Integrating group antenatal care into routine services:
- manuscript
- 01 January 2026
Référence
Integrating group antenatal care into routine services: . manuscript, 2026.
Résumé
A registry-based cohort study in Geita, Tanzania
Study Overview
Overview of the G‑ANC model in Geita (source: PHIT)
This registry-based cohort study, conducted between January 2023 and November 2024 across six public health facilities in Geita, Tanzania, evaluated the integration of group antenatal care (G-ANC) into routine government services[cite: 535, 536]. Enrolling 5,936 pregnant women, the study sought to examine service utilization patterns and birth outcomes by transitioning traditional one-to-one consultations into structured group sessions that provide clinical assessments, health education, and peer support[cite: 518, 540, 575]. The implementation followed a standardized, government-led strategy aligned with WHO recommendations, utilizing a curriculum that covered critical topics such as maternal nutrition, malaria prevention, and birth preparedness[cite: 548, 560, 564].
Key Findings
The key outcome of the study was a high completion rate of maternal health services, with 93.9% of participants attending four or more antenatal care (ANC) visits[cite: 507, 630]. Furthermore, the multivariable analysis revealed that attending four or more visits was strongly associated with a significant reduction in adverse birth outcomes, such as stillbirths[cite: 510, 647, 683]. While the G-ANC model demonstrated high uptake for essential interventions like malaria preventive treatment (76.1%) and iron-folate supplementation (92.6%), the researchers noted that future adaptations should focus on promoting earlier enrollment in the first trimester to fully align with global health guidelines.
Détails de la publication
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Catégorie manuscript
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Publié 01 January 2026
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Format PDF
Publications associées
- PHIT 2025 Annual Report Highlights: From Evidence to Impact July 2026
- PREPRINT: Beyond Attendance: Facility-level variations in the delivery of essential Antenatal Care interventions during routine Group Antenatal Care implementation in Tanzania: A Secondary Analysis July 2026
- Machine learning for risk stratification of hypertensive disorders of pregnancy: July 2026