Household‐level correlates of children's physical activity levels in and across 12 countries
Bibliographic record
Abstract
OBJECTIVE: Household factors (electronic media equipment, play equipment, physical activity in the home, and social support) have been associated with childhood moderate- to vigorous-intensity physical activity (MVPA), but little is known about how these factors differ across diverse countries. The objective was to explore household correlates of objective MVPA in children from 12 countries. METHODS: Overall, 5,859 nine- to eleven-year-old children from 12 countries representing a range of human and socioeconomic development indicators wore an accelerometer for 7 days and parents reported on household factors. Multilevel general linear models explored associations among household factors and MVPA variables controlling for age, sex, and parental education. RESULTS: Across sites, children with at least one piece of bedroom electronic media had lower MVPA (∼4 min/day; P < 0.001) than those who did not. More frequent physical activity in the home and yard, ownership of more frequently used play equipment, and higher social support for physical activity were associated with more MVPA (all P < 0.001). The association between play equipment ownership and MVPA was inconsistent across countries (interaction P < 0.01). CONCLUSIONS: With the exception of play equipment ownership, modifiable household factors showed largely consistent and important associations with MVPA across high-, mid-, and low-income countries.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".