Relative body fat and anthropometric prediction of body density of male athletes.
Two hundred and seven male members of South Australian representative squads in 18 sports (mean +/- s = 24.2 +/- 4.7 years) were tested in order to provide descriptive data on relative body fat (% BF), develop a population specific equation and cross-validate existing equations. Measurements were taken of 10 circumferences, 2 diameters and 8 skinfolds; body density (BD) was measured by underwater weighing with the residual volume (RV) being determined by He dilution. The overall mean BD was 1.0761 g X cm-3 (s = 0.0085 g X cm-3; range = 1.0465-1.0968 g X cm-3) which corresponded to 10.0% BF according to Siri (s = 3.7%; range = 1.3-23.0%). The games players (n = 129) registered an overall mean of 10.3% BF (s = 3.7%; range = 2.2-23.0%). There were significant differences (p less than 0.05) for % BF between the lacrosse players (mean = 12.3%) an both the Australian Rules footballers (mean = 8.0%) and track and field athletes (mean = 8.7%). A stepwise multiple regression on 185 subjects yielded the following equation, which had an R of 0.787: BD = 1.078865-0.000419 (sigma abdominal, medial calf, front thigh and juxta-nipple skinfolds in mm) +0.000948 (neck circumference in cm) -0.000266 (age in decimal years) -0.000564 (ankle circumference in cm). Only those predictors which resulted in a significantly increased correlation (p less than or equal to 0.05) were included. The standard error of estimate of 0.00537 g X cm-3 was equivalent to 2.3% BF at the mean. This equation was satisfactorily cross-validated against the BD of a separate sample (n = 22) from the same population. However, cross-validation of 11 previously published equations indicated that they have limited applicability to State representative sportsmen.
D000273:Adipose Tissue / Q000033:anatomy & histology*; D000328:Adult; D000886:Anthropometry / Q000379:methods*; D001835:Body Weight; D003720:Densitometry; D005544:Forecasting; D006801:Humans; D008297:Male; D010806:Physical Education and Training; D012044:Regression Analysis