Citation

Lord S, Galna B, Verghese J, Coleman S, Burn D, Rochester L. J. Gerontol. A Biol. Sci. Med. Sci. 2013; 68(7): 820-827.

Affiliation

Address correspondence to Lynn Rochester, Professor of Human Movement Science, Institute for Ageing and Health, Newcastle University, Clinical Ageing Research Unit, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL. E-mail: lynn.rochester@ncl.ac.uk.

Copyright

(Copyright © 2013, Gerontological Society of America)

DOI

10.1093/gerona/gls255

PMID

23250001

Abstract

BACKGROUND: Gait is an important predictor of survival in older adults. Gait characteristics help to identify markers of incipient pathology, inform diagnostic algorithms and disease progression, and measure efficacy of interventions. However, there is no clear framework to guide selection of gait characteristics. This study developed and validated a model of gait in older adults based on a strong theoretical paradigm. METHODS: One hundred and eighty-nine older adults with a mean (SD) age of 69.5 (7.6) years were assessed for 16 spatiotemporal gait variables using a 7-m instrumented walkway (GAITRite) while walking for 2 minutes. Principal components analysis and factor analysis "varimax" procedure were used to derive a model that was validated using a multimethod approach: replication of previous work; association of gait domains with motor, cognitive, and behavioral attributes; and discriminatory properties of gait domains using age as a criterion. RESULTS: Five factors emerged from the principal components analysis: pace (22.5%), rhythm (19.3%), variability (15.1%), asymmetry (14.5%), and postural control (8.0%), explaining 79.5% of gait variance in total. Age, executive function, power of attention, balance self-efficacy, and physical fatigue were independently and selectively associated with 4 gait domains, explaining up to 40.1% of total variance. Median age discriminated pace, variability, and postural control domains. CONCLUSIONS: This study supports a 5-factor model of gait in older adults with domains that preferentially select for motor, cognitive, and behavioral attributes. Future research is required to validate the model. If successful, it will facilitate hypothesis-driven research to explain underlying gait mechanisms, identify contributory features to gait disturbance, and examine the effect of intervention.

Language: en