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The diet quality index (DQI) for preschool children is a new index developed to reflect compliance with four main food-based dietary guidelines for preschool children in Flanders. The present study investigates: (1) the validity of this index by comparing DQI scores for preschool children with nutrient intakes, both of which were derived from 3 d estimated diet records; (2) the reproducibility of the DQI for preschoolers based on a parentally reported forty-seven-item FFQ DQI, which was repeated after 5 weeks; (3) the relative validity of the FFQ DQI with 3 d record DQI scores as reference. The study sample included 510 and 58 preschoolers (2.5-6.5 years) for validity and reproducibility analyses, respectively. Increasing 3 d record DQI scores were associated with decreasing consumption of added sugars, and increasing intakes of fibre, water, Ca and many micronutrients. Mean FFQ DQI test-retest scores were not significantly different: 72 (sd 11) v. 71 (sd 10) (P = 0.218) out of a maximum of 100. Mean 3 d record DQI score (66 (sd 10)) was significantly lower than mean FFQ DQI (71 (sd 10); P < 0.001). The reproducibility correlation was 0.88. Pearsons correlation (adjusted for within-person variability) between FFQ and 3 d record DQI scores was 0.82. Cross-classification analysis of the FFQ and 3 d record DQI classified 60 % of the subjects in the same category and 3% in extreme tertiles. Cross-classification of repeated administrations classified 62% of the subjects in the same category and 3% in extreme categories. The FFQ-based DQI approach compared well with the 3 d record approach, and it can be used to determine diet quality among preschoolers. [ABSTRACT FROM AUTHOR]

Few studies have investigated the relative validity of FFQ in young children and no study has investigated the relative validity of changes in children's food intake in a longitudinal context. The aim of the present study was to compare the FFQ of the longitudinal Family Influences on Food Intake study, assessing children's food intake in the previous 3 months, with a 3 d online food record when children were 3 and 7 years old, as well as to investigate the relative validity of changes in food group intake over a 4-year period. Parents (n 89) completed the FFQ and an online food record over three non-consecutive days on two separate occasions (January-April 2008 and 2012). Wilcoxon signed-rank tests and Spearman's correlations were used to compare food group intake and changes in intake assessed using both methods. In 2008, the intake of eleven of the twenty-two food groups was overestimated and that of four food groups underestimated in the FFQ in comparison with the online tool; in 2012, the intake of four food groups was overestimated and that of seven food groups underestimated. Nevertheless, changes in intake did not differ significantly between the two methods for eighteen food groups. Correlations in 2008 and 2012 were, on average, 0.47; correlations between the changes in dietary intake were, on average, 0.26. The results suggest that despite the significant differences between the two methods for a number of food groups at both baseline and/or follow-up, the FFQ can be used to monitor changes in dietary intake for groups of young children.

Food-based dietary guidelines (FBDG) aim to address the nutritional requirements at population level in order to prevent diseases and promote a healthy lifestyle. Diet quality indices can be used to assess the compliance with these FBDG. The present study aimed to investigate whether the newly developed Diet Quality Index for Adolescents (DQI-A) is a good surrogate measure for adherence to FBDG, and whether adherence to these FBDG effectively leads to better nutrient intakes and nutritional biomarkers in adolescents. Participants included 1804 European adolescents who were recruited in the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) Study. Dietary intake was assessed by two, non-consecutive 24 h recalls. A DQI-A score, considering the components' dietary quality, diversity and equilibrium, was calculated. Associations between the DQI-A and food and nutrient intakes and blood concentration biomarkers were investigated using multilevel regression analysis corrected for centre, age and sex. DQI-A scores were associated with food intake in the expected direction: positive associations with nutrient-dense food items, such as fruits and vegetables, and inverse associations with energy-dense and low-nutritious foods. On the nutrient level, the DQI-A was positively related to the intake of water, fibre and most minerals and vitamins. No association was found between the DQI-A and total fat intake. Furthermore, a positive association was observed with 25-hydroxyvitamin D, holo-transcobalamin and n-3 fatty acid serum levels. The present study has shown good validity of the DQI-A by confirming the expected associations with food and nutrient intakes and some biomarkers in blood.