Impact of Two Whole-Body Vibration Exercise Protocols on Body Composition of Patients with Metabolic Syndrome
A Randomized Controlled Trial
Bibliographic Data
(1) Background: This study investigated the effects of two 6-week whole-body vibration exercise (WBVE) protocols on body composition in patients with metabolic syndrome (MSy). Thirty-three patients were allocated to either the Fixed Frequency WBVE Group (FFG-WBVE) or the Variable Frequency WBVE Group (VFG-WBVE). (2) Methods: A side-alternating vibration platform was used and the patients remained in the semi-squat position on this platform. In the FFG-WBVE ( n = 12; median age = 50.50 years) and (body mass index BMI = 31.95 kg/m 2 ), patients were exposed to 10 s of mechanical vibration at a fixed frequency of 5 Hz, followed by 50 s without vibration. In the VFG-WBVE ( n = 10; median age = 57.50 years) and (BMI = 32.50 kg/m 2 ), the patients performed 60 s of mechanical vibration at different frequencies from 5 to 16 Hz). Body composition evaluated through (bioelectrical impedance analysis and anthropometric measurements) were was evaluated before and after the all the interventions in each group. (3) Results: The VFG-WBVE decreased waist circumference, p = 0.01 and segmental fat mass [left arm, p = 0.01; right arm, p = 0.02 and trunk, p = 0.03]. Bone content increased, p = 0.01. No significant changes were observed in the FFG- WBVE. (4) Conclusions: In conclusion, this study demonstrated that 6 weeks of WBVE with a protocol with variable frequency can positively modify the body composition of MSY patients. These findings might contribute to improvements in the metabolic health of these patients
Anthropometry · Bioelectrical impedance analysis · Biology · Body mass index · Body water · Body weight · Fat mass · Physical therapy · Physics · Randomized controlled trial · Trunk · Vibration · Waist · Whole body vibration · Effects of Vibration on Health · Medicine · Noise Effects and Management · Occupational Health and Performance · Internal Medicine
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Statistical power analyses using G*Power 3.1
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