Main content

Home

Menu

Loading wiki pages...

View
Wiki Version:
ABSTRACT Introduction: Muscle fitness has been positively associated with functional ability and independence in older adults. Physical function tests that can be performed in homes and community centers, such as sit-to-stand (STS) velocity and hand grip strength (HGS), are used in this population to monitor muscle power and strength, respectively. Bone strength has been associated with muscle fitness however, the relationship between muscle strength and power has yet to be resolved. Here, the relationships between HGS and STS power to trabecular and cortical bone parameters of the radius are examined in older adults (ages 60-95 years). Fourteen participants (8 women) were recruited from campus and local community centers. Bone strength was assessed with a peripheral quantitative computed tomography scan of the radius. Lower limb muscle power was assessed with a linear position transducer during the rising phase of the STS. Bilateral HGS was assessed with a Jamar hand-grip dynamometer. Results: No significant correlations were found between combined handgrip strength (CGS; sum of peak HGS for right and left) and peak lower limb power. CGS was associated with (SSI?) cortical geometry (r = 0.733), moment of inertia and strength (r = 0.702; r = 0.766). Peak lower limb power was associated with trabecular bone mineral content (r = 0.731), density (r = 0.762), and strength (r = 0.762), and cortical geometry (r = 0.626). Conclusions: These data suggest that muscle fitness testing may be a promising tool to monitor bone strength in older adults.
OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
Accept
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.
Accept
×

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.