The nutritional content of children’s breakfast cereals: a cross-sectional analysis of New Zealand, Australia, the UK, Canada and the USA
Bibliographic record
Abstract
OBJECTIVE: To compare the Nutrition Information Panel (NIP) content, serving size and package size of children's ready-to-eat breakfast cereals (RTEC) available in five different Western countries. DESIGN: NIP label information was collected from RTEC available for purchase in major supermarket chains. Kruskal-Wallis, Mann-Whitney U and χ2 tests were applied to detect differences between countries on manufacturer-declared serving size, total energy (kJ), total protein, fat, saturated fat, carbohydrate, total sugar, Na and fibre content. The Nutrient Profiling Scoring Criterion (NPSC) was used to evaluate the number of products deemed to be 'unhealthy'. SETTING: Supermarkets in Australia, Canada, New Zealand, the UK and the USA. PARTICIPANTS: Children's breakfast cereals (n 636), including those with and without promotional characters. RESULTS: The majority of children's RTEC contained substantial levels of total sugar and differences were apparent between countries. Median sugar content per serving was higher in US cereals than all other countries (10·0 v. 7·7-9·1 g; P < 0·0001). Median fat and saturated fat content were lowest in Australia and New Zealand RTEC, while the Na content of RTEC was 60-120 % higher in the USA and Canada than in Australia and the UK (all P ≤ 0·01). CONCLUSIONS: Across all countries, there was a high proportion of RTEC marketed for children that had an unhealthy nutrient profile. Strategies and policies are needed to improve the nutrient value of RTEC for children, so they provide a breakfast food that meets nutrition guidelines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".