Towards objective measurements of habitual dietary intake patterns: comparing NMR metabolomics and food frequency questionnaire data in a population-based cohort.

backgroundLow-quality, non-diverse diet is a main risk factor for premature death. Accurate measurement of habitual diet is challenging and there is a need for validated objective methods. Blood metabolite patterns reflect direct or enzymatically diet-induced metabolites. Here, we aimed to evaluate associations between blood metabolite patterns and a priori and data-driven food intake patterns.

methods1, 895 participants in the Northern Sweden Health and Disease Study, a population-based prospective cohort study, were included. Fasting plasma samples were analyzed with

resultsAge, sex, body mass index, education and year of study participation had significant influence on OPLS metabolite models. OPLS models for healthful PDI and LCA-clusters were not significant, whereas for HDS, rMDS, PDI and unhealthful PDI significant models were obtained (CV-ANOVA p < 0.001). Still, model statistics were weak and the ability of the models to correctly classify participants into highest and lowest quartiles of rMDS, PDI and unhealthful PDI was poor (50%/78%, 42%/75% and 59%/70%, respectively).

conclusionAssociations between blood metabolite patterns and a priori as well as data-driven food intake patterns were poor. NMR metabolomics may not be sufficiently sensitive to small metabolites that distinguish between complex dietary intake patterns, like lipids.