A comparison of the nutritional quality of products offered by the top packaged food and beverage companies in Canada
Bibliographic record
Abstract
BACKGROUND: Canada's food supply is abundant in less healthy products, increasing Canadians' risk of obesity and non-communicable diseases. Food companies strongly influence the food supply; however, no studies have examined differences in the healthfulness of products offered by various companies in Canada. This study aimed to compare the nutritional quality of products offered by the top packaged food and beverage companies in Canada. METHODS: Twenty-two top packaged food and beverage manufacturing companies were selected, representing > 50% of the Canadian market share in 2018. Nutritional information for products (n = 8277) was sourced from the University of Toronto Food Label Information Program 2017 database. Descriptive analyses examined the nutritional quality of products based on: 1) the Health Star Rating (HSR) system; 2) calories, sodium, saturated fat and total sugars per 100 g (or mL) and per reference amounts (RAs) defined by Health Canada; and 3) "high in" thresholds for sodium, saturated fat and total sugars proposed by Health Canada for pending front-of-package labelling regulations. Kruskal-Wallis tests compared HSRs of products between companies. RESULTS: Mean HSRs of companies' total product offerings ranged from 1.9 to 3.6 (out of 5.0). Differences in HSRs of products between companies were significant overall and for 19 of 22 food categories (P < 0.05), particularly for fats/oils and beverages. Calories, sodium, saturated fat and total sugars contents varied widely between companies for several food categories, and depending on whether they were examined per 100 g (or mL) or RA. Additionally, 66.4% of all products exceeded ≥1 of Health Canada's "high in" thresholds for sodium (31.7%), saturated fat (28.3%) and/or sugars (28.4%). The proportion of products offered by a company that exceeded at least one of these thresholds ranged from 38.5 to 97.5%. CONCLUSIONS: The nutritional quality of products offered by leading packaged food and beverage manufacturers in Canada differs significantly overall and by food category, with many products considered less healthy according to multiple nutrient profiling methods. Variation within food categories illustrates the need and potential for companies to improve the healthfulness of their products. Identifying companies that offer less healthy products compared with others in Canada may help prompt reformulation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".