Vol. 2, Issue 1, Part A (2025)

Background: The formative period of intrauterine life is crucial in shaping the foundation of an infant’s physical, cognitive, and neurological development. Ayurveda outlines a comprehensive regimen known as Garbhini Paricharya, a sequence of dietary, behavioral, and herbal guidelines tailored for each trimester to support healthy fetal growth, maternal wellbeing, and optimal Garbha Bala. The classical Ayurvedic texts emphasize this regimen not only to ensure uncomplicated delivery but also to nurture higher neurocognitive faculties (Medha, Smriti, Buddhi) of the child.

Objective: This study investigates the relationship between adherence to Ayurvedic Garbhini Paricharya and early neurodevelopmental milestones in infants during their first year, analyzing both traditional and contemporary neurobehavioral indicators.

Methods: A comparative observational study was conducted with 80 pregnant women, divided into two groups. Group A followed trimester-specific Garbhini Paricharya, while Group B received routine antenatal care. Infant developmental milestones were assessed at birth, 3, 6, 9, and 12 months using standard Denver Developmental Screening Test (DDST) criteria, with additional qualitative measures of Bala, Medha, and Pravritti derived from Ayurvedic pediatric principles.

Results: Infants in the Garbhini Paricharya group showed statistically significant early attainment of major neurodevelopmental milestones including head control, object permanence, babbling, and social smiling. Enhanced maternal outcomes such as reduced delivery complications, better lactation, and lower postnatal fatigue were also observed. Ayurvedic interpretation linked these outcomes to improved Ojas, Sattva Bala, and fetal nourishment via Rasa Dhatu.

Conclusion: The findings suggest that Ayurvedic Garbhini Paricharya may serve as a vital, non-invasive protocol for enhancing infant neurodevelopment. Integrating such traditional frameworks with modern perinatal care may offer a holistic approach to child health in resource-limited settings.