Associations between Screen-Based Activities, Physical Activity, and Dietary Habits in Mexican Schoolchildren
Bibliographic record
Abstract
Screen-based activities are associated with increased risk of obesity and contribute to physical inactivity and poor dietary habits. The primary aim of this study was to examine the associations among screen-based activities, physical activity, and dietary habits in school-aged children in Guadalajara, Puerto Vallarta, and Mexico City, Mexico. The secondary aim was to examine these associations across sex. The School Physical Activity and Nutrition survey was used to assess screen-based activities (TV watching, video game use, computer use), physical activity, and dietary habits. Organized activity/sports participation, unhealthy dietary habits, and household income were correlated with screen-based activities. While TV watching was associated with decreased participation in organized activity/sports participation, computer and video game use was associated with increased organized activity/sports participation. Boys engaged in more TV watching and video game use compared to girls. All screen-based activities were associated with age among boys; whereas video game and computer use were associated with higher income among girls. These findings suggest a need for sex- and age-specific strategies that acknowledge the differential use of screen-based activities across sex and age. Future research should continue to identify underlying correlates linking screen-based activities with health behaviors to inform strategies to reduce screen-time in Mexican children.
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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 | 0.000 | 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 | 0.000 | 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".