LAUSR

Background Biomarkers of meat intake hold promise in clarifying the health effects of meat consumption, yet the differentiation between red and white meat remains a challenge. We measure meat intake objectively in a free-living population by applying a newly developed, three-step strategy for biomarker-based assessment of dietary intakes aimed to indicate if (1) any meat was consumed, (2) what type it was and (3) the quantity consumed. Methods Twenty-four hour urine samples collected in a four-way crossover RCT and in a cross-sectional analysis of a longitudinal lifestyle intervention (the PREVIEW Study) were analyzed by untargeted LC–MS metabolomics. In the RCT, healthy volunteers consumed three test meals (beef, pork and chicken) and a control; in PREVIEW, overweight participants followed a diet with high or moderate protein levels. PLS-DA modeling of all possible combinations between six previously reported, partially validated, meat biomarkers was used to classify meat intake using samples from the RCT to predict consumption in PREVIEW. Results Anserine best separated omnivores from vegetarians (AUROC 0.94–0.97), while the anserine to carnosine ratio best distinguished the consumption of red from white meat (AUROC 0.94). Carnosine showed a trend for dose–response between non-consumers, low consumers and high consumers for all meat categories, while in combination with other biomarkers the difference was significant. Conclusion It is possible to evaluate red meat intake by using combinations of existing biomarkers of white and general meat intake. Our results are novel and can be applied to assess qualitatively recent meat intake in nutritional studies. Further work to improve quantitation by biomarkers is needed.