BackgroundDespite the importance of body composition in athletes, reference sex- and sport-specific body composition data are lacking. We aim to develop reference values for body composition and anthropometric measurements in athletes.MethodsBody weight and height were measured in 898 athletes (264 female, 634 male), anthropometric variables were assessed in 798 athletes (240 female and 558 male), and in 481 athletes (142 female and 339 male) with dual-energy X-ray absorptiometry (DXA). A total of 21 different sports were represented. Reference percentiles (5th, 25th, 50th, 75th, and 95th) were calculated for each measured value, stratified by sex and sport. Because sample sizes within a sport were often very low for some outcomes, the percentiles were estimated using a parametric, empirical Bayesian framework that allowed sharing information across sports.ResultsWe derived sex- and sport-specific reference percentiles for the following DXA outcomes: total (whole body scan) and regional (subtotal, trunk, and appendicular) bone mineral content, bone mineral density, absolute and percentage fat mass, fat-free mass, and lean soft tissue. Additionally, we derived reference percentiles for height-normalized indexes by dividing fat mass, fat-free mass, and appendicular lean soft tissue by height squared. We also derived sex- and sport-specific reference percentiles for the following anthropometry outcomes: weight, height, body mass index, sum of skinfold thicknesses (7 skinfolds, appendicular skinfolds, trunk skinfolds, arm skinfolds, and leg skinfolds), circumferences (hip, arm, midthigh, calf, and abdominal circumferences), and muscle circumferences (arm, thigh, and calf muscle circumferences).ConclusionsThese reference percentiles will be a helpful tool for sports professionals, in both clinical and field settings, for body composition assessment in athletes.

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Bioimpedance standards are well established for the normal healthy population and in clinical settings, but they are not available for many sports categories. The aim of this study was to develop reference values for male and female athletes using classic bioimpedance vector analysis (BIVA). In this study, 1556 athletes engaged in different sports were evaluated during their off-season period. A tetrapolar bioelectrical impedance analyzer was used to determine measurements of resistance (R) and reactance (Xc). The classic BIVA procedure, which corrects bioelectrical values for body height, was applied, and fat-free mass, fat mass, and total body water were estimated. In order to verify the need for specific references, classic bioelectrical values were compared to the reference values for the general male and female populations. Additionally, athletes were divided into three groups: endurance, velocity/power, and team sports. In comparison with the general healthy male and female populations, the mean vectors of the athletes showed a shift to the left on the R–Xc graph. Considering the same set of modalities, BIVA confidence graphs showed that male and female endurance athletes presented lower body fluids, fat mass, and fat-free mass than other sets of modalities. This study provides BIVA reference values for an athletic population that can be used as a standard for assessing body composition in male and female athletes.

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An accurate assessment of total energy expenditure (TEE) during a competitive season is required. We aimed to validate TEE estimated by self-reported energy intake (EI) and the dietary reference intake (DRI) method in 19 elite basketball players (aged 16-18 years) using doubly labeled water (DLW) as the reference method. The DRI models and EI from dietary records over a 7-day period were simultaneously assessed for TEE estimation. Resting energy expenditure was assessed by indirect calorimetry. Fat and fat-free mass (FFM) were determined by a 4-compartment model (body volume by air displacement plethysmography, bone mineral by DXA, and water by deuterium dilution). Fat and FFM ranged from 4 to 19 kg and from 47 to 81 kg, respectively. The physical activity level ranged from 2.2 to 3.7 with a mean value of 2.8 ± 0.4. Total energy expenditure from DLW (17,598 ± 3,298 kJ·d) was significantly underestimated by EI (11,274 ± 2,567 kJ·d), whereas no differences were found using DRI (17,008 ± 3,206 kJ·d). The EI and DRI methods explained TEE from DLW by 34% (p = 0.057) and 44% (p = 0.002), respectively, and wide limits of agreement were observed. Our findings suggested that EI is not a valid tool for TEE assessment. The DRI method may be valid at a group level but inaccurate for estimating individual TEE in young players during a demanding competitive season period.