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Despite some advantages over traditional methods, Web-based studies elicit concerns about generalizability. To address this issue, we compared dietary intakes between an electronic (e-) cohort study and a nationally representative survey. We studied 49,443 French volunteers aged 18-74 years recruited during 2009-2010 in the NutriNet-Santé Study, a general population-based e-cohort study. The Etude Nationale Nutrition Santé (ENNS; 2006-2007), a cross-sectional study with a nationally representative sample of 2,754 French adults aged 18-74 years, served as the reference data set. Reported dietary intakes from three 24-hour dietary records were weighted and compared between the two studies via Student t tests for mean location, using a >5% cutoff for establishing practically meaningful differences. We observed similar intakes as regards carbohydrates, total lipids, protein, and total energy. However, intakes of fruit and vegetables, fiber, vitamins B6, B9, C, D, and E, iron, and magnesium were higher in the e-cohort than in the ENNS, while intakes of alcohol and nonalcoholic beverages were lower in the e-cohort. Significant sex-specific differences were observed regarding vitamins A and B12, zinc, and potassium. True intake differences, mode effects, and volunteer bias might each contribute to explaining the findings. In the future, repeated use of the same tool in large e-cohorts with heterogeneous dietary exposures could serve research purposes and supplement group-level monitoring of dietary trends. [ABSTRACT FROM AUTHOR]

Purpose: To assess the cross-sectional association between dietary indexes (DI) that underlie, respectively, the Nutri-score (NS), the proposed Canadian 'High In' Symbol (CHIL) and the Diabetes Canada Clinical Practice Guidelines (DCCP) with food consumption, nutrient intakes and metabolic markers. Methods: 1836 adults (18–74 years) participating in the representative ESTEBAN study, conducted in mainland France in 2014–2016, were included in the analysis. Food consumption was assessed with three repeated 24 h dietary recalls. Anthropometric measurements and biomarkers of metabolic risk (cholesterol—total, LDL (Low Density Lipoprotein), HDL (High Density Lipoprotein)—triglycerides, glucose) were obtained through a clinical examination and fasting blood draw. The DI were assessed for their association with food consumption, dietary intakes and metabolic biomarkers as quintiles and continuous variables using multi-adjusted linear regression. Heathier diets were assigned to lower scores. Results: Correlations between scores ranged from + 0.62 between CHIL-DI and NS-DI to + 0.75 between NS-DI and DCCP-DI. All DIs discriminated individuals according to the nutritional quality of their diets through food consumption and nutrient intakes (healthier diets were associated with lower intakes of energy, added sugars and saturated fat; and with higher intakes of fiber, vitamins and minerals). NS-DI was associated with blood glucose (adjusted mean in Q1 = 5 vs. Q5 = 5.46 mmol/dl, ptrend = 0.001) and DCCP-DI was associated with BMI (Q1 = 24.8 kg/m2 vs. Q5 = 25.8 kg/m2, ptrend = 0.025), while CHIL showed no significant association with any anthropometric measures or biomarkers. Conclusions: This study provides elements supporting the validity of the nutrient profiling systems underlying front-of-package nutrition labellings (FOPLs) to characterize the healthiness of diets. [ABSTRACT FROM AUTHOR]