Nutrient intakes and top food categories contributing to intakes of energy and nutrients-of-concern consumed by Canadian adults that would require a ‘high-in’ front-of-pack symbol according to Canadian labelling regulations
Bibliographic record
Abstract
Canada recently mandated front-of-pack (FOP) labelling regulations, where foods meeting and/or exceeding recommended thresholds for nutrients-of-concern (i.e., saturated fat, sodium, and sugars) must display a 'high-in' FOP nutrition symbol. However, there is limited research on the amounts and sources of foods consumed by Canadians that would require a FOP symbol. The objective was to examine the intakes of nutrients-of-concern from foods that would display a FOP symbol and to identify the top food categories contributing to intakes for each nutrient-of-concern. Using the first day 24-hour dietary recall from the nationally representative 2015 Canadian Community Health Survey-Nutrition (CCHS), Canadian adults' intakes of nutrients-of-concern from foods that would display a FOP symbol was examined. Foods were assigned to 1 of 62 categories to identify the top food categories contributing to intakes of energy and nutrient-of-concern that would display a FOP symbol for each nutrient-of-concern. Canadian adults (n = 13,495) consumed approximately 24% of total calories from foods that would display a FOP symbol. Foods that would display a FOP symbol for exceeding thresholds for nutrients-of-concern accounted for 16% of saturated fat, 30% of sodium, 25% of total sugar, and 39% of free sugar intakes among Canadian adults. The top food category contributing intakes of each nutrient-of-concern that would display a FOP symbol were nutrient-specific: Processed meat and meat substitutes for saturated fat; Breads for sodium; and Fruit juices & drinks for total and free sugars. Our findings show that Canadian FOP labelling regulations have the potential to influence the intakes of nutrients-of-concern for Canadian adults. Using the findings as baseline data, future studies are warranted to evaluate the impact of FOP labelling regulations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".