(13-02-09) Skeletal Muscle and Mortality Results From the InCHIANTI Study.

Cesari M, Pahor M, Lauretani F, Zamboni V, Bandinelli S, Bernabei R, Guralnik JM, Ferrucci L.
Department of Aging and Geriatric Research, College of Medicine, Institute on Aging, University of Florida, PO Box 112610, Gainesville, FL 32611. [email protected].

BACKGROUND: Sarcopenia, the age-related loss of muscle mass, may not be an isolated process but is associated with an increase in fat mass. The aim of this study was to estimate the mortality risk of sarcopenia in the presence or absence of obesity. METHODS: Data are from 934 participants aged 65 years or older, enrolled in the "Invecchiare in Chianti" study, and followed for 6 years. At baseline, a peripheral quantitative computerized tomography (pQCT) scan was performed on all participants to evaluate the muscle density, and the muscular and fat cross-sectional areas of the calf. Walking speed was measured on a 7-m track. Cox proportional hazard models were performed to estimate the association of pQCT measures (per 1 standard deviation increase) with mortality. RESULTS: Unadjusted analyses showed significant associations of muscle density (hazard ratio [HR] 0.78, 95% confidence interval [CI] 0.69-0.88), muscle area (HR 0.75, 95% CI 0.66-0.86), and fat area (HR 0.82, 95% CI 0.73-0.92) with mortality. After adjustment for potential confounders, no body composition parameter was significantly associated with mortality. Walking speed (used as a reference measure to verify whether the negative results were due to peculiarities of the study sample) confirmed its well-established association with mortality risk (HR 0.73, 95% CI 0.60-0.88). These results did not change after the analyses were stratified according to sarcopenia and body mass index groups, and restricted to participants with frailty or a high inflammatory profile. CONCLUSIONS: Calf skeletal muscle and fat mass are not significant risk factors for mortality in community-dwelling older adults. Walking speed confirmed to be a powerful predictor of health-related events

Source: . J Gerontol A Biol Sci Med Sci. 2009 Jan 30.

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