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

Farhad Vahid, Axelle Hoge, James R. Hébert, Torsten Bohn*, Ala’a Alkerwi, Stephanie Noppe, Charles Delagardelle, Jean Beissel, Anna Chioti, Saverio Stranges, Jean Claude Schmit, Marie Lise Lair, Marylène D’Incau, Jessica Pastore, Gloria Aguayo, Gwenaëlle Le Coroller, Michel Vaillant, Hanen Samouda, Brice Appenzeller, Laurent MalisouxSophie Couffignal, Manon Gantenbein, Yvan Devaux, Laetitia Huiart, Dritan Bejko, Guy Fagherazzi, Magali Perquin, Maria Ruiz-Castell, Isabelle Ernens, On behalf of the ORISCAV working group*.

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)2063-2085
Number of pages23
JournalEuropean Journal of Nutrition
Issue number5
Early online date14 Mar 2023
Publication statusPublished - Aug 2023


  • Chronic disease risk
  • Diet quality scores
  • Dietary patterns
  • Inflammation
  • Non-communicable diseases
  • Oxidative stress
  • Systemic Immune-Inflammation Index (SII)
  • Type 2 diabetes


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