biostudies-literatureBlumlhuber ABavarian Ministry for Food, Agriculture and Forestry441https://www.ebi.ac.uk/biostudies/studies/S-EPMC12297984biostudies-literatureUnknown15(7)<h4>Background</h4>Chronic non-communicable diseases (NCDs) are a major global health challenge, with unhealthy diets contributing significantly to their burden. Metabolomics data offer new possibilities for identifying nutritional biomarkers, as demonstrated in short-term intervention studies. This study investigated associations between habitual dietary intake and urinary metabolites, a not well-studied area.<h4>Methods</h4>Data were available from 496 participants of the population-based MEIA study. Linear and median regression models examined associations between habitual dietary intake and metabolites, adjusted for possible confounders. K-means clustering identified urinary metabolite clusters, and multinomial regression models were applied to analyze associations between food intake MetabolitesAssociation Between Habitual Dietary Intake and Urinary Metabolites in Adults-Results of a Population-Based Study.PMC12297984A/19/15Rohm FBlumlhuber ALinseisen JMeisinger CWawro NFreuer DfalseAssociation Between Habitual Dietary Intake and Urinary Metabolites in Adults-Results of a Population-Based Study.<h4>Background</h4>Chronic non-communicable diseases (NCDs) are a major global health challenge, with unhealthy diets contributing significantly to their burden. Metabolomics data offer new possibilities for identifying nutritional biomarkers, as demonstrated in short-term intervention studies. This study investigated associations between habitual dietary intake and urinary metabolites, a not well-studied area.<h4>Methods</h4>Data were available from 496 participants of the population-based MEIA study. Linear and median regression models examined associations between habitual dietary intake and metabolites, adjusted for possible confounders. K-means clustering identified urinary metabolite clusters, and multinomial regression models were applied to analyze associations between food intake 2025-01-01T00:00:00Z2025 Jul2025-08-13T03:04:16.261Z2025-08-13T03:04:16.261ZS-EPMC122979844071054210.3390/metabo15070441