Literature DB >> 27020175

Gait variability analysed using an accelerometer is associated with locomotive syndrome among the general elderly population: The GAINA study.

Hiromi Matsumoto1, Hiroshi Hagino2, Mari Osaki3, Shinji Tanishima4, Chika Tanimura5, Akihiro Matsuura6, Tomoyuki Makabe7.   

Abstract

BACKGROUND: Gait variability analysed using an accelerometer provides a unique measurement of locomotive dysfunction in patients with musculoskeletal disease or in frail elderly subjects. Therefore, assessing gait variability may become a clinical screening method for the locomotive syndrome. The purpose of this study was to investigate whether gait variability analysed using an accelerometer was associated with locomotive syndrome in the general elderly population.
METHODS: A total of 273 residents were screened after a yearly medical check-up, and of these, 223 subjects (mean age, 73.6 ± 8.3 years) met the eligibility criteria. Demographic information, body function and structure measurements (bone mass, grip strength, muscle mass, and postural alignment), and gait parameters were assessed. Gait variability analysis was based on acceleration using a wireless tri-axial accelerometer attached to the 3rd lumbar vertebra process by a trunk belt. Autocorrelation coefficients were used to represent gait variability in three directions: vertical, mediolateral, and anteroposterior. The subjects were classified as either having or not having the locomotive syndrome based on the 5-question Geriatric Locomotive Function Scale.
RESULTS: Of the 223 subjects, 41 (18.3%) had the locomotive syndrome. Autocorrelation coefficients in three directions were lower in the subjects with locomotive syndrome. Using multivariate logistic regression analysis with adjustment factors, of the autocorrelation coefficients only gait variability in the vertical axis remained a significant independent associated with the locomotive syndrome.
CONCLUSION: This finding suggested that gait variability based on evaluation of autocorrelation coefficients in the vertical axis measured using an accelerometer has the potential to become a screening method for the locomotive syndrome in the general elderly population.
Copyright © 2016 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

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Year:  2016        PMID: 27020175     DOI: 10.1016/j.jos.2016.02.003

Source DB:  PubMed          Journal:  J Orthop Sci        ISSN: 0949-2658            Impact factor:   1.601


  5 in total

1.  Evaluation of gait characteristics in subjects with locomotive syndrome using wearable gait sensors.

Authors:  Yuki Saito; Tomoya Ishida; Yoshiaki Kataoka; Ryo Takeda; Shigeru Tadano; Teppei Suzuki; Kentaro Nakamura; Akimi Nakata; Satoshi Osuka; Satoshi Yamada; Mina Samukawa; Harukazu Tohyama
Journal:  BMC Musculoskelet Disord       Date:  2022-05-14       Impact factor: 2.562

2.  A Path Model Analysis of the Causal Relationship between Self-care Agency and Healthy Behavior in Community-dwelling Older People from the GAINA Study.

Authors:  Chika Tanimura; Hiromi Matsumoto; Junko Yoshimura; Yasuko Tokushima; Yoko Yamamoto; Yukiko Fujihara; Masayuki Miyoshi; Hiroshi Hagino
Journal:  Yonago Acta Med       Date:  2019-03-28       Impact factor: 1.641

3.  Relationship of Physical Activity to Self-Care Agency and Physical Condition Among Older Adults in a Rural Area.

Authors:  Junko Yoshimura; Chika Tanimura; Hiromi Matsumoto; Yasuko Tokushima; Kazuoki Inoue; Daeho Park; Hiroshi Hagino
Journal:  Yonago Acta Med       Date:  2021-01-06       Impact factor: 1.641

4.  Acceleration Gait Measures as Proxies for Motor Skill of Walking: A Narrative Review.

Authors:  Pritika Dasgupta; Jessie VanSwearingen; Alan Godfrey; Mark Redfern; Manuel Montero-Odasso; Ervin Sejdic
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2021-03-01       Impact factor: 3.802

Review 5.  Locomotive Syndrome and Lumbar Spine Disease: A Systematic Review.

Authors:  Takaomi Kobayashi; Tadatsugu Morimoto; Koji Otani; Masaaki Mawatari
Journal:  J Clin Med       Date:  2022-02-27       Impact factor: 4.241

  5 in total

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