Changing the default order of food items in an online grocery store may nudge healthier food choices.

Restructuring food environments, such as online grocery stores, has the potential to improve consumer health by encouraging healthier food choices. The aim of this study was to investigate whether repositioning foods within an experimental online grocery store can be used to nudge healthier choices. Specifically, we investigated whether repositioning product categories displayed on the website main page, and repositioning individual products within those categories, will influence selection. Adults residing in Australia (n = 175) were randomised to either intervention (high-fibre foods on top) or comparator condition (high-fibre foods on the bottom). Participants completed a shopping task using the experimental online grocery store, with a budget of up to AU$100 to for one person's weekly groceries. The results of this study show that the total fibre content per 100 kcal per cart (p < .001) and total fibre content per cart (p = .036) was higher in the intervention compared to comparator condition. Moreover, no statistical difference between conditions was found for the total number of fibre-source foods (p = .67), the total energy per cart (p = .17), and the total grocery price per cart (p = .70) indicating no evidence of implications for affordability. Approximately half of the participants (48%) reported that they would like to have the option to sort foods based on a specific nutrient criterion when shopping online. This study specifically showed that presenting higher-fibre products and product categories higher up on the online grocery store can increase the fibre content of customers' purchases. These findings have important implications for consumers, digital platform operators, researchers in health and food domains, and for policy makers.

SnackTrack-An App-Based Tool to Assess the Influence of Digital and Physical Environments on Snack Choice.

As food choices are usually processed subconsciously, both situational and food environment cues influence choice. This study developed and tested a mobile app to investigate the association between physical and digital environments on snack choices. SnackTrack was designed and used to collect data on the snack choices of 188 users in real-life settings during an 8-week feasibility trial. The app asks users to take a photo of the food they are planning to consume and to provide additional information regarding the physical environment and context in which this food was eaten. The app also displayed various user interface designs (i.e., different background images) to investigate the potential effects of images on snack choice. Preliminary results suggest that the time of snack obtainment did not have a significant effect on the healthfulness of the snacks chosen. Conversely, it was found that unhealthy background images appeared to encourage healthier snack choices. In conclusion, despite consumers having the knowledge to make healthy choices, environmental cues can alter food choices. SnackTrack, a novel tool to investigate the influence of physical and digital environments on consumers' food choices, provides possibilities for exploring what encourages (un)healthy eating behaviours.

CafeteriaSA corpus: scientific abstracts annotated across different food semantic resources.

In the last decades, a great amount of work has been done in predictive modeling of issues related to human and environmental health. Resolution of issues related to healthcare is made possible by the existence of several biomedical vocabularies and standards, which play a crucial role in understanding the health information, together with a large amount of health-related data. However, despite a large number of available resources and work done in the health and environmental domains, there is a lack of semantic resources that can be utilized in the food and nutrition domain, as well as their interconnections. For this purpose, in a European Food Safety Authority-funded project CAFETERIA, we have developed the first annotated corpus of 500 scientific abstracts that consists of 6407 annotated food entities with regard to Hansard taxonomy, 4299 for FoodOn and 3623 for SNOMED-CT. The CafeteriaSA corpus will enable the further development of natural language processing methods for food information extraction from textual data that will allow extracting food information from scientific textual data. Database URL: https://zenodo.org/record/6683798#.Y49wIezMJJF.

CafeteriaFCD Corpus: Food Consumption Data Annotated with Regard to Different Food Semantic Resources.

Besides the numerous studies in the last decade involving food and nutrition data, this domain remains low resourced. Annotated corpuses are very useful tools for researchers and experts of the domain in question, as well as for data scientists for analysis. In this paper, we present the annotation process of food consumption data (recipes) with semantic tags from different semantic resources-Hansard taxonomy, FoodOn ontology, SNOMED CT terminology and the FoodEx2 classification system. FoodBase is an annotated corpus of food entities-recipes-which includes a curated version of 1000 instances, considered a gold standard. In this study, we use the curated version of FoodBase and two different approaches for annotating-the NCBO annotator (for the FoodOn and SNOMED CT annotations) and the semi-automatic StandFood method (for the FoodEx2 annotations). The end result is a new version of the golden standard of the FoodBase corpus, called the CafeteriaFCD (Cafeteria Food Consumption Data) corpus. This corpus contains food consumption data-recipes-annotated with semantic tags from the aforementioned four different external semantic resources. With these annotations, data interoperability is achieved between five semantic resources from different domains. This resource can be further utilized for developing and training different information extraction pipelines using state-of-the-art NLP approaches for tracing knowledge about food safety applications.

