Toggle Main Menu Toggle Search

Open Access padlockePrints

Independent Domains of Gait in Older Adults and Associated Motor and Nonmotor Attributes: Validation of a Factor Analysis Approach

Lookup NU author(s): Dr Susan Lord, Dr Brook Galna, Dr Shirley ColemanORCiD, Professor David Burn, Professor Lynn RochesterORCiD

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


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.


Publication metadata

Author(s): Lord S, Galna B, Verghese J, Coleman S, Burn D, Rochester L

Publication type: Article

Publication status: Published

Journal: Journals of Gerontology Series A: Biological Sciences & Medical Sciences

Year: 2013

Volume: 68

Issue: 7

Pages: 820-827

Print publication date: 18/12/2012

ISSN (print): 1079-5006

ISSN (electronic): 1758-535X

Publisher: Oxford University Press

URL: http://dx.doi.org/10.1093/gerona/gls255

DOI: 10.1093/gerona/gls255

PubMed id: 23250001


Altmetrics

Altmetrics provided by Altmetric


Share