Examining changes in the sodium content of Canadian prepackaged foods: 2013 to 2017
Bibliographic record
Abstract
In an effort to improve high sodium consumption in the population, in 2012 Health Canada released voluntary sodium reduction targets for prepackaged foods to be met before 2017. This study used the University of Toronto’s Food Label Information Program database (FLIP), 2013 and 2017 collections, to evaluate changes and differences in mean sodium content of Canadian prepackaged foods and manufacturers’ progress in meeting Health Canada’s average and maximum sodium reduction targets. Changes to sodium content (reformulation) in products present in both FLIP years and differences across years including both new and existing products were assessed via paired and independent t-tests, respectively. The average sodium content from FLIP 2017 was also compared to previously published sales-weighted average sodium content published by Health Canada to aid in the interpretation of our results. Our reformulation analyses of consistent products between years revealed that 50% of food subcategories did not have significant changes in mean sodium from 2013 to 2017. Examining both new and existing foods, 59% of subcategories had no significant difference in mean sodium content between 2013 and 2017. The proportion of foods meeting final sodium targets was 33.6% in 2013 and 37.3% in 2017. In 2013 and 2017, 20.8% and 19.6% of products exceeded the maximum sodium targets, respectively. For almost all major food categories, a greater proportion of new products in 2017 met final sodium targets compared to existing foods (present in both FLIP 2013 and 2017). Nearly, half the major food categories examined had more new products meeting the maximum sodium target than existing products. Less than half of food subcategories (48%, n = 45/94) from FLIP 2017 differed by ≥20% compared to sales-weighted averages published by Health Canada. Our findings reveal limited progress in the reduction of sodium in prepackaged foods. Calls for more robust policy initiatives and the continued independent monitoring of food industry efforts in Canada are warranted.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".