Inadequate Intake of Dietary Fibre in Adolescents, Adults, and Elderlies: Results of Slovenian Representative SI. Menu Study.

Dietary fibre has proven to promote healthy body mass and reduce the risk of non-communicable diseases. To date, in Slovenia, there were only a few outdated studies of dietary fibre intake; therefore, we explored the dietary fibre intake using food consumption data collected in the SI.Menu project. Following the EU Menu methodology, data were collected on representative samples of adolescents, adults, and elderlies using a general questionnaire, a food propensity questionnaire, and two 24 h recalls. The results indicate that the intake of dietary fibre in Slovenia is lower than recommended. The proportion of the population with inadequate fibre intakes (<30 g/day) was 90.6% in adolescents, 89.6% in adults, and 83.9% in elderlies, while mean daily fibre intakes were 19.5, 20.9, and 22.4 g, respectively. Significant determinants for inadequate dietary fibre intake were sex in adolescents and adults, and body mass index in adults. The main food groups contributing to dietary fibre intake were bread and other grain products, vegetables and fruits, with significant differences between population groups. Contribution of fruits and vegetables to mean daily dietary fibre intake was highest in elderlies (11.6 g), followed by adults (10.6 g) and adolescents (8.5 g). Public health strategies, such as food reformulation, promoting whole-meal alternatives, consuming whole foods of plant origin, and careful planning of school meals could beneficially contribute to the overall dietary fibre intake in the population.

Impact of COVID-19 confinement on eating behaviours across 16 European countries: The COVIDiet cross-national study.

We aimed to evaluate the changes in eating behaviours of the adult population across 16 European countries due to the COVID-19 confinement and to evaluate whether these changes were somehow related to the severity of the containment measures applied in each country. An anonymous online self-reported questionnaire on socio-demographic characteristics, validated 14-items Mediterranean diet (MedDiet) Adherence Screener (MEDAS) as a reference of a healthy diet, eating and lifestyle behaviours prior to and during the COVID-19 confinement was used to collect data. The study included an adult population residing in 16 European countries at the time of the survey. Aggregated Stringency Index (SI) score, based on data from the Oxford COVID-19 Government Response Tracker, was calculated for each country at the time the questionnaire was distributed (range: 0-100). A total of 36,185 participants completed the questionnaire (77.6% female, 75.2% with high educational level and 42.7% aged between 21 and 35 years). In comparison to pre-confinement, a significantly higher adherence to the MedDiet during the confinement was observed across all countries (overall MEDAS score prior to- and during confinement: 5.23 ± 2.06 vs. 6.15 ± 2.06; p < 0.001), with the largest increase seen in Greece and North Macedonia. The highest adherence to MedDiet during confinement was found in Spain and Portugal (7.18 ± 1.84 and 7.34 ± 1.95, respectively). Stricter contingency restrictions seemed to lead to a significantly higher increase in the adherence to the MedDiet. The findings from this cross-sectional study could be used to inform current diet-related public health guidelines to ensure optimal nutrition is followed among the population, which in turn would help to alleviate the current public health crisis.

FoodEx2vec: New foods' representation for advanced food data analysis.

In food and toxicology science, a huge amount of research and other data has been collected. To enable its full utilization, advanced statistical and computer methods are required. All data is related to food items, but additionally include different kinds of information. Nowadays the consumption of avocado has increased. To understand the full impact of this increased consumption on public health and the environment, different data related to avocado need to be considered. In this paper, we present an approach for representing foods in the form of vectors of continuous numbers (food embeddings) as an alternative solution to manual indexing. The utility of representing food data as a vector of continuous numbers was evaluated and demonstrated in four tasks: i) automated determination of different food groups, ii) automated detection of the food class for each food concept (raw, derivative or composite), iii) identification of most similar food concepts for a given food concept, and iv) qualitative evaluation by a food expert. The experimental results showed that these kind of vector representations outperform the traditional representational methods used for food data analysis, and thus they present a step forward to more advanced food data analysis used for discovering new knowledge.