Contributing factors for low consumption of animal food among children aged 6-23 months in alive and thrive intervention areas of Bangladesh
Notice bibliographique
Résumé
Introduction: In Bangladesh about two-thirds of total food consumption is rice as \nmain staple food, especially for the poor, in addition to some vegetables, pulses and \nsmall quantities of fish, meat, egg, etc. if and when available. The similar dietary \npattern and practices were found for under-two children in the intervention areas of \nAlive and Thrive (A& T) project where mothers were counseled on appropriate \ncomplementary feeding practice as a component of Infant and Young Child Feeding \n(IYCF). BRAG-RED intended to explore these issues to recognize the gaps that might \nbe addressed to increase the consumption of protein from animal foods among the \nchildren through the IYCF interventions in A& T areas. \nObjective: This study aims to identify the barriers leading to low consumption of \nanimal foods by children aged 6-23 months in A & T intervention areas; and to assess \ntheir knowledge and practices of dietary intake through 24-hour recall. \nMethods: Mixed methods were chosen to find comprehensive information in 12 \nupazi/as, 3 from each of Barguna, Sylhet, Chittagong and Dinajpur districts. The Pusti \nKormi (PK), Shasthya Shebika (SS), and mothers/caregivers enrolled in the A& T \nintervention areas were selected for interview; and those who had involvement in \nproviding the services. In addition, other programme staff from the supervisory level \nwho involved in providing services was also interviewed. \nFindings: The study revealed from the quantitative findings that, in intervention areas \nintake from animal sources was 7 -12g at 1 years and 18g at 2 years where the \nrecommended dietary average (RDA) was 14g for less than one years and 16g for \nless than 2 years. On the other hand in control areas at both age groups the intake \nratio was lower. From the qualitative findings majors contributing factors for feeding \nfrom animal sources was, lack of knowledge, lack of awareness on protein deficiency, \nbarriers from the family members, myth, etc. Almost similar barriers was found from \nthe quantitative findings like; financial crisis (80.3%), mothers lack of knowledge and \nawareness (67%), unavailability of the products in near local market (5%), etc. \nConclusion: Food consumption from animal sources might be increased among less \nthan two years children by reducing those barriers, by strengthening efforts in the \nawareness development process in creating demand for appropriate IYCF services at \nhousehold level especially intake foods from animal sources to improve children's \nnutritional status.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».