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Personalized nutrition approach in pediatrics: a narrative review

Journal

PEDIATRIC RESEARCH
Volume 89, Issue 2, Pages 384-388

Publisher

SPRINGERNATURE
DOI: 10.1038/s41390-020-01291-8

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Funding

  1. Italian Ministry of Health (IRCCS grant)

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Personalized dietary advice is more effective in preventing chronic diseases than general diet recommendations. In a pediatric setting, Artificial Neural Networks algorithms are important technologies that can help practitioners provide customized nutrition. While other approaches to personalized nutrition are promising in adults and for basic research, they are still far from practical application in pediatrics.
Dietary habits represent the main determinant of health. Although extensive research has been conducted to modify unhealthy dietary behaviors across the lifespan, obesity and obesity-associated comorbidities are increasingly observed worldwide. Individually tailored interventions are nowadays considered a promising frontier for nutritional research. In this narrative review, the technologies of importance in a pediatric clinical setting are discussed. The first determinant of the dietary balance is represented by energy intakes matching individual needs. Most emerging studies highlight the opportunity to reconsider the widely used prediction equations of resting energy expenditure. Artificial Neural Network approaches may help to disentangle the role of single contributors to energy expenditure. Artificial intelligence is also useful in the prediction of the glycemic response, based on the individual microbiome. Other factors further concurring to define individually tailored nutritional needs are metabolomics and nutrigenomic. Since most available data come from studies in adult groups, new efforts should now be addressed to integrate all these aspects to develop comprehensive and-above all-effective interventions for children. Impact Personalized dietary advice, specific to individuals, should be more effective in the prevention of chronic diseases than general recommendations about diet. Artificial Neural Networks algorithms are technologies of importance in a pediatric setting that may help practitioners to provide personalized nutrition. Other approaches to personalized nutrition, while promising in adults and for basic research, are still far from practical application in pediatrics.

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