Development and application of a new food composition database to reveal patterns of human milk composition

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In the crucial early phase of infancy, nutrition profoundly shapes offspring health and development, emphasizing the importance of human milk (HM) in the first 1,000 days of life. HM offers a unique composition rich in bioactive components crucial for infant growth and immunity. However, our understanding of HM composition remains fragmented due to methodological limitations and a lack of comprehensive data frameworks. Existing research often focuses on isolated factors within the mother-milk-infant triad, hindering a holistic understanding. To address this gap, we propose the establishment of a standardized database capable of capturing the dynamic nature of HM composition while integrating maternal, infant, and methodological variables. Such a database would enable researchers to explore the intricate interplay of factors influencing HM composition.

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Food composition, Food database, Computational nutrition, Data science, Human milk, Big Data
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