Effect of school-based physical activity interventions on body mass index in children: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: The prevalence of childhood obesity is increasing at an alarming rate. Many local governments have enacted policies to increase physical activity in schools as a way to combat childhood obesity. We conducted a systematic review and meta-analysis to determine the effect of school-based physical activity interventions on body mass index (BMI) in children. METHODS: We searched MEDLINE, EMBASE, CINAHL and the Cochrane Central Register of Controlled Trials up to September 2008. We also hand-searched relevant journals and article reference lists. We included randomized controlled trials and controlled clinical trials that had objective data for BMI from before and after the intervention, that involved school-based physical activity interventions and that lasted for a minimum of 6 months. RESULTS: Of 398 potentially relevant articles that we identified, 18 studies involving 18 141 children met the inclusion criteria. The participants were primarily elementary school children. The study duration ranged from 6 months to 3 years. In 15 of these 18 studies, there was some type of co-intervention. Meta-analysis showed that BMI did not improve with physical activity interventions (weighted mean difference -0.05 kg/m(2), 95% confidence interval -0.19 to 0.10). We found no consistent changes in other measures of body composition. INTERPRETATION: School-based physical activity interventions did not improve BMI, although they had other beneficial health effects. Current population-based policies that mandate increased physical activity in schools are unlikely to have a significant effect on the increasing prevalence of childhood obesity.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.057 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".