Television viewing and food intake during television viewing in normal-weight, overweight and obese 9- to 11-year-old Canadian children: a cross-sectional analysis
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
It is unclear if children of different weight status differ in their nutritional habits while watching television. The objective of the present paper was to determine if children who are overweight or obese differ in their frequency of consumption of six food items while watching television compared with their normal-weight counterparts. A cross-sectional study of 550 children (57·1 % female; mean age = 10 years) from Ottawa, Canada was conducted. Children's weight status was categorised using the Centers for Disease Control and Prevention cut-points. Questionnaires were used to determine the number of hours of television watching per day and the frequency of consumption of six types of foods while watching television. Overweight/obese children watched more television per day than normal-weight children (3·3 v. 2·7 h, respectively; P = 0·001). Obese children consumed fast food and fruits/vegetables more frequently while watching television than normal-weight or overweight children (P < 0·05). Children who watched more than 4 h of television per d had higher odds (OR 3·21; 95% CI 1·14, 9·03; P = 0·03) of being obese, independent of several covariates, but not independent of moderate-to-vigorous physical activity. The finding that both television watching and the frequency of consumption of some food items during television watching are higher in children who are obese is concerning. While the nature of the present study does not allow for the determination of causal pathways, future research should investigate these weight-status differences to identify potential areas of intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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