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

Publisher: BioMed Central Country of Publication: England NLM ID: 101152213 Publication Model: Electronic Cited Medium: Internet ISSN: 1475-2891 (Electronic) Linking ISSN: 14752891 NLM ISO Abbreviation: Nutr J Subsets: MEDLINE

Original Publication: London : BioMed Central, 2002-

Eating* ; Diet, Mediterranean*; Humans ; Prospective Studies ; Magnetic Resonance Spectroscopy ; Surveys and Questionnaires

Background: Low-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.
Methods: 1, 895 participants in the Northern Sweden Health and Disease Study, a population-based prospective cohort study, were included. Fasting plasma samples were analyzed with ¹ H Nuclear Magnetic Resonance. Food intake data from a 64-item validated food frequency questionnaire were summarized into a priori Healthy Diet Score (HDS), relative Mediterranean Diet Score (rMDS) and a set of plant-based diet indices (PDI) as well as data driven clusters from latent class analyses (LCA). Orthogonal projections to latent structures (OPLS) were used to explore clustering patterns of metabolites and their relation to reported dietary intake patterns.
Results: Age, 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).
Conclusion: Associations 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.
(© 2024. The Author(s).)

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Keywords: Diet intake patterns; Food frequency questionnaire; Habitual dietary intake; NMR metabolomics; Northern Sweden health and disease study

Date Created: 20240301 Date Completed: 20240304 Latest Revision: 20240304

20240304

PMC10908051

10.1186/s12937-024-00929-1

38429740