An updated analysis of trans fatty acids in Canadian packaged foods
Bibliographic record
Abstract
The Canadian food industry has voluntarily reduced the trans fatty acid (TFA) content of foods, however there are no updated analyses of TFA levels in Canadian foods. This study assessed TFA levels in Canadian packaged foods in 2013, compared to historical data. Data from Health Canada's Trans Fat Monitoring Program (TFMP, n=541 in 2006‐09) and the University of Toronto Food Label Information Program (n=1999 in 2010; n=2542 in 2013) were used. In 2013, 97% of foods met the TFA limits, increased from 95% in 2010 and 78% during the TFMP. The proportion of products meeting the TFA limits was below the overall average for lard (0%), coffee whiteners (67%), brownies (88%), snack puddings (92%) and garlic bread (94%). Among food categories with >10% of products exceeding TFA limits in 2010, there were few significant increases in the proportion of foods meeting TFA limits in 2013 compared to 2010, including dairy free cheeses (0% to 83% meeting, p=0.002) and cakes with pudding/mousse (77% to 97%, p=0.046). When assessing TFA as a percent total fat, Mexican kits was the only category with a significant increase in mean TFA as a percent total fat (7.6±1.8% to 20.3±5.9%). Categories exceeding 20% TFA as a percentage of total fat were coffee whiteners (55.6±16.7%), frosting (23.1±9.7%), lard and shortening (22.0±17.8%), margarine (20.5±14.4%) and popcorn (37.5%). There has been an overall improvement in the proportion of packaged food products that meet the recommended TFA limits and the majority of food categories did not have increased levels of TFA. However, several categories continue to have an unacceptably high proportion of foods exceeding TFA limits, suggesting that action by the food industry and/or government is still required to ensure maximal health benefits for 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".