Effects of Ashwagandha (Withania somnifera) on Physical Performance: Systematic Review and Bayesian Meta-Analysis
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Abstract
Ashwagandha (Withania somnifera) is considered a potent adaptogen and anti-stress agent that could have some potential to improve physical performance. This preferred reporting items for systematic reviews and meta-analyses (PRISMA)-based comprehensi...
Ashwagandha (Withania somnifera) is considered a potent adaptogen and anti-stress agent that could have some potential to improve physical performance. This preferred reporting items for systematic reviews and meta-analyses (PRISMA)-based comprehensive systematic review and Bayesian meta-analysis aimed to evaluate clinical trials up to 2020 from PubMed, ScienceDirect, and Google Scholar databases regarding the effect of Ashwagandha supplementation on physical performance in healthy individuals. Besides implementing estimation statistics analysis, we developed Bayesian hierarchical models for a pre-specified subgroup meta-analysis on strength/power, cardiorespiratory fitness and fatigue/recovery variables. A total of 13 studies met the requirements of this systematic review, although only 12 were included in the quantitative analysis. A low-to-moderate overall risk of bias of the trials included in this study was detected. All Bayesian hierarchical models converged to a target distribution (Ȓ = 1) for both meta-analytic effect size (μ) and between-study standard deviation (τ). The meta-analytic approaches of the included studies revealed that Ashwagandha supplementation was more efficacious than placebo for improving variables related to physical performance in healthy men and female. In fact, the Bayesian models showed that future interventions might be at least in some way beneficial on the analyzed outcomes considering the 95% credible intervals for the meta-analytic effect size. Several practical applications and future directions are discussed, although more comparable studies are needed in exercise training, and athletic populations are needed to derive a more stable estimate of the true underlying effect.