Children-and-Partner’s Food Preferences and Role of Woman as Caregiver: Key Elements of Food Choice Linked to Social Environment in a Consumer Population of Hermosillo City
Notice bibliographique
Résumé
The main objective was to identify determinants of food choice linked to the community food environment in a marginalized consumer population in the city of Hermosillo, Mexico. The specific objectives were to develop group interviews with women and to frame the data analysis within the field of research in food and nutrition security. In this qualitative study design, we employed the focus group technique to ask participants “How do you decide which foods to obtain for your family's diet?”. To investigate further we asked, “What are those reasons that explain the selection of those foods?” Women who regularly attended a community center localized in a neighborhood with a very high grade of urban marginalization participated in the focus groups. Interviews were transcribed verbatim and three distinct methods were used to perform analysis: (1) content analysis (2) data organization, using software QSR NVivo, in relation to five dimensions of food and nutrition security: affordability, accessibility, acceptability, food quality, and care; and (3) triangulation between five co-authors (A.C.N., P.B.C., A.D.C.P., G.E.P.A., and M.I.O.V.). From May to November of 2019, four focus groups were conducted by a single facilitator in two community centers of Hermosillo (n = 27 participants). Reasons that explained the participant's food choices within the community food environment and that showed the highest number of mentions in the interviews were identified in relation to acceptability factors: children's food preferences, partner's food preferences, all household-members’ food preferences. The following extract reflects the main study findings: “When I can't do a certain thing it is because it's very expensive, but if there is a way, even if it's a little… for example, my middle-aged son really likes peppers and he eats them alone. So, I know that when I go to the store, I have to bring at least one, for him to eat other things.” The study of food choice in this group of women denotes that their role as caregiver of food and nutrition in relation to their children-and-partner's food preferences are key elements of food decision-making processes, preceding the socioeconomic factors and constraints, they certainly face. Institutional small grant C.I.A.D., A.C.
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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 ».