Mobility screening for fall prediction in the Canadian Longitudinal Study on Aging (CLSA): implications for fall prevention in the decade of healthy ageing

Acceptability, Reliability, and Validity of Virtually Administered Gait Speed Tests

OBJECTIVES

To evaluate the acceptability, reliability (inter- and intrarater), and validity (convergent, known groups, and predictive) of virtually administered gait speed tests for community-dwelling older adults.

DESIGN

A prospective cohort study was performed, tracking health outcomes for a year.

SETTING AND PARTICIPANTS

The 3-m gait speed test at usual and fast pace was administered to community-dwelling older adults over Zoom.

METHOD

To examine acceptability, participants completed questionnaires regarding telehealth usability and experience. Virtual gait speed tests were administered at baseline and 24 to 72 hours later to evaluate reliability. Self-report mobility measures were used to examine convergent and known-groups validity. Participants' health outcomes were tracked for a year to evaluate predictive validity.

RESULTS

Sixty participants completed the baseline assessment and 52 completed the second assessment. Participants reported an overall positive experience with the test. Intraclass correlation coefficients for reliability ranged from 0.79 to 0.90. For convergent validity, correlations >0.30 were found predominantly for usual gait speed with self-report mobility measures. Both the usual- and fast-gait speed were able to discriminate between difficulty walking and gait aid use. Usual gait speed was able to predict specialist and family doctor visits and fast gait speed was able to predict rehabilitation specialist visits over 1 year.

CONCLUSIONS AND IMPLICATIONS

Our findings demonstrate support for the acceptability, reliability, and validity of virtually administered gait speed tests for community-dwelling older adults. Although future studies are needed to examine the validity of virtual gait speed tests in larger and more diverse samples to improve generalizability of results, clinicians and researchers can virtually administer 3-m gait speed tests with confidence that scores are trustworthy and reflect older adults' mobility.

Balance measures for fall risk screening in community-dwelling older adults with COPD: A longitudinal analysis

BACKGROUND

Chronic obstructive pulmonary disease (COPD) increases fall risk, but consensus is lacking on suitable balance measures for fall risk screening in this group. We aimed to evaluate the reliability and validity of balance measures for fall risk screening in community-dwelling older adults with COPD.

METHODS

In a secondary analysis of two studies, participants, aged ≥60 years with COPD and 12-month fall history or balance issues were tracked for 12-month prospective falls. Baseline balance measures - Brief Balance Evaluation Systems Test (Brief BESTest), single leg stance (SLS), Timed Up and Go (TUG), and TUG Dual-Task (TUG-DT) test - were assessed using intra-class correlation (ICC2,1) for reliability, Pearson/Spearman correlation with balance-related factors for convergent validity, t-tests/Wilcoxon rank-sum tests with fall-related and disease-related factors for known-groups validity, and area under the receiver operator characteristic curve (AUC) for predictive validity.

RESULTS

Among 174 participants (73 ± 8 years; 86 females) with COPD, all balance measures showed excellent inter-rater and test-retest reliability (ICC2,1 = 0.88-0.97) and moderate convergent validity (r = 0.34-0.77) with related measures. Brief BESTest and SLS test had acceptable known-groups validity (p < 0.05) for 12-month fall history, self-reported balance problems, and gait aid use. TUG test and TUG-DT test discriminated between groups based on COPD severity, supplemental oxygen use, and gait aid use. All measures displayed insufficient predictive validity (AUC<0.70) for 12-month prospective falls.

CONCLUSION

Though all four balance measures demonstrated excellent reliability, they lack accuracy in prospectively predicting falls in community-dwelling older adults with COPD. These measures are best utilized within multi-factorial fall risk assessments for this population.

Measurement properties of the usual and fast gait speed tests in community-dwelling older adults: a COSMIN-based systematic review

OBJECTIVE

The gait speed test is one of the most widely used mobility assessments for older adults. We conducted a systematic review to evaluate and compare the measurement properties of the usual and fast gait speed tests in community-dwelling older adults.

METHODS

Three databases were searched: MEDLINE, EMBASE and CINAHL. Peer-reviewed articles evaluating the gait speed test's measurement properties or interpretability in community-dwelling older adults were included. The Consensus-based Standards for the selection of health Measurement Instruments guidelines were followed for data synthesis and quality assessment.

RESULTS

Ninety-five articles met our inclusion criteria, with 79 evaluating a measurement property and 16 reporting on interpretability. There was sufficient reliability for both tests, with intraclass correlation coefficients (ICC) generally ranging from 0.72 to 0.98, but overall quality of evidence was low. For convergent/discriminant validity, an overall sufficient rating with moderate quality of evidence was found for both tests. Concurrent validity of the usual gait speed test was sufficient (ICCs = 0.79-0.93 with longer distances) with moderate quality of evidence; however, there were insufficient results for the fast gait speed test (e.g. low agreement with longer distances) supported by high-quality studies. Responsiveness was only evaluated in three articles, with low quality of evidence.

