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Association of diet quality indices with serum and metabolic biomarkers in participants of the ORISCAV-LUX-2 study

PURPOSE: Diet quality is a critical modifiable factor related to health, including the risk of cardiometabolic complications. Rather than assessing the intake of individual food items, it is more meaningful to examine overall dietary patterns. This study investigated the adherence to common dietary ...

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Detalles Bibliográficos
Autores principales: Vahid, Farhad, Hoge, Axelle, Hébert, James R., Bohn, Torsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10349755/
https://www.ncbi.nlm.nih.gov/pubmed/36917281
http://dx.doi.org/10.1007/s00394-023-03095-y
Descripción
Sumario:PURPOSE: Diet quality is a critical modifiable factor related to health, including the risk of cardiometabolic complications. Rather than assessing the intake of individual food items, it is more meaningful to examine overall dietary patterns. This study investigated the adherence to common dietary indices and their association with serum/metabolic parameters of disease risk. METHODS: Dietary intakes of the general adult population (n = 1404, 25–79 years) were assessed by a validated food-frequency questionnaire (174 items). The French ANSES-Ciqual food composition database was used to compute nutrient intakes. Seven indicators were calculated to investigate participants’ diet quality: the Alternative Healthy Eating Index (AHEI), Dietary Approaches to Stop Hypertension Score (DASH-S), Mediterranean Diet Score (MDS), Diet Quality Index-International (DQI-I), Dietary Inflammatory Index (DII), Dietary Antioxidant Index (DAI), and Naturally Nutrient-Rich Score (NNRS). Various serum/metabolic parameters were used in the validity and association analyses, including markers of inflammation, blood glucose, and blood lipid status. RESULTS: Following linear regression models adjusted for confounders, the DASH-S was significantly associated with most metabolic parameters (14, e.g., inversely with blood pressure, triglycerides, urinary sodium, uric acid, and positively with serum vitamin D), followed by the DQI-I (13, e.g., total cholesterol, apo-A/B, uric acid, and blood pressure) and the AHEI (11, e.g., apo-A, uric acid, serum vitamin D, diastolic blood pressure and vascular age). CONCLUSION: Food-group-based indices, including DASH-S, DQI-I, and AHEI, were good predictors for serum/metabolic parameters, while nutrient-based indices, such as the DAI or NNRS, were less related to biological markers and, thus, less suitable to reflect diet quality in a general population. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00394-023-03095-y.