Benchmarking the transparency, comprehensiveness and specificity of population nutrition commitments of major food companies in Malaysia
Notice bibliographique
Résumé
BACKGROUND: The aim of this study was to assess the commitments of food companies in Malaysia to improving population nutrition using the Business Impact Assessment on population nutrition and obesity (BIA-Obesity) tool and process, and proposing recommendations for industry action in line with government priorities and international norms. METHODS: BIA-Obesity good practice indicators for food industry commitments across a range of domains (n = 6) were adapted to the Malaysian context. Euromonitor market share data was used to identify major food and non-alcoholic beverage manufacturers (n = 22), quick service restaurants (5), and retailers (6) for inclusion in the assessment. Evidence of commitments, including from national and international entities, were compiled from publicly available information for each company published between 2014 and 2017. Companies were invited to review their gathered evidence and provide further information wherever available. A qualified Expert Panel (≥5 members for each domain) assessed commitments and disclosures collected against the BIA-Obesity scoring criteria. Weighted scores across domains were added and the derived percentage was used to rank companies. A Review Panel, comprising of the Expert Panel and additional government officials (n = 13), then formulated recommendations. RESULTS: Of the 33 selected companies, 6 participating companies agreed to provide more information. The median overall BIA-Obesity score was 11% across food industry sectors with only 8/33 companies achieving a score of > 25%. Participating (p < 0.001) and global (p = 0.036) companies achieved significantly higher scores than non-participating, and national or regional companies, respectively. Corporate strategy related to population nutrition (median score of 28%) was the highest scoring domain, while product formulation, accessibility, and promotion domains scored the lowest (median scores < 10%). Recommendations included the establishment of clear targets for product formulation, and strong commitments to reduce the exposure of children to promotion of unhealthy foods. CONCLUSIONS: This is the first BIA-Obesity study to benchmark the population nutrition commitments of major food companies in Asia. Commitments of companies were generally vague and non-specific. In the absence of strong government regulation, an accountability framework, such as provided by the BIA-Obesity, is essential to monitor and benchmark company action to improve population nutrition.
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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 ».