Predictive accuracy of gait speed for falls: An individual participant data meta-analysis: An individual participant data meta-analysis

ORCID

Abstract

BackgroundGait speed is included in the World Falls Guidelines (WFG) fall risk algorithm, yet its ability to discriminate fallers from non-fallers remains unclear. This individual participant data meta-analysis examined the discriminative ability of the WFG-recommended cut point (<0.8 m/s) and the performance of a higher cut point (<1.0 m/s) for predicting falls in community-dwelling older adults and clinical populations at elevated risk of falls.MethodsIndividual data from 28 studies with a quantitative measure of gait speed and at least three months of prospectively reported falls were analysed using modified Poisson regression and Negative Binomial regression, followed by random-effects meta-analyses.ResultsEight studies involving community-dwelling older adults (n = 3627) and twenty studies involving clinical populations (n = 3981) were included. Walking at < 0.8 m/s was associated with increased risk of falling (Relative Risk: 1.27 (95%CI 1.17 – 1.38)) and fall rate (Incidence Rate Ratio: 1.54 (95%CI 1.34 – 1.77)). Diagnostic accuracy was modest (58%, specificity 77%, sensitivity 35%), with consistent findings across planned subgroup analyses for population, fall history, and sex. Analyses using the < 1.0 m/s cut point produced similar effect sizes and accuracy metrics but identified a larger proportion of fallers in both community-dwelling (30.1% vs. 8.7%) and clinical populations (66.9% vs. 46.0%) compared to the < 0.8 m/s cut point.ConclusionSlower gait speed is associated with an increased risk and rate of falling across both population groups, but discriminative accuracy is low. While the < 0.8 m/s threshold shows consistent associations, a < 1.0 m/s cut point may be more clinically useful in community-dwelling and clinical settings because it identifies more fallers.

Publication Date

2026-08-01

Publication Title

Ageing Research Reviews

Volume

120

ISSN

1568-1637

Acceptance Date

2026-06-14

Deposit Date

2026-08-12

Embargo Period

2027-06-19

Funding

C.H. reports financial support was provided by an Australian Government Research Training Program Scholarship and Betty Fyfe Scholarship, NeuRA. C.M.D. reports financial support was provided by New South Wales Ministry of Health, the National Health and Medical Research Council that includes: funding grants and Macquarie University that includes: employment. K.D. reports financial support from a National Health and Medical Research Council L1 Investigator Grant [grant number 1193766]. H.G. reports financial support was provided by Chartered Society of Physiotherapy (UK) Physiotherapy Research Foundation. E.J.H. is employed by the University of Bristol and has an honorary role as a Consultant Geriatrician at the Royal United Hospitals, Bath. E.J.H. received research funding from the National Institute of Health Research (NIHR), Engineering and Physical Sciences Research Council, The British Geriatrics Society, The Gatsby Foundation, Royal Osteoporosis Society, The Dunhill Society and Parkinson’s UK. P.H. is currently employed by MS Plus Australia. M.D.L. reports administrative support was provided by The University of Sydney. D.M. reports financial support was provided by National Health and Medical Research Council. D.L.S. reports financial support was provided by University of New South Wales. S.R.L. reports a National Health and Medical Research Council L3 Investigator Grant [grant number 2002096]. Financial supporters had no role in the design, execution, analysis and interpretation of data, or writing of the study.

Keywords

Accidental falls, Older people, Aged, Risk, Gait, Walking speed, Predictive Value of Tests, Risk Assessment, Humans, Risk Factors, Walking Speed/physiology, Accidental Falls/prevention & control, Gait/physiology

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This item is under embargo until 19 June 2027

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