Prevalence and determinants of misreporting among European children in proxy-reported 24 h dietary recalls

Abstract

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.

Diet–obesity associations in children: approaches to counteract attenuation caused by misreporting

“…This may be explained by either: (i) differences in the mean intake levels to which the effects are put into relation ( Our results argue against combining UdR and OvR into one group in stratified analyses as determinants of misreporting and participants' characteristics are likely to differ (30) . Moreover, the differences between the groups of UdR, PR and OvR suggest that data exclusions may actually introduce a selection bias, so that exclusion of misreports is not recommended.…”

“…Calculation of the propensity score In a previous study based on the IDEFICS data (30) , backward elimination in the course of multilevel logistic regression analysis was applied to identify factors significantly related to misreporting in proxy reports for young children. The covariables that turned out to be significantly associated with misreporting were used in the construction of the propensity score: age and sex of the child (31,32) , net household income (dummy: high v. medium/low), number of persons below 18 years of age in the household and day of the interview (dummy: weekday v. Saturday/Sunday).…”

Usual energy and macronutrient intakes in 2–9-year-old European children

“…6 Black 47 and Goldberg et al 48 defined cutoff values to classify 24-HDRs in energy underreports (UnR), plausible reports and overreports (OvR), respectively. The cutoffs allow for the errors associated with the duration of dietary assessment (number of recall days), the sample size as well as variation in basal metabolic rate, physical activity level and energy intake.…”

“…Details are given elsewhere. 6,50 For the sake of convenience, the adapted Goldberg cutoffs are given in Table 1. Based on these age-and sex-specific cutoffs, the 24-HDRs were classified in UnR, plausible reports and OvR.…”

“…Hence, the problem of unintentional misreporting may be even more pronounced in data relying on proxies. 6 In large epidemiological studies, food frequency questionnaires (FFQs) or single/repeated short-term measurements like 24-h dietary recalls (24-HDR) or food records are generally used for dietary assessment for cost and time reasons. 7 FFQs are limited to a finite food list and are hampered by the inability of individuals to accurately report their long-term consumption frequencies/ amounts, in particular, for irregular or seasonally consumed foods.…”