The Benefits to Bone Health in Children and Pre-School Children with Additional Exercise Interventions: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: Determine if exercise interventions, beyond what is already provided to children and preschool children, improve bone health and reduce fracture incidence. DESIGN: Systematic review and meta-analysis reported using the PRISMA guidelines. Certainty of evidence was assessed using GRADE recommendations. DATA SOURCES: Five electronic databases were searched for records: PUBMED; CINAHL; CENTRAL; SPORTDiscus; Web of Science. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Randomised, quasi-randomised and non-randomised controlled trials (including cluster-randomised) assessing the impact of additional exercise interventions (e.g., increased physical education classes or specific jumping programs) on bone health in children (6-12 years) and pre-school children (2-5 years) without dietary intervention. RESULTS: = 790, SMD = 0.55, 95% CI = 0.01 to 1.09) was reported, however this was not significant following sensitivity analysis. Other DXA and pQCT measures, as well as fracture incidence, did not appear to significantly differ over time between intervention and control groups. No studies reported adverse events. Studies failed to report all domains within the TIDieR checklist. All studies were at high risk of bias using the Cochrane RoB Tool 2.0. The certainty of the evidence was very low. CONCLUSIONS: The addition of exercise interventions, beyond what is provided to children, does not appear to improve DXA and pQCT measures of bone health. The effect of additional exercise interventions on bone health in pre-school children is largely unknown. Future trials should ensure adherence is clearly reported and controlled for within analysis as well as including reports of adverse events (e.g., apophysitis) that occur due to increased exercise interventions.
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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 | 0.017 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.050 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".