Physical Activity and Anthropometric Characteristics Among Urban Youth in Mexico: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Obesity is a critical problem among Mexican youth, but few studies have investigated associations among physical activity (PA) modes and anthropometrics in this population. This study examined associations among active commuting to school (ACS), sports or other organized PA, outdoor play, and body mass index (BMI) percentile and waist circumference (WC) among Mexican youth. METHODS: Parents of school children (N = 1996, ages 6 to 14 years, 53.1% female) in 3 Mexican cities reported PA participation using the (modified) fourth grade School Physical Activity and Nutrition Survey. Trained assessors measured BMI percentile and WC in person. RESULTS: Parents reported that 52.3% of children engaged in ACS, 57.3% participated in sports or organized PA, and a median of 2 days in the previous week with at least 30 minutes of outdoor play. In complete case analyses (n = 857), ACS was negatively associated with BMI percentile, and outdoor play was negatively associated with WC after adjusting for school, age, sex, and income. In analyses incorporating data from multiple imputation (N = 1996), outdoor play was negatively associated with WC (all Ps < . 05). CONCLUSIONS: ACS and outdoor play are favorably associated with anthropometrics and may help prevent childhood obesity in Mexico. ACS and outdoor play should be priorities for increasing youth PA in Mexico.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".