Bone properties and skeletal maturity in adolescent males, as assessed by quantitative ultrasound
Bibliographic record
Abstract
ABSTRACT \nBackground: \nPrevious studies have implied that weight-bearing, intense and prolonged \nphysical activities optimize bone accretion during the grow^ing years. The \nmajority of past inquiries have used dual-energy X-ray absorptiometry (DXA) to \nexamine bone strength and hand-wrist radiography to determine skeletal \nmaturity in children. Recently, quantitative ultrasound (QUS) technologies have \nbeen developed to examine bone properties and skeletal maturity in a safe, noninvasive \nand cost-effective manner. \nObjective: \nThe purpose of this study was to compare bone properties and skeletal \nmaturity in competitive male child and adolescent athletes with minimallyactive, \nage-matched controls, using QUS technology. >. \nMethods: \nIn total, 224 males were included in the study. The 115 pre-pubertal boys \naged 10-12 years consisted of control, minimally-active children (n=34), soccer \nplayers (n=26), gymnasts (n=25) and hockey players (n=30). In addition, the 109 \nlate-pubertal boys aged 14-16 years consisted of control, minimally-active \nadolescents (n=31), soccer players (n=30), gymnasts (n=17) and hockey players \n(n=31). The athletic groups were elite level players that predominantly trained \nyear-round. Physical activity, nutrition and sports participation were assessed with various questionnaires. Anthropometries, such as height, weight and \nrelative body fat percentage (BF%) were assessed using standard measures. \nSkeletal strength and age were evaluated using bone QUS. Lastly, salivary \ntestosterone (sT) concentration was measured using Radioimmunoassay (RIA). \nResults: \nWithin each age group, there were no significant differences between the \nactivity groups in age and pubertal stage. An age effect was apparent in all \nvariables, as expected. A sport effect was noted in all physical characteristics: \nthe child and adolescent gymnasts were shorter and lighter than other sports \ngroups. Adiposity was greater in the controls and in the hockey players. All \nchild subjects were pubertal stage (fanner) I or II, while adolescent subjects were \npubertal stage IV or V. There were no differences in daily energy and mineral \nintakes between sports groups. In both age groups, gymnasts had a higher \ntraining volume than other athletic groups. Bone speed of sound (50s) was \nhigher in adolescents compared with the children. Gymnasts had signifieantly \nhigher radial 50S than controls, hockey and soccer players in both age cohorts. \nHockey athletes also had higher radial 50S than controls and soccer players in \nthe child and adolescent groups, respectiyely. Child gymnasts and soccer \nplayers had greater tibial 50S compared with the hockey players and control \ngroups. Likewise, adolescent gymnasts and soccer players had higher tibial SoS compared with the control group. No interaction was apparent between age and \ntype of activity in any of the bone measures. » \nLastly, maturity as assessed by sT and secondary sex characteristics (Tanner \nstage) was not different between sports group within each age group. Despite \nthe similarity in chronological age, androgen levels and sexual maturity, \ndifferences between activity groups were noted in skeletal maturity. In the \nyounger group, hockey players had the highest bone age while the soccer players \nhad the lowest bone age. In the adolescent group, gymnasts and hockey players \nwere characterized by higher skeletal maturity compared with controls. An \ninteraction between the age and sport type effects was apparent in skeletal \nmaturity, reflecting the fact that among the children, the soccer players were \nsignificantly less mature than the rest of the groups, while in the adolescents, the \ncontrols were the least skeletally mature. \nSummary and Conclusions: \nIn summary, radial and tibial SOS are enhanced by the unique loading \npattern in each sport (i.e, upper and lower extremities in gymnastics, lower \nextremities in soccer), with no cumulative effect between childhood and \nadolescence. That is, the effect of sport participation on bone SOS was apparent \nalready among the young athletes. Enhanced bone properties among athletes of \nspecific sports suggest that participation in these sports can improve bone \nstrength and potential bone health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".