title: Validation of a bioelectrical impedance analysis equation to predict appendicular skeletal muscle mass (ASMM).
abstract: BACKGROUND
  Appendicular skeletal muscle mass (ASMM) is useful in the evaluation of nutritional status because it reflects the body muscle protein mass. The purpose of this study was to validate, against dual-energy X-ray absorptiometry (DEXA), a BIA equation to predict ASMM to be used in volunteers and patients.
  
  
  METHODS
  Healthy men (n = 246 men, BMI 25.3+/-2.9 kg/m(2)) and women (n =198, 24.1+/-3.6 kg/m(2)), and heart, lung and liver transplant patients (213 men, BMI of 24.6+/-4.4 kg/m(2); 113 women, BMI 23.0+/-5.2 kg/m(2)) were measured by BIA (Xitron Technologies) and DEXA (Hologic QDR 4500). A BIA equation to predict ASMM (kg) that included height(2)/resistance, weight, gender, age and reactance, was developed by means of multiple regressions. [table: see text] Mean difference (Bland-Altman) for volunteers was 0.1+/-1.1 kg, r =0.95, SEE 1.12 kg and for patients -0.4+/-1.5 kg, r =0.91, SEE 1.5 kg. Best fitted multiple regression equation was -4.211 + (0.267 x height2 / resistance) + (0.095 x weight)+(1.909 x sex (men = 1, women = 0)) + (-0.012 x age) + (0.058 x reactance).
  
  
  CONCLUSIONS
  BIA permits the prediction of ASMM in healthy volunteers and patients between 22 and 94 years of age. A slightly larger, though clinically not significant, error was noted in patients.
authors: Clinical Nutrition, Geneva University Hospital, Geneva, Switzerland.
authors: U G
authors: UG
authors: Kyle
authors: Laurence
authors: L
authors: Genton
authors: D
authors: D
authors: Hans
authors: C
authors: C
authors: Pichard
mesh_terms: D015502:Absorptiometry, Photon; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000886:Anthropometry; D001823:Body Composition / Q000502:physiology*; D017097:Electric Impedance; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000502:physiology*; D011237:Predictive Value of Tests; D012016:Reference Values; D012044:Regression Analysis; D015203:Reproducibility of Results