Associations Between Potentially Modifiable and Nonmodifiable Risk Factors and Gait Speed in Middle- and Older-Aged Adults: Results From the Canadian Longitudinal Study on Aging

Abstract

Abstract Background Gait speed is a strong predictor of morbidity and mortality in older adults. Understanding the factors associated with gait speed and the associated adverse outcomes will inform mitigation strategies. We assessed the potentially modifiable and nonmodifiable factors associated with gait speed in a large national cohort of middle and older-aged Canadian adults. Methods We examined cross-sectional baseline data from the Canadian Longitudinal Study on Aging (CLSA) Comprehensive cohort. The study sample included 20 201 community-dwelling adults aged 45–85 years. The associations between sociodemographic and anthropometric factors, chronic conditions, and cognitive, clinical, and lifestyle factors and 4-m usual gait speed (m/s) were estimated using hierarchical multivariable linear regression. Results The coefficient of determination, R 2, of the final regression model was 19.7%, with 12.9% of gait speed variability explained by sociodemographic and anthropometric factors, and nonmodifiable chronic conditions and 6.8% explained by potentially modifiable chronic conditions, cognitive, clinical, and lifestyle factors. Potentially modifiable factors significantly associated with gait speed include cardiovascular conditions (unstandardized regression coefficient, B = −0.018; p < .001), stroke (B = −0.025; p = .003), hypertension (B = −0.007; p = .026), serum Vitamin D (B = 0.004; p < .001), C-reactive protein (B = −0.005; p = .005), depressive symptoms (B = −0.003; p < .001), physical activity (B = 0.0001; p < .001), grip strength (B = 0.003; p < .001), current smoking (B = −0.026; p < .001), severe obesity (B = −0.086; p < .001), and chronic pain (B = −0.008; p = .018). Conclusions The correlates of gait speed in adulthood are multifactorial, with many being potentially modifiable through interventions and education. Our results provide a life-course-perspective framework for future longitudinal assessments risk factors affecting gait speed.