Ultra-processed foods (UPFs) are common worldwide and associated with poorer health outcomes. This work aimed to explore the UPF consumption associated factors and its main dietary sources, by sex, in Portugal. Participants from the National Food, Nutrition and Physical Activity Survey (IAN-AF) 2015–2016, aged 3–84 years, were included (n 5005). Dietary intake was assessed through two 1-day food diaries/24 h recalls. UPFs were identified using the NOVA classification. Associations were evaluated through linear regression models. Median UPF consumption was 257 g/d (10⋅6 % of total quantity; 23⋅8 % of total energy). Adolescents were those with higher consumption (490 g/d). Compared to adults, younger ages were positively associated with UPF consumption (e.g. adolescents ( $\hat{\beta }$ -females: 192, 95 % confidence interval (CI): 135, 249; $\hat{\beta }$ -males: 327, 95 % CI: 277, 377)). A lower educational level was associated with lower UPF consumption ( $\hat{\beta }$ -females: −63; 95 % CI: −91, −34; $\hat{\beta }$ -males: −68; 95 % CI: −124, −12). Also, a lower UPF consumption was observed in married males/couples compared to singles ( $\hat{\beta }$ : −48, 95 % CI: −96, −1). Furthermore, female current/former smokers were associated with a higher UPF consumption v. never smokers ( $\hat{\beta }$ : 79, 95 % CI: 41, 118; $\hat{\beta }$ : 42, 95 % CI: 8, 75, respectively). Main UPF sources were yoghurts, soft drinks and cold meats/sausages differing strongly by sex, age and education level. Yoghurts containing additives were the main contributors to the UPF consumption in children and adult females from all education (~20 %). Soft drinks were leaders in adolescents (females: 26⋅0 %; males: 31⋅6 %) and young male adults (24⋅4 %). Cold meats/sausages stood out among low-educated males (20⋅5 %). Males, younger age groups, higher education, children with less-educated parents, married/couple males and smoking females were positively associated with UPF consumption.

Ultra-processed food (UPF) can be harmful to the population’s health. To establish associations between UPF and health outcomes, food consumption can be assessed using availability data, such as purchase lists or household budget surveys. The aim of this systematic review was to search studies that related UPF availability with noncommunicable diseases or their risk factors. PRISMA guidelines were used. Searches were performed in PubMed, EBSCO, Scopus and Web of Science in February 2021. The search strategy included terms related to exposure (UPF) and outcomes (noncommunicable diseases and their risk factors). Studies that assessed only food consumption at an individual level and did not present health outcomes were excluded. Two reviewers conducted the selection process, and a third helped when disagreement occurred. The Newcastle–Ottawa Scale was used to assess the studies’ quality; 998 records were analyzed. All 11 eligible studies were ecological and assessed overweight and obesity as a health outcome, only one showed no positive association with UPF availability. Two studies included the prevalence of diabetes as an outcome, however no significant association was found with UPF availability. Studies relating UPF availability and health outcomes are focused on overweight and obesity. It is necessary to further explore the relationship between other health outcomes and UPF availability using purchase or sales data.

Abstract 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.

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Objective:The aim of the current study was to evaluate energy intake misreporting prevalence, its associated factors and its effects on nutrient intake, in the Portuguese population aged from 18 to 84 years.Design:Cross-sectional study.Setting:Portugal.Subjects:Adults participants from the National Food, Nutrition and Physical Activity Survey, IAN-AF, 2015–2016, who provided two complete 24 h dietary recall and complete covariate information.Results:Under, plausible and over-reporters were identified according to the Goldberg method. Total misreporting prevalence was 29·9 %, being 28·5 % of under-reporting and 1·4 % of over-reporting. The current study found higher odds of being classified as an under-reporter especially in participants with higher BMI and in those who self-reported health perception status as non-favourable. Energy intake estimation increases by 853.5 kJ/d (204 kcal/d) when misreporters are excluded, and the same tendency is observed for macro and micronutrients. It is worth mentioning that the prevalence of inadequacy for protein intake decreases by about 5 % when considering plausible reporters.Conclusions:The exclusion of misreporters has a small impact on the crude energy and nutrient estimates as well as on assessing the contribution of nutrients to total energy intake. However, a moderate impact was observed in the estimation of nutrient inadequacy prevalence.