Bone mineral accrual in 4- to 10-year-old precompetitive, recreational gymnasts: A 4-year longitudinal study
Bibliographic record
Abstract
Competitive female gymnasts have greater bone mineral measures than nongymnasts. However, less is known about the effect of recreational and/or precompetitive gymnastics participation on bone development. The purpose of this study was to investigate whether the differences previously reported in the skeleton of competitive female gymnasts are also demonstrated in young children with a current or past participation history in recreational or precompetitive gymnastics. One hundred and sixty-three children (30 gymnasts, 61 ex-gymnasts, and 72 nongymnasts) between 4 and 6 years of age were recruited and measured annually for 4 years (not all participants were measured at every occasion). Total-body (TB), lumbar spine (LS), and femoral neck (FN) bone mineral content (BMC) were measured by dual-energy X-ray absorptiometry (DXA). Multilevel random-effects models were constructed and used to predict differences in TB, LS, and FN BMC between groups while controlling for differences in body size, physical activity, and diet. Gymnasts had 3% more TB and 7% more FN BMC than children participating in other recreational sports at year 4 (p < .05). No differences were found at the LS between groups, and there were no differences between ex-gymnasts' and nongymnasts' bone parameters (p > .05). These findings suggest that recreational and precompetitive gymnastics participation is associated with greater BMC. This is important because beginner gymnastics skills are attainable by most children and do not require a high level of training. Low-level gymnastics skills can be implemented easily into school physical education programs, potentially affecting skeletal health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".