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. 2022 Jul 28;23(15):8344.
doi: 10.3390/ijms23158344.

Effects of the Treatment with Flavonoids on Metabolic Syndrome Components in Humans: A Systematic Review Focusing on Mechanisms of Action

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Effects of the Treatment with Flavonoids on Metabolic Syndrome Components in Humans: A Systematic Review Focusing on Mechanisms of Action

Henrique J C B Gouveia et al. Int J Mol Sci. .

Abstract

Diets high in bioactive compounds, such as polyphenols, have been used to mitigate metabolic syndrome (MetS). Polyphenols are a large group of naturally occurring bioactive compounds, classified into two main classes: non-flavonoids and flavonoids. Flavonoids are distributed in foods, such as fruits, vegetables, tea, red wine, and cocoa. Studies have already demonstrated the benefits of flavonoids on the cardiovascular and nervous systems, as well as cancer cells. The present review summarizes the results of clinical studies that evaluated the effects of flavonoids on the components of the MetS and associated complications when offered as supplements over the long term. The results show that flavonoids can significantly modulate several metabolic parameters, such as lipid profile, blood pressure, and blood glucose. Only theaflavin and catechin were unable to affect metabolic parameters. Moreover, only body weight and body mass index were unaltered. Thus, the evidence presented in this systematic review offers bases in support of a flavonoid supplementation, held for at least 3 weeks, as a strategy to improve several metabolic parameters and, consequently, reduce the risk of diseases associated with MetS. This fact becomes stronger due to the rare side effects reported with flavonoids.

Keywords: biomarkers; blood pressure; dyslipidemias; inflammation; insulin resistance; lipid metabolism; metabolic syndrome; polyphenols.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Structures and classification of the polyphenols and the main flavonoids.
Figure 2
Figure 2
PRISMA flow diagram of study selection process. From: [23].
Figure 3
Figure 3
Risk of bias graph: review authors’ judgements about each risk of bias item presented as percentages across all included cluster randomized trials (parallel groups).
Figure 4
Figure 4
Risk of bias graph: review authors’ judgements about each risk of bias item presented as percentages across all included crossover trials (individually randomized).

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