Sex-Specific Fall Trajectories and Associated Self-Reported Risk Factors: A Prospective Analysis of the 3-Year...

Few studies have explored specific trajectories or patterns of falls over time in older adults, and the role of sex and self-reported risk factors for these trajectories were overlooked. This study aimed to identify sex-specific fall trajectories over 3 years and the self-reported risk factors associated with each trajectory in European older adults.

Observational analysis of DO-HEALTH, a double-blind, randomized controlled trial.

Multicenter trial conducted in 7 European centers: Zurich, Basel, Geneva (Switzerland), Berlin (Germany), Innsbruck (Austria), Toulouse (France), and Coimbra (Portugal), including 2157 community-dwelling adults aged 70 years and older without major health events in the 5 years prior to enrollment, with sufficient mobility and good cognitive status.

Falls were recorded prospectively via phone calls and in-person assessments every 3 months over 3 years of follow-up. Group-based trajectory modeling was used to identify sex-specific trajectories based on the number of falls experienced over the follow-up, and penalized logistic regression models identified the self-reported risk factors most associated with each trajectory.

A total of 1958 participants were included in this analysis (mean age: 74.9 years, 61.7% women). We identified a "lower fall trajectory" and a "higher fall trajectory" among women and a "lower fall trajectory" and an "increasing fall trajectory" among men. In women, living alone was the only self-reported risk factor associated with the higher fall trajectory. In men, living alone (marginal), as well as reporting fatigue, pain or discomfort, mobility issues, and higher self-rated health, were significantly associated with experiencing the increasing fall trajectory.

This study provides a comprehensive assessment of falls over 3 years, highlighting differences in fall patterns and associated self-reported risk factors between men and women. These findings may offer valuable insights for developing sex-specific fall risk prediction models and targeted fall prevention strategies.