We aimed to assess the dietary Fe intake and the prevalence of inadequate Fe intake over two post-fortification periods in Brazil. The intake was analysed according to sex, life stage, geographic region and stratum of family income per capita. Excluding pregnant and lactating women, this population-based study included 32 749 and 44 744 participants aged ≥ 10 years from the National Dietary Survey-Brazilian Household Budget Surveys 2008–2009 and 2017–2018, respectively. The National Cancer Institute method was used to predict usual dietary Fe intakes. The prevalence of Fe intake inadequacy was estimated following a probabilistic approach for women of childbearing age or with the Estimated Average Requirement cut-off point method. Over an interval of 10 years, the mean Fe intake remained almost unchanged for most sex-age groups, except for women of childbearing age. In this specific group, the prevalence of Fe intake inadequacy was > 20 % in 2008–2009 and have increased to > 25 % in 2017–2018, with the highest reductions in mean Fe intake found in the highest income strata and richest Brazilian regions. Meanwhile, the highest prevalence of Fe intake inadequacy (> 40 %) occurred among the poorest women aged 31–50 years from the lowest family income stratum, irrespective of the study period. Beans were the main Fe source, while fortified breads, pastas, pizzas, cakes and cookies contributed approximately 40 % of the Fe intake. The results provide important insights into the long-standing dietary impacts of food fortification, which can guide future (re)formulation of effective public health strategies to combat Fe deficiency.

Assessing the dietary intake of polyphenols and their major food sources is the first step towards documenting the associations with health outcomes. Considering recent changes in dietary patterns of the Brazilian population, continuous monitoring of polyphenol intake is important. Thus, the present study was conducted to estimate the polyphenol intake and major food sources in the diet of the Brazilian population using data from the most recent National Dietary Survey (NDS, 2017–2018), to characterise the intake changes according to demographic characteristics and to compare the intake over the past decade in Brazil. Data from two cross-sectional population-based surveys were analyzed in the study. Trends in polyphenol intake and major food sources were estimated using food consumption data from NDS 2008–2009 (n 34 003) and 2017–2018 (n 46 164). The median (25–75th percentiles) of energy-adjusted polyphenol intake in 2017–2018 was 216·3 mg (125·3–495·2 mg) per 1000 kcal/d (4184 kJ/d), representing an increase of 12·3 mg/d from 2008–2009. However, unadjusted polyphenol intakes were similar between the surveys (medians: 364·3 mg/d in 2008–2009 and 366·9 mg/d in 2017–2018). The main food sources of total and polyphenol intake classes presented some variations between 2008–2009 and 2017–2018, with greater contribution of beans preparations, salads and tea to polyphenol intake, and decrease of orange contribution. Our study provided an updated information on polyphenol intake and its major food sources. The median intake remains lower than the reported by other populations. Furthermore, the results may contribute to future studies investigating temporal trends in polyphenol intake and disease risk.

Examining the composition of breakfast concerning weight status is essential for evaluating adolescent health and understanding this gap. This study aimed to identify breakfast patterns and investigate the relationship with weight status among Brazilian adolescents. We used a subsample of 7425 adolescents aged 10–19 years from the 2008–2009 Brazilian Household Budget Survey. Breakfast eaters were those with intake of at least 50 kcal (209·2 kJ) between 05.00 and 10.00 hours. Breakfast dietary patterns were derived by principal component factor analysis with varimax rotation. We performed logistic regression analyses between breakfast patterns and weight status, considering the complexity of the survey sample design. Three breakfast patterns were identified explaining 44·8 % of data variability: (1) the Cereal, protein, fruit beverages and Northern/Northeastern pattern, characterised by high consumption of cookies, meats, dairy products, preparations with maize, eggs, fruit juices/fruit drinks/soya-based drinks, tubers/roots/potatoes and cereals, and negative adherence to cold cut meat and savoury snacks/crackers; (2) the Protein-based pattern, characterised by positive loadings for cold cut meat, milk and cheese, and negative for cookies, fruit juices/fruit drinks/soya-based drinks, tubers/roots/potatoes and cereals; and (3) the Mixed pattern, with positive loadings for cakes, coffee/tea, bread, fruit juices/fruit drinks/soya-based drinks, chocolate/desserts and savoury snacks/crackers. No association was found between skipping and weight status. Overweight adolescents had lower adherence to the Cereal, protein, fruit beverages and Northern/Northeastern pattern (OR = 0·67; 95 % CI 0·47, 0·96). This is the first study to address dietary patterns at the meal level with adolescent population-based data, which requires further investigation.

The aim was to design culturally acceptable and healthy diets with reduced energetic share of ultra-processed foods (UPF%) at no cost increment and to evaluate the impact of the change in the UPF% on diet quality. Food consumption and price data were obtained from the Household Budget Survey (n 55 970 households) and National Dietary Survey (n 32 749 individuals). Linear programming models were performed to design diets in which the mean population UPF% was reduced up to 5 % with no cost increment relative to the observed costs. The models were isoenergetic or allowed the energy content to vary according to the UPF%, and they were not constrained to nutritional goals (nutrient-free models) or maximised the compliance with dietary recommendations (nutrient-constrained models). Constraints regarding food preference were introduced in the models to obtain culturally acceptable diets. The mean population UPF% was 23·8 %. The lowest UPF% attained was approximately 10 %. The optimised diet cost was up to 20 % cheaper than the observed cost, depending on the model and the income level. In the optimised diets, the reduction in the UPF% was followed by an increase in fruits, vegetables, beans, tubers, dairy products, nuts, fibre, K, Mg, vitamin A and vitamin C in the nutrient-constrained models, compared with the observed consumption in the population. There was little variation in most nutrients across the UPF% reduction. The UPF% reduction in the nutrient-free models impacted only trans-fat and added sugar content. UPF% reduction and increase in diet quality are possible at no cost increment.