Food and Beverage Marketing in Schools: A Review of the Evidence
Notice bibliographique
Résumé
Despite growing interest from government agencies, non-governmental organizations and school boards in restricting or regulating unhealthy food and beverage marketing to children, limited research has examined the emerging knowledge base regarding school-based food and beverage marketing in high-income countries. This review examined current approaches for measuring school food and beverage marketing practices, and evidence regarding the extent of exposure and hypothesized associations with children's diet-related outcomes. Five databases (MEDLINE, Web of Science, CINAHL, Embase, and PsycINFO) and six grey literature sources were searched for papers that explicitly examined school-based food and beverage marketing policies or practices. Twenty-seven papers, across four high-income countries including Canada (n = 2), Ireland (n = 1), Poland (n = 1) and United States (n = 23) were identified and reviewed. Results showed that three main methodological approaches have been used: direct observation, self-report surveys, and in-person/telephone interviews, but few studies reported on the validity or reliability of measures. Findings suggest that students in the U.S. are commonly exposed to a broad array of food and beverage marketing approaches including direct and indirect advertising, although the extent of exposure varies widely across studies. More pervasive marketing exposure was found among secondary or high schools compared with elementary/middle schools and among schools with lower compared with higher socio-economic status. Three of five studies examining diet-related outcomes found that exposure to school-based food and beverage marketing was associated with food purchasing or consumption, particularly for minimally nutritious items. There remains a need for a core set of standard and universal measures that are sufficiently rigorous and comprehensive to assess the totality of school food and beverage marketing practices that can be used to compare exposure between study contexts and over time. Future research should examine the validity of school food and beverage marketing assessments and the impacts of exposure (and emerging policies that reduce exposure) on children's purchasing and diet-related knowledge, attitudes and behaviors in school settings.
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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».