Purpose: Considering the different loading and training characteristics of the sports practiced during growth, it is important to specify and categorize the bone and soft tissue adaptations in adolescent athletes. This study aimed to categorize 10 different loading sports and a nonsport group and identify the differences in bone density and soft tissues.Methods: The sample included 625 adolescents (10 to 17 yr of age) of 10 sports (soccer, basketball, volleyball, track and field, judo, karate, kung fu, gymnastics, baseball, and swimming) and a nonsport group. Dual-energy x-ray absorptiometry assessed areal bone mineral density (aBMD), bone mineral apparent density (BMAD), and soft tissues (lean soft tissue and fat mass). The results were adjusted for sex, peak height velocity status, lean soft tissue, fat mass, and weekly training volume.Results: The comparisons among groups showed that soccer had the highest whole-body aBMD (mean ± SEM: 1.082 ± 0.007 g·cm⁻²) and lower limb aBMD (1.302 ± 0.010 g·cm⁻²). Gymnastics presented the highest upper limb aBMD (0.868 ± 0.012 g·cm⁻²) and whole-body BMAD (0.094 ± 0.001 g·cm⁻³). Swimming presented the lowest aBMD values in all skeletal sites (except at the upper limbs) and whole-body BMAD. The soft tissue comparisons showed that soccer players had the highest lean soft tissue (43.8 ± 0.7 kg). The lowest fat mass was found in gymnasts (8.04 ± 1.0 kg).Conclusion: The present study investigated and categorized for the first time 10 different sports according to bone density and soft tissue profiles. Soccer and gymnastics sport groups were found to have the highest bone density in most body segments, and both sports were among the groups with the lowest fat mass.

Purpose: To investigate the mediating effect of muscle mass on the relationship between training load and bone density in adolescent swimmers. Methods: A cross-sectional study involving 87 control and 22 swimmers aged 10–19 years (overall sample: n = 109). Swimmers had a minimum of 1 year of competition in regional and national championships, and control adolescents reported 1 year without any organized sport. Bone density was the main outcome (dual-energy X-ray absorptiometry), which was measured in upper limbs, lower limbs, spine, and whole body. Monthly training load was the independent variable, while the mediation effect of lean soft tissue was assessed. Maturity offset, age, inflammation, and vitamin D intake were treated as covariates. Results: Swimmers had lower bone density than controls; there was a significant and positive relationship between training load and muscle mass. In boys, training load presented a negative correlation with bone density in lower limbs [r = −.293; 95% confidence interval (CI), −.553 to −.034]. In girls, training load was negatively related to bone mineral density in lower limbs (r = .563; 95% CI, −.770 to −.356) and whole body (r = −.409; 95% CI, −.609 to −.209). Conclusion: Training load had a negative relationship on bone density of swimmers of both sexes, independently of the positive effect of lean soft tissue on bone density.

Background: To examine the association of handgrip strength (HGS) and bone mineral density (BMD) of Brazilian children and adolescents. Methods: The sample included 243 children and adolescents aged from 4 to 15 years (9.3 ± 2.2 years), 171 males and 72 females. The following measurements were performed: weight, height, trunk length, and years to the peak height velocity (PHV). The percentage lean soft tissue (PLST), percentage fat mass (PFM), and BMD were obtained using Dual Energy X-ray Absorptiometry (DXA) and HGS using a dynamometer. Results: In girls, HGS was positively associated with higher BMD, even after the adjustments, by arms [β = 0.006; p < 0.001], legs [β = 0.014; p < 0.001], pelvis [β = 0.019; p < 0.001], trunk [β = 0.013; p < 0.001], spine [β = 0.013; p = 0.008], and total body [β = 0.009; p < 0.001]. The same occurred in the boys, even after the adjustments a positive relationship was observed, whereas higher HGS was related to greater BMD in arms [β = 0.006; p < 0.001], legs [β = 0.017; p < 0.001], pelvis [β = 0.014; p < 0.001], trunk [β = 0.009; p < 0.001], spine [β = 0.008; p < 0.001], and total body [β = 0.007; p < 0.001]. Conclusion: HGS was positively associated to BMD in boys and girls, regardless of age, PHV, PLST, and PFM.

Objective: To analyze the association of potential risk factors to health with body fatness and insulin resistance. Baseline measures of the ongoing longitudinal Analysis of Behaviors of Children During (ABCD) Growth Study. Materials and Methods: The sample was composed of 280 adolescents of both sexes (198 boys and 82 girls) aged from 10 to 18 years. Four risk factors were considered, as follows: no sports practice, skipping breakfast, poor sleep quality, and TV viewing. The outcomes considered were insulin resistance (HOMA-IR) and body fatness (densitometer scanner). Age, sex, maturity offset, and ethnicity were treated as covariates. Results: No sports practice and skipping breakfast were associated with higher body fatness (Sports practice: Wald: 8.786; p = 0.003. Breakfast: Wald: 9.364; p = 0.002). Poor sleep quality was related to a greater HOMA-IR index (Wald: 6.013; p = 0.014). Adolescents with ≥3 risk factors presented a higher risk of high HOMA-IR (OR = 4.89 (95%CI: 1.61 to 14.84)) than their counterparts with no risk factors. Conclusion: Lifestyle risk factors seem relevant to affect obesity and insulin resistance, while the aggregation of these risk factors affects insulin resistance, independent of adiposity.