Factors influencing gait speed in community-dwelling older women: A Bayesian approach.

Gait Posture

Integrative Physiology Research Center, Department of Biological Sciences, Universidade Estadual do Sudoeste da Bahia (UESB), Jequié, BA 45210-506, Brazil; Research Group in Neuromuscular Physiology, Department of Biological Sciences, Universidade Estadual do Sudoeste da Bahia (UESB), Jequié, BA 45210-506, Brazil; Postgraduate Program in Nursing & Health, Universidade Estadual do Sudoeste da Bahia (UESB), Jequié, BA 45210-506, Brazil. Electronic address:

Published: February 2022

Background: Human gait is a complex task resulting from the interaction of sensory perception, muscle force output, and sensory-motor integration, which declines with the aging process and impacts gait speed in older women.

Research Question: What are the separate and combined impacts of sensory-motor factors on gait speed of older women?

Methods: Sixty healthy older women (69.3 ± 5.9 years) volunteered for this study. A previous screening using Pearson's correlation selected variables significantly correlated with gait speed: age, plantar tactile perception, lower limb explosive force, and mean velocity (MV) of the center of pressure (CoP). Simple and multivariate regression models were performed with selected variables. The magnitude of evidence was obtained using Bayesian inference, determining posterior probabilities based on our data.

Results: Gait speed was negatively correlated with age and positively correlated with plantar tactile perception, MV (Romberg index), and lower limb explosive force. The coefficient of determination (R) varied between 0.06 for plantar tactile perception and 0.22 for explosive force (p < 0.05). The multivariate model, including age, MV (Romberg index), and lower limb explosive force, explained 44% (R = 0.44) of the variance in gait speed, with a small standard error of estimate (0.14 m/s). Bayesian inference confirmed the good posterior probability of the model.

Significance: Age, plantar tactile perception, MV (Romberg index), and lower limb explosive force impact gait speed, whereas the combination of the first three factors has an excellent posterior probability of predicting or affecting gait speed.

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Source
http://dx.doi.org/10.1016/j.gaitpost.2021.12.022DOI Listing

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