Functional Tests As Predictors Of Balance, Fear, And Risk Of Falling In Healthy Subjects

• Main Author: Veras T.G.*
• Publication Date: 2022
• Other Authors: Venancio R.S.*, Klein S.R.*, Heinz P.D.R.*, Gulart, Aline Almeida, Munari, Anelise Bauer, Mayer, Anamaria Fleig
• Format: Article
• Language: eng
• Source: Repositório Institucional da Udesc
• dARK ID: ark:/33523/0013000009wt2
• Download full: https://repositorio.udesc.br/handle/UDESC/3455

© 2021 Taylor & Francis Group, LLC.Objective: Verify which test, Glitttre-ADL test (TGlittre) or six-minute walk test (6MWT), better predicts balance, fear, and risk of falling in middle-aged and older adults. Method: Twenty-eight individuals (15 women) completed the study protocol, which included: anthropometric assessment, spirometry, Falls Efficacy Scale-International-Brazil (FES-I-Brazil), Activities-specific Balance Confidence Scale (ABC), Timed Up and Go Test (TUG), Berg Balance Scale (BBS), TGlittre, and 6MWT. The Shapiro Wilk test investigated the distribution of the data. To verify if there was a correlation between the performance in TGlittre and 6MWT and the balance, fear, and risk of falling variables, the Pearson or Spearman correlation coefficient were used. Simple linear regression and stepwise multiple linear regression were conducted to identify which functional capacity test better predicts balance, fear, and risk of falling. Results: Both TGlittre and 6MWT correlated (r = 0.44, p = .02 and r = −0.59, p = .003, respectively) and were able to predict the TUG (R2 = 0.17 and R2 = 0.26, p < .005, respectively). However, when analyzed in a multiple regression model, the 6MWT was better predictor of TUG (26%). Only TGlittre correlated (r = 0.39 and r = −0.38, p = .04) and was able to predict the FES-I-Brazil and BBS scores (17%), suggesting that TGlittre better reflects the worry about falls and balance in multiple ADL contexts. Conclusions: The 6MWT and the TGlittre are able to predict balance assessed by the TUG. However, the 6MWT has proved to be more effective in predicting TUG results.