Screen time is associated with dietary intake in overweight Canadian children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To describe the relationship between screen time and dietary intake among children, and to examine this association in relation to body weight. METHODS: A cross-sectional analysis of 630 Canadian children aged 8-10 years with at least one obese biological parent. Measurements included body mass index (BMI), screen time (television, video game, computer), physical activity (accelerometer over 7 days), and diet (three 24-hour recalls for the calculation of the Canadian Healthy Eating Index (HEI-C)). Multivariate linear regression models were used to describe the relationship between screen time (≥ 2 h/d vs. < 2 h/d) and intake of nutrients and foods among healthy weight and overweight/obese children. RESULTS: The overall median [interquartile range] daily screen time was 2.2 [2.4] hours and 43% of children had a BMI of ≥ 85th percentile. Longer screen time above the recommendation (≥ 2 h/d) was associated with higher intake of energy (74 kcal, SE = 35), lower intake of fiber (- 0.6 g/1000 kcal, SE = 0.2) and vegetables & fruit (- 0.3 serving/1000 kcal, SE = 0.1) among all participants and with higher estimates in the overweight subgroup. An overall lower HEI-C (- 1.6, SE = 0.8) was also observed among children with screen time of ≥ 2 h/d. Among children of < 85th BMI percentile, longer screen time was associated with lower intake of vegetables & fruit (- 0.3 serving/1000 kcal, SE = 0.1) only. CONCLUSION: Screen time is associated with less desirable food choices, particularly in overweight children.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it