This dataset provides a longitudinal analysis of urinary metabolomic profiles from 198 children aged 1 month, 6 months, 1 year, 3 years, and 5 years. Demographic information, including birth history, feeding practices, parental atopic history, household income, and atopic disease status at different ages, was collected. Total and allergen-specific IgE levels (mite, egg, cow's milk) were measured to evaluate allergic sensitization over time. Atopic disease status was also monitored at multiple time points to assess its development. The urinary metabolomic data, generated using advanced 1H-nuclear magnetic resonance (NMR) spectroscopy, were processed and normalized to support robust metabolic modeling. This dataset aims to provide insights into the relationships among early growth, metabolomic changes, and the development of allergic sensitization and atopic diseases in early childhood.
Kuo et al. (Tue,) studied this question.