Independent and combined associations of total sedentary time and television viewing time with food intake patterns of 9- to 11-year-old Canadian children
Bibliographic record
Abstract
The relationships among sedentary time, television viewing time, and dietary patterns in children are not fully understood. The aim of this paper was to determine which of self-reported television viewing time or objectively measured sedentary time is a better correlate of the frequency of consumption of healthy and unhealthy foods. A cross-sectional study was conducted of 9- to 11-year-old children (n = 523; 57.1% female) from Ottawa, Ontario, Canada. Accelerometers were used to determine total sedentary time, and questionnaires were used to determine the number of hours of television watching and the frequency of consumption of foods per week. Television viewing was negatively associated with the frequency of consumption of fruits, vegetables, and green vegetables, and positively associated with the frequency of consumption of sweets, soft drinks, diet soft drinks, pastries, potato chips, French fries, fruit juices, ice cream, fried foods, and fast food. Except for diet soft drinks and fruit juices, these associations were independent of covariates, including sedentary time. Total sedentary time was negatively associated with the frequency of consumption of sports drinks, independent of covariates, including television viewing. In combined sedentary time and television viewing analyses, children watching >2 h of television per day consumed several unhealthy food items more frequently than did children watching ≤2 h of television, regardless of sedentary time. In conclusion, this paper provides evidence to suggest that television viewing time is more strongly associated with unhealthy dietary patterns than is total sedentary time. Future research should focus on reducing television viewing time, as a means of improving dietary patterns and potentially reducing childhood obesity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".