Extensive programmes around the world endeavour to measure and catalogue the composition of food. Here we analyse the nutrient content of the full US food supply and show that the concentration of each nutrient follows a universal single-parameter scaling law that accurately captures the eight orders of magnitude in nutrient content variability. We show that the universality is rooted in the biochemical constraints obeyed by the metabolic pathways responsible for nutrient modulation, allowing us to confirm the empirically observed scaling law and to predict its variability in agreement with the data. We propose that the natural nutrient variability in food can be quantitatively formalized. This provides a mathematical rationale for imputing missing values in food composition databases and paves the way towards a quantitative understanding of the impact of food processing on nutrient balance and health effects.
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This work was partially supported by NIH grant no. 1P01HL132825, American Heart Association grant no. 151708, ERC grant no. 810115-DYNASET and Rockefeller Foundation grant no. 2019 FOD 026. We thank J. Loscalzo for useful discussions and insights on enzyme kinetics, as well as M. Sebek and S. Ofaim for helping with the chemical classification and disambiguation.
A.-L.B. is the founder of Scipher Medicine and Naring Health, companies that explore the use of network-based tools in health, and Datapolis, which focuses on urban data.
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Menichetti, G., Barabási, AL. Nutrient concentrations in food display universal behaviour. Nat Food 3, 375–382 (2022). https://doi.org/10.1038/s43016-022-00511-0
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