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Background and aims <p>30% of people aged 65 + fall at least once a year. The “world guidelines for falls prevention and management for older adults: a global initiative” (WGFs) have published an algorithm for fall risk prediction (low, intermediate or high risk) and proposed measures requiring health resources adapted to the risk level. We performed a real-life study to estimate the distribution of fall risk categories according to the WGFs algorithm in a population of old volunteers.</p> Methods <p>We performed a cross-sectional study in unselected 65-85-year-old participants attending an information meeting on WGFs falls and wishing a personalized assessment of their falls-risk.</p> Results <p>Among the 165 participants tested (mean age: 78.3 ± 6.1, 82% females), the number of fallers was significantly higher (51.2% 95% CL: 43.6–58.8%). than in previous published studies testing the WFGs. The intermediate risk concerned 15.1% and the high risk 47.3% of participants. In fallers, 90.1% were at high risk.</p> Conclusion <p>Information meetings about the WGFs could raise awareness among older people and help identify people at high risk of falling. In accordance with previous studies, most fallers would be classified at high risk of falling by using the WGFs, which makes it difficult to propose the multifactorial assessments and tailored interventions recommended by the WGFs in around 25% of all 65+.</p>

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Assessment of the “world guidelines for falls prevention and management” algorithm in older volunteers

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月27日

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  • Hubert Blain,
  • Pierre Louis Bernard,
  • Gilles Berrut,
  • Olivier Coste,
  • Maxence Josset,
  • Marie Christine Picot,
  • Jean Bousquet

摘要

Background and aims

30% of people aged 65 + fall at least once a year. The “world guidelines for falls prevention and management for older adults: a global initiative” (WGFs) have published an algorithm for fall risk prediction (low, intermediate or high risk) and proposed measures requiring health resources adapted to the risk level. We performed a real-life study to estimate the distribution of fall risk categories according to the WGFs algorithm in a population of old volunteers.

Methods

We performed a cross-sectional study in unselected 65-85-year-old participants attending an information meeting on WGFs falls and wishing a personalized assessment of their falls-risk.

Results

Among the 165 participants tested (mean age: 78.3 ± 6.1, 82% females), the number of fallers was significantly higher (51.2% 95% CL: 43.6–58.8%). than in previous published studies testing the WFGs. The intermediate risk concerned 15.1% and the high risk 47.3% of participants. In fallers, 90.1% were at high risk.

Conclusion

Information meetings about the WGFs could raise awareness among older people and help identify people at high risk of falling. In accordance with previous studies, most fallers would be classified at high risk of falling by using the WGFs, which makes it difficult to propose the multifactorial assessments and tailored interventions recommended by the WGFs in around 25% of all 65+.