Functional Stratification Reveals Speed-Independent Gait Impairments Beyond Chronological Age
Wu, Y.; Wang, X.; Manini, T.; Hu, B.
Show abstract
BackgroundGait is a clinically relevant indicator of functional decline in aging populations. However, most studies classify older adults by chronological rather than functional age, which may obscure early impairments detectable through kinematic profiling. This study examined whether stratifying older adults by functional status using the Short Physical Performance Battery (SPPB) enhances sensitivity in detecting gait abnormalities and instability-related compensatory patterns. MethodsA total of 190 adults completed gait trials on a pressure-sensitive walkway. Twenty-eight spatial, temporal, and variability-based gait parameters were derived. Participants were categorized as young adults or older adults, who were further stratified into high- and low-functioning groups based on SPPB scores. Analysis of covariance (ANCOVA) was performed, adjusting for habitual walking speed to isolate functional effects. FindingsAfter adjusting for speed, the low-functioning group demonstrated longer stance and double-support durations, wider step width, and greater step-to-step variability in both spatial and temporal domains compared with both the high-functioning and young reference groups. These findings indicate a compensatory, instability-driven control strategy that challenges the assumption of a "slower but steady" gait in aging. High-functioning older adults exhibited gait patterns more closely resembling those of younger adults. InterpretationFunctional classification using the SPPB provided greater sensitivity than chronological age in detecting early mobility decline. Gait variability emerged as a salient biomarker of impaired neuromuscular control. Integrating quantitative gait profiling with validated functional assessments may improve early screening, targeted intervention, and fall prevention strategies.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.