Purpose Dietary behaviours may be influenced by perceptions of barriers to healthy eating. Using data from a large cross-European study (N = 5900), we explored associations between various perceived barriers to healthy eating and dietary behaviours among adults from urban regions in five European countries and examined whether associations differed across regions and socio-demographic backgrounds. Methods Frequency of consumption of fruit, vegetables, fish, fast food, sugar-sweetened beverages, sweets, breakfast and home-cooked meals were split by the median into higher and lower consumption. We tested associations between barriers (irregular working hours; giving up preferred foods; busy lifestyle; lack of willpower; price of healthy food; taste preferences of family and friends; lack of healthy options and unappealing foods) and dietary variables using multilevel logistic regression models. We explored whether associations differed by age, sex, education, urban region, weight status, household composition or employment. Results Respondents who perceived any barrier were less likely to report higher consumption of healthier foods and more likely to report higher consumption of fast food. ‘Lack of willpower’, ‘time constraints’ and ‘taste preferences’ were most consistently associated with consumption. For example, those perceiving lack of willpower ate less fruit [odds ratio (OR) 0.57; 95% confidence interval (CI) 0.50–0.64], and those with a busy lifestyle ate less vegetables (OR 0.54; 95% CI 0.47–0.62). Many associations differed in size, but not in direction, by region, sex, age and household composition. Conclusion Perceived ‘lack of willpower’, ‘time constraints’ and ‘taste preferences’ were barriers most strongly related to dietary behaviours, but the association between various barriers and lower intake of fruit and vegetables was somewhat more pronounced among younger participants and women.

Background: Obesogenic food environments may influence dietary behaviours and contribute to obesity. Few countries quantified changes in their foodscape. We explored how the availability of different types of food retailers has changed in the Netherlands across levels of neighbourhood socioeconomic status (SES) and urbanisation. Methods: This longitudinal ecological study conducted in the Netherlands had as unit of analysis administrative neighbourhoods. From 2004 to 2018, the geographic location and type of each food retailer were objectively assessed by a commercial company. Food retailers were categorised as local food shops, fast food restaurants, food delivery, restaurants, supermarkets, and convenience stores. Information on neighbourhood SES and urbanisation was obtained from Central Bureau of Statistics (CBS). To test the change in the counts of food retailers we used negative binomial generalized estimating equations (GEE), with neighbourhoods as the group variable, time as the independent variable and the counts of each type of food retailer as outcome. To account for changes in population density, analyses were adjusted for the number of inhabitants per neighbourhood. We tested effect modification by adding an interaction term for neighbourhood SES and urbanisation to the models. Results: In Dutch neighbourhoods between 2004 and 2018, a 120 and 35% increase was found in the count of food delivery outlets and restaurants, respectively, and a 24% decrease in count of local food shops. Stratified analyses showed an increase in the availability of supermarkets and convenience stores in the more urbanised and lower SES neighbourhoods, while a decrease was observed in the less urbanised and higher SES neighbourhoods. Conclusions: We observed considerable changes in the Dutch foodscape. Over a 14 years period, the foodscape changed towards a higher availability of food retailers offering convenience and ready-to-eat foods. These findings can help policy makers aiming to promote a healthier food environment and obesity prevention.

Previous studies have explored the relationships of air pollution and metabolic profiles with lung function. However, the metabolites linking air pollution and lung function and the associated mechanisms have not been reviewed from a life-course perspective. Here, we provide a narrative review summarising recent evidence on the associations of metabolic profiles with air pollution exposure and lung function in children and adults. Twenty-six studies identified through a systematic PubMed search were included with 10 studies analysing air pollution-related metabolic profiles and 16 studies analysing lung function-related metabolic profiles. A wide range of metabolites were associated with short- and long-term exposure, partly overlapping with those linked to lung function in the general population and with respiratory diseases such as asthma and COPD. The existing studies show that metabolomics offers the potential to identify biomarkers linked to both environmental exposures and respiratory outcomes, but many studies suffer from small sample sizes, cross-sectional designs, a preponderance on adult lung function, heterogeneity in exposure assessment, lack of confounding control and omics integration. The ongoing EXposome Powered tools for healthy living in urbAN Settings (EXPANSE) project aims to address some of these shortcomings by combining biospecimens from large European cohorts and harmonised air pollution exposure and exposome data.

The aim of this study was to validate a Dutch commercial dataset containing information on the types and locations of food retailers against field audit data. Field validation of a commercial dataset (“Locatus”) was conducted in February 2019. Data on the location and classification of food retailers were collected through field audits in 152 streets from four urban and four rural neighborhoods in the Netherlands. The classification of food retailers included eight types of grocery stores (e.g., supermarkets, bakeries) and four types of food outlets (e.g., cafés, take away restaurants). The commercial dataset in the studied area listed 322 food retailers, whereas the field audit counted 315 food retailers. Overall, the commercially available data showed “good” to “excellent” agreement statistics (>0.71) with field audit data for all three levels of analysis (i.e., location, classification and both combined) and across urban as well as rural areas. The commercial dataset under study provided an accurate description of the measured food environment. Therefore, policymakers and researchers should feel confident in using this commercial dataset as a source of secondary data.

Objective The association between screen time and dietary patterns and overweight/obesity among adolescents was analysed in this study. Methods In this cross-sectional study, 963 Brazilian adolescents, aged between 11 and 14 years were evaluated. Body mass index was used to assess overweight/obesity. Dietary patterns and screen time were assessed using qualitative questionnaires. Principal component analysis was used to obtain dietary patterns. Confounder variables were: type of school (public or private), sexual maturation, mother’s weight and mother’s education. The Chi-square test was used for the crude analysis; for the adjusted analysis was used Poisson regression with sample weighting. Results Overweight/obesity prevalence was 29.8% and statistically higher among boys (34.7%). Higher screen time prevalence was 39.1%. The dietary patterns obtained were: obesogenic; coffee and dairy products; traditional Brazilian meal; fruit and vegetables; bread and chocolate milk. The dietary pattern that more closely represented student food consumption was the obesogenic pattern. Screen time was not significantly associated with overweight/obesity. The obesogenic pattern (in both sexes), the coffee and dairy products pattern, and the bread and chocolate milk pattern (only in girls), were inversely associated with overweight/obesity. In this study, dietary patterns influenced overweight/obesity, although in some cases, in an inverse way from what expected. Conclusion A high prevalence of overweight/obesity and a high proportion of screen time activities among the adolescents were observed. Our results indicate a high consumption of unhealthy dietary pattern among adolescents.