title: Assessing appendicular skeletal muscle mass with bioelectrical impedance analysis in free-living Caucasian older adults.
abstract: OBJECTIVE
  Aging is characterized by a loss of appendicular skeletal muscle mass (ASMM) leading to physical disability and death. Bioelectrical impedance analysis (BIA) is reliable in estimating ASMM but no prediction equations are available for elderly Caucasian subjects. The aim of the study was to develop and validate an equation derived from bioelectrical impedance analysis (BIA) to predict appendicular skeletal muscle mass (ASMM) in healthy Caucasian elderly subjects, taking dual X-ray absorptiometry (DXA) as the reference method, and comparing the reliability of the new equation with another BIA-based model developed by Kyle et al. (Kyle UG, Genton L, Hans D, Pichard C, 2003).
  
  
  METHODS
  With a cross-sectional design, 296 free-living, healthy Caucasian subjects (117 men, 179 women) over 60 years of age were enrolled. Lean mass of limbs was measured with DXA to ascertain ASMM (ASMMDxA). Whole-body tetrapolar BIA was performed to measure resistance (Rz), resistance normalized for stature (RI), and reactance (Xc). The BIA multiple regression equation for predicting ASMM was developed using a double cross-validation technique. The predicted ASMM values were compared with ASMMKyle, i.e. ASMM estimates derived from the model developed by Kyle et al. (Kyle et al., 2003).
  
  
  RESULTS
  Cross-validation resulted in a unique equation using the whole sample: ASMM (kg) = -3.964 + (0.227*RI) + (0.095*weight) + (1.384*sex) + (0.064*Xc) [R(2) = 0.92 and SEE = 1.14 kg]. In our sample, ASMMKyle differed significantly from the ASMMDxA (p < 0.0001), with a mean error of -0.97 ± 1.34 kg (5.1 ± 6.9%). Unlike the present BIA prediction equation, the Kyle et al. model showed a correlation between the bias and the mean of ASMMDxA and ASMMKyle (r = -0.406, p < 0.001).
  
  
  CONCLUSIONS
  The new BIA equation provides a valid estimate of ASMM in older Caucasian adults.
authors.affiliation: Department of Medicine - DIMED, Geriatrics Division, University of Padova, Padova, Italy.
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Sergi
authors.affiliation: Department of Medicine - DIMED, Geriatrics Division, University of Padova, Padova, Italy. Electronic address: marinaderui@gmail.com.
authors.forename: Marina
authors.initials: M
authors.lastname: De Rui
authors.affiliation: Department of Medicine - DIMED, Geriatrics Division, University of Padova, Padova, Italy.
authors.forename: Nicola
authors.initials: N
authors.lastname: Veronese
authors.affiliation: Department of Medicine - DIMED, Geriatrics Division, University of Padova, Padova, Italy.
authors.forename: Francesco
authors.initials: F
authors.lastname: Bolzetta
authors.affiliation: Department of Medicine - DIMED, Geriatrics Division, University of Padova, Padova, Italy.
authors.forename: Linda
authors.initials: L
authors.lastname: Berton
authors.affiliation: Department of Medicine - DIMED, Geriatrics Division, University of Padova, Padova, Italy.
authors.forename: Sara
authors.initials: S
authors.lastname: Carraro
authors.affiliation: Department of Medicine - DIMED, Geriatrics Division, University of Padova, Padova, Italy.
authors.forename: Giulia
authors.initials: G
authors.lastname: Bano
authors.affiliation: Department of Medicine - DIMED, Geriatrics Division, University of Padova, Padova, Italy.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Coin
authors.affiliation: Department of Medicine - DIMED, Geriatrics Division, University of Padova, Padova, Italy; National Research Council, Aging Branch, Institute of Neuroscience, Padova, Italy.
authors.forename: Enzo
authors.initials: E
authors.lastname: Manzato
authors.affiliation: Department of Cardiac, Thoracic and Vascular Sciences, Biostatistics, Epidemiology and Public Health Unit, University of Padova, Padova, Italy.
authors.forename: Egle
authors.initials: E
authors.lastname: Perissinotto
mesh_terms: D015502:Absorptiometry, Photon; D000368:Aged; D000369:Aged, 80 and over; D001823:Body Composition; D015992:Body Mass Index; D001835:Body Weight; D003430:Cross-Sectional Studies; D017097:Electric Impedance; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D018482:Muscle, Skeletal / Q000378:metabolism*; D015203:Reproducibility of Results; D044465:White People
keywords: Body composition; Limbs lean mass; Older adults; Prediction equation; Sarcopenia