Inadequate nutrient intakes put children at risk for impaired growth and development. We described diet, usual intakes of energy and macro- and micronutrients and prevalence of nutrient intake adequacies among 4–8-year-old Zambian children. Children not yet in school and living in Mkushi District, Central Province, Zambia were enrolled into an efficacy trial of pro-vitamin A biofortified maize. Children in the non-intervened arm were included in this analysis (n 202). Dietary intake data were collected by tablet-based 24-h recall on a monthly basis over the 6-month trial. Observed nutrient intakes were derived from reported food quantities, standard recipes and food composition tables. Usual nutrient intake distributions were modelled based on observed intakes. Prevalence of inadequacy was estimated by comparing the usual nutrient intake distribution to the nutrient requirement distribution. Frequency and quantity of consumption of commonly reported foods were described and key sources of energy and nutrients were identified. Median usual energy intake was 6422 kJ/d (1535 kcal/d). Most childrens’ macronutrient intakes fell within recommended ranges (74–98 %). Estimated prevalences of inadequate intakes of Fe, folate, vitamin B12 and Ca were 25, 57, 76 and >99 %, respectively. Estimated prevalences of inadequacy for other micronutrients were low (0·1–2·2 %). Commonly consumed foods included maize, vegetable oil, tomatoes, rape leaves and small fish (>0·6 servings/d), whereas meat, eggs or dairy were rarely eaten (<0·2 servings/d). These findings suggest that the heavily plant-based diet of rural Zambian children provides inadequate Ca, folate, vitamin B12 and Fe to meet recommended nutrient intakes.

The aim of this study was to validate the estimated habitual dietary intake from a newly developed web-based FFQ (WebFFQ), for use in an adult population in Norway. In total, ninety-two individuals were recruited. Total energy expenditure (TEE) measured by doubly labelled water was used as the reference method for energy intake (EI) in a subsample of twenty-nine women, and multiple 24-h recalls (24HR) were used as the reference method for the relative validation of macronutrients and food groups in the entire sample. Absolute differences, ratios, crude and deattenuated correlations, cross-classifications, Bland–Altman plot and plots between misreporting of EI (EI–TEE) and the relative misreporting of food groups (WebFFQ–24HR) were used to assess the validity. Results showed that EI on group level was not significantly different from TEE measured by doubly labelled water (0·7 MJ/d), but ranking abilities were poor (r −0·18). The relative validation showed an overestimation for the majority of the variables using absolute intakes, especially for the food groups ‘vegetables’ and ‘fish and shellfish’, but an improved agreement between the test and reference tool was observed for energy adjusted intakes. Deattenuated correlation coefficients were between 0·22 and 0·89, and low levels of grossly misclassified individuals (0–3 %) were observed for the majority of the energy adjusted variables for macronutrients and food groups. In conclusion, energy estimates from the WebFFQ should be used with caution, but the estimated absolute intakes on group level and ranking abilities seem acceptable for macronutrients and most food groups.

There are statistical methods that remove the within-person random error and estimate the usual intake when there is a second 24-h recall (24HR) for at least a subsample of the study population. We aimed to compare the distribution of usual food intake estimated by statistical models with the distribution of observed usual intake. A total of 302 individuals from Rio de Janeiro (Brazil) answered twenty, non-consecutive 24HR; the average length of follow-up was 3 months. The usual food intake was considered as the average of the 20 collection days of food intake. Using data sets with a pair of 2 collection days, usual percentiles of intake of the selected foods using two methods were estimated (National Cancer Institute (NCI) method and Multiple Source Method (MSM)). These estimates were compared with the percentiles of the observed usual intake. Selected foods comprised a range of parameter distributions: skewness, percentage of zero intakes and within- and between-person intakes. Both methods performed well but failed in some situations. In most cases, NCI and MSM produced similar percentiles between each other and values very close to the true intake, and they better represented the usual intake compared with 2-d mean. The smallest precision was observed in the upper tail of the distribution. In spite of the underestimation and overestimation of percentiles of intake, from a public health standpoint, these biases appear not to be of major concern.

Information on dietary composition is vitally important for elite athletes to optimise their performance and recovery, which requires valid tools. The aim of the present study was to investigate the validity of assessing protein intake using three web-based 24-h recalls and questionnaires, by comparing these with three urinary N excretions on the same day. A total of forty-seven Dutch elite top athletes, both disabled and non-disabled, aged between 18 and 35 years, with a BMI of 17·5–31 kg/m2, exercising >12 h/week were recruited. Estimated mean dietary protein intake was 109·6 (sd 33·0) g/d by recalls and questionnaires v. 141·3 (sd 38·2) g/d based on N excretions in urine; the difference was 25·5 (sd 21·3) % between the methods (P<0·05). We found a reasonably good association between methods for protein intake of 0·65 (95 % CI 0·45, 0·79). On an individual level, under-reporting was larger with higher protein intakes than with lower intakes. No significant differences were found in reporting absolute differences between subcategories (sex, under-reporting, BMI, collection of recalls within a certain amount of time and using protein supplements or not). In conclusion, combined, multiple, 24-h recalls and questionnaires underestimated protein intake in these young elite athletes more than that reported for non-athlete populations. The method proved to be suitable for ranking athletes according to their protein intake as needed in epidemiological studies. On an individual level, the magnitude of underestimation was about equal for all athletes except for those with very high protein intakes.