The Health Canada Surveillance Tool could be an effective method for assessing alignment with 2019 Canada's Food Guide
Notice bibliographique
Résumé
Abstract The Health Canada Surveillance Tool (HCST), a Canadian nutrient profile (NP) model, assesses products’ adherence to the 2007 Canada's Food Guide (CFG), using thresholds for total fat, saturated fat, sugars and sodium. In 2019, new dietary guidelines were published (i.e., CFG 2019); however; the HCST has not been updated to reflect changes implemented in this new guide. Given suggestions to adapt previously validated NP models rather than create new models, this research aimed to assess whether the HCST could be a useful tool to assess alignment with updated dietary guidance. Specifically, the objective of this study was to test the agreement between products’ alignment with the CFG 2007 (as per the HCST) and products’ alignment with the recently released CFG 2019 guidelines. This study analyzed data from the University of Toronto Food Label Information Program (FLIP) 2017 database. FLIP contains label and nutrition information for prepackaged food products from top Canadian grocery retailers. Products were categorized into Tiers based on HCST thresholds: Tiers 1 and 2 were considered “in line” with dietary guidance, while Tiers 3, 4 and “Other” (i.e. foods not addressed by CFG) were considered “not in line”. Two raters independently classified foods according to their alignment to CFG 2019. Proportions of products that were considered “in line” with CFG 2007 and 2019 were calculated. Overall agreement between alignment with CFG 2007 and 2019 was determined by cross-classifications of the proportion of products considered “in line” or “not in line” with both CFG versions. Cohen's Kappa (κ) statistic tested the level of agreement (Interpretation of κ: 0.01–0.20, “slight”; 0.21–0.40, “fair”; 0.41–0.60, “moderate”; 0.61–0.80, “substantial”; and 0.81–0.99, “almost perfect”). Analyses were conducted overall and by Health Canada's Table of Reference Amounts for Food category. In total, n = 16,973 products were analyzed, with 98% inter-rater reliability for CFG 2019 alignment. Overall, 30.2% and 28.2% of products were “in line” with CFG 2007 and 2019, respectively, with 80.4% overall agreement and “moderate” kappa agreement (κ [95% CI]: 0.49 [0.46, 0.49]). Overall agreement in individual food categories ranged from 100% (Dessert Toppings, Sauces, Sugars and Sweets; κ: N/A) to 54.8% (Eggs, κ: 0.21 [-0.01, 0.4]). From these results, the HCST appears to be an effective NP model for assessing alignment with CFG 2019. Further analysis could elucidate specific areas for adaptation of the HCST to optimize its functionality in this context.
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 | 0,001 | 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 | 0,000 | 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 ».