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THE UTILIZATION OF POWER TO PREDICT CHANGES IN DYNAMIC BALANCE

Abstract

Conner Buckles1, Nic Gillis1, Larissa Boyd1, Melissa Powers1, & Michelle Gray 2 1University of Central Oklahoma, Edmond, Oklahoma; 2University of Arkansas, Fayetteville, Arkansas; e-mail: cbuckles2@uco.edu

Power production and dynamic balance are important in maintaining and improving functionality in older adults. When working to improve exercise performance or activities of daily living (ADLs), older adults often encounter difficulty due to insufficient power or balance. While a relationship exists between power and dynamic balance, more research is necessary to further understand this connection. PURPOSE: The purpose of this study was to determine whether the ability to produce power predicted changes in performance on the 8-Foot Up-and-Go (UPGO) following 6 months of strength training at 80% 1RM in older adults. METHODS: Thirty-three older adults over the age of 65 (M=81.665.91) participated in a six month total body strength training program at 80% one-rep max (1RM). Power was assessed at pre-test using a velocity sensor system attached to a broomstick. Participants held the broomstick across their chest and performed a chair stand as quickly as possible. The mean output of 10 trials were recorded for average and peak power. The UPGO test was used to determine dynamic balance. Difference scores were calculated on the UPGO from pre- to post-test. A linear regression analysis was utilized. RESULTS: One outlier was removed from the dataset. UPGO improved by .30.55 seconds on average from pre- to post-test. Peak power (M=832.27201.56 W) was a significant predictor of UPGO mean difference scores (β=.40, t(30)=2.45, p=.02), significantly accounting for 13.5% of the variance (R2= .13, F(1,31)=5.98, p=.02). Average power (M=476.20137.21 W) did not significantly predict changes in UPGO performance (p=.18). CONCLUSION: While previous research has found a positive correlation between power and dynamic balance, peak power may be a more significant contributor than average power. Furthermore, 86.5% of the variance was unexplained, suggesting dynamic balance may be predicted by multiple factors.

Funding provided by Oklahoma Center for the Advancement of Science and Technology

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