↓ Skip to main content

PLOS

A Behavioral Mechanism of How Increases in Leg Strength Improve Old Adults’ Gait Speed

Overview of attention for article published in PLOS ONE, October 2014
Altmetric Badge

Mentioned by

twitter
13 X users
facebook
2 Facebook pages

Citations

dimensions_citation
38 Dimensions

Readers on

mendeley
129 Mendeley
Title
A Behavioral Mechanism of How Increases in Leg Strength Improve Old Adults’ Gait Speed
Published in
PLOS ONE, October 2014
DOI 10.1371/journal.pone.0110350
Pubmed ID
Authors

Azusa Uematsu, Kazushi Tsuchiya, Norio Kadono, Hirofumi Kobayashi, Takamasa Kaetsu, Tibor Hortobágyi, Shuji Suzuki

Abstract

We examined a behavioral mechanism of how increases in leg strength improve healthy old adults' gait speed. Leg press strength training improved maximal leg press load 40% (p = 0.001) and isometric strength in 5 group of leg muscles 32% (p = 0.001) in a randomly allocated intervention group of healthy old adults (age 74, n = 15) but not in no-exercise control group (age 74, n = 8). Gait speed increased similarly in the training (9.9%) and control (8.6%) groups (time main effect, p = 0.001). However, in the training group only, in line with the concept of biomechanical plasticity of aging gait, hip extensors and ankle plantarflexors became the only significant predictors of self-selected and maximal gait speed. The study provides the first behavioral evidence regarding a mechanism of how increases in leg strength improve healthy old adults' gait speed.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Netherlands 1 <1%
Finland 1 <1%
Denmark 1 <1%
Japan 1 <1%
Unknown 124 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 14%
Student > Master 17 13%
Student > Bachelor 13 10%
Researcher 11 9%
Student > Doctoral Student 8 6%
Other 21 16%
Unknown 41 32%
Readers by discipline Count As %
Sports and Recreations 24 19%
Medicine and Dentistry 17 13%
Nursing and Health Professions 15 12%
Engineering 6 5%
Psychology 5 4%
Other 14 11%
Unknown 48 37%