Erica Figgins1,2, Yun-Hee Choi2, Mark Speechley1,2,3, Manuel Montero-Odasso1,2,4. 1. Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, Ontario, Canada. 2. Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada. 3. Schulich Interfaculty Program in Public Health, University of Western Ontario, London, Canada. 4. Department of Medicine and Division of Geriatric Medicine, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada.
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.
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.
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