Diet quality, physical activity, body weight and health-related quality of life among grade 5 students in Canada
Bibliographic record
Abstract
OBJECTIVE: To assess how diet quality, physical activity and body weight are related to health-related quality of life (HRQOL) among children in the Canadian province of Alberta. DESIGN: In 2008, we surveyed 3421 grade 5 students and their parents from 148 randomly selected schools. Students completed the Harvard Food Frequency Questionnaire, questions on physical activities, and had their height and weight measured. The HRQOL of the students was assessed using the EQ-5D-Y. Parents completed questions on socio-economic background and children's lifestyle. We applied multilevel regression methods to examine the importance of children's diet quality, physical activity and weight status for the EQ-5D-Y Visual Analogue Scale and for the EQ-5D-Y dimensions. SETTING: The province of Alberta, Canada. SUBJECTS: Grade 5 students. RESULTS: Students with better diet quality, higher physical activity levels and normal body weights were statistically significantly more likely to report better HRQOL than students who ate less healthily, were less active or were overweight or obese. CONCLUSIONS: The importance of diet quality, physical activity and body weight status for HRQOL may help justify broader implementation of school health programmes that promote healthy eating and active living, as these programmes will help reduce the burden of childhood obesity and improve quality of life.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".