title: Anthropometric models to predict appendicular lean soft tissue in adolescent athletes.
abstract: OBJECTIVE
  Skeletal muscle (SM), which is found mainly within the appendicular lean soft tissue (ALST) compartment, is a biological important body compartment. Simple and accurate methods to estimate both SM and ALST remain difficult to obtain. We aimed to develop and to cross-validate anthropometric models for ALST in athletes, using dual-energy x-ray absorptiometry (DXA) as the reference method.
  
  
  METHODS
  ALST equations were developed in 176 athletic boys (15.0 +/- 2.8 yr; 64.5 +/- 15.8 kg; 1.72 +/- 0.15 m) and 92 athletic girls (14.6 +/- 2.8 yr; 53.0 +/- 13.1 kg; 1.61 +/- 0.13 m). Skinfolds were measured at the triceps, the thigh, and medial calf, and circumferences were measured at the midupper arm, the midthigh, and the midcalf. ALST was assessed using DXA (QDR-4500; Hologic, Walthman, MA; fan-beam mode). Two models were developed: a body weight model (WHt model) and a corrected muscle girth model (CMG model, which included the parameters height x CAG, height x CTG, and height x CCG, where CAG is corrected arm girth, CTG is corrected thigh girth, and CCG is the corrected calf). Simple regression analysis was used to identify the best model fit. The equations were internally cross-validated using the predicted residual sum of squares method, and performance of new equations was analyzed by regression analysis and agreement between methods.
  
  
  RESULTS
  The new WHt model generated the following equation: ALST = -20.338 + 0.199(W) + 3.294(gender) + 14.230(height) + 0.192(age), where gender = 1 for male and 0 for female. The CMG model produced the following equation: ALST = 3.260 + 0.002(height x CTG) + 0.007(height x CAG) + 0.003(height x CCG). WHt equation had an R = 0.91 and an SEE = 2.00 kg, whereas CMG equation presented an R = 0.93 and an SEE = 1.80 kg. In both equations, slopes and intercepts did not differ from the line of identity; no mean differences between predicted and measured values and no trend line were observed (P > 0.05).
  
  
  CONCLUSIONS
  Both models accurately predict ALST in young athletes, affording a practical means to quantify this compartment.
authors.affiliation: Exercise and Health Laboratory, Faculty of Human Movement, Technical University of Lisbon, Lisboa, Portugal.
authors.forename: Ana L
authors.initials: AL
authors.lastname: Quiterio
authors.forename: Elvis A
authors.initials: EA
authors.lastname: Carnero
authors.forename: Analiza M
authors.initials: AM
authors.lastname: Silva
authors.forename: Brianna C
authors.initials: BC
authors.lastname: Bright
authors.forename: Luis B
authors.initials: LB
authors.lastname: Sardinha
mesh_terms: D000293:Adolescent; D000465:Algorithms; D000886:Anthropometry / Q000379:methods*; D001823:Body Composition / Q000502:physiology*; D002648:Child; D005260:Female; D006801:Humans; D008297:Male; D018482:Muscle, Skeletal / Q000033:anatomy & histology*; D013177:Sports