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Medical, sensorimotor and cognitive factors associated with gait variability: a longitudinal population-based study


Jayakody, O and Breslin, M and Srikanth, V and Callisaya, M, Medical, sensorimotor and cognitive factors associated with gait variability: a longitudinal population-based study, Frontiers in Aging Neuroscience, 10 Article 419. ISSN 1663-4365 (2018) [Refereed Article]


Copyright Statement

Copyright 2018 Jayakody, Breslin, Srikanth and Callisaya. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

DOI: doi:10.3389/fnagi.2018.00419


Background: Greater gait variability increases the risk of falls. However, little is known about changes in gait variability in older age. The aims of this study were to examine: (1) change in gait variability across time and (2) factors that predict overall mean gait variability and its change over time.

Methods: Participants (n = 410; mean age 72 years) were assessed at baseline and during follow up visits at an average of 30 and 54 months. Step time, step length, step width and double support time (DST) were measured using a GAITRite walkway. Variability was calculated as the standard deviation of all steps for each individual. Covariates included demographic, medical, sensorimotor and cognitive factors. Mixed models were used to determine (1) change in gait variability over time (2) factors that predicted or modified any change.

Results: Over 4.6 years the presence of cardiovascular disease at baseline increased the rate of change for step length variability (p = 0.04 for interaction), lower education increased the rate of change for DST variability (p = 0.04) and weaker quadriceps strength increased the rate of change for step width variability (p = 0.01). Greater postural sway predicted greater variability on average across the three phases (p < 0.05). Arthritis, a higher body mass index (BMI), slower processing speed and lower quadriceps strength predicted greater mean step time variability (p < 0.05). Arthritis and a higher BMI predicted greater mean step length variability, while slower processing speed and BMI predicted greater mean DST variability (p < 0.05).

Conclusion: Over a nearly 5-year period, variability in different gait measures do not show uniform changes over time. Furthermore, each variability measure appears to be modified and predicted by different factors. These results provide information on potential targets for future trials to maintain mobility and independence in older age.

Item Details

Item Type:Refereed Article
Keywords:cognition, gait, gait variability, longitudinal study, older age, sensorimotor
Research Division:Health Sciences
Research Group:Epidemiology
Research Field:Epidemiology not elsewhere classified
Objective Division:Health
Objective Group:Specific population health (excl. Indigenous health)
Objective Field:Health related to ageing
UTAS Author:Jayakody, O (Ms Shanika Jayakody Arachchige Dona)
UTAS Author:Breslin, M (Dr Monique Breslin)
UTAS Author:Srikanth, V (Dr Velandai Srikanth)
UTAS Author:Callisaya, M (Dr Michele Callisaya)
ID Code:130509
Year Published:2018
Web of Science® Times Cited:7
Deposited By:Menzies Institute for Medical Research
Deposited On:2019-01-30
Last Modified:2019-03-18
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