A comparison of the nutritional quality of kids’ versus adult meals from chain sit‐down restaurants (390.2)
Bibliographic record
Abstract
The objectives were to compare the nutritional quality of restaurant meals from regular (adult) menus in contrast to meals from kids’ menus, and to compare the nutritional quality of meals marketed as being “healthy kids’ meals” in contrast to “healthy adult meals”. Nutrition information was collected from Canadian chain restaurant websites in 2010. Nutrient levels (including calories, sodium, sugar, saturated fat, fiber, protein and trans fat) and Ofcom nutrient profile scores in 1630 adult meals and 248 kids’ meals from seven restaurant chains were analyzed. In addition, 46 “healthy kids’ meals” and 20 “healthy adult meals” were compared. On average, kids’ meals had a significantly lower nutritional quality in comparison to adult meals (p<0.01). However, the difference varied depending on the restaurant. “Healthy kids’ meals” had significantly higher amounts of calories, sugar, trans and saturated fat (both per serving and per 100g, p<0.05) when compared to “healthy adult meals”. Additionally, “healthy kids’ meals” had two‐times more saturated fat, almost three‐times more sugar and a significantly higher percentage of total energy coming from fat (33% [healthy kids’ meals] vs 25% [healthy adult meals]), saturated fat (11% vs 7%) and sugar (23% vs 11%). In conclusion, kids’ meals are often nutritionally worse than adult meals, and there is a gap between what is being marketed as a “healthy meal” for kids versus adults. Grant Funding Source : Supported By: Vanier Canada Graduate Scholarship, CIHR/HSF PICDP Fellowship, OGS, McHenry Grant
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".