Estimation Of Fat-free Mass By Height, Corrected Girths And Skeletal Diameters In Mexican Athletes

Fat-free mass (FFM) is a key factor in athletic performance. Although FFM can be estimated through many body composition assessment techniques, anthropometry remains a practical option among exercise science professionals. Anthropometric models traditionally focus on fat mass estimation to predict FFM as the remaining component. However, corrected girths that assume geometric models to enhance theoretical validity have been promising for estimating FFM directly. PURPOSE: To develop and validate a prediction model for estimating FFM using corrected girths, skeletal widths, and height. METHODS: A total of 220 male university athletes (age: 24.2 ± 4.7 y; weight: 73.9 ± 8.2 kg; height 1.77 ± 0.06 m; FFM: 61.7 ± 6.1 kg) underwent a whole-body DXA scan (Hologic QDR 4500) to assess their FFM, and anthropometric measurements according to the ISAK protocol and carried out by certified personnel. We calculated three corrected girths (CG) as Girth - (π * skinfold) for the arm, forearm, and calf girths corrected for the triceps, biceps, and calf skinfolds, respectively. The CG, four appendicular skeletal widths (SW) (wrist, elbow, knee, and ankle), four trunk SW (bi-acromial, bi-ileocrestal, transverse and anteroposterior chest), and height were included to set an Anthropometric Lean Constitution method (ALCM), which was calculated as ALCM = Average CG (cm) * Average SW (m) * Height (m). The ALCM was calculated with either the appendicular (ALCM4) or all (ALCM8) the SW. We used two-thirds of the sample for model development (linear regression) and the third remaining for validation using Bland-Altman analysis. RESULTS: The mean ALCM4 and ALCM8 were 3.94 ± 0.41 and 9.72 ± 1.11, respectively. The obtained regression equations were FFM = 13.16 + 10.02 * ALCM4 (SEE = 2.53 kg, R2 = 0.81), and FFM = 5.66 + 6.69 * ALCM8 (SEE = 2.18 kg, R2 = 0.91). The mean difference (95% limits of agreement) between the equations and DXA-derived FFM were -0.37 kg (-4.77 to 4.03) for ALCM4 and 1.01 kg (-2.72 to 4.74) for ALCM8. CONCLUSIONS: Estimating FFM using the ALCM is feasible. The strong correlation between ALCM and DXA-derived FFM suggests that ALCM can be used as an indicator of FFM on athletes without the necessity of estimating FFM.