Dietary assessment is strongly affected by misreporting (both under-and over-reporting), which results in measurement error. Knowledge about misreporting is essential to correctly interpret potentially biased associations between diet and health outcomes. In young children, dietary data mainly rely on proxy respondents but little is known about determinants of misreporting here. The present analysis was conducted within the framework of the multi-centre IDEFICS (Identification and prevention of dietary-and lifestyle-induced health effects in children and infants) study and is based on 6101 children aged 2-9 years with 24 h dietary recall (24-HDR) and complete covariate information. Adapted Goldberg cut-offs were applied to classify the 24-HDR as 'over-report', 'plausible report' or 'under-report'. Backward elimination in the course of multi-level logistic regression analyses was conducted to identify factors significantly related to under-and over-reporting. Next to characteristics of the children and parents, social factors and parental concerns/perceptions concerning their child's weight status were considered. Further selective misreporting was addressed, investigating food group intakes commonly perceived as more or less socially desirable. Proportions of under-, plausible and over-reports were 8.0, 88.6 and 3.4%, respectively. The risk of under-reporting increased with age (OR 1.19, 95% CI 1.05, 1.83), BMI z-score of the child (OR 1.23, 95% CI 1.10, 1.37) and household size (OR 1.12, 95% CI 1.01, 1.25), and was higher in low/medium income groups (OR 1.45, 95% CI 1.13, 1.86). Over-reporting was negatively associated with BMI z-scores of the child (OR 0.78, 95% CI 0.69, 0.88) and higher in girls (OR 1.70, 95% CI 1.27, 2.28). Further social desirability and parental concerns/perceptions seemed to influence the reporting behaviour. Future studies should involve these determinants of misreporting when investigating diet-disease relationships in children to correct for the differential reporting bias.
Socio-economic inequalities in childhood can determine dietary patterns, and therefore future health. This study aimed to explore associations between social vulnerabilities and dietary patterns assessed at two time points, and to investigate the association between accumulation of vulnerabilities and dietary patterns. A total of 9301 children aged 2-9 years participated at baseline and 2-year follow-up examinations of the Identification and prevention of Dietary-and lifestyle-induced health EFfects In Children and infantS study. In all, three dietary patterns were identified at baseline and follow-up by applying the K-means clustering algorithm based on a higher frequency of consumption of snacks and fast food (processed), sweet foods and drinks (sweet), and fruits and vegetables (healthy). Vulnerable groups were defined at baseline as follows: children whose parents lacked a social network, children from single-parent families, children of migrant origin and children with unemployed parents. Multinomial mixed models were used to assess the associations between social vulnerabilities and children's dietary patterns at baseline and follow-up. Children whose parents lacked a social network (OR 1.31; 99% CI 1.01, 1.70) and migrants (OR 1.45; 99% CI 1.15, 1.83) were more likely to be in the processed cluster at baseline and follow-up. Children whose parents were homemakers (OR 0.74; 99% CI 0.60, 0.92) were less likely to be in the processed cluster at baseline. A higher number of vulnerabilities was associated with a higher probability of children being in the processed cluster (OR 1.78; 99% CI 1.21, 2.62). Therefore, special attention should be paid to children of vulnerable groups as they present unhealthier dietary patterns.
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.