1. Comparison of a Multi-Component Physical Function Battery to Usual Walking Speed for Assessing Lower Extremity Function and Mobility Limitation in Older Adults
- Author
-
C. Riwniak, Leatha A Clark, David W. Russ, Brian C. Clark, Janet E. Simon, Nathan P. Wages, and Todd M. Manini
- Subjects
Male ,Battery (electricity) ,medicine.medical_specialty ,030309 nutrition & dietetics ,Medicine (miscellaneous) ,Article ,Correlation ,03 medical and health sciences ,0302 clinical medicine ,Physical medicine and rehabilitation ,medicine ,Humans ,030212 general & internal medicine ,Mobility Limitation ,Aged ,Balance (ability) ,Aged, 80 and over ,Principal Component Analysis ,0303 health sciences ,Nutrition and Dietetics ,Receiver operating characteristic ,business.industry ,Gait ,Walking Speed ,Preferred walking speed ,Cross-Sectional Studies ,Lower Extremity ,Quality of Life ,Female ,Observational study ,Geriatrics and Gerontology ,business ,human activities - Abstract
OBJECTIVES: To compare a composite measure of physical function that comprises locomotor and non-locomotor tests (i.e., the Mobility Battery Assessment (MBA)) with traditional measures of mobility (4-m usual gait speed (UGS), six-minute walk (6MW) gait speed, and short physical performance battery (SPPB) score) for assessing lower extremity function and discriminating community dwelling older adults with and without mobility limitations. DESIGN: Cross-sectional, observational study. SETTING: Laboratory-based. PARTICIPANTS: 89 community-dwelling older adults (74.9±6.7). MEASUREMENTS: Using principal component analysis we derived an MBA score for 89 community-dwelling older adults, and quantified 4-m UGS, 6MW gait speed, and SPPB score. The MBA score was based on five lab-based tests. We also quantified self-reported lower extremity function/mobility using the Neuro-QOL Lower Extremity Function-Mobility instrument. Based on this data a continuous score was derived and subjects were classified as “mobility limited” or “non-mobility limited”. Correlations between the mobility measures and the Neuro-QOL score were calculated, and ROC curves were constructed to determine the AUC for the mobility measures ability to predict mobility limitations. RESULTS: The MBA had the largest AUC (0.92) for discriminating mobility limitations and exhibited the strongest correlation (0.73) with the Neuro-QOL Lower Extremity Function-Mobility Scale. The worst performing predictors were the 4-meter UGS and stair climb power both with an AUC of 0.8 for discriminating mobility limitations, and a low correlation with Neuro-QOL Lower Extremity Function Scale of 0.39 and 0.46, respectively. CONCLUSION: The MBA score moderately improves the magnitude of correlation and discrimination of mobility limitation in older adults than singular, standard tests of mobility.
- Published
- 2020