Trends in the use of gluten-free claims on Canadian food labels between 2013–2017 and assessment of their nutritional quality
Bibliographic record
Abstract
Abstract Gluten-free claims (GFC) on food labels are becoming popular despite the fact that 1% and 6% of the population have celiac disorder or gluten sensitivity, respectively. A previous Canadian study found that GFC were displayed on 8% of food labels; however, certain food categories (e.g., snacks, meat products) were among the ones carrying most GFC. This study aimed to assess trends in the use of GFC on Canadian food labels in top food categories carrying GFC from 2013 to 2017 and to determine the nutritional quality between products with and without GFC. This study was a repeated cross-sectional analysis of the University of Toronto Food Label Information Program 2013–2017. GFC were identified by systematically reviewing the photographs of food labels (n = 9,179) in seven food categories previously identified as carrying larger proportions of GFC: 1) desserts; 2) desserts toppings and fillings; 3) meat products; 4) nuts and seeds; 5) sauces and dips; 6) snacks; and 7) soups. GFC were coded as present, if a gluten-free declaration or symbol was made on package, otherwise products were coded as claim absent. Proportions of products displaying GFC were calculated overall and by food category. Mean contents of saturated fat (g per 100g/ml), sodium (mg per 100g/ml) and sugar (g per 100g/ml) were calculated for products with and without GFC. Chi-square and Mann-Whitney-Wilcoxon tested differences in proportions and mean contents of those nutrients between years. Results showed that among these categories, GFC have significantly increased from 11% in 2013 to 23% in 2017 (p < 0.001). At a category level, snacks had the greatest increase of GFC as their prevalence doubled (15% to 33%, p < 0.001), followed by nuts and seeds (12% to 27%, p < 0.001) and meat products (15% to 28%, p < 0.001), respectively for 2013 and 2017. The proportion of GFC in dessert toppings and fillings remained constant (16% in 2013 and 14% in 2017, p = 0.74). When the nutritional composition was examined, results were mixed: in dessert toppings and filling, meat products and, nuts and seeds, products with GFC had higher contents of saturated fat, sodium and sugar in comparison to their counterpart without claims, whereas the opposite was true for foods within desserts, sauces and dips, snacks, and soups categories (p < 0.001 for all nutrients, except for saturated fat in nuts and seeds). In conclusion, prevalence of GFC has doubled in the Canadian food supply; such claims are not indicative of better nutritional composition.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".