Anthropometric and cardiometabolic effects of polyphenols in people with overweight and obesity: an umbrella review.

CONTEXT: Polyphenols are plant-based compounds with potential anti-inflammatory, antioxidant, and anti-obesogenic properties. However, their effects on health outcomes remain unclear. OBJECTIVE: To evaluate the effects of polyphenols on anthropometric and cardiometabolic markers. DATA SOURCES: Six electronic databases-namely, EMBASE, CINAHL, PubMed, Scopus, The Cochrane Library (reviews only), and Web of Science-were searched for relevant systematic reviews with meta-analyses (SRMAs). DATA EXTRACTION: Three reviewers performed the data extraction via a data-extraction Microsoft Excel spreadsheet. DATA ANALYSIS: An umbrella review and meta-analysis of existing SRMAs was conducted. Eighteen SRMAs published from 2015 to 2023, representing 445 primary studies and 838 unique effect sizes, were identified. Meta-analyses were conducted using random-effects models with general inverse variance. Polyphenol-containing foods were found to significantly improve weight (-0.36 kg; 95% confidence interval [CI]: -0.62, 0.77 kg; P < 0.01, I2 = 64.9%), body mass index (-0.25 kg/m2; 95% CI: -0.34, -0.17 kg/m2; P < 0.001, I2 = 82.4%), waist circumference (-0.74 cm; 95% CI: -1.34, -0.15 cm; P < 0.01, I2 = 99.3%), low-density-lipoprotein cholesterol (-1.75 mg/dL; 95% CI: -2.56, -0.94; P < 0.001, I2 = 98.6%), total cholesterol (-1.23 mg/dL; 95% CI: -2.00, -0.46; P = 0.002, I2 = 94.6%), systolic blood pressure (-1.77 mmHg; 95% CI: -1.77, -0.93 mmHg; P < 0.001, I2 = 72.4%), diastolic blood pressure (-1.45 mmHg; 95% CI: -2.09, -0.80 mmHg; P < 0.001, I2 = 61.0%), fat percentage (-0.70%; 95% CI: -1.03, -0.36%; P < 0.001, I2 = 52.6%), fasting blood glucose (-0.18 mg/dL; 95% CI: -0.35, -0.01 mg/dL; P = 0.04, I2 = 62.0%), and C-reactive protein (CRP; including high-sensitivity-CRP [hs-CRP]) (-0.2972 mg/dL; 95% CI: -0.52, -0.08 mg/dL; P = 0.01, I2 = 87.9%). No significant changes were found for high-density-lipoprotein cholesterol (-0.12 mg/dL; 95% CI: -1.44, 0.69; P = 0.67, I2 = 89.4%) and triglycerides (-1.29 mg/dL; 95% CI: -2.74, 0.16; P = 0.08, I2 = 85.4%). Between-study heterogeneity could be explained by polyphenol subclass differences. CONCLUSION: The findings of this umbrella review support the beneficial effects of polyphenols on anthropometric and metabolic markers, but discretion is warranted to determine the clinical significance of the magnitude of the biomarker improvements. SYSTEMATIC REVIEW REGISTRATION: International Prospective Register of Systematic Reviews no. CRD42023420206.

A Class Effect Network Meta-analysis of Lipid Modulation in Non-alcoholic Steatohepatitis for Dyslipidemia.

Background and Aims: Pharmaceutical therapy for NASH is associated with lipid modulation, but the consensus on drug treatment is limited and lacks comparative analysis of effectiveness. A network meta-analysis was conducted to compare NASH drug classes in lipid modulation. Methods: Online databases were searched for randomized controlled trails (RCTs) evaluating NASH treatments in biopsy-proven NASH patients. Treatments were classified into four groups: (1) inflammation, (2) energy, (3) bile acids, and (4) fibrosis based on the mechanism of action. A Bayesian network analysis was conducted with outcome measured by mean difference (MD) with credible intervals (Crl) and surface under the cumulative ranking curve (SUCRA). Results: Forty-four RCTs were included in the analysis. Bile acid modulating treatments (MD: 0.05, Crl: 0.03-0.07) were the best treatment for improvement in high-density lipid (HDL) cholesterol, followed by treatments modulating energy (MD: 0.03, Crl: 0.02-0.04) and fibrosis (MD: 0.01, Crl: -0.12 to 0.14) compared with placebo. The top three treatments for reduction in triglycerides were treatments modulating energy (MD: -0.46, Crl: -0.49 to -0.43), bile acids (MD: -0.22, Crl: -0.35 to -0.09), and inflammation (MD: -0.08, Crl: -0.13 to -0.03) compared with placebo. SUCRA found treatment modulating fibrosis (MD: -1.27, Crl: -1.76 to -0.79) was the best treatment for reduction in low-density lipid (LDL) cholesterol followed by treatment modulating inflammation (MD: -1.03, Crl: -1.09 to -0.97) and energy (MD: -0.37, Crl: -0.39 to -0.34) compared with placebo, but LDL cholesterol was worsened by treatments modulating bile acids. Conclusions: Network analysis comparing the class effects of dyslipidemia modulation in NASH found that treatment targets can include optimization of atherogenic dyslipidemia. Future studies are required to evaluate the cardiovascular outcomes.