[A dose-response meta-analysis on the relationship between daily tea intake and cardiovascular mortality based on the GRADE system].

医学 漏斗图 出版偏见 荟萃分析 置信区间 林地 随机效应模型 内科学 队列研究 死亡率 优势比 相对风险 人口学 危险系数 随机对照试验 混淆 子群分析 血压 观察研究 社会学
作者
K F Liu,Yue Xue,Congqun Lu,Xin Zhang,Shuping Yan,Jian Kang,Jie Zhao
出处
期刊:Chinese journal of cardiovascular diseases 卷期号:49 (5): 496-502
标识
DOI:10.3760/cma.j.cn112148-20200726-00592
摘要

Objective: To explore the relationship between daily tea intake and cardiovascular disease (CVD) mortality. Methods: PubMed, EMbase, The Cochrane, Chinese Biomedical Literature Database, CNKI, and Wanfang Database were searched to collect research on tea intake and CVD mortality. The search period was from the establishment of the database to June 2020. Two researchers independently screened and extracted literature. The risk of bias was evaluated in the included studies, a dose-response meta-analysis was conducted, sensitivity analysis and publication bias analysis of the research results, and quality evaluation of the included literature and GRADE classification of the evidence body were performed. Results: A total of 21 cohort or case-control studies were included, including 1 304 978 subjects. Among them, 38 222 deaths from CVD were reported. The quality scores of the included studies were all ≥ 6 points. The dose-response meta-analysis showed that for every additional cup of tea intake per day, the mortality rate of CVD decreased by about 3% (95%CI 0.95-0.98, P 0.05). The results of the bias analysis showed that Begg=0.42 and Egger=0.62, indicating that the distribution on both sides of the funnel chart is symmetrical, suggesting that there is no publication bias. The results of sensitivity analysis showed that the effect size of the outcome index did not change significantly after excluding any article, indicating that the results are robust and credible. The GRADE evaluation showed that the evidence grades of the outcome indicators were all low grade. Conclusions: Daily tea consumption is related to reduced CVD mortality. It is therefore recommended to drink an appropriate amount of tea daily.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
4秒前
曾经的臻完成签到,获得积分10
4秒前
充电宝应助123456采纳,获得10
5秒前
1111完成签到,获得积分10
6秒前
1391451653完成签到,获得积分10
6秒前
威武鞅发布了新的文献求助10
7秒前
8秒前
科研通AI2S应助勤恳书包采纳,获得10
9秒前
9秒前
9秒前
tanglu发布了新的文献求助10
12秒前
Wu完成签到,获得积分10
12秒前
lalala发布了新的文献求助10
13秒前
15秒前
zhouyi发布了新的文献求助10
16秒前
标致小翠完成签到,获得积分10
17秒前
ppprotein完成签到,获得积分10
17秒前
18秒前
一期一会完成签到,获得积分10
18秒前
jordan应助cm采纳,获得10
19秒前
19秒前
顾矜应助爽o采纳,获得10
20秒前
tanglu完成签到,获得积分10
20秒前
炒饭发布了新的文献求助10
23秒前
自来水完成签到,获得积分10
25秒前
共享精神应助舒服的幼荷采纳,获得10
25秒前
zhouyi完成签到,获得积分20
26秒前
dg g g g g g g完成签到,获得积分10
28秒前
Zhou完成签到,获得积分0
28秒前
man发布了新的文献求助10
30秒前
yearluren完成签到,获得积分10
30秒前
炒饭完成签到,获得积分10
31秒前
36秒前
科研通AI2S应助man采纳,获得10
41秒前
lalala发布了新的文献求助10
41秒前
多情晓曼发布了新的文献求助10
42秒前
42秒前
论文多多发布了新的文献求助10
43秒前
lewisll发布了新的文献求助10
44秒前
高分求助中
Handbook of Fuel Cells, 6 Volume Set 1666
Interaction Effects in Linear and Generalized Linear Models: Examples and Applications Using Stata® 1000
求助这个网站里的问题集 1000
Floxuridine; Third Edition 1000
Tracking and Data Fusion: A Handbook of Algorithms 1000
La décision juridictionnelle 800
Rechtsphilosophie und Rechtstheorie 800
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 免疫学 细胞生物学 电极
热门帖子
关注 科研通微信公众号,转发送积分 2867764
求助须知:如何正确求助?哪些是违规求助? 2474770
关于积分的说明 6710131
捐赠科研通 2163266
什么是DOI,文献DOI怎么找? 1149355
版权声明 585523
科研通“疑难数据库(出版商)”最低求助积分说明 564353