Availability and properties of commercially produced food products offered in European public universities: A North–South comparison

Received: 1 December 2023 Revised: 15 February 2024 Accepted: 21 February 2024 DOI: 10.1111/1750-3841.17022 ORIGINAL ARTICLE Health, Nutrition, and Food Availability and properties of commercially produced food products offered in European public universities: A North–South comparison Naiara Martinez-Perez1,2LivElinTorheim 3Marta Arroyo-Izaga2,4,5 1Department of Nursing I, Faculty of Medicine and Nursing, University of the Basque Country UPV/EHU, Leioa, Spain 2BIOMICs Research Group, Microfluidics & BIOMICs Cluster, Lascaray Research Center, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain 3Department of Nursing and Health Promotion, Faculty of Health Sciences, OsloMet—Oslo Metropolitan University, Oslo, Norway 4Department of Pharmacy and Food Sciences, Faculty of Pharmacy, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain 5Bioaraba, BA04.03, Vitoria-Gasteiz, Spain Correspondence Marta Arroyo-Izaga, Department of Pharmacy and Food