title: Skeletal muscle and mortality results from the InCHIANTI Study.
abstract: 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.
authors.affiliation: Department of Gerontology, Geriatrics, and Physiatry, Catholic University of Sacred Heart, Rome, Italy. macesari@gmail.com
authors.forename: Matteo
authors.initials: M
authors.lastname: Cesari
authors.forename: Marco
authors.initials: M
authors.lastname: Pahor
authors.forename: Fulvio
authors.initials: F
authors.lastname: Lauretani
authors.forename: Valentina
authors.initials: V
authors.lastname: Zamboni
authors.forename: Stefania
authors.initials: S
authors.lastname: Bandinelli
authors.forename: Roberto
authors.initials: R
authors.lastname: Bernabei
authors.forename: Jack M
authors.initials: JM
authors.lastname: Guralnik
authors.forename: Luigi
authors.initials: L
authors.lastname: Ferrucci
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D015992:Body Mass Index; D016009:Chi-Square Distribution; D015331:Cohort Studies; D015897:Comorbidity; D016001:Confidence Intervals; D004797:Enzyme-Linked Immunosorbent Assay; D005260:Female; D015577:Geriatric Assessment / Q000379:methods*; D006801:Humans; D018836:Inflammation Mediators / Q000378:metabolism; D008297:Male; D009026:Mortality / Q000639:trends*; D018908:Muscle Weakness / Q000175:diagnosis / Q000453:epidemiology*; D018482:Muscle, Skeletal / Q000378:metabolism / Q000503:physiopathology*; D009765:Obesity / Q000175:diagnosis / Q000453:epidemiology*; D010807:Physical Endurance / Q000502:physiology; D016016:Proportional Hazards Models; D012307:Risk Factors; D012508:Sarcolemma / Q000378:metabolism; D012680:Sensitivity and Specificity; D018709:Statistics, Nonparametric; D016138:Walking / Q000502:physiology
chemical_list: D018836:Inflammation Mediators