Association of gait with global cognitive function and cognitive domains detected by MoCA-J among community-dwelling older adults: a cross-sectional study

Wen Hao,Wenjing Zhao,Akiko Tamakoshi,Shigekazu Ukawa,Katsunori Kondo,Takashi Kimura,Ken Kadoya

doi:10.1186/s12877-021-02467-5

Abstract

BackgroundGait was proved to be strongly associated with global cognitive function and multiple cognitive domains; however, previous research usually concentrated on individual gait parameters. This study used wearable sensors to measure gait parameters in different aspects and comprehensively explored the association of gait with global cognitive function and cognitive domains.MethodsThe data of this cross-sectional study were obtained from 236 community-dwelling Japanese older adults (125 men and 111 women) aged 70–81 years. Gait was measured by asking participants to walk a 6-m course and back using the Physilog® sensors (GaiUp®, Switzerland). Global cognitive function and cognitive domains were evaluated by face-to-face interviews using the Japanese version of the Montreal Cognitive Assessment. Twenty gait parameters were summarized as independent gait factors using factor analysis. A generalized linear model and linear regression model were used to explore the relationship of gait with global cognitive function and cognitive domains adjusted for several confounding factors.ResultsFactor analysis yielded four gait factors: general cycle, initial contact, propulsion, and mid-swing. Among them, general cycle factor was significantly associated with global cognitive function (β = − 0.487, [− 0.890, − 0.085]) and executive function (P = 0.049); initial contact was associated with executive function (P = 0.017).ConclusionGeneral cycle of gait might be the better marker of global cognitive function and gait is most strongly associated with executive function. The longitudinal relationships should be examined in future cohort studies.

Highlights

Gait was proved to be strongly associated with global cognitive function and multiple cognitive domains; previous research usually concentrated on individual gait parameters
Based on the knowledge that quantitative gait parameters are highly correlated with each other and their individual relationships with cognitive function may be difficult to observe while adjusting for other gait variables [7], conceptual models using principal component analysis or factor analysis to provide a simplified framework for selecting grouped gait factors were suggested in gait analysis [8]
Factor analysis with quartimax rotation yielded exactly four orthogonal factors that accounted for 89.17% of the variance in 20 gait parameters (Table 2)

Summary

Introduction

Gait was proved to be strongly associated with global cognitive function and multiple cognitive domains; previous research usually concentrated on individual gait parameters. Based on the knowledge that quantitative gait parameters are highly correlated with each other and their individual relationships with cognitive function may be difficult to observe while adjusting for other gait variables [7], conceptual models using principal component analysis or factor analysis to provide a simplified framework for selecting grouped gait factors were suggested in gait analysis [8]. Under these circumstances, research that includes gait parameters from different aspects and uses a conceptual model for systemically analyzing gait and cognitive function is scarce

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