Can A Simple Transfer Task Predict Lower-Extremity Physical Function As Measured By Standardized Clinical Measures?

PURPOSE: Lower-extremity physical function (LEPF) is associated with health outcomes such as risk for falling, physical disability, and mortality in older adults. Due to increasing evidence of disability onset occurring earlier in the lifespan, expanding assessment of functional status in middle-age adults is of growing importance. Furthermore, administering many of the current standardized objective tests (i.e. 6-Minute Walk Test, Timed Up and Go, and 30-second Chair Stand tests) in clinical settings is not feasible due to limited time, space, and equipment. Identifying simple, cost-effective assessments to evaluate LEPF status is paramount due to the potential for clinical application. Thus, this study aimed to evaluate if a simple transfer task could predict LEPF in middle-age and older adults. METHODS: Middle-age and older adults (n=230, 17% male; 52-89 yo; 29.1+5.8 kg/m2) completed a transfer task (TRANSFER). This required them to start in a standing position, and without the use of assistive devices, sit on the floor, and return to a standing position as quickly as possible. LEPF was calculated using a composite Z-score based on scores from conventional and standardized 6-Minute Walk Test, Timed Up and Go, and 30-second Chair Stand tests. RESULTS: Bivariate correlations revealed that TRANSFER was associated with age (r = 0.27, p < 0.01), comorbidities (r = 0.33, p < 0.01), and BMI (r = 0.28, p < 0.01). Using linear regression analyses, TRANSFER was a significant predictor of LEPF Z-score (standardized β = -0.73, p < 0.01) independently accounting for 39.6% of the variance after adjustment for covariates. CONCLUSION: Our results suggest that the ability to lower oneself to the ground and return to a standing positon is a significant indicator of LEPF in middle-age and older adults. Further study is warranted to determine the clinical relevance of this simplified evaluation of LEPF and its ability to predict falls, physical disability, and mortality.