Abstract
Objective
To identify homogeneous subsets of survivors of chronic stroke who share similar characteristics
across several domains and test if these groups differ in real-world walking activity.
We hypothesized that variables representing the domains of walking ability, psychosocial,
environment, and cognition would be important contributors in differentiating real-world
walking activity in survivors of chronic stroke.
Design
Cross-sectional, secondary data analysis.
Setting
University/laboratory.
Participants
A total of 283 individuals with chronic (≥6mo) stroke (N=238).
Interventions
Not applicable.
Main Outcome Measures
Thirteen variables representing 5 domains were included: (1) walking ability: 6-minute
walk test (6MWT), self-selected speed (SSS) of gait; (2) psychosocial: Patient Health
Questionnaire-9, Activities-specific Balance Confidence (ABC) scale; (3) physical
health: low-density lipoprotein cholesterol, body mass index, Charlson Comorbidity
Index (CCI); (4) cognition: Montreal Cognitive Assessment (MoCA); and (5) environment:
living situation and marital status, work status, Area Deprivation Index (ADI), Walk
Score. Mixture modeling was used to identify latent classes of survivors of stroke.
After identifying the latent classes, walking activity, measured as steps per day
(SPD), was included as a distal outcome to understand if classes were meaningfully
different in their real-world walking
Results
A model with 3 latent classes was selected. The 6MWT, SSS, ABC scale, and Walk Score
were significantly different among all 3 classes. Differences were also seen for the
MoCA, ADI, and CCI between 2 of the 3 classes. Importantly, the distal outcome of
SPD was significantly different in all classes, indicating that real-world walking
activity differs among the groups identified by the mixture model.
Conclusions
Survivors of stroke with lower walking ability, lower self-efficacy, lower cognitive
abilities, and greater area deprivation had lower SPD. These results demonstrate that
the physical and social environment (including socioeconomic factors) and cognitive
function should also be considered when developing interventions to improve real-world
walking activity after stroke.
Keywords
List of abbreviations:
ABC (Activities-specific Balance Confidence), AIC (Akaike's information criterion), ADI (Area Deprivation Index), BIC (Bayesian information criterion), BMI (body mass index), CCI (Charlson Comorbidity Index), IQR (interquartile range), LDL (low-density lipoprotein), MoCA (Montreal Cognitive Assessment), PHQ-9 (Patient Health Questionnaire-9), SSS (self-selected speed), 6MWT (6-minute walk test), SPD (steps per day), VLMR (Vuong-Lo-Mendell-Rubin likelihood ratio test)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: April 21, 2021
Accepted:
March 22,
2021
Received in revised form:
December 10,
2020
Received:
July 23,
2020
Footnotes
Supported in part by a Florence P. Kendall Doctoral Scholarship from the Foundation for Physical Therapy Research and in part from a National Institutes of Health grant (grant no. 1R01HD086362-01A1). The research was also funded by National Institutes of Health (grant no. K12 HD055931). These funding sources played no role in the analysis and interpretation of data, writing, or decision to submit the article for publication.
Disclosures: none
Identification
Copyright
© 2021 The American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.
