Related Experiment Video
Updated: Jan 31, 2026

A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments
Published on: April 15, 2014
Medical, Sensorimotor and Cognitive Factors Associated With Gait Variability: A Longitudinal Population-Based Study
Oshadi Jayakody1, Monique Breslin1, Velandai Srikanth1,2
1Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
Abstract:
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.
Related Concept Videos
Longitudinal Research
Longitudinal Studies
Cognitive Dissonance
Population Growth
What is Population Genetics?
What are Populations and Communities?

