Food and beverage marketing in primary and secondary schools in Canada
Notice bibliographique
Résumé
Background: Unhealthy food marketing is considered a contributor to childhood obesity. In Canada, food marketing in schools is mostly self-regulated by industry though it is sometimes restricted through provincial school policies. The purpose of this study was to document the type of food marketing activities occurring in Canadian schools and examine differences by school characteristics. Methods: An online survey was sent to public primary and secondary schools from 27 school boards in Ontario, British Columbia, and Nova Scotia and was completed by 154 Principals in spring 2016. This survey queried the type of food marketing occurring in schools including advertisements, food product displays, fundraising, exclusive marketing agreements, and incentive programs, among others. The occurrence of food marketing was described using frequencies, medians, and ranges. Chi-square and Fisher Exact tests were conducted to assess school-level differences in the frequency of marketing activities by school type (primary versus secondary), province (Ontario versus British Columbia), and the socio-economic status of most students (low versus middle/high income). The significance level was set at α < 0.05 for all tests. Results: Overall, 84% of schools reported at least one type of food marketing and the median number of distinct types of marketing per school was 1 (range 0–6). The most frequently reported forms of marketing were the sale of branded food, particularly chocolate, pizza, and other fast food, for fundraising (64% of schools); food advertisements on school property (26%), and participation in incentive programs (18%). Primary schools (n = 108) were more likely to report participating in incentive programs (25%) and selling branded food items (72%) compared to secondary schools (n = 46; 2 and 43% respectively; p < 0.01). Conversely, secondary schools were more likely to report food advertising on school property (56%), exclusive marketing arrangements with food companies (43%), and food product displays (19%) than primary schools (13, 5 and 2%, respectively; p < 0.01). Conclusion: The presence of food marketing in most participating schools suggests that the current patchwork of policies that restrict food marketing in Canadian schools is inadequate. Comprehensive restrictions should be mandated by government in both primary and secondary schools to protect children and youth from this marketing.
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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 | 0,000 | 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 ».