Food Insecurity Is Not Related to Cognitive Function in School-Aged Children in Querétaro, Mexico
Notice bibliographique
Résumé
To evaluate the relationship between household food insecurity and food insecurity of the mothers during her childhood with cognitive function in school children in Querétaro. A total of 153 children (6–10 y) of public elementary schools in the municipality of Querétaro participated in a cross-sectional study. Household food insecurity was measured using the ELCSA (Latin American and Caribbean Food Security Scale) and a validated questionnaire to measure food insecurity of the mother during her childhood. Anthropometric measurements (weight, height, waist circumference) were taken by standardized personnel and the WISC IV scale adapted to children for the determination of cognitive function was applied by trained psychologists. Statistical ANOVA tests were used to determine mean differences in cognitive function between children with and without food insecurity. A logistic regression was also calculated to determine the odds of having low cognitive function in the presence of food insecurity, both at the household level and of the mother during her childhood. All analyses were adjusted for maternal level of education as a confounder. The children had a combined prevalence of overweight and obesity of 39.9%. A total of 54.3% of the households had food insecurity and 80.4% of the mothers had food insecurity in their childhood. The prevalence of the average score of the Total Intelligence Quotient (TIQ) of the children was 52.3%, and 38.2% had TIQ below average. Children living in households with food insecurity and with mothers that had food insecurity in their past had lower TIQ (89.08 ± 8.23, and, 91.87 ± 11.18, respectively) compared with children in food secure households (95.39 ± 12.20) and with mothers that had food security in their childhood (96.87 ± 12.03). However, after adjusting for maternal level of education, no relationship was observed between food insecurity and TIQ. Similarly, the adjusted logistic regression model showed no relationship between food insecurity in the household and mother's food insecurity in the past with TIQ. In the present study, food insecurity was not related to cognitive function of school-aged children in Querétaro, Mexico. Partially funded by CONACYT.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| 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 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,001 |
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 ».