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Resveratrol Supplementation and its Potential Benefits in Obesity-related Non-communicable Diseases

Shen CY, Li CP, Yu JT, Ho YJ, Tsai RY

In vivo (Athens, Greece), 2026

2,551 participants · 4 citations

Abstract

Background/aim: Resveratrol, a polyphenolic compound found in grapes, berries, and peanuts, has been linked to antioxidant, anti-inflammatory, and vasoprotective effects. Yet, evidence from randomized controlled trials (RCTs) remains inconsistent, and the quality, dosage, and cost of commercial resveratrol products vary considerably, raising uncertainty about their true efficacy. A comprehensive synthesis of its effects on obesity-related non-communicable diseases (NCDs) is therefore warranted. Given that obesity is a key driver of metabolic dysregulation underlying diabetes, cardiovascular disease, and fatty liver disease, clarifying resveratrol's potential in overweight and obese populations is of particular importance.

Materials and methods: We systematically searched PubMed, Embase, the Cochrane Library, and Web of Science for RCTs published up to July 2025 that evaluated resveratrol supplementation in adults with obesity-related metabolic disorders or associated risk factors. Study selection and data extraction followed PRISMA 2020 guidelines. Pooled estimates were calculated using random-effects models, and heterogeneity was assessed with the I2 statistic.

Results: Forty RCTs involving 2551 participants were included. Resveratrol significantly reduced the homeostatic model assessment of insulin resistance (HOMA-IR), total cholesterol (TC), triglycerides (TG), low density lipoprotein (LDL) cholesterol, systolic blood pressure (SBP) and diastolic blood pressure (DBP),…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 2,551 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

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