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. 2023 Jul 1;52(7):afad129.
doi: 10.1093/ageing/afad129.

The use of the World Guidelines for Falls Prevention and Management's risk stratification algorithm in predicting falls in The Irish Longitudinal Study on Ageing (TILDA)

Peter Hartley  1   2   3 , Faye Forsyth  2 , Scott Rowbotham  4 , Robert Briggs  1   5 , Rose Anne Kenny  1   5 , Roman Romero-Ortuno  1   5   6
Affiliations

The use of the World Guidelines for Falls Prevention and Management's risk stratification algorithm in predicting falls in The Irish Longitudinal Study on Ageing (TILDA)

Peter Hartley et al. Age Ageing. .

Abstract

Background: the aim of this study was to retrospectively operationalise the World Guidelines for Falls Prevention and Management (WGFPM) falls risk stratification algorithm using data from The Irish Longitudinal Study on Ageing (TILDA). We described how easy the algorithm was to operationalise in TILDA and determined its utility in predicting falls in this population.

Methods: participants aged ≥50 years were stratified as 'low risk', 'intermediate' or 'high risk' as per WGFPM stratification based on their Wave 1 TILDA assessments. Groups were compared for number of falls, number of people who experienced one or more falls and number of people who experienced an injury when falling between Wave 1 and Wave 2 (approximately 2 years).

Results: 5,882 participants were included in the study; 4,521, 42 and 1,309 were classified as low, intermediate and high risk, respectively, and 10 participants could not be categorised due to missing data. At Wave 2, 17.4%, 43.8% and 40.5% of low-, intermediate- and high-risk groups reported having fallen, and 7.1%, 18.8% and 18.7%, respectively, reported having sustained an injury from falling.

Conclusion: the implementation of the WGFPM risk assessment algorithm was feasible in TILDA and successfully differentiated those at greater risk of falling. The high number of participants classified in the low-risk group and lack of differences between the intermediate and high-risk groups may be related to the non-clinical nature of the TILDA sample, and further study in other samples is warranted.

Keywords: falls; longitudinal; older people; prediction; risk; stratification.

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Conflict of interest statement

R.A.K. was a co-author of the 2022 publication of the World Falls Guidelines (https://doi.org/10.1093/ageing/afac205).

Figures

Figure 1
Figure 1
Operationalisation of the World Guidelines for Falls Prevention and Management risk stratification algorithm in Wave 1 of The Irish Longitudinal Study on Ageing. * number indicates a positive response/criterion, participants can have multiple positive responses/criteria.
See this image and copyright information in PMC

References

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