Assessing nutrition and other claims on food labels: a repeated cross-sectional analysis of the Canadian food supply
Notice bibliographique
Résumé
In 2010, nutrition claims were investigated in Canadian foods; however, many nutrition and other claims have been introduced since then. This study aimed to determine: i) the proportion of foods carrying claims in 2013, ii) the types and prevalence of nutrition claims (nutrient content claims, health claims, general health claims) and other claims displayed on labels in 2013, iii) and trends in use of nutrition claims between 2010 and 2013. Repeated cross-sectional analysis of the University of Toronto Food Label Information Program (FLIP) of Canadian foods (2010/11 n = 10,487; 2013 n = 15,342). Regulated nutrition claims (nutrient content, health claims) were classified according to Canadian regulations. A decision tree was used to classify non-regulated general health claims (e.g., front-of-pack claims). Other claims (e.g., gluten-free) were also collected. Proportions of claims in 2013 were determined and χ 2 was used to test significant differences for different types of claims between 2010 and 2013. Overall, 49% of products in 2013 displayed any type of claim and 46% of foods in FLIP 2013 carried a nutrition claim (nutrient content claim, health claim, general health claim). Meal replacements and fruits/fruits juices were the categories with the largest proportion of foods with claims. At least one approved nutrient content claim was carried on 42.9% of products compared to 45.5% in 2010 ( p < 0.001). Health claims, specifically disease risk reduction claims, were slightly lower in 2013 (1.5%) compared to 1.7% in 2010 ( p = 0.225). General health claims, specifically front-of-pack claims, were carried on 20% of foods compared to 18.9% in 2010 ( p = 0.020). Other claims, specifically gluten-free, were present on 7.3% of foods. Nutrition and other claims were used on half of Canadian prepackaged foods in 2013. Many claims guidelines and regulations have been released since 2010; however, little impact has been seen in the prevalence of such claims in the food supply. Claims related to nutrients of public health priority, such as sugars and sodium, were not commonly used on food labels. Monitoring trends in the use of nutrition and other claims is essential to determine if their use on food labels reflects public health objectives, or instead are being used as marketing tools.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».