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bioRxiv · 10.1101/2023.10.26.564308

Reliance on self-reports and estimated food composition data in nutrition research introduces significant bias that can only be addressed with biomarkers

Ottaviani, J. I.·Sagi-Kiss, V.·Schroeter, H.·Kuhnle, G. G. C.
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Abstract

The chemical composition of foods is complex, variable, and dependent on many factors. This has a major impact on nutrition research as it foundationally affects our ability to adequately assess actual intake of nutrients and other compounds. Despite of this, accurate data on nutrient intake are key for investigating associations and causal relationships between intake, health, and disease risk at the service of developing evidence-based dietary guidance that enables improvements in population health. Here, we exemplify the importance of this challenge by investigating the impact of food content variability on nutrition research using three bioactives as model: flavan-3-ols, (-)-epicatechin, and nitrate. Our results show that common approaches aimed at addressing the high compositional variability of even the same foods impede the accurate assessment of nutrient intake, generally. This suggests that the results of many nutrition studies using food composition data are potentially unreliable and carry greater limitations than commonly appreciated, consequently resulting in dietary recommendations with significant limitations and unreliable impact on public health. Thus, current challenges related to nutrient intake assessments need to be addressed and mitigated by the development of improved dietary assessment methods involving the use of nutritional biomarkers.

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Ottaviani, J. I., Sagi-Kiss, V., Schroeter, H., Kuhnle, G. G. C.. 2023-10-31. Reliance on self-reports and estimated food composition data in nutrition research introduces significant bias that can only be addressed with biomarkers. https://doi.org/10.1101/2023.10.26.564308

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