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.

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.

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.

This study aimed to evaluate the risk of the Portuguese population’s exposure to six non-nutritive intense sweeteners (NNIS) and their main associated factors. A tiered approach was used to estimate the usual exposure to the NNIS obtained from two 1-day food diaries among children and two 24-hour recalls among adults in the Portuguese national dietary survey (IAN-AF 2015–2016; age: 3–84 y; n = 5005). The tiers considered were the following: Tier 2.1 represents the most conservative tier, in which all foods reported were matched with the respective maximum permitted levels (MPLs); in Tier 2.2, the MPLs were attributed only to the foods for which the brand’s label information identified the presence of an added NNIS; finally, Tier 3 was identical to Tier 2.2, but analytical NNIS occurrence data were used, instead of MPLs. The usual exposure of the Portuguese population to each NNIS was very low in all tiers across all age groups, as was the estimated prevalence of exposure above the acceptable daily intake. Soft drinks were the main source of exposure for most sweeteners, and acesulfame K and aspartame were the most consumed NNIS. The odds of exposure to at least one NNIS were higher in more highly educated adults and elderly, obese elderly, women, and people with lower healthy diet scores. The estimated risk of exceeding the safety levels of NNIS intake was very low in all evaluated population groups, even when considering the most conservative approach.

Bisphenol A (BPA) is an endocrine disruptor used in food contact materials, by the application of polycarbonate plastics and epoxy resins. The main objective of this study is to compare the estimate of daily BPA exposure at 13 years of age and in the adult Portuguese population, using different methodological approaches, and assess the associations between this exposure and sociodemographic characteristics. Methodology: Cross-sectional data of 13-years follow-up from a population-based birth cohort Generation XXI (GXXI) (n = 2804) and from the National Food, Nutrition and Physical Activity Survey (IAN-AF 2015–2016) (n = 3845, ≥18 years old) was used. Dietary information was collected through three food diaries for adolescents and two non-consecutive 24-hour-recalls for adults. To estimate the daily exposure to BPA, three methodological approaches were used. “Food groups attribution” merged the food consumption data with the concentration of BPA in food groups. “Regression tree model” and “random forest” combined food consumption information with urinary BPA, measured in a subsample of 24-hour urine (in adolescents n = 216, and in adults n = 82), both used to predict BPA exposure in the remaining sample. The fit-index of the methodologies was assessed through the root mean square error (RMSE), mean absolute error (MAE) and Spearman correlation coefficient (ρ). Associations between BPA exposure and sociodemographic variables were tested by linear regression models, adjusted for sex, age groups (in adults) and educational level. Tolerable Daily Intake (TDI) of 0.2 ng/kg body weight (bw), recently proposed by the European Food Safety Authority (EFSA), was used for the risk characterization of BPA exposure. Results: The “random forest” was found as the best methodology to estimate the daily BPA exposure (adolescents: RMSE = 0.989, MAE = 0.727, ρ = 0.168; adults: RMSE = 0.193, MAE = 0.147, ρ = 0.250). The median dietary BPA exposure, calculated by “food groups attribution”, was 79.1 and 46.1 ng/kg bw/day for adolescents and adults, respectively, while “random forest” estimated a BPA exposure of 26.7 and 38.0 ng/kg bw/day. 99.9% of the Portuguese population presented a daily exposure above TDI. Male adolescents, females and higher educated adults, were those more exposed to BPA. Conclusions: The estimated daily BPA exposure strongly depends on the methodological approach. Food groups attribution may overestimate the exposure while the random forest appears to be a better methodological approach to estimate BPA exposure. Nevertheless, for all methods, the Portuguese population presented an unsafe BPA exposure by largely exceeding the safe levels proposed by EFSA.

Ultra-processed foods (UPF) consumption has been associated with unhealthy outcomes. However, the literature lacks robust longitudinal studies considering its cumulative effect, particularly in young populations. This study aimed to evaluate the relationship between UPF consumption patterns throughout childhood with growth and adiposity trajectories. Generation XXI population-based birth cohort (Porto, Portugal) participants were included. Food frequency questionnaire items at 4, 7 and 10 years were classified according to the processing degree using NOVA. UPF consumption patterns based on total quantity were identified using a probabilistic Gaussian mixture model using participants with complete data and predicting for the total sample (n = 8647). To assess whether the outcome trajectories from 4 to 13 years [body weight (kg), height (cm), body mass index (BMI) z-score, waist circumference (WC) (cm) and fat mass (FM) (%)] depend on UPF patterns, a mixed-effects model with linear and quadratic terms for age adjusted for confounders was used. Participants with at least 2 measurements at 4, 7, 10 or 13 years were included in this study (n range: 5885-6272). Four UPF consumption patterns were identified: constantly lower consumption (15.4%), constantly intermediate consumption (56.4%), transition from low to high consumption (11.2%), and constantly higher consumption (17.1%). Compared to the constantly lower UPF consumption, the constantly higher consumption pattern was associated with greater acceleration in body weight (β: 0.119; 95%CI: 0.027; 0.212), BMI z-score (β: 0.014; 95%CI: 0.004; 0.023), WC (β: 0.232; 95%CI: 0.144; 0.319) and FM% (β: 0.200; 95%CI: 0.092; 0.308) and with lower acceleration in height (β: -0.063; 95%CI: -0.111;-0.015). The constantly intermediate UPF consumption pattern was associated with greater acceleration in body weight (β: 0.123; 95%CI: 0.043; 0.203), WC (β: 0.120; 95%CI: 0.045; 0.195) and FM% (β: 0.146; 95%CI: 0.054; 0.238). Constantly higher and constantly intermediate UPF consumption throughout childhood were associated with worse growth and adiposity trajectories until adolescence.