The effect of whole-body electromyostimulation on metabolic syndrome in affected adults: A subanalysis of a randomized controlled trial

全身电刺激对代谢综合征成年患者的影响:一项随机对照试验的亚组分析

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Abstract

Many people with osteoarthritis of the knee suffer from overweight, obesity, and cardiometabolic conditions. In the present subanalysis of a randomized controlled trial of the effect of whole-body electromyostimulation (WB-EMS) on knee osteoarthritis in overweight Caucasians, we focus on participants with Metabolic Syndrome (MetS). Based on previous research, we hypothesized that WB-EMS significantly improves the Metabolic Syndrome Z score (MetS-Z score) compared with non-training controls. Thirty-two of the initial 72 overweight adults (58 ± 6 years, body mass index: 31 ± 4 kg/m(2)) with knee osteoarthritis, randomly allocated to a 29-week standard WB-EMS application or to a non-exercising control group (CG) and suffering from MetS, were included. The primary outcome was the MetS-Z score, based on the criteria of the International Diabetes Federation. Secondary outcomes were MetS components, i.e., waist circumference, mean arterial blood pressure, fasting glucose, triglycerides, and HDL-cholesterol. Based on the intention-to-treat principle, analysis of covariance determines differences between the groups (i.e., "effects"). In total, three participants were lost to 29-week follow-up. The attendance rate averaged 89% ± 9% in the WB-EMS group. Adverse effects related to the intervention were not observed. WB-EMS (n = 17) induced a non-significant, medium-size effect (p = 0.061; η (2) = 0.13) on the MetS-Z score compared with non-exercise CG (n = 15). In addition, no significant effects (p ≥ 0.146) were observed for MetS components. In the present study, we observed a moderate, although non-significant effect on the MetS-Z score. Given that the WB-EMS application was well-tolerated and accepted by the participants, we conclude that this exercise technology may offer (limited) benefits for MetS treatment. Nevertheless, further studies should address this issue with higher statistical power.

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