Fall risk stratification in older adults: low and not-at-risk status still associated with falls and injuries

Manuel Montero-Odasso; Frederico Pieruccini-Faria; Surim Son; Daniela Cristina Carvalho de Abreu; Susan Hunter; Jia Qi Liu; Marissa Moore; Areej Hezam; Nathalie van der Velde; Tahir Masud; Jesper Ryg; Mirko Petrovic; Mark Speechley

doi:10.1093/ageing/afaf064

Fall risk stratification in older adults: low and not-at-risk status still associated with falls and injuries

Age Ageing. 2025 Mar 3;54(3):afaf064. doi: 10.1093/ageing/afaf064.

Authors

Manuel Montero-Odasso^{1

2

3}, Frederico Pieruccini-Faria^{1

3}, Surim Son^{2

3}, Daniela Cristina Carvalho de Abreu^{3

4}, Susan Hunter⁵, Jia Qi Liu³, Marissa Moore^{3

6}, Areej Hezam³, Nathalie van der Velde^{7

8}, Tahir Masud⁹, Jesper Ryg¹⁰, Mirko Petrovic¹¹, Mark Speechley^{2

12}

Affiliations

¹ Western University, Schulich School of Medicine and Dentistry, Department of Medicine, Division of Geriatric Medicine, London, Ontario, Canada.
² Western University, Schulich School of Medicine and Dentistry, Department of Epidemiology and Biostatistics, London, Ontario, Canada.
³ Parkwood Institute, Gait and Brain Laboratory, London, Ontario, Canada.
⁴ University of Sao Paulo, Department of Health Science, Ribeirão Preto Medical School, Sao Paulo, Brazil.
⁵ Western University, Faculty of Health Sciences, School of Physiotherapy, London, Ontario, Canada.
⁶ Western University, Faculty of Health Sciences, School of Kinesiology, London, Ontario, Canada.
⁷ Amsterdam University Medical Centers, location Academic Medical Center, Internal Medicine and Geriatrics, University of Amsterdam, Meibergdreef 9, North Holland, 1105 AZ, Amsterdam, The Netherlands.
⁸ Amsterdam Public Health Research Institute, North Holland, 1081 HV, Amsterdam, The Netherlands.
⁹ Nottingham University Hospitals NHS Trust, Department of Geriatric Medicine, Nottingham, United Kingdom.
¹⁰ Odense Universitetshospital, Department of Geriatric Medicine, Odense, Denmark.
¹¹ Section of Geriatrics, Department of Internal Medicine and Paediatrics, Ghent University, Corneel Heymanslaan 10, Ghent, Belgium.
¹² Western University Schulich Interfaculty Program in Public Health, London, Ontario, Canada.

Abstract

Background: Falls guidelines recommendations for individuals classified as 'not-at-risk' range from no further actions to offering education and exercises. However, there is a scarcity of prospective studies analysing the rate of falls and injuries in this not-at-risk group to inform recommendations.

Objective: To prospectively estimate the rate of falls and injuries in older adults considered 'not-at-risk' for falls.

Design: Prospective cohort study.

Setting: Geriatric Medicine Clinics.

Subjects: Community-dwelling older adults aged 65 and older.

Methods: Falls risk stratification was operationalised by adapting the Centers for Disease Control and Prevention's Stopping Elderly Accidents, Deaths and Injuries algorithm. Associations of risk strata (screened not-at-risk vs. at-risk) with incident falls and injuries were estimated using incidence rate ratios [adjusted incident rate ratio (aIRR), Poisson regression model]. Associations between slow gait speed (<1 m/s) and injurious falls were estimated by risk strata using hazard ratios (adjusted hazard ratio, Cox and Poisson regression model).

Results: Of 403 participants, 64% of at-risk individuals fell during the follow-up compared to 41.3% in the not-at-risk group, whilst injurious falls were reported by 63.2% of the not-at-risk group and by 59.7% of the at-risk group. At-risk individuals had a higher rate of falls (aIRR = 3.91, 95% CI: 3.30-4.64, P < .001) but a similar rate of injurious falls as the not-at-risk individuals (aIRR = 1.26, 95% CI: 0.93-1.71; P = .11). Not-at-risk individuals with slow gait speed sustained injurious falls at twice the rate (aIRR = 1.83, 95% CI: 1.12-3.91, P = .008) than those without slow gait speed.

Conclusions: Being screened as not-at-risk for falls does not mean no risk at all. Routinely and universally assessing gait speed could identify not-at-risk individuals who are likely to sustain injuries after a fall and could benefit from primary prevention.

Keywords: falls; gait speed; mobility; older adults; older people; risk stratification.

MeSH terms

Accidental Falls* / prevention & control
Accidental Falls* / statistics & numerical data
Age Factors
Aged
Aged, 80 and over
Female
Geriatric Assessment / methods
Humans
Incidence
Independent Living
Male
Prospective Studies
Risk Assessment
Risk Factors
Walking Speed
Wounds and Injuries* / diagnosis
Wounds and Injuries* / epidemiology
Wounds and Injuries* / prevention & control

Abstract

MeSH terms

Grants and funding