Purpose Assessing the body composition of children and adolescents is important to monitor their health status. Anthropometric measurements are feasible and less-expensive than other techniques for body composition assessment. This study aimed to systematically map anthropometric equations to predict adipose tissue, body fat, or density in children and adolescents, and to analyze methodological aspects of the development of anthropometric equations using skinfolds. Methods A scoping review was carried out following the PRISMA-ScR criteria. The search was carried out in eight databases. The methodological structure protocol of this scoping review was retrospectively registered in the Open Science Framework (https:// osf. io/ 35uhc/). Results We included 78 reports and 593 anthropometric equations. The samples consisted of healthy individuals, people with different diseases or disabilities, and athletes from different sports. Dual-energy X-ray absorptiometry (DXA) was the reference method most commonly used in developing equations. Triceps and subscapular skinfolds were the anthropometric measurements most frequently used as predictors in the equations. Age, stage of sexual maturation, and peak height velocity were used as complementary variables in the equations. Conclusion Our scoping review identified equations proposed for children and adolescents with a great diversity of characteristics. In many of the reports, important methodological aspects were not addressed, a factor that may be associated with equation bias. Level IV Evidence obtained from multiple time series analysis such as case studies. (NB: dramatic results in uncontrolled trials might also be regarded as this type of evidence).

Objective To verify the validity of anthropometric methods body adiposity index (BAI), relative fat mass (RFM) and body fat index (BFI) to estimate body fat percentage (%BF) in adolescents. Methods A cross-sectional study was carried out with 420 Brazilian adolescents aged 15-19 years, stratified by age (< 18 years, n = 356; ≥ 18 years, n = 64) and sex (boys, n = 216; girls, n = 204). The Anthropometric measurements height, body weight, hip circumference and waist circumference were collected to calculate the %BF by BAI, RFM, BFI methods. Subsequently, %BF was measured by dual emission X-ray absorptiometry (DXA), adopted as a reference method. In the statistical analysis of the data, the Pearson correlation test and the paired t test between %BF obtained by the equations and by the DXA were performed. The method validation criterion was that 68% of individuals should be within an acceptable error range of ± 3.5% of BF and Cohen's Kappa index ≥ 0.61. Additionally, the Bland-Altman graphical analysis was performed. Results All methods showed a high correlation with DXA. For the Kappa index, only the RFM reached the criterion in the total sample (0.67) and in the sample < 18 years (0.68). None of the methods reached the criterion of 68% of the sample within the error range of ± 3.5% of BF. ConclusionThe BAI, RFM and BFI equations were not valid for predicting BF in the studied sample according to the criteria adopted regardless of sex or age. Level of evidence Level V, cross-sectional descriptive study.

A detraining period after resistance training causes a significant decrease in trained-induced muscular adaptations. However, it is unclear how long muscle strength and hypertrophy gains last after different detraining periods. Thus, the present systematic review with meta-analysis aimed to evaluate the chronic effects of detraining on muscle strength and hypertrophy induced by resistance training. Searches were conducted on PubMed, Scopus, EBSCO, CINAHL, CENTRAL, and Web of Science. The difference in means and pooled standard deviations of outcomes were converted into Hedges’ g effect sizes (g). Twenty randomized and non-randomized trials (high and moderate risks of bias, respectively, and fair quality) were included for qualitative analysis of muscle strength and hypertrophy, while only two studies were included in the meta-analysis for maximum muscle strength. The resistance training group presented a significant increase in one-repetition maximum (1RM) chest press (g: 4.43 [3.65; 5.22], p < 0.001) and 1RM leg press strength (g: 4.47 [2.12; 6.82], p < 0.001) after training. The strength gains observed in the resistance training group were also maintained after 16–24 weeks of detraining (g: 1.99 [0.62; 3.36], p = 0.004; and g: 3.16 [0.82; 5.50], p = 0.008; respectively), when compared to the non-exercise control group. However, 1RM chest press and leg press strength level was similar between groups after 32 (g: 1.81 [−0.59; 4.21], p = 0.139; and g: 2.34 [−0.48; 5.16], p = 0.104; respectively) and 48 weeks of detraining (g: 1.01 [−0.76; 2.79], p = 0.263; and g: 1.16 [−1.09; 3.42], p = 0.311; respectively). There was not enough data to conduct a meta-analysis on muscular hypertrophy. In conclusion, the present systematic review and meta-analysis demonstrated that, when taking random error into account, there is no sufficient high-quality evidence to make any unbiased claim about how long changes in muscle strength induced by RT last after a DT period. Moreover, the effect of different DT periods on muscle hypertrophy induced by RT remains unknown since there was not enough data to conduct a meta-analysis with this variable.

This study compared the effects of different conditioning activities on the 100-m dash performance of 11 male, high school track and field athletes (mean age = 16.3; SD = 1.2 years). Participants performed a 100-m dash seven minutes after each of four randomized conditioning protocols, with each condition and 100-m dash separated by 3-10 days. The conditioning protocols were (a) control, no conditioning activity; (b) weighted plyometric, three sets of 10 repetitions of alternate leg bounding with additional load of 10% of the body mass; (c) free sprint, two 20-m sprints; and (d) resisted sprint (RS), two 20-m resisted sprints using an elastic tubing tool. We obtained session ratings of perceived exertion (SRPE) immediately after each conditioning protocol. There were no significant differences between any of the three experimental conditioning activities on 100-m sprint time, but the RS protocol improved 100-m sprint time compared with the control (no conditioning) protocol ( p < .001). The RS also led to greater sprint velocity and higher SRPE compared with the control condition ( p < .01). There was no significant association between SRPE and 100-m performance ( p = .77, r = .05). These results suggest a benefit for young male track and field athletes to the elastic tubing warm-up activities prior to the 100-m dash.