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食用红肉、家禽和鱼类与糖尿病风险:中国慢性病前瞻性研究的 9 年前瞻性队列研究。

Red meat, poultry and fish consumption and risk of diabetes: a 9 year prospective cohort study of the China Kadoorie Biobank.

机构信息

Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK.

Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK.

出版信息

Diabetologia. 2020 Apr;63(4):767-779. doi: 10.1007/s00125-020-05091-x. Epub 2020 Jan 22.

Abstract

AIMS/HYPOTHESIS: Previous evidence linking red meat consumption with diabetes risk mainly came from western countries, with little evidence from China, where patterns of meat consumption are different. Moreover, global evidence remains inconclusive about the associations of poultry and fish consumption with diabetes. Therefore we investigated the associations of red meat, poultry and fish intake with incidence of diabetes in a Chinese population.

METHODS

The prospective China Kadoorie Biobank recruited ~512,000 adults (59% women, mean age 51 years) from ten rural and urban areas across China in 2004-2008. At the baseline survey, a validated interviewer-administered laptop-based questionnaire was used to collect information on the consumption frequency of major food groups including red meat, poultry, fish, fresh fruit and several others. During ~9 years of follow-up, 14,931 incidences of new-onset diabetes were recorded among 461,036 participants who had no prior diabetes, cardiovascular diseases or cancer at baseline. Cox regression analyses were performed to calculate adjusted HRs for incident diabetes associated with red meat, poultry and fish intake.

RESULTS

At baseline, 47.0%, 1.3% and 8.9% of participants reported a regular consumption (i.e. ≥4 days/week) of red meat, poultry and fish, respectively. After adjusting for adiposity and other potential confounders, each 50 g/day increase in red meat and fish intake was associated with 11% (HR 1.11 [95% CI 1.04, 1.20]) and 6% (HR 1.06 [95% CI 1.00, 1.13]) higher risk of incident diabetes, respectively. For both, the associations were more pronounced among men and women from urban areas, with an HR (95% CI) of 1.42 (1.15, 1.74) and 1.18 (1.03, 1.36), respectively, per 50 g/day red meat intake and 1.15 (1.02, 1.30) and 1.11 (1.01, 1.23), respectively, per 50 g/day fish intake. There was no significant association between diabetes and poultry intake, either overall (HR 0.96 [95% CI 0.83, 1.12] per 50 g/day intake) or in specific population subgroups.

CONCLUSIONS/INTERPRETATION: In Chinese adults, both red meat and fish, but not poultry, intake were positively associated with diabetes risk, particularly among urban participants. Our findings add new evidence linking red meat and fish intake with cardiometabolic diseases.

DATA AVAILABILITY

Details of how to access the China Kadoorie Biobank data and rules of China Kadoorie Biobank data release are available from www.ckbiobank.org/site/Data+Access.

摘要

目的/假设:先前将红肉摄入量与糖尿病风险联系起来的证据主要来自西方国家,而来自中国的证据很少,因为中国的肉类消费模式有所不同。此外,全球证据对于禽肉和鱼肉摄入与糖尿病之间的关联仍然没有定论。因此,我们在中国人群中调查了红肉、禽肉和鱼肉摄入与糖尿病发病的关系。

方法

中国慢性病前瞻性研究(CKB)于 2004-2008 年从中国十个农村和城市地区招募了约 51.2 万名成年人(59%为女性,平均年龄 51 岁)。在基线调查中,使用经过验证的基于笔记本电脑的访谈者管理问卷收集了主要食物组(包括红肉、禽肉、鱼、新鲜水果和其他几种食物)的消费频率信息。在大约 9 年的随访期间,在基线时无糖尿病、心血管疾病或癌症的 461036 名参与者中记录了 14931 例新发糖尿病。使用 Cox 回归分析计算了与红肉、禽肉和鱼肉摄入相关的新发糖尿病的调整后 HR。

结果

在基线时,分别有 47.0%、1.3%和 8.9%的参与者报告经常(即≥4 天/周)食用红肉、禽肉和鱼肉。在调整了肥胖和其他潜在混杂因素后,每天增加 50 克红肉和鱼肉的摄入量分别与 11%(HR 1.11 [95% CI 1.04, 1.20])和 6%(HR 1.06 [95% CI 1.00, 1.13])的新发糖尿病风险升高相关。两者的关联在来自城市地区的男性和女性中更为明显,每天摄入 50 克红肉的 HR(95%CI)分别为 1.42(1.15, 1.74)和 1.18(1.03, 1.36),每天摄入 50 克鱼肉的 HR(95%CI)分别为 1.15(1.02, 1.30)和 1.11(1.01, 1.23)。禽肉摄入量与糖尿病之间没有显著关联,无论是总体上(HR 0.96 [95% CI 0.83, 1.12] 每天摄入 50 克)还是在特定人群亚组中。

结论/解释:在中国成年人中,红肉和鱼肉摄入与糖尿病风险呈正相关,而禽肉摄入则没有相关性,这种关联在城市参与者中更为明显。我们的研究结果提供了新的证据,将红肉和鱼肉摄入与心血管代谢疾病联系起来。

数据可用性

有关如何访问中国慢性病前瞻性研究数据以及中国慢性病前瞻性研究数据发布规则的详细信息可在 www.ckbiobank.org/site/Data+Access 上获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ada5/7054352/0b9e97b52a35/125_2020_5091_Fig1_HTML.jpg

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