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Big data and personalized nutrition: the key evidence gaps

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The field of personalized nutrition hypothesizes that ‘big data’ — biological, behavioural, social and environmental — can be leveraged to make more precise and effective dietary recommendations to individuals for improving health outcomes, compared to generic dietary advice. This article describes the research questions that need to be answered to understand whether personalized nutrition brings additional clinical utility.

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Authors and Affiliations

  1. Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

    Nicola Guess

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  1. Nicola Guess
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Correspondence to Nicola Guess.

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Competing interests

N.G. has received payment for consultancy services for digital dietary interventions and products for Diet Doctor, Fixing Dad (a low-carbohydrate app), Weight Watchers, Oviva and Babylon Health.

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Nature Metabolism thanks Anders Rosengren and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Guess, N. Big data and personalized nutrition: the key evidence gaps. Nat Metab (2024). https://doi.org/10.1038/s42255-023-00960-2

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  • DOI: https://doi.org/10.1038/s42255-023-00960-2

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