Objective: To compare, specifically by age group, proxy-reported food group estimates obtained from the food frequency section of the Children's Eating Habits questionnaire (CEHQ-FFQ) against the estimates of two non-consecutive 24h dietary recalls (24-HDR). Design: Estimates of food group intakes assessed via the forty-three-food-group CEHQ-FFQ were compared with those obtained by a computerized 24-HDR. Agreement on frequencies of intakes (equal to the number of portions per recall period) between the two instruments was examined using crude and de-attenuated Pearson's correlation coefficients, cross-classification analyses, weighted kappa statistics (kappa(w)) and Bland-Altman analysis. Setting: Kindergartens/schools from eight European countries participating in the IDEFICS (Identification and prevention of Dietary- and lifestyle-induced health EFfects In Children and infantS) Study cross-sectional survey (2007-2008). Subjects: Children aged 2-9 years (n 2508, 50.4% boys). Results: The CEHQ-FFQ provided higher intake estimates for most of the food groups than the 24-HDR. De-attenuated Pearson correlation coefficients ranged from 0.01 (sweetened fruit) to 0.48 (sweetened milk) in children aged 2-<6 years (mean = 0.25) and from 0.01 (milled cereal) to 0.44 (water) in children aged 6-9 years (mean = 0.23). An average of 32 % and 31 % of food group intakes were assigned to the same quartile in younger and older children, respectively, and classification into extreme opposite quartiles was <= 12 % for all food groups in both age groups. Mean kappa(w) was 0.20 for 2-<6-year-olds and 0.17 for 6-9-year-olds. Conclusions: The strength of association estimates assessed by the CEHQ-FFQ and the 24-HDR varied by food group and by age group. Observed level of agreement and CEHQ-FFQ ability to rank children according to intakes of food groups were considered to be low.
Background: Evidence for the effect of dietary energy on BMI z-scores in young children is limited. We aim to investigate cross-sectional and longitudinal effects of daily energy intake (EI) on BMI z-scores of European boys and girls considering growth-related height dependencies of EI using residual EI. Methods: To investigate cross-sectional and longitudinal effects of daily energy intake (EI) on BMI z-scores of European boys and girls considering growth-related height dependencies of EI using residual EI. Methods: Subjects were children aged 2-< 10 y old (N = 2753, 48.2 % girls) participating in the IDEFICS (Identification and prevention of Dietary-and lifestyle-induced health EFfects In Children and infantS) baseline and follow-up examination. Usual EI (kcal/day) was calculated based on the National Cancer Institute-method excluding subjects with implausible reported EI. Effect of age, height and sex-adjusted residuals of EI on BMI z-score was investigated stratified by baseline age-group (2-< 4 y, 4-< 6 y, 6-< 8 y and 8-< 10 y) cross-sectionally using linear regression models adjusted for relevant confounders (crude model: age, sex, country; fully adjusted model: plus parental ISCED level, parental BMI, screen time; subgroup analysis: plus objectively measured physical activity). Longitudinal associations were estimated between changes in (Delta) residual EI per year and Delta BMI z-score per year with adjustments analogously to the cross-sectional models but with additional adjustment for residual EI at baseline. Results: Cross-sectionally, positive associations were observed between residual EI and BMI z-score for the full study sample, for boys and in older (>= 6 years) but not in younger children in the crude and fully adjusted model. Longitudinally, small positive associations were observed between Delta residual EI per y on Delta BMI z-score per y for the full study sample and in 4-< 6 y olds in the crude and fully adjusted model. Conclusion: In conclusion, EI above the average intakes for a certain sex, age and height are weakly associated with BMI z-scores in European children. Residual EI may be considered as a useful exposure measure in children as it accounts for growth-related changes in usual EI during childhood.
Exploring changes in children's diet over time and the relationship between these changes and socio-economic status (SES) may help to understand the impact of social inequalities on dietary patterns. The aim of the present study was to describe dietary patterns by applying a cluster analysis to 9301 children participating in the baseline (2-9 years old) and follow-up (4-11 years old) surveys of the Identification and Prevention of Dietary-and Lifestyle-induced Health Effects in Children and Infants Study, and to describe the cluster memberships of these children over time and their association with SES. We applied the K-means clustering algorithm based on the similarities between the relative frequencies of consumption of forty-two food items. The following three consistent clusters were obtained at baseline and follow-up: processed (higher frequency of consumption of snacks and fast food); sweet (higher frequency of consumption of sweet foods and sweetened drinks); healthy (higher frequency of consumption of fruits, vegetables and wholemeal products). Children with higher-educated mothers and fathers and the highest household income were more likely to be allocated to the healthy cluster at baseline and follow-up and less likely to be allocated to the sweet cluster. Migrants were more likely to be allocated to the processed cluster at baseline and follow-up. Applying the cluster analysis to derive dietary patterns at the two time points allowed us to identify groups of children from a lower socio-economic background presenting persistently unhealthier dietary profiles. This finding reflects the need for healthy eating interventions specifically targeting children from lower socio-economic backgrounds.