Assessment of dietary intake in children (6–48 months) and mothers (15–49 years) in different farming systems in Kenya using multiple pass 24-h recall
Notice bibliographique
Résumé
Background Inadequate food intake is the most common cause of malnutrition worldwide. There is paucity of knowledge on the influence of farming systems, a proxy for contextualizing community-based food networks, and sociocultural perspectives necessary for creating impactful nutritional programs and policies for young children from infancy to early childhood in Kenya and their mothers, especially in Kenya. This study sought to evaluate nutrient intakes of young children and their mothers from Pastoral, Agro-pastoral and Mixed farming system in Kenya. Methods Mothers and their children were recruited from households in Narok south as part of the Animal Health Innovation Study. One day multiple pass 24-h dietary recall was completed for a sample of infants 6–11 months, and toddlers aged 12–48 months (n = 161), and women of reproductive age (15–49 years) (n = 161) via face-to-face interviews with the primary caregiver. Nutrient intakes were estimated using CS Dietary Software and compared with the Adequate Intakes, Recommended Dietary Allowance and/or Estimated Average Requirement. Results The mean intake of key nutrients varied across farming systems. Children aged 6–11 months, met the Adequate Intake and Recommended Dietary Allowance levels for protein and Vitamin A. However, deficiencies were noted in thiamine, vitamin C, vitamin B6, selenium, and niacin across different farming systems, with insufficient Iron intake, particularly in pastoral and agro-pastoral systems (3 mg/d vs. 7 mg/d and 5 mg/d vs. 7 mg/d respectively. Folate intake was significantly lower in pastoral and mixed farming systems, with levels below the recommended 100 μg dfe/d. Calcium intake was sufficient across all farming systems, while phosphorus intake was consistently below the AI of 180 mg/d in children aged 12–48 months. In the mixed farming group, intake exceeded the Recommended Nutrient Intake for calcium, while phosphorus intake remained low across all age groups in agro-pastoral and mixed farming systems. Magnesium intake fell below AI levels in all groups (<65AI). Among women of reproductive age (15–49 years), the agro-pastoral group exhibited the highest carbohydrate intake, while the mixed farming group had the highest protein intake (51.07 ± 6.5). Women met vitamin A recommendations, with zinc, iron, and selenium intake felling below the Adequate Intake in all groups. Conclusion While certain nutrients such as protein and vitamin A intake were met in children and mothers, deficiencies were noted in crucial nutrients like iron and folate across various farming systems. These findings underscore the importance of considering local contextual factors when designing nutrition interventions. To address nutritional disparities and improve overall health outcomes and wellbeing for children and mothers in diverse agricultural settings in Kenya, it is important to prioritize an understanding sociocultural contexts and/or regional variations in designing and implementation of targeted interventions.
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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 | 0,000 | 0,001 |
| 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 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».