Objective: The aim of the current study was to evaluate the accuracy of the new software eAT24 used to assess dietary intake in the National Food, Nutrition and Physical Activity Survey (IAN-AF) against urinary biomarkers: N (nitrogen), K (potassium) and Na (sodium).Design: We conducted a cross-sectional study. Two non-consecutive 24-h dietary recalls (24-HDR) were applied, and a 24-h urine sample was collected. We examined differences between estimates from dietary and urine measures, Pearson correlation coefficients were calculated and the Bland–Altman plots were drawn. Multiple linear regression was used to evaluate the factors associated with the difference between estimates.Setting: Sub-sample from the Portuguese IAN-AF sampling frame.Participants: Ninety-five adults (men and women) aged 18–84 years.Results: The estimated intake calculated using the dietary recall data was lower than that estimated from urinary excretion for the three biomarkers studied (protein 94·3 v. 100·4 g/d, K 3212 v. 3416 mg/d and Na 3489 v. 4003 mg/d). Considering 2 d of recall, the deattenuated correlation coefficients were 0·33, 0·64 and 0·26 for protein, K and Na, respectively. For protein, differences between dietary and urinary estimates varied according to BMI (β = −1·96, P = 0·017). The energy intake and 24-h urine volume were significantly associated with the difference between estimates for protein (β = 0·03, P < 0·001 and β = −0·02, P = 0·002, respectively), K (β = 0·71, P < 0·001 and β = −0·42, P = 0·040, respectively) and Na (β = 1·55, P < 0·001 and β = −0·81, P = 0·011, respectively).Conclusions: The new software eAT24 performed well in estimating protein and K intakes, but lesser so in estimating Na intake, using two non-consecutive 24-HDR.

Zearalenone and alternariol are mycotoxins produced by Fusarium and Alternaria species, respectively, that present estrogenic activity and consequently are classified as endocrine disruptors. To estimate the exposure of the Portuguese population to these two mycotoxins at a national level, a modelling approach, based on data from 94 Portuguese volunteers, was developed considering as inputs: i) the food consumption data generated within the National Food and Physical Activity Survey; and ii) the human biomonitoring data used to assess the exposure to the referred mycotoxins. Six models of association between mycoestrogens urinary levels (zearalenone, total zearalenone and alternariol) and food items (meat, cheese, and fresh-cheese, breakfast cereals, sweets) were established. Applying the obtained models to the consumption data (n = 5811) of the general population, the median estimates of the probable daily intake revealed that a fraction of the Portuguese population might exceed the tolerable daily intake defined for zearalenone. A reference intake value for alternariol is still lacking, thus the characterization of risk due to the exposure to this mycotoxin was not possible to perform. Although the unavoidable uncertainties, these results are important contributions to understand the exposure to endocrine disruptors in Portugal and the potential Public Health consequences.

This study aimed to assess the extent to which first-morning void (FMV) urine samples can estimate sodium and potassium excretion compared with 24-hour (24-h) urine samples at the population level. We conducted a cross-sectional study collecting urine samples (FMV and 24-h) and two non-consecutive 24-h dietary recalls in a sub-sample from the Portuguese IAN-AF sampling frame. Six predictive equations were used to estimate 24-h sodium and potassium excretion from FMV urine samples. Pearson correlation coefficients were calculated to compare the association between FMV and 24-h urine collections. Cross-classifications into tertiles were computed to calculate the agreement between measured and estimated excretion with and without calibration. Pearson correlation coefficients were calculated to compare the excretion estimation from FMV and reported intake from 24-h dietary recalls. Bland–Altman plots assessed the agreement between two-day dietary recall and the best-performing calibrated equation. Data from eighty-six subjects aged 18–84 were analysed. Estimated sodium and potassium concentrations from the predictive equations moderate or strongly correlated with the measured 24-h urine samples. The Toft equation was the most predictive and reliable, displaying a moderate correlation (r=0.655) with no risk of over or underestimation of sodium excretion (p=0.096). Tanaka and Kawasaki equations showed a similar moderate correlation (r=0.54 and r=0.58, respectively) but tended to underestimate the 24-h urine excretion of potassium (p<0.001). Calibrated predictive equations using FMV urine samples provide a moderately accurate alternative and resource-efficient option for large-scale nutritional epidemiology studies when 24-h urine collection is impractical.