Nutritional value of child-targeted food products: results from the Food Quality Observatory
Bibliographic record
Abstract
OBJECTIVE: To characterise the nutritional quality of food products targeted to children, we aimed: (1) to determine if the nutritional composition of child-targeted food products is different from those for the general population and (2) to verify differences in the nutrient content of child-targeted food products between three selected food categories. DESIGN: The present study is part of the work conducted by the Food Quality Observatory, created in 2016 in the province of Quebec (Canada). Ready-to-eat (RTE) breakfast cereals (n 331), granola bars (n 310) and yoghurts and dairy desserts (n 380) were the food categories analysed. SETTING: Nutritional values and all packaging information were obtained by purchasing every product available in supermarkets, grocery stores and specialty grocery stores. Free sugars were manually differentiated from total sugars for each product. Products were classified according to two targeted consumer groups: children or general population. RESULTS: The nutrient profile of RTE breakfast cereals, granola bars and yoghurts and dairy desserts targeted to children differed from that of products intended at the general population. Child-targeted RTE breakfast cereals had the least favourable nutritional composition, with significantly higher content of carbohydrates, total sugars, free sugars and Na compared with breakfast cereals for the general population as well as child-targeted granola bars and yoghurts and dairy desserts. All child-targeted products analysed contained free sugars. CONCLUSIONS: The current study supports the relevance to further regulate marketing to children on food product packages to ensure that such marketing is not present on food products with poor nutritional quality.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".