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

The World Guidelines for Falls Prevention and Management (WGF) propose a global algorithm to stratify fall risk in older adults using fall history (FH) or key questions (KQ). However, evidence on the applicability of this screening tool in low- and middle-income countries, and on whether these approaches produce different population estimates, remains limited. Implementing this tool may enhance the identification of older adults at higher risk of falls.

This study estimated national and regional fall risk prevalence in Brazil using both methods and examined geographic differences.

We conducted a cross-sectional study using data from older participants (≥ 60 years) of the third wave of the Brazilian Longitudinal Study of Aging (ELSI-Brazil, 2023-2024), a nationally representative study. According to the WGF algorithm, participants were classified as high, intermediate, or low fall risk based on FH or two KQ (concern about falling and postural instability) combined with gait speed ≤ 0.8 m/s and severity markers. KQ included concern about falling, assessed using the short version of the Falls Efficacy Scale-International, and postural instability evaluated using the tandem stance test (impaired balance if < 10 s). Poisson regression with robust variance adjusted for sociodemographic factors was used to examine regional differences in fall risk prevalence.

A total of 7515 older adults participated in this study (67.8 ± 0.2 years; 57.1% female). Using FH alone, 82.2% of older adults were classified as low risk, 7.8% as intermediate, and 10.0% as high risk. Using KQ, the prevalence was 50.4%, 34.6%, and 15.0%, respectively. With the KQ approach, older adults in the Northeast and Southeast had a lower probability of being low risk and a higher probability of being intermediate risk compared with those in the South. No regional differences were observed for high-risk classification or when FH alone was used.

Operationalizing the WGF algorithm with KQ substantially increases intermediate fall risk identification compared to FH alone. Based on national population estimates, approximately 3.5 million older Brazilian adults may be at high risk of falls. Within-country regional disparities reinforce the need for tailored strategies to address contextual differences in fall prevention.