title: A Skinfold Model to Predict Fat-Free Mass in Female Athletes.
abstract: OBJECTIVE: Despite widespread use of skinfolds to estimate body fatness, few prediction models have been validated on female athletes. Most skinfold models have been validated with hydrodensitometry, which does not account for the variability in bone density that may exist among female athletes. Our purpose was to develop a skinfold model that predicts fat-free mass (FFM) in female collegiate athletes. DESIGN AND SETTING: A skinfold model was developed using dual-energy x-ray absorptiometry (DEXA) as the criterion method. Four skinfold measures (abdominal, suprailiac, thigh, triceps), height, and weight were entered into a regression model. The best model was developed and validated by calculating the predicted error sum of squares statistic. SUBJECTS: Study participants included 101 National Collegiate Athletic Association Division I female athletes (age = 20.3 +/- 1.4 years, height = 166.7 +/- 7.8 cm, mass = 63.1 +/- 8.1 kg) from several sports. MEASUREMENTS: Each participant's FFM was measured via DEXA. Skinfold thicknesses were measured and entered into the regression model. RESULTS: The final regression model included mass and abdominal and thigh skinfolds: FFM = 8.51 + (0.809 x mass) - (0.178 x abdominal skinfold) - (0.225 x thigh skinfold). The model showed excellent predictive ability (R = 0.98, standard error of the estimate = 1.1 kg). Pairwise comparisons indicated that prediction error showed no overprediction or underprediction bias. CONCLUSIONS: In female collegiate athletes, FFM can be predicted accurately from body mass and abdominal and thigh skinfolds. This model is practical and can be used in most athletic settings.
authors.affiliation: Michigan State University, East Lansing, MI.
authors.forename: Evelyn R
authors.initials: ER
authors.lastname: Warner
authors.forename: Willa C
authors.initials: WC
authors.lastname: Fornetti
authors.forename: Jennifer J
authors.initials: JJ
authors.lastname: Jallo
authors.forename: James M
authors.initials: JM
authors.lastname: Pivarnik