Consumption of non-nutritive sweeteners by pre-schoolers of the food and environment Chilean cohort (FECHIC) before the implementation of the Chilean food labelling and advertising law
Notice bibliographique
Résumé
BACKGROUND: Consumption of non-nutritive sweeteners (NNS) is becoming increasingly more frequent, particularly in the context of obesity prevention policies. The aim of this study was to describe the consumption of NNS in an ongoing cohort of pre-schoolers (4-6-year-old) before the implementation of the Chilean Food Labelling and Advertising Law, identify sociodemographic and anthropometric characteristics associated with their consumption, and describe the main dietary sources of each NNS sub-type. METHODS: In 959 low-medium income pre-schoolers from the Food and Environment Chilean Cohort (FECHIC), dietary data from a single 24-h recall was linked to NNS content information obtained from packaged foods (n = 12,233). The prevalence of NNS consumption was estimated by food source and characterized by child and maternal sociodemographic and anthropometric variables. Intakes and main dietary sources were described for the six most prevalent NNS in Chile: Sodium Cyclamate, Saccharin, Aspartame, Acesulfame Potassium, Sucralose, and Steviol glycosides. RESULTS: Sixty-eight percent of the pre-schoolers consumed at least one source of NNS on the day of the dietary recall; most of them consumed NNS from foods and beverages (n = 532), while only 12% (n = 119) also consumed table-top sweeteners. The prevalence of NNS consumption was significantly higher among children whose mothers had a high educational level compared to children whose mothers did not complete high school (p < 0.05); however, it did not differ by any other variable studied. The highest intakes of NNS were observed for Aspartame [2.5 (1.4-3.7) mg/kg per consumer], followed by Sodium Cyclamate [1.6 (1.3-2.6) mg/kg per consumer] and Steviol glycosides [1.2 (0.2-2.1) mg/kg per consumer]. Beverages were the only food group that contributed to the intake of the six NNS studied, accounting for 22% of the overall intake of Saccharine and up to 99% of Aspartame intake. CONCLUSIONS: Before the implementation of the Food Labelling and Advertising Law, NNS consumption was highly prevalent among a cohort of low-middle income Chilean pre-schoolers. Continuous monitoring of NNS consumption is essential given potential food reformulation associated with the implementation of this set of obesity-prevention policies.
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 | 0,000 |
| 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 ».