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Fall risk assessment using the World Guidelines for Falls Prevention Algorithm: Evidence from the ELSI-Brazil study.

Núbia Carelli Pereira de Avelar1, Ana Lúcia Danielewicz2, Bruno de Souza Moreira3

  • 1Laboratory of Aging, Resources and Rheumatology, Department of Physiotherapy, Federal University of Santa Catarina, Campus Araranguá, Rod. Governador Jorge Lacerda, 3201, Urussanguinha, Araranguá, Santa Catarina, 88906-072, Brazil. nubia.carelli@ufsc.br.

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Summary
This summary is machine-generated.

The World Guidelines for Falls Prevention and Management (WGF) algorithm using key questions (KQ) identifies more older adults at intermediate fall risk than fall history (FH) alone. This highlights significant regional disparities in fall risk across Brazil.

Keywords:
Accidental fallsCommunity-dwellingOlder adultsPrevalence

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Area of Science:

  • Gerontology
  • Public Health
  • Epidemiology

Background:

  • The World Guidelines for Falls Prevention and Management (WGF) offer a global algorithm for fall risk stratification in older adults.
  • This algorithm utilizes either fall history (FH) or key questions (KQ) for screening.
  • Limited evidence exists on the applicability of WGF in low- and middle-income countries and the comparative population estimates from FH versus KQ methods.

Purpose of the Study:

  • To estimate national and regional fall risk prevalence in Brazil using both WGF screening methods (FH and KQ).
  • To examine geographic variations in fall risk across different regions of Brazil.
  • To assess the impact of using KQ versus FH on population estimates of fall risk.

Main Methods:

  • A cross-sectional study utilizing data from the third wave of the Brazilian Longitudinal Study of Aging (ELSI-Brazil, 2023-2024).
  • Participants aged 60 years and older were classified using the WGF algorithm based on FH or KQ (concern about falling, postural instability, gait speed ≤ 0.8 m/s, severity markers).
  • Poisson regression adjusted for sociodemographic factors was employed to analyze regional differences in fall risk prevalence.

Main Results:

  • Out of 7515 older adults, FH alone classified 82.2% as low risk, 7.8% as intermediate, and 10.0% as high risk.
  • Using KQ, classifications were 50.4% low risk, 34.6% intermediate risk, and 15.0% high risk.
  • The KQ approach revealed lower low-risk and higher intermediate-risk prevalence in the Northeast and Southeast compared to the South, with no regional differences for high-risk classification or FH-based results.

Conclusions:

  • Operationalizing the WGF algorithm with KQ significantly increases the identification of intermediate fall risk compared to FH alone.
  • An estimated 3.5 million older Brazilian adults may be at high risk of falls based on national estimates.
  • Identified within-country regional disparities underscore the necessity for tailored fall prevention strategies addressing contextual variations.