TY - JOUR
T1 - Independent domains of gait in older adults and associated motor and nonmotor attributes
T2 - Validation of a factor analysis approach
AU - Lord, Sue
AU - Galna, Brook
AU - Verghese, Joe
AU - Coleman, Shirley
AU - Burn, David
AU - Rochester, Lynn
N1 - Funding Information:
Funding The research was supported by the National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre based at Newcastle upon Tyne Hospitals National Health Service (NHS) Foundation Trust and Newcastle University.
PY - 2013/7
Y1 - 2013/7
N2 - 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.
AB - 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.
KW - Factor analysis
KW - Gait
KW - Model.
KW - Older adults
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U2 - 10.1093/gerona/gls255
DO - 10.1093/gerona/gls255
M3 - Article
C2 - 23250001
AN - SCOPUS:84875173244
SN - 1079-5006
VL - 68
SP - 820
EP - 827
JO - Journals of Gerontology - Series A Biological Sciences and Medical Sciences
JF - Journals of Gerontology - Series A Biological Sciences and Medical Sciences
IS - 7
ER -