School of Health and Biomedical Sciences, RMIT University Bundoora, VIC, Australia.
School of Science, RMIT University, Melbourne VIC, Australia.
J Obes. 2021 Mar 9;2021:3250723. doi: 10.1155/2021/3250723. eCollection 2021.
This review investigated the effects and safety of Chinese herbal medicine (CHM) formulas on weight management.
Eighteen databases in English, Chinese, Korean, and Japanese were searched from their inceptions to September 2019. The treatment groups included CHM formulations, and the control included placebo, Western medication (WM), and lifestyle intervention (LI), with or without cointerventions (WM and/or LI). Quality of studies was assessed using Cochrane Collaboration's risk of bias assessment tool. Body weight and body mass index (BMI) were analysed in RevMan v5.4.1 and expressed as mean differences with 95% confidence intervals (CI), while adverse events were expressed as risk ratio with 95% CI.
Thirty-nine RCTs were eligible for qualitative analysis, 34 of which were included in the meta-analyses. The majority of studies had a high or unclear risk of selection, performance, and detection bias. Twenty-five CHM studies involving cointerventions revealed that CHM had significant adjunct effects on body weight and BMI at the end of treatment compared to control. No serious adverse events were reported in the CHM groups.
CHM indicates a promising adjunct to facilitate WM or lifestyle change for weight management. However, methodological barriers such as lack of allocation concealment and double-blinding may have led to challenges in data synthesis. More rigorously designed RCTs involving cointerventions are warranted.
本综述旨在探讨中草药(CHM)配方在体重管理方面的作用和安全性。
从建库至 2019 年 9 月,检索了英文、中文、韩文和日文的 18 个数据库。治疗组包括 CHM 配方,对照组包括安慰剂、西药(WM)和生活方式干预(LI),以及有无联合干预(WM 和/或 LI)。使用 Cochrane 协作风险偏倚评估工具评估研究质量。体重和体重指数(BMI)在 RevMan v5.4.1 中进行分析,以均数差及 95%置信区间(CI)表示,而不良反应则以风险比及 95%CI 表示。
39 项 RCT 符合定性分析标准,其中 34 项纳入荟萃分析。大多数研究存在选择、实施和检测偏倚的高风险或不确定风险。25 项 CHM 联合干预研究表明,与对照组相比,CHM 在治疗结束时对体重和 BMI 具有显著的辅助作用。CHM 组未报告严重不良事件。
CHM 为 WM 或生活方式改变辅助体重管理提供了一种有前景的方法。然而,方法学障碍,如缺乏分配隐藏和双盲,可能导致数据综合存在挑战。需要进行更多设计严谨的联合干预 RCT 研究。