Seeking evidence to support efforts to increase use of antenatal care: a cross-sectional study in two states of Nigeria
Notice bibliographique
Résumé
BACKGROUND: Antenatal care (ANC) attendance is a strong predictor of maternal outcomes. In Nigeria, government health planners at state level and below have limited access to population-based estimates of ANC coverage and factors associated with its use. A mixed methods study examined factors associated with the use of government ANC services in two states of Nigeria, and shared the findings with stakeholders. METHODS: A quantitative household survey in Bauchi and Cross River states of Nigeria collected data from women aged 15-49 years on ANC use during their last completed pregnancy and potentially associated factors including socio-economic conditions, exposure to domestic violence and local availability of services. Bivariate and multivariate analysis examined associations with having at least four government ANC visits. We collected qualitative data from 180 focus groups of women who discussed the survey findings and recommended solutions. We shared the findings with state, Local Government Authority, and community stakeholders to support evidence-based planning. RESULTS: 40% of 7870 women in Bauchi and 46% of 7759 in Cross River had at least four government ANC visits. Women's education, urban residence, information from heath workers, help from family members, and household owning motorized transport were associated with ANC use in both states. Additional factors for women in Cross River included age above 18 years, being married or cohabiting, being less poor (having enough food during the last week), not experiencing intimate partner violence during the last year, and education of the household head. Factors for women in Bauchi were presence of government ANC services within their community and more than two previous pregnancies. Focus groups cited costly, poor quality, and inaccessible government services, and uncooperative partners as reasons for not attending ANC. Government and other stakeholders planned evidence-based interventions to increase ANC uptake. CONCLUSION: Use of ANC services remains low in both states. The factors related to use of ANC services are consistent with those reported previously. Efforts to increase uptake of ANC should focus particularly on poor and uneducated women. Local solutions generated by discussion of the evidence with stakeholders could be more effective and sustainable than externally driven interventions.
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 | 0,004 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».