A recent Japanese study has identified key indicators that can help predict which older adults are most likely to experience falls, paving the way for more effective prevention strategies.

THE researchpublished in Curéusfollowed 1,173 healthy community-dwelling adults aged 65 and older for one year, examining their scores on the 25-question Geriatric Locomotive Function Scale (GLFS-25) and subsequent falls. Results revealed that people who experienced falls during the study period had significantly higher GLFS-25 scores than those who did not fall. Two factors were particularly predictive of fall risk: reported body pain and fall-related anxiety.

The study also followed frequency of fallsrevealing that 138 participants experienced one fall, 82 experienced two falls, 24 reported three falls, and eight participants experienced four falls during the monitored period. Notably, people diagnosed with even mild locomotor syndrome (LS-1 or higher on the GLFS-25) were more than twice as likely to experience falls as those who did not suffer from it. This increased risk persists even after accounting for factors such as age, body mass index, smoking and physical activity levels.

Higher GLFS-25 scores were correlated with both the likelihood of falling and the frequency of falls within a month. However, annual frequency of falls was specifically associated with GLFS-25 domain scores for physical pain and anxiety, while scores from other domains, such as movement difficulties, were not significant predictors.

“Our results highlight the importance of preventing falls in people with mild musculoskeletal syndrome and suggest that the GLFS-25 total score could predict recurrent falls,” the researchers concluded.

The implications of the study could be significant for aging populations around the world. As the frequency of falls and the severity of fall-related injuries increase among older adults, early identification of those at risk can help prevent injuries and promote independence. Researchers suggest that using assessment tools such as the GLFS-25 could allow healthcare providers to identify those most at risk and implement preventative measures before falls occur.