Score evaluation for the consumption of ultra-processed foods in children and its relationship with cardiometabolic risk
Notice bibliographique
Résumé
Ultra-processed foods (UPF) are industrial formulations nutritionally unbalanced and highly palatable. The high consumption of UPF is associated with development of metabolic alterations in children. However, considering that there is a diversity of UPF frequently consumed by children, it is necessary to evaluate a score specific for these foods, identifying their subgroups and their relationship with cardiometabolic risk. This study aimed to evaluate the score of ultra-processed food consumption in children and its relationship with cardiometabolic risk. Firstly, it was conducted a systematic review with the longitudinal evidence on the association between consumption of UPF and cardiometabolic risk. Data extraction of this systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study quality and risk of bias were assessed with the Newcastle-Ottawa Scale. Scopus, Science direct, Scielo, PubMed, and Google scholar databases were searched without any restriction on publication dates. Ten longitudinal studies were selected for this review, being four conducted with children and six with adults. The findings showed a positive association between the high consumption of UPF and cardiometabolic risk a long term, independent of the age (PROSPERO registration no: CRD42022327714). For the original investigation, it was carried out a cross-sectional study with 378 children aged 8 and 9 years attending in all urban public and private schools in Viçosa, Minas Gerais Brazil. A semi-structured questionnaire was applied to obtain sociodemographic and lifestyle information. The cardiometabolic risk was evaluated according to total and android body fat, lipid profile, blood pressure, uric acid, fasting glucose, and HOMA-IR. From the application of three 24-hour recalls, a score of UPF consumption was created with 24 items. From this list, three subgroups of UPF were obtained: "sugary foods and beverages", "fatty foods" and "salty foods and processed meats". Multivariate linear regression models were used to assess the association of the UPF score and its subgroups with cardiometabolic risk markers. The “sugary foods and beverages” score was positively associated with LDL-c and uric acid. Every 1 SDof "sugary foods and beverages” score was associated to 3.1 (95%CI: 0.8, 5.3) and 0.1 (95%CI: 0.1, 0.2) units higher in LDL-c and uric acid, respectively. The “salty foods and meat products” score was positively associated with total cholesterol and LDL-c. Every 1 SD of “salty foods and meat products” score was associated to 3.0 (95%CI: 0.2, 5.8) and 3.3 (95%CI: 1.0, 5.6) units higher in total cholesterol and LDL-c, respectively. Finally, UPF score was positively associated with LDL-c. Every 1 SD of UPF score was associated to 2.8 (95%CI: 0.6, 4.9) units higher in LDL-c. In conclusion of both investigations, it is important to implement effective strategies in the public health to prevent the excessive consumption of UPF and protect their effect in the long- term health, independent of age. In addition, the use of the score for the UPF consumption in childhood can be an easy and quick method to identify unhealthy eating habits and evaluate their associations (at whole and subgroups) with cardiometabolic risk at early age. Keywords: Eating. Cardiometabolic risk factors. Nutritional epidemiology.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,013 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,009 |
| Bibliométrie | 0,008 | 0,008 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».