Exploring reasons for high levels of food insecurity and low fruit and vegetable consumption among university students post-COVID-19
Notice bibliographique
Résumé
High rates of food insecurity and low consumption of fruit and vegetables among university students have been observed prior to the COVID-19 pandemic and intensified during the pandemic. This study aimed to investigate food insecurity among university students and its associations with sociodemographic factors, fruit and vegetable consumption behaviours, and preferred campus programs to address these issues. A convenience sample of 237 Australian university students completed a cross-sectional online survey from October to December 2022. Food insecurity was assessed using the 10-item US Adult Food Security Module, applying the Canadian classification scheme. Sociodemographic variables, fruit and vegetable consumption behaviours, and perceptions of fruit and vegetable access and their affordability were included in the survey. Students were also asked to select the most suitable program(s) and provide reasons for their choice using open-ended questions. Approximately half of respondents (46.4%) were identified as food insecure. The proportion of students meeting the recommended intake of vegetables as specified in the Australian Dietary Guidelines was very low (5.1%) compared with fruit (46.2%). Low fruit consumption was significantly associated with food insecurity (OR = 1.81; 95%CI 1.03, 3.18, p = 0.038). Factors such as the perceived lower accessibility and higher price of fruit and vegetables were significantly associated with higher odds of food insecurity. In terms of potential programs, a free fruit and vegetable campaign was the most popular program, with affordability and physical access being the most frequently cited reasons. These findings suggest that food insecurity is associated with low fruit and vegetable consumption in university students. Therefore, transforming campus food environments and developing food policies at the university level must be considered to address food and nutrition security in university students.
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 | 0,000 |
| 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 | 0,001 | 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 ».