Reformulation of sugar contents in Canadian prepackaged foods and beverages between 2013 and 2017 and resultant changes in nutritional composition of products with sugar reductions
Bibliographic record
Abstract
OBJECTIVE: To quantify total sugar reformulation in Canadian prepackaged foods and beverages between 2013 and 2017 and identify changes in the nutritional composition of the foods and beverages reformulated to be lower in total sugar. DESIGN: Longitudinal examination of foods and beverages present in both 2013 and 2017 collections of the University of Toronto's Food Label Information Program database (n 6628 matched products). The proportion of products with changes in sugar levels was determined. Wilcoxon signed-rank test was used to examine changes in sugar levels overall for products lower or higher in sugar and changes in nutrient composition for products lower in sugar. SETTING: Largest grocery retailers by market share in Canada. PARTICIPANTS: Canadian prepackaged foods and beverages. RESULTS: The majority (76·6 %) of products had no change in total sugar content, 12·4 % were reformulated to be lower in sugar and 11·0 % were higher in sugar. A median sugar reduction of 19·0 % (1·6 g) was seen among products lower in sugar which was offset by a median 18·0 % (1·5 g) increase among products higher in sugar. Overall, median levels of energies and other nutrients stayed the same or decreased among products reformulated to be lower in sugar, the exception was for starch, which increased. CONCLUSIONS: Limited progress was made to reformulate foods and beverages to be lower in total sugar between 2013 and 2017. Results from this study identify areas in the food supply where attention may be needed to avoid unintended consequences of sugar-focused reformulation in terms of overall nutritional composition.
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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 | 0.000 | 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".