Dementia and Geriatric Cognitive Disorders

Original Research Article

Gait Variability Can Predict the Risk of Cognitive Decline in Cognitively Normal Older People

Byun S.a,b · Han J.W.a · Kim T.H.c · Kim K.d · Kim T.H.a · Park J.Y.a · Suh S.W.a · Seo J.Y.e · So Y.a · Lee K.H.f · Lee J.R.a · Jeong H.a · Jeong H.-G.g · Han K.a · Hong J.W.a · Kim K.W.a,b,h

Author affiliations

aDepartment of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
bDepartment of Psychiatry, School of Medicine, Seoul National University, Seoul, Republic of Korea
cDepartment of Psychiatry, Yonsei University Wonju Severance Christian Hospital, Wonju, Republic of Korea
dDepartment of Psychiatry, National Center for Mental Health, Seoul, Republic of Korea
eDepartment of Neuropsychiatry, Changwon Gyeongsang National University Hospital, Jinju, Republic of Korea
fDepartment of Psychiatry, Bongseng Memorial Hospital, Busan, Republic of Korea
gDepartment of Psychiatry, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
hDepartment of Brain and Cognitive Science, Seoul National University College of Natural Sciences, Seoul, Republic of Korea

Keywords: GaitMild cognitive impairmentElderlyVariabilitySpeed

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Dement Geriatr Cogn Disord 2018;45:251–261
https://doi.org/10.1159/000489927

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Article / Publication Details

First-Page Preview
Abstract of Original Research Article

Received: January 09, 2018
Accepted: May 09, 2018
Published online: June 28, 2018
Issue release date: August 2018

Number of Print Pages: 11
Number of Figures: 1
Number of Tables: 2

ISSN: 1420-8008 (Print)
eISSN: 1421-9824 (Online)

For additional information: https://www.karger.com/DEM

Abstract

Background: The aim of this study was to investigate the association of gait speed and gait variability, an index of how much gait parameters, such as step time, fluctuate step-to-step, with risk of cognitive decline in cognitively normal elderly individuals. While high gait variability is emerging as an early indicator of dementing illnesses, there is little research on whether high gait variability predicts cognitive decline in cognitively normal elderly who have no evidence of cognitive impairment. Methods: In this 4-year prospective cohort study on 91 community-dwelling cognitively normal elderly individuals without cerebral ischemic burden or Parkinsonism, we evaluated gait speed and step time variability using a tri-axial accelerometer placed on the center of body mass, and diagnosed mild cognitive impairment (MCI) according to the International Working Group on MCI. We performed Kaplan-Meier analysis with consecutive log-rank testing for MCI-free survival by cohort-specific tertiles of gait speed; hazard ratios (HR) of incident MCI were estimated using Cox proportional hazards regression analysis adjusted for age, sex, education level, Cumulative Illness Rating Scale score, GDS score, and presence of the apolipoprotein E ε4 allele. Results: Out of the 91 participants in the baseline assessment, 87 completed one or more 2-year follow-up assessments, and the median duration of follow-up was 47.1 months. Kaplan-Meier curves of incident MCI show evident differences in risk by gait variability group (χ2 = 9.64, p = 0.002, log-rank test). Mean MCI-free survival in the high variability group was 12% shorter than in the mid-to-low tertile group (47.4 ± 1.74 [SD] vs. 54.04 ± 0.52 months), while it was comparable between gait speed groups (51.59 ± 0.70 vs. 50.64 ± 1.77 months; χ2 = 1.16, p = 0.281). In multivariate analysis, subjects with high gait variability showed about 12-fold higher risk of MCI (HR = 11.97, 95% CI = 1.29–111.37) than those with mid-to-low variability. However, those with slow gait speed showed comparable MCI risk to those with mid-to-high speed (HR = 5.04, 95% CI = 0.53–48.18). Conclusions: Gait variability may be a better predictor of cognitive decline than gait speed in cognitively normal elderly individuals without cerebral ischemic burden or Parkinsonism.

© 2018 S. Karger AG, Basel



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Article / Publication Details

First-Page Preview
Abstract of Original Research Article

Received: January 09, 2018
Accepted: May 09, 2018
Published online: June 28, 2018
Issue release date: August 2018

Number of Print Pages: 11
Number of Figures: 1
Number of Tables: 2

ISSN: 1420-8008 (Print)
eISSN: 1421-9824 (Online)

For additional information: https://www.karger.com/DEM

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