AUTHOR=Kim Sung-Woo , Park Hun-Young , Jung Hoeryong , Lim Kiwon TITLE=Development of Functional Fitness Prediction Equation in Korean Older Adults: The National Fitness Award 2015–2019 JOURNAL=Frontiers in Physiology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2022.896093 DOI=10.3389/fphys.2022.896093 ISSN=1664-042X ABSTRACT=

The main advantage of measuring functional fitness (FF) in older adults is that individual tests can estimate and track the rate of decline with age. This study aimed to develop a multiple linear regression model for predicting FF variables using easy-to-measure independent variables (e.g., sex, age, body mass index, and percent body fat) in Korean older adults. National Fitness Award datasets from the Republic of Korea were used in this analysis. The participants were aged ≥65 years and included 61,465 older men and 117,395 older women. The FF variables included the hand grip strength, lower body strength (30-s chair stand), lower body flexibility (chair sit-and-reach), coordination (figure of 8 walk), agility/dynamic balance (timed up-and-go), and aerobic endurance (2-min step test). An estimation multiple linear regression model was developed using a stepwise technique. In the regression model, the coefficient of determination in the hand grip strength test (adjusted R2 = 0.773, p < 0.001) was significantly high. However, the coefficient of determination in the 30-s chair stand (adjusted R2 = 0.296, p < 0.001), chair sit-and-reach (adjusted R2 = 0.435, p < 0.001), figure of 8 walk (adjusted R2 = 0.390, p < 0.001), timed up-and-go (adjusted R2 = 0.384, p < 0.001), and 2-min step tests (adjusted R2 = 0.196, p < 0.001) was significantly low to moderate. Our findings suggest that easy-to-measure independent variables can predict the hand grip strength in older adults. In future studies, explanatory power will be further improved if multiple linear regression analysis, including the physical activity level and nutritional status of older adults, is performed to predict the FF variables.