Thriving beyond survival: Understanding utilization of perinatal health services as predictors of birth registration: A cross-sectional study
Notice bibliographique
Résumé
BACKGROUND: There are an estimated 35 million unregistered children in Indonesia. To understand ways to best leverage existing health system-related resources and ensure greater protective measures for these vulnerable children, this study explores the predictive relationship between the utilization of perinatal health services and birth certificate ownership in two Indonesian provinces. METHODS: This study employed a cross-sectional design with interviewer-administered household surveys to heads of households in West Nusa Tenggara and East Nusa Tenggara from May to July of 2013. The primary outcome of interest was birth certificate ownership among children under the age of 5 years old. Bivariate and multivariable regression analyses using Generalized Estimating Equations (GEE) considered a set of covariates that represented child and household socio-demographic characteristics along with health services utilization variables during pregnancy and post-pregnancy periods. RESULTS: 389 heads of households were interviewed, yielding data on a sample of 451 children under the age of 5. Fewer than 28% of children in this sample possessed a birth certificate. Nearly 57% (n = 259) of children were delivered in a clinical facility, though only 36% (n = 93) of these were legally registered. Of children born in the home (n = 194), registration dropped to 16% (n = 31). Adjusted analyses accounting for socio-demographic factors suggest that children born in a clinic facility (AOR = 2.33, 95% CI: 1.27, 4.33), hospital (AOR = 2.38, 95% CI: 1.12, 5.09), or in the presence of a skilled birth attendant (AOR = 2.35, 95% CI: 1.31, 4.23) were significantly more likely to be registered. Children whose mothers sought post-natal care were 2.99 times more likely to possess a birth certificate (AOR = 2.99, 95% CI: 1.1, 7.57). Pre-natal care was not associated with birth registration. CONCLUSION: These findings suggest that use of perinatal health services increases the likelihood of registering a child's birth despite a lack of formal integration of vital registration with the health sector. Formally leveraging existing community-based health workers and perinatal services may serve to further increase registration rates in hard to reach areas of Indonesia.
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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 | 0,001 | 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 | 0,000 | 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 ».