Changes in Sodium Levels in Canadian Packaged Foods: 2010 to 2013
Bibliographic record
Abstract
In 2010, Canada implemented a population‐wide sodium reduction strategy that included sodium reduction benchmarks for packaged foods; however, no evaluation of this policy has been conducted. This study measured changes to sodium levels in packaged foods contributing the most sodium to the Canadian diet. A database containing the nutrition information on 25,883 Canadian packaged foods available on the market in 2010 and 2013 was used (presented as means ± SD, mg/100g). The greatest reductions were observed in condiments (1309 ± 790 to 1048 ± 620; 19.9% reduction, p=0.005), breakfast cereals (375 ± 246 to 301 ± 242; 19.7% reduction, p=0.001), canned vegetables and legumes (269 ± 156 to 217 ± 180; 19.3% reduction, p<0.001), plain chips (462 ± 196 to 376 ± 198; 18.6% reduction, p=0.004, canned condensed soup (291 ± 62 to 250 ± 57; 14.1% reduction, p=0.003), sausages and wieners (912 ± 219 to 814 ± 195; 10.7% reduction, p=0.012), fresh and frozen meat and poultry (535 ± 228 to 496 ± 323; 7.3% reduction, p=0.001), and shelf‐stable mixed dishes (330 ± 114 to 308 ± 111; 6.7% reduction, p=0.002). Only 2 categories had higher sodium levels: oriental sauces (1355 ± 1345 to 3783 ± 2443; 179.2% increase, p<0.001), oriental noodles (222 ± 110 to 258 ± 79; 16.2%, p=0.025). Overall, there was a slight increase in the proportion of foods that met at least one of the sodium benchmark targets, from 51.4% of products in 2010 to 55.7% in 2013. This data shows that some progress has been made in reducing the sodium content of packaged foods, but that continual action by the food industry is still required. Funding: Canadian Institutes of Health Research
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".