This study evaluated changes in the use of sweeteners over one decade and the relationship between socio-demographics, diet and weight status with the type of sweetener. Data came from the Brazilian National Dietary Surveys of 2008–2009 and 2017–2018, including ≥ 10-year-old individuals (n 32 749; n 44 744, respectively, after excluding pregnant and lactating women). The use of table sugar, non-caloric sweeteners (NCS), both or none was reported through a specific question. Food consumption was assessed using two non-consecutive food records (2008–2009) and 24-h recalls (2017–2018). For the last survey, means of energy, macro and micronutrient intake, food groups’ contribution (%) to daily energy intake and age- and energy-adjusted nutrient intake were estimated according to the type of sweetener used. Differences in means and proportions across the categories of sweeteners used were evaluated based on the 95 % CI. All analyses were stratified by sex and considered sample design and weights. Over 10 years, the use of table sugar decreased by 8 %, while the habit of not using any sweetener increased almost three times, and the use of NCS remained stable. Larger reductions in the use of table sugar were observed in the highest income level and among men. Regardless of sex, compared with NCS users, table sugar users had greater mean intake of energy, carbohydrates and added sugar and lower micronutrient intake means. Although table sugar is still the most used sweetener, the increased choice of ‘no sweetener’ is noteworthy in Brazil.

The WHO encourages countries to conduct national dietary surveys (NDS) to inform preventative policies targeting malnutrition and noncommunicable diseases. Previous reviews have found inadequate nutrient intakes and survey provision across Europe. This research is the first to provide an updated review of NDS provision within the whole WHO European Region, across the lifecourse, with reference to disadvantaged groups, obesity and nutrients of concern. Over a third of WHO European countries, mainly Central and Eastern European countries (CEEC), had no identifiable NDS. Where countries reported nutrient intakes, poor WHO recommended nutrient intake attainment was Europe-wide across the lifecourse, particularly in CEEC. Lower educated individuals had poorer diet quality. However, heterogeneity in age group sampled, dietary assessment method, nutrient composition database and under-reporting hindered inter-country comparisons. Average population trans fatty acid intakes below WHO recommended limits may hide inequalities in disadvantaged groups; legislative bans may help alleviate this. There were few associations between NDS-derived consumed food portion size (FPS) and BMI. However, consumed FPS was greater than on-pack serving-size in the majority of foods studied. This review illustrates how NDS can generate information on diet, nutrient intakes and the food environment. However, to enable valid inter-country comparisons, countries should be encouraged to conduct and report harmonised NDS, particularly in the age groups sampled, dietary assessment methodology, nutrient range, underpinning food composition database and treatment of under-reporters. This will aid effective, coordinated policy development that can have a real impact on dietary improvement, on a population and subgroup level, throughout Europe.

Dietary patterns derived by statistical procedures is a way to identify overall dietary habits in specific populations. The aim of this study was to identify and characterise dietary patterns in Swedish adults using data from the national dietary survey Riksmaten adults 2010–11 (952 women, 788 men). Principal component analyses were used and two patterns were identified in both sexes: a healthy pattern loading positively on vegetables, fruits, fish and seafood, and vegetable oils, and negatively on refined bread and fast food, and a Swedish traditional pattern loading positively on potatoes, meat and processed meat, full-fat milk products, sweet bakery products, sweet condiments and margarine. In addition, a light-meal pattern was identified in women with positive loadings on fibre-rich bread, cheese, rice, pasta and food grain dishes, substitute products for meat and dairy products, candies and tea. The healthy pattern was positively correlated to dietary fibre (r 0·51–0·58) and n-3 (r 0·25–0·31) (all P<0·0001), and had a higher nutrient density of folate, vitamin D and Se. The Swedish traditional and the light-meal pattern were positively correlated to added sugar (r 0·20–0·25) and the Swedish traditional also to SFA (r 0·13–0·21) (all P<0·0001); both patterns were in general negatively correlated to micronutrients. Dietary pattern scores were associated with, for example, age, physical activity, education and income. In conclusion, we identified three major dietary patterns among Swedish adults. The patterns can be further used for examining the association between whole diet and health outcomes.

In the interpretation of dietary trends, it is important to consider the potential effect of modifications in the dietary assessment method. Therefore, our objective was to explore the comparability of data obtained at two time points by a semi-quantitative FFQ (SFFQ) which has had slight modifications over time. In the national dietary surveys among Norwegian 2-year-olds, diet was assessed by an SFFQ which underwent modifications between the 1999 survey and the 2007 survey. In the present study, fifty-nine families with a 2-year-old child participated by completing both the SFFQ in a crossover design within a month's time. With regard to the reported intake of energy and nutrients, the largest significant differences observed between the two questionnaires were for carbohydrates and added sugar. According to intake of food groups, significant differences were observed for five out of sixteen food groups. Spearman's correlation coefficients for energy, nutrients and food groups ranged from 0·43 (Ca) to 0·85 (soft drinks). Most Bland–Altman plots indicated broad limits of agreement. The differences between the two questionnaires can be explained by changes in the questionnaires, changes in the food composition databases used and random variation. Comparing differences between the questionnaires by maternal educational level, number of children and type of day care revealed minor differences. In conclusion, this study showed that at the group level there was reasonable comparability between the two questionnaires, except for carbohydrates, added sugar and some food groups. Moreover, there were moderate to high correlations for energy, nutrients and food groups.