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.

This review and meta-analysis (PROSPERO registration number: CRD42020138845) critically evaluates test-retest reliability, concurrent validity and criterion validity of different physical activity (PA) levels of three most commonly used international PA questionnaires (PAQs) in official language versions of European Union (EU): International Physical Activity Questionnaire (IPAQ-SF), Global Physical Activity Questionnaire (GPAQ), and European Health Interview Survey-Physical Activity Questionnaire (EHIS-PAQ). In total, 1749 abstracts were screened, 287 full-text articles were identified as relevant to the study objectives, and 20 studies were included. The studies’ results and quality were evaluated using the Quality Assessment of Physical Activity Questionnaires checklist. Results indicate that only ten EU countries validated official language versions of selected PAQs. A meta-analysis revealed that assessment of moderate-to-vigorous PA (MVPA) is the most relevant PA level outcome, since no publication bias in any of measurement properties was detected while test-retest reliability was moderately high (rw = 0.74), moderate for the criterion (rw = 0.41) and moderately-high for concurrent validity (rw = 0.72). Reporting of methods and results of the studies was poor, with an overall moderate risk of bias with a total score of 0.43. In conclusion, where only self-reporting of PA is feasible, assessment of MVPA with selected PAQs in EU adult populations is recommended.

To date, few data on how the COVID-19 pandemic and restrictions affected children's physical activity in Europe have been published. This study examined the prevalence and correlates of physical activity and screen time from a large sample of European children during the COVID-19 pandemic to inform strategies and provide adequate mitigation measures. An online survey was conducted using convenience sampling from 15 May to 22 June, 2020. Parents were eligible if they resided in one of the survey countries and their children aged 6-18 years. 8,395 children were included (median age [IQR], 13 [10-15] years; 47% boys; 57.6% urban residents; 15.5% in self-isolation). Approximately two-thirds followed structured routines (66.4% [95%CI, 65.4-67.4]), and more than half were active during online P.E. (56.6% [95%CI, 55.5-57.6]). 19.0% (95%CI, 18.2-19.9) met the WHO Global physical activity recommendation. Total screen time in excess of 2 hours/day was highly prevalent (weekdays: 69.5% [95%CI, 68.5-70.5]; weekend: 63.8% [95%CI, 62.7-64.8]). Playing outdoors more than 2 hours/day, following a daily routine and being active in online P.E. increased the odds of healthy levels of physical activity and screen time, particularly in mildly affected countries. In severely affected countries, online P.E. contributed most to meet screen time recommendation, whereas outdoor play was most important for adequate physical activity. Promoting safe and responsible outdoor activities, safeguarding P.E. lessons during distance learning and setting pre-planned, consistent daily routines are important in helping children maintain healthy active lifestyle in pandemic situation. These factors should be prioritised by policymakers, schools and parents.

The objective was to compare measures from dual-energy X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA) and anthropometry with a reference four-compartment model to estimate fat mass (FM) and fat-free mass (FFM) changes in overweight and obese women after a weight-loss programme. Forty-eight women (age 39.8^5.8 years; weight 79·2^11·8 kg; BMI 30·7^3·6 kg/m 2 ) were studied in an out-patient weight-loss programme, before and after the 16-month intervention. Women attended weekly meetings for the first 4 months, followed by monthly meetings from 4 to 12 months. Body composition variables were measured by the following techniques: DXA, anthropometry (waist circumference-based model; Antrform), BIA using Tanita (TBF-310) and Omron (BF300) and a reference four-compartment model. Body weight decreased significantly (23·3 (SD 3·1) kg) across the intervention. At baseline and after the intervention, FM, percentage FM and FFM assessed by Antrform, Tanita, BF300 and DXA differed significantly from the reference method (P#0·001), with the exception of FFM assessed by Tanita (baseline P¼ 0·071 and after P¼0·007). DXA significantly overestimated the change in FM and percentage FM across weight loss (2 4·5 v. 23·3 kg; P, 0·001 and 23·7 v. 22·0 %; P,0·001, respectively), while Antrform underestimated FM and percentage FM (22·8 v. 2 3·3 kg; P¼ 0·043 and 2 1·1 v. 2 2·0 %; P¼ 0·013) compared with the four-compartment model. Tanita and BF300 did not differ (P. 0·05) from the reference model in any body composition variables. We conclude that these methods are widely used in clinical settings, but should not be applied interchangeably to detect changes in body composition. Furthermore, the several clinical methods were not accurate enough for tracking body composition changes in overweight and obese premenopausal women after a weight-loss programme.

The aims of this study were to analyze the usefulness of raw bioelectrical impedance (BI) parameters in assessing water compartments and fluid distribution in athletes. A total of 202 men and 71 female athletes were analyzed. Total body water (TBW) and extracellular water (ECW) were determined by dilution techniques, while intracellular water (ICW) was calculated. Fluid distribution was calculated as the ECW/ICW ratio (E:I). Phase angle (PhA), resistance (R) and reactance (Xc) were obtained through BI spectroscopy using frequency 50kHz. Fat (FM) and fat-free mass (FFM) were assessed by dual-energy X-ray absorptiometry. After adjusting for height, FM, FFM, age and sports category we observed that: PhA predicted ICW (females: β = 1.62, p < 0.01; males: β = 2.70, p < 0.01) and E:I (males and females: β = −0.08; p < 0.01); R explained TBW (females: β = −0.03; p < 0.01; males: β = −0.06; p < 0.01) and ECW (females: β = –0.02, p < 0.01; males: β = −0.03, p < 0.01) and ICW (females: β = –0.01, p < 0.053; males: β = –0.03 p < 0.01); and Xc predicted ECW (females: β = −0.06, p < 0.01; males: β = −0.12, p < 0.01). A higher PhA is a good predictor of a larger ICW pool and a lower E:I, regardless of body composition, age, height, and sports category. Lower R is associated with higher water pools whereas ECW expansion is explained by lower Xc. Raw BI parameters are useful predictors of total and extracellular pools, cellular hydration and fluid distribution in athletes.