Mediating role of television time, diet patterns, physical activity and sleep duration in the association between television in the bedroom and adiposity in 10 year-old children
Bibliographic record
Abstract
BACKGROUND: Having a TV in the bedroom is associated with adiposity in children. It is not known how lifestyle behaviours (television viewing time, diet patterns, physical activity, and sleep duration) mediate this association. The objective of this study was to examine the mediating role of these lifestyle behaviours in the association between TV in the bedroom and percent body fat (% BF). METHODS: Cross-sectional data from 1 201 children (57.3% female; mean age = 9.8 years) from Ottawa, Canada and Baton Rouge, USA were examined. % BF was directly measured. Accelerometers were used to determine physical activity and sleep duration (24-h, 7-day protocol). Questionnaires were used to assess TV viewing time and healthy/unhealthy diet patterns (derived using factor analysis from food frequency questionnaire data). RESULTS: Canadian boys and girls with a TV in their bedroom had a higher % BF, watched more TV and had unhealthier diets. American boys and girls with a TV in their bedroom watched more TV, while boys had a higher % BF and a more unhealthy diet, and girls had less MVPA. In Canadian girls, TV viewing time mediated the association between having a TV in the bedroom and adiposity, independent of diet patterns, MVPA, and sleep duration. Other lifestyle mediators were not significant in Canadian boys or in US children. CONCLUSION: TV viewing is a mediating lifestyle behaviour in the association between TV in the bedroom and adiposity in Canadian girls. Future research is needed to identify lifestyle behaviours as intermediate mediators.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".