelines. The EU, the Medical Research Council, and the National Institute of Health Research Cambridge Biomedical Research Centre.
中文翻译:
肉类消费和 2 型糖尿病事件:对 20 个国家 31 个队列的 1·9700 万成年人和 10 万个事件病例进行的个体参与者联合荟萃分析
肉类消费可能会增加患 2 型糖尿病的风险。然而,证据主要基于对欧洲和北美人群的研究,具有异质性分析策略,并且更关注红肉而不是家禽。我们的目的是利用来自全球队列的数据和统一的分析方法来调查未加工的红肉、加工肉类和家禽消费与 2 型糖尿病的关联。这项个人参与者联合荟萃分析涉及来自参与 InterConnect 项目的 31 个队列的数据。队列来自美洲地区 (n=12)、东地中海地区 (n=2)、欧洲地区 (n=9)、东南亚地区 (n=1) 和西太平洋地区 (n=7)。每个队列都提供对个人参与者数据的访问;如果参与者年龄在 18 岁或以上,并且拥有有关饮食消费和 2 型糖尿病事件的可用数据,则参与者有资格被纳入;如果参与者在基线时诊断出任何类型的糖尿病或缺少数据,则被排除在外。估计每种肉类的特定群组风险比 (HR) 和 95% CI,根据潜在的混杂因素(包括 BMI)进行调整,并使用随机效应荟萃分析进行汇总,并通过荟萃回归来调查异质性的潜在来源。在 1 966 444 名符合参与资格的成年人中,在中位随访 10 年(IQR 7-15)期间发现了 107 271 例 2 型糖尿病病例。各队列中未加工红肉的肉类消费量中位数为 0-110 克/天,加工肉为 0-49 克/天,家禽为 0-72 克/天。 三种肉类的摄入量增加与 2 型糖尿病发病率增加相关,每 100 克/天未加工红肉的 HR 为 1·10 (95% CI 1·06–1·15) (=61 %)、每 50 克/天加工肉类 1·15 (1·11–1·20) (=59%)、每 100 克/天家禽 1·08 (1·02–1·14) ( =68%)。在北美、欧洲和西太平洋地区观察到肉类消费与 2 型糖尿病之间呈正相关; CI 在其他地区也很广泛。我们没有发现任何证据表明异质性可以用年龄、性别或体重指数来解释。在替代模型假设下,家禽消费的结果较弱。用未加工的红肉或家禽代替加工肉类可以降低 2 型糖尿病的发病率。肉类的消费,特别是加工肉类和未加工的红肉,是人群患 2 型糖尿病的危险因素。这些发现强调了减少肉类消费对公共卫生的重要性,并应为膳食指南提供参考。欧盟、医学研究委员会和国家卫生研究院剑桥生物医学研究中心。
更新日期:2024-08-20
中文翻译:
肉类消费和 2 型糖尿病事件:对 20 个国家 31 个队列的 1·9700 万成年人和 10 万个事件病例进行的个体参与者联合荟萃分析
肉类消费可能会增加患 2 型糖尿病的风险。然而,证据主要基于对欧洲和北美人群的研究,具有异质性分析策略,并且更关注红肉而不是家禽。我们的目的是利用来自全球队列的数据和统一的分析方法来调查未加工的红肉、加工肉类和家禽消费与 2 型糖尿病的关联。这项个人参与者联合荟萃分析涉及来自参与 InterConnect 项目的 31 个队列的数据。队列来自美洲地区 (n=12)、东地中海地区 (n=2)、欧洲地区 (n=9)、东南亚地区 (n=1) 和西太平洋地区 (n=7)。每个队列都提供对个人参与者数据的访问;如果参与者年龄在 18 岁或以上,并且拥有有关饮食消费和 2 型糖尿病事件的可用数据,则参与者有资格被纳入;如果参与者在基线时诊断出任何类型的糖尿病或缺少数据,则被排除在外。估计每种肉类的特定群组风险比 (HR) 和 95% CI,根据潜在的混杂因素(包括 BMI)进行调整,并使用随机效应荟萃分析进行汇总,并通过荟萃回归来调查异质性的潜在来源。在 1 966 444 名符合参与资格的成年人中,在中位随访 10 年(IQR 7-15)期间发现了 107 271 例 2 型糖尿病病例。各队列中未加工红肉的肉类消费量中位数为 0-110 克/天,加工肉为 0-49 克/天,家禽为 0-72 克/天。 三种肉类的摄入量增加与 2 型糖尿病发病率增加相关,每 100 克/天未加工红肉的 HR 为 1·10 (95% CI 1·06–1·15) (=61 %)、每 50 克/天加工肉类 1·15 (1·11–1·20) (=59%)、每 100 克/天家禽 1·08 (1·02–1·14) ( =68%)。在北美、欧洲和西太平洋地区观察到肉类消费与 2 型糖尿病之间呈正相关; CI 在其他地区也很广泛。我们没有发现任何证据表明异质性可以用年龄、性别或体重指数来解释。在替代模型假设下,家禽消费的结果较弱。用未加工的红肉或家禽代替加工肉类可以降低 2 型糖尿病的发病率。肉类的消费,特别是加工肉类和未加工的红肉,是人群患 2 型糖尿病的危险因素。这些发现强调了减少肉类消费对公共卫生的重要性,并应为膳食指南提供参考。欧盟、医学研究委员会和国家卫生研究院剑桥生物医学研究中心。