Body composition can substantially impact elite swimming performance. In practice, changes in fat and lean mass of elite swimmers are estimated using body mass, sum of seven skinfolds (∑7) and lean mass index (LMI). However, LMI may be insufficiently accurate to detect small changes in body composition which could meaningfully impact swimming performance. This study developed equations which estimate dual-energy x-ray absorptiometry (DXA)-derived lean and fat mass using body mass and ∑7 data. Elite Australian swimmers (n = 44; 18 male, 26 female) completed a DXA scan and standardised body mass and ∑7 measurements. Equations to estimate DXA-derived lean and fat mass based on body mass, ∑7 and sex were developed. The relationships between ∑7, body mass and DXA-derived lean and fat mass were non-linear. Fat mass (Adjusted R2 = 0.91; standard error = 1.0 kg) and lean mass (Adjusted R2 = 0.99; standard error = 1.0 kg) equations were considered sufficiently accurate. Lean mass estimates outperformed the LMI in identifying the correct direction of change in lean mass (82% correct; LMI 71%). Using the accurate estimations produced by these equations will enhance the prescription and evaluation of programmes to optimise the body composition and subsequent performance in swimmers.
Keywords: Three compartment model; adipose tissue; athletes; body composition; muscle mass; swimming.