Longitudinal associations between physical activity intensity and mental health problems in overweight/obese youth
Bibliographic record
Abstract
Mental health challenges in overweight/obese youth represent a growing public health concern. Physical activity (PA) may protect against adverse mental health outcomes in this population. However, research has yet to fully examine how specific PA dosage characteristics, such as PA intensity, affect mental health trajectories among overweight/obese youth. This study used longitudinal data from the Millennium Cohort Study (N = 858) to examine how PA intensity at age 7 predicts mental health outcomes at ages 11 and 14. Accelerometer-measured PA was categorized into moderate-to-vigorous-intensity (MVPA) and light-intensity (LPA) activity. Higher MVPA at age 7 predicted fewer internalizing problems at ages 11 (β = -0.014, p = 0.018) and 14 (β = -0.023, p = 0.001), with stronger effects over time being observed for the peer problem-related component of the Strengths and Difficulties Questionnaire (SDQ). In contrast, LPA was associated with increased externalizing problems at age 11 (β = 0.007, p = 0.008), particularly the hyperactivity component of the SDQ, and this effect was no longer reliable at 14. These findings suggest that promoting MVPA is important to support mental health outcomes in overweight/obese youth, although intervention studies are needed to test causality.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".