The importance of eating patterns for health-related quality of life among children aged 10–11 years in Alberta of Canada
Bibliographic record
Abstract
Children with unhealthy eating behaviours are more likely to experience poor physical and mental health. Few studies have investigated the importance of eating patterns for health-related quality of life (HRQoL) among children. This study aimed to identify common eating patterns, and their associations with HRQoL among Canadian children. Data were collected from 9150 grade five students (aged 10-11 years) in repeat cross-sectional population-based surveys in Alberta, Canada. Students' eating behaviours were analyzed using latent class analysis to identify the eating patterns. We applied multilevel multivariable logistic regression to examine the association of the eating patterns with HRQoL. We identified three groups of children with distinct eating patterns: eating healthy (52%), less healthy (31%) and unhealthy (17%). The first group had a higher proportion of students engaged in healthy eating behaviours. The unhealthy pattern group (third group) included a higher proportion of students with poor eating behaviours. Students' eating behaviours in the second group were healthier than the third group but less healthy than the first group. Children with unhealthy and less healthy patterns were more likely to experience lower HRQoL than children with the healthy pattern. Health promotion programs effective in improving healthy eating patterns may not only reduce the risk for chronic diseases in the long term, but also improve the HRQoL in the short term.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 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".