Added sugar in the packaged foods and beverages available at a major Canadian retailer in 2015: a descriptive analysis
Bibliographic record
Abstract
Background: Excess consumption of added sugars has been associated with a variety of health problems, but there is little information available characterizing added sugar in the Canadian food supply. This study examined the presence and types of added sugars in the packaged food and beverage products available at a major Canadian grocery retailer. Methods: We searched the ingredients lists of over 40 000 packaged food products available for sale in March 2015 for a variety of added sugar terms. Proportions of food products containing added sugar were identified overall and within food product categories. Differences in total sugar content were identified between food products with and without added sugar. Results: Overall, 66% of the packaged food products analyzed contained at least 1 added sugar. The added sugar term "sugar" (and its variations) appeared the most frequently, followed by "dextrose." Added sugar presence and total sugar content varied within many product categories but were consistently higher in expected categories such as "beverages." Mean total sugar content was significantly higher in products with added sugar than in those without, both overall (p < 0.001) and within most product subcategories (p < 0.02). Interpretation: About two-thirds of the packaged foods and beverages available at a major Canadian grocery retailer contain added sugar, similar to recent patterns estimated for the US food supply. The results provide an estimation of the baseline characterization of added sugar in the Canadian food supply, which can be used to assess outcomes of future changes to sugar labelling policies in Canada.
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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 | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".