BACKGROUND: It is unknown how much age-related changes in muscle performance represent normal aging versus the effects of chronic disease and life style. We examined the correlates of four performance measures-gait speed, timed chair stands (TCS), grip strength, and maximal inspiratory pressure (MIP)-using baseline data from the Cardiovascular Health Study (CHS), a population-based study of risk factors for heart disease and stroke in persons > or = age 65. METHODS: We analyzed data from the 5,201 CHS participants. Variables were arranged into nine categories: Personal Characteristics, Anthropometry, Physical Condition, Reported Functional Status, Subjective Health, Psychological Factors, Symptoms, Cognitive Status, Habits and Lifestyle, and Prevalent Disease. Independent correlates were identified using stepwise linear regression. RESULTS: The regression models explained 17.7-25.4% of the observed variability. Although age significantly correlated with each measure, it explained little of the variability (< or = 5.7%). Anthropometric features plus physical condition explained 14.0-17.4% of the variability for grip strength and MIP, but 2.8-12.9% of the variability for gait speed and the log of TCS. Subjective health and psychological factors explained 1.8-9.4% of the variability in gait speed and the log of TCS, but < or = 1.2% of the variability in grip strength and MIP. Variables for prevalent disease explained < or = 1.3% of the variability in each measure. CONCLUSIONS: After age 64, age explained little of the variability in muscle performance in a large sample of mostly functionally intact, community-dwelling older persons. Complex measures such as gait speed were more associated with subjective factors than were direct measures of strength. Prevalent disease contributed surprisingly little to muscle performance.
BACKGROUND: It is unknown how much age-related changes in muscle performance represent normal aging versus the effects of chronic disease and life style. We examined the correlates of four performance measures-gait speed, timed chair stands (TCS), grip strength, and maximal inspiratory pressure (MIP)-using baseline data from the Cardiovascular Health Study (CHS), a population-based study of risk factors for heart disease and stroke in persons > or = age 65. METHODS: We analyzed data from the 5,201 CHSparticipants. Variables were arranged into nine categories: Personal Characteristics, Anthropometry, Physical Condition, Reported Functional Status, Subjective Health, Psychological Factors, Symptoms, Cognitive Status, Habits and Lifestyle, and Prevalent Disease. Independent correlates were identified using stepwise linear regression. RESULTS: The regression models explained 17.7-25.4% of the observed variability. Although age significantly correlated with each measure, it explained little of the variability (< or = 5.7%). Anthropometric features plus physical condition explained 14.0-17.4% of the variability for grip strength and MIP, but 2.8-12.9% of the variability for gait speed and the log of TCS. Subjective health and psychological factors explained 1.8-9.4% of the variability in gait speed and the log of TCS, but < or = 1.2% of the variability in grip strength and MIP. Variables for prevalent disease explained < or = 1.3% of the variability in each measure. CONCLUSIONS: After age 64, age explained little of the variability in muscle performance in a large sample of mostly functionally intact, community-dwelling older persons. Complex measures such as gait speed were more associated with subjective factors than were direct measures of strength. Prevalent disease contributed surprisingly little to muscle performance.
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