title: Walking ability to predict future cognitive decline in old adults: A scoping review.
abstract: Early identification of individuals at risk for cognitive decline may facilitate the selection of those who benefit most from interventions. Current models predicting cognitive decline include neuropsychological and/or biological markers. Additional markers based on walking ability might improve accuracy and specificity of these models because motor and cognitive functions share neuroanatomical structures and psychological processes. We reviewed the relationship between walking ability at one point of (mid) life and cognitive decline at follow-up. A systematic literature search identified 20 longitudinal studies. The average follow-up time was 4.5 years. Gait speed quantified walking ability in most studies (n=18). Additional gait measures (n=4) were step frequency, variability and step-length. Despite methodological weaknesses, results revealed that gait slowing (0.68-1.1 m/sec) preceded cognitive decline and the presence of dementia syndromes (maximal odds and hazard ratios of 10.4 and 11.1, respectively). The results indicate that measures of walking ability could serve as additional markers to predict cognitive decline. However, gait speed alone might lack specificity. We recommend gait analysis, including dynamic gait parameters, in clinical evaluations of patients with suspected cognitive decline. Future studies should focus on examining the specificity and accuracy of various gait characteristics to predict future cognitive decline.
authors: University of Groningen, University Medical Centre Groningen, Center for Human Movement Sciences, A. Deusinglaan 1, 9700 AD Groningen, The Netherlands; Univ. Grenoble Alpes, EA AGEIS, La Tronche, France. Electronic address: l.h.j.kikkert@umcg.nl.
authors: Lisette H J
authors: LHJ
authors: Kikkert
authors: Univ. Grenoble Alpes, EA AGEIS, La Tronche, France; Institut Universitaire de France, Paris, France. Electronic address: nicolas.vuillerme@agim.eu.
authors: Nicolas
authors: N
authors: Vuillerme
authors: MC Slotervaart Hospital, Department of Geriatric Medicine, Amsterdam, The Netherlands. Electronic address: Jos.vanCampen@slz.nl.
authors: Jos P
authors: JP
authors: van Campen
authors: University of Groningen, University Medical Centre Groningen, Center for Human Movement Sciences, A. Deusinglaan 1, 9700 AD Groningen, The Netherlands; Faculty of Health and Life Sciences, Northumbria University, Newcastle Upon Tyne, UK. Electronic address: t.hortobagyi@umcg.nl.
authors: Tibor
authors: T
authors: Hortobágyi
authors: University of Groningen, University Medical Centre Groningen, Center for Human Movement Sciences, A. Deusinglaan 1, 9700 AD Groningen, The Netherlands. Electronic address: c.j.c.lamoth@umcg.nl.
authors: Claudine J
authors: CJ
authors: Lamoth
mesh_terms: D000368:Aged; D003071:Cognition; D060825:Cognitive Dysfunction / Q000175:diagnosis*; D006801:Humans; D051346:Mobility Limitation; D015233:Models, Statistical; D009482:Neurophysiology / Q000379:methods; D011379:Prognosis; D016138:Walking / Q000523:psychology*; D000072797:Walking Speed
keywords: Biomarker; Cognitive impairment; Dementia; Gait; MCI; Prediction models