Organized sport and physical activity participation and body mass index in children and youth: A longitudinal study
Bibliographic record
Abstract
The relationship between sport participation and BMI in children and adolescents is unclear, with some studies showing no association at all and others suggesting that sport is linked to lower BMI. Another possibility, however, is that this relationship is bidirectional, with sport leading to lower BMI but BMI also influencing sport participation. Here, we examine the direction of this association by analyzing a longitudinal dataset. Data come from the Physical Health Activity Study Team (PHAST) study, a prospective open cohort study including 2278 children at baseline, followed from 2004 to 2010. We fit 3 lagged mixed effects models: One examining the simultaneous relationship, one regressing past BMI on present sport participation, and one regressing sport participation on present BMI. Our baseline sample included 1999 children, of whom 50% were female. Mean BMI increased over the study period from 19.0 (SD = 3.7) to 21.2 (SD = 4.1), while organized sport participation declined. Model results showed that BMI and sport are weakly associated, and that each of these variables predicts the other, which generally supports a bidirectional relationship. Consistent with some previous reports, however, the effect size in both directions is very small. At the levels of participation in our sample, activity and BMI are very weakly related. Findings should not obscure the other benefits of physical activity.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".