Food Insecurity and it’s Predictors Among Vulnerable Children
Notice bibliographique
Résumé
Background: To determine the prevalence of food insecurity and some socio demographic predictors of food insecurity among Vulnerable Children (VC) in Jos, North- central Nigeria. Methods: A cross-sectional comparative study involving 202 VC selected using multi-stage sampling technique across two orphanages and three communities located in sub-urban areas in Jos East, Jos North and Jos South Local Government Area was carried out. A VC was defined as a child who has loss mother, father or both or children who reside with chronically ill parents or reside in institution during the study. Only VC greater than five years but less than 18 years were enrolled. Food security was measured using four questions that were adapted from existing questionnaires. Food insecurity was defined and graded has mild, moderate or high if there was an affirmative response to any one, two or three of four questions. Data generated were analyzed using EPI Info version 3.65 software. The independent variables orphan status, age, gender, place of residence, child level of education, child work, were compared with the dependent variables of food insecurity using bivariate and multivariate analysis. In all statistical test p < 0.05 was considered statistically significant. Results: Of the 202 VC analyzed 38.6 %(78) were girls and 61.4 %(124) were boys with a mean age of 12.7+ 2.6 years. One hundred and two (50.5%) were IVC while 100(49.5%) were HVC. The VC were mostly orphans (83.2% [168]) while 16.8 %(34) were non orphans. All children were enrolled into school, 137 were in primary school, while the rest were in secondary school. Majority of the HVC were cared for by their mother (24.8% 50[VC]), father (1.9% [4]), uncles (8.4% [17]), aunts (10% [5.0]), grandparents (5.4% [11]), and non relatives (8% [4.0]). The overall prevalence of food insecurity was 48.5%. Of the 98 Food insecure VC 65% were HVC compared to 35% observed among IVC(p <0.05); 69.6 % were children older than 12 years compared to 30.4% obsereved in VC who were <12 years. The odds of food insecurity was 2.1 times in older VC aged 13-18 years (CI=1.1-3.9). VC attending Secondary School were 1.9 time likely to be food insecure compared to those in primary school (CI=1.1-3.5). Similarly, HVC were 3.6 times more likely to be food insecure compared to IVC. (CI=1.9-6.9). VC who worked to earn money had a 2.8times odd to be food insecure (CI=1.2-6.24). Paternal orphans were 2.4 times more likely to be food insecure (CI= 1.0-6.5) compared to other group of VC. Being a maternal orphan, a double orphan or non orphan VC does not predict food insecurity. Sexual experience was also not a predictor of food insecurity. Conclusion: The implication of hunger, in an adolescent child who considered himself/herself overworked is enormous on child physical, emotional and social development. This might lead to more children living their homes to seek shelter in orphanages were the food security status even though not perfect is better than the household. This can be prevented if Household VC are actively identified and their families supported with programs that can make them food secure.
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 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».