Accuracy of Canadian Food Labels for Sodium Content of Food
Bibliographic record
Abstract
The accuracy of the Nutrition Facts table (NFt) has a significant impact on Canadian efforts to reduce dietary sodium and monitor sodium content in foods. This study assessed the accuracy of sodium (and calories, trans fat, saturated fat, sugar) reported on the NFt for selected foods and beverages in Canada. The Canadian Food Inspection Agency (CFIA) sampled over 1000 foods and beverages from supermarkets, bakeries, and restaurants across Canada between January 2006 and December 2010. The samples were analyzed in CFIA laboratories. Results were requested for products with ≥1 of the following nutrients tested: sodium, calories, saturated fat, trans fat, and sugar. Differences between the label and laboratory values were calculated for each product. Overall, 16.7% (n = 169) of products were "unsatisfactory" with laboratory values exceeding ±20% of the NFt value. Sodium had the highest number of unsatisfactory products (n = 49, 18.4%) and trans fat had the lowest number of unsatisfactory products (n = 16, 4.3%). The proportion of unsatisfactory products for saturated fat, calories, and sugar was 15.8%, 14.2%, and 12.9%, respectively. All of the unsatisfactory products had excess nutrient content relative to the NFt. Sodium and calories were consistently underreported (p < 0.05), while NFt values for the other nutrients were not statistically different than laboratory values. Increased monitoring of NFt sodium values is recommended in order to increase consumer confidence in this nutrition tool, to encourage industry to accurately report nutrient content and to continue using the NFt to guide research, education, and policy development.
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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".