Evaluation of Methods to Assess Children's Diets in the School Context: A Systematic Review
Notice bibliographique
Résumé
Background & Objectives Schools are a proposed site for public health action to improve children's diet quality, but valid and reliable methods are needed to evaluate what children eat at school and the impact of emerging school‐based nutrition interventions. The objective of this study was to systematically review dietary assessment instruments and dietary measures developed and/or applied to assess the quality of foods and beverages consumed in the school context. Methods A systematic review of the literature was conducted using the PRISMA (Preferred Reporting Items for Systematic reviews and Meta‐Analyses) statement. Three health databases (MEDLINE, CINAHL and PubMed) were searched for full‐text English‐language publications that developed or applied: 1) dietary assessment instruments to collect dietary data in the school context and/or 2) included at least one dietary intake measure evaluating the quality of intake of foods consumed in the school context. Papers were reviewed if they described a method applicable to school‐age children (6–17 years). Evidence synthesis A total of 45 studies met the inclusion criteria. Dietary instruments : 27 studies described self‐report instruments (e.g. 24‐hour recalls, food records, food frequency questionnaires) and 18 described observational dietary instruments (e.g. visual estimation techniques) to evaluate dietary intake in school settings. Each instrument offers trade‐offs between level of detail, accuracy, ease of administration, and costs. Such characteristics affect the type of measurement error which holds implications for assessing diet quality at the population‐level. Dietary outcomes : 36 studies described dietary outcomes for foods and beverage intake in the school context. The majority of studies (n=26) used multiple food groups and/or nutrient intakes to evaluate diet quality at school, but some (n=6) used a single food group as a proxy for overall diet quality. Only one a priori composite diet quality index assessed quality of lunch‐time intakes: the Meal Index of Dietary Quality (Denmark). In addition, one study used the U.S. Healthy Eating Index (HEI)‐2005 to evaluate diet quality during school hours to examine temporal variations in diet quality based on children's participation in the U.S. National School Meal Program. Originally developed to assess diet quality based on a whole day, the U.S. HEI uses scoring standards expressed as amounts per 1,000 kcal consumed. As such, it can be potentially applied to a portion of the school day. Conclusions Assessing dietary quality is methodologically difficult, both from the perspective of data collection and data analysis. The choice of method depends on the goal of the study and resources available. No analytical method has been developed to specifically assess the quality of foods and beverage consumed by children in the North American school context. However, the U.S. HEI appears to have potential in this regard. Such methods could have many meaningful applications for planning and designing tailored nutrition interventions and assessing the impacts of school‐based nutrition interventions. Support or Funding Information Canadian Institute for Health Research (CIHR) Food Practices on School Days Study; Leonard S Klinck Memorial Fellowship; Land and Food System Graduate Student Awards
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 | 0,065 | 0,188 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,014 | 0,015 |
| Bibliométrie | 0,019 | 0,017 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».