Effect of the herbal medicines in obesity and metabolic syndrome: A systematic review and meta‐analysis of clinical trials

医学 肥胖 肥胖管理 荟萃分析 代谢综合征 传统医学 超重 临床试验 随机对照试验 内科学 减肥
作者
Moloud Payab,Shirin Hasani‐Ranjbar,Nazila Shahbal,Mostafa Qorbani,Azadeh Aletaha,Hamed Haghi‐Aminjan,Akbar Soltani,Fatemeh Khatami,Shekoufeh Nikfar,Shokoufeh Hassani,Mohammad Abdollahi,Bagher Larijani
出处
期刊:Phytotherapy Research [Wiley]
卷期号:34 (3): 526-545 被引量:112
标识
DOI:10.1002/ptr.6547
摘要

Obesity is a medical situation in which excess body fat has gathered because of imbalance between energy intake and energy expenditure. In spite of the fact that the variety of studies are available for obesity treatment and management, its "globesity" still remains a big challenge all over the world. The current systematic review and meta-analysis aimed to evaluate the efficacy, safety, and mechanisms of effective herbal medicines in the management and treatment of obesity and metabolic syndrome in human. We systematically searched all relevant clinical trials via Web of Science, Scopus, PubMed, and the Cochrane database to assess the effects of raw or refined products derived from plants or parts of plants on obesity and metabolic syndrome in overweight and obesity adult subjects. All studies conducted by the end of May 2019 were considered in the systematic review. Data were extracted independently by two experts. The quality assessment was assessed using Consolidated Standards of Reporting Trials checklist. The main outcomes were anthropometric indices and metabolic syndrome components. Pooled effect of herbal medicines on obesity and metabolic syndrome were presented as standardized mean difference (SMD) and 95% confidence interval (CI). A total of 279 relevant clinical trials were included. Herbals containing green tea, Phaseolus vulgaris, Garcinia cambogia, Nigella sativa, puerh tea, Irvingia gabonensis, and Caralluma fimbriata and their active ingredients were found to be effective in the management of obesity and metabolic syndrome. In addition, C. fimbriata, flaxseed, spinach, and fenugreek were able to reduce appetite. Meta-analysis showed that intake of green tea resulted in a significant improvement in weight ([SMD]: -0.75 [-1.18, -0.319]), body mass index ([SMD]: -1.2 [-1.82, -0.57]), waist circumference ([SMD]: -1.71 [-2.66, -0.77]), hip circumference ([SMD]: -0.42 [-1.02, -0.19]), and total cholesterol, ([SMD]: -0.43 [-0.77, -0.09]). In addition, the intake of P. vulgaris and N. sativa resulted in a significant improvement in weight ([SMD]: -0.88, 95 % CI: [-1.13, -0.63]) and triglyceride ([SMD]: -1.67, 95 % CI: [-2.54, -0.79]), respectively. High quality trials are still needed to firmly establish the clinical efficacy of the plants in obesity and metabolic syndrome.
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
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
漂亮的盼波完成签到 ,获得积分10
刚刚
乐观啤酒应助永远的爱采纳,获得10
刚刚
帅气的怼怼完成签到,获得积分10
刚刚
刚刚
小白发布了新的文献求助10
3秒前
我是老大应助整齐的夏波采纳,获得10
3秒前
4秒前
7秒前
7秒前
chen完成签到,获得积分10
7秒前
zx完成签到,获得积分10
9秒前
爆米花应助dddd采纳,获得10
10秒前
款冬发布了新的文献求助10
10秒前
fyin发布了新的文献求助10
11秒前
xzyin完成签到,获得积分10
12秒前
13秒前
优秀爆米花完成签到,获得积分10
14秒前
俗签完成签到,获得积分10
14秒前
TillySss发布了新的文献求助30
14秒前
科研通AI5应助默默的傲云采纳,获得30
14秒前
yujian发布了新的文献求助10
14秒前
min完成签到,获得积分10
14秒前
研友_LmeK4L完成签到,获得积分10
15秒前
illuminate完成签到 ,获得积分10
15秒前
852应助科研小废物采纳,获得10
18秒前
yinjw发布了新的文献求助10
18秒前
嘀嗒完成签到 ,获得积分20
19秒前
谦谦神棍完成签到,获得积分10
21秒前
TillySss完成签到,获得积分10
21秒前
22秒前
怡然雁凡完成签到,获得积分10
23秒前
25秒前
Sherl完成签到,获得积分10
26秒前
琉璃非离应助科研通管家采纳,获得10
26秒前
天天快乐应助科研通管家采纳,获得30
26秒前
科研通AI5应助科研通管家采纳,获得10
26秒前
科研通AI2S应助科研通管家采纳,获得10
26秒前
26秒前
尹博士应助科研通管家采纳,获得10
27秒前
27秒前
高分求助中
Seven new species of the Palaearctic Lauxaniidae and Asteiidae (Diptera) 400
Where and how to use plate heat exchangers 350
Handbook of Laboratory Animal Science 300
Fundamentals of Medical Device Regulations, Fifth Edition(e-book) 300
Beginners Guide To Clinical Medicine (Pb 2020): A Systematic Guide To Clinical Medicine, Two-Vol Set 250
A method for calculating the flow in a centrifugal impeller when entropy gradients are present 240
机器学习与人工智能:从理论到实践 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3706116
求助须知:如何正确求助?哪些是违规求助? 3255274
关于积分的说明 9894123
捐赠科研通 2967625
什么是DOI,文献DOI怎么找? 1627386
邀请新用户注册赠送积分活动 771471
科研通“疑难数据库(出版商)”最低求助积分说明 743382