CONCLUSION

Findings from this review demonstrated evidence in support of the reliability and validity of the usual and fast gait speed tests in community-dwelling older adults. However, future validation studies should employ rigorous methodology and evaluate the tests' responsiveness.

Fall risk classification with posturographic parameters in community-dwelling older adults: a machine learning and explainable artificial intelligence approach

BACKGROUND

Computerized posturography obtained in standing conditions has been applied to classify fall risk for older adults or disease groups. Combining machine learning (ML) approaches is superior to traditional regression analysis for its ability to handle complex data regarding its characteristics of being high-dimensional, non-linear, and highly correlated. The study goal was to use ML algorithms to classify fall risks in community-dwelling older adults with the aid of an explainable artificial intelligence (XAI) approach to increase interpretability.

METHODS

A total of 215 participants were included for analysis. The input information included personal metrics and posturographic parameters obtained from a tracker-based posturography of four standing postures. Two classification criteria were used: with a previous history of falls and the timed-up-and-go (TUG) test. We used three meta-heuristic methods for feature selection to handle the large numbers of parameters and improve efficacy, and the SHapley Additive exPlanations (SHAP) method was used to display the weights of the selected features on the model.

RESULTS

The results showed that posturographic parameters could classify the participants with TUG scores higher or lower than 10 s but were less effective in classifying fall risk according to previous fall history. Feature selections improved the accuracy with the TUG as the classification label, and the Slime Mould Algorithm had the best performance (accuracy: 0.72 to 0.77, area under the curve: 0.80 to 0.90). In contrast, feature selection did not improve the model performance significantly with the previous fall history as a classification label. The SHAP values also helped to display the importance of different features in the model.

CONCLUSION

Posturographic parameters in standing can be used to classify fall risks with high accuracy based on the TUG scores in community-dwelling older adults. Using feature selection improves the model's performance. The results highlight the potential utility of ML algorithms and XAI to provide guidance for developing more robust and accurate fall classification models. Trial registration Not applicable.

Examination of the Increased Risk for Falls Among Individuals With Knee Osteoarthritis: A Canadian Longitudinal Study on Aging Population-Based Study

OBJECTIVE

To characterize the profile of individuals with and without knee osteoarthritis (OA) who fell, and to identify factors contributing to an individual with knee OA experiencing 1 or multiple injurious falls.

METHODS

Data are from the baseline and 3-year follow-up questionnaires of the Canadian Longitudinal Study on Aging, a population-based study of people ages 45-85 years at baseline. Analyses were limited to individuals either reporting knee OA or no arthritis at baseline (n = 21,710). Differences between falling patterns among those with and without knee OA were tested using chi-square tests and multivariable-adjusted logistic regression models. An ordinal logistic regression model examined predictors of experiencing 1 or more injurious falls among individuals with knee OA.

RESULTS

Among individuals reporting knee OA, 10% reported 1 or more injurious falls; 6% reported 1 fall, and 4% reported 2+ falls. Having knee OA significantly contributed to the risk of falling (odds ratio [OR] 1.33 [95% confidence interval (95% CI) 1.14-1.56]), and individuals with knee OA were more likely to report having a fall indoors while standing or walking. Among individuals with knee OA, reporting a previous fall (OR 1.75 [95% CI 1.22-2.52]), previous fracture (OR 1.42 [95% CI 1.12-1.80]), and having urinary incontinence (OR 1.38 [95% CI 1.01-1.88]) were significant predictors of falling.

CONCLUSION

Our findings support the idea that knee OA is an independent risk factor for falls. The circumstances in which falls occur differ from those for individuals without knee OA. The risk factors and environments that are associated with falling may provide opportunities for clinical intervention and fall prevention strategies.

How to tackle the global challenge of falls?

Worldwide, falls and accompanying injuries are increasingly common, making their prevention and management a critical global challenge. The wealth of evidence to support interventions to prevent falls has recently (2022) been distilled in the first World Falls Guideline for Prevention and Management for Older Adults. The core of falls prevention includes (i) risk assessment and stratification; (ii) general recommendations on optimising physical function and mobility for all and (iii) offering a holistic, multidomain intervention to older adults at high risk of falls, in which the older adult's priorities, beliefs and resources are carefully considered. In recent decades, sustainable and adequately resourced falls prevention has proved challenging, although evidence suggests that suboptimal implementation of falls prevention is ineffective. Future research should focus on understanding the most successful approaches for implementation. To further optimise falls prevention, recent developments include technological innovation to identify and prevent falls, including exergaming. Further work is warranted to understand how to best incorporate the concepts of frailty and sarcopenia in falls prevention and management. This themed collection includes key articles in the field of falls prevention, covering several topics including risk factors, effective interventions, older adult's views, implementation issues and future perspectives.