Multifactorial predictors of falls in older adults: a decade of data from the National Health and Aging Trends Study

Abstract

Background: Falls are a leading cause of injury and loss of independence among older adults, yet comprehensive, population-level models that integrate diverse risk factors across broad demographic groups remain limited. Prior studies often focus on isolated variables or narrow subpopulations, limiting their generalizability. Methods: To address this, we developed a robust, comprehensive model of fall risk among community-dwelling older adults using 11 years of data from the National Health and Aging Trends Study (NHATS), a longitudinal study of older adults in the United States designed to be nationally representative across a wide range of demographic and socioeconomic backgrounds. We conducted a retrospective analysis of 5,816 person-year observations from 2011 to 2022, applying univariate chi-squared tests and multivariable logistic regression to identify features associated with self-reported falls within a given month in the preceding year. Risk factors examined included sociodemographic characteristics, health status, cognitive function, and physical performance. Results: Approximately 10% of respondents reported a fall during a specific time within the past year. Consistent features associated with increased fall risk included prior fall history, impaired balance, depressive symptoms, and use of mobility aids. Cross-category analyses revealed important variations in risk profiles by age, functional status and ability to perform certain exercises. Conclusions: This study presents a decade-spanning model that reflects the multifactorial nature of fall risk and the diversity of aging trajectories in the U.S., providing a foundation for more inclusive and personalized fall prevention strategies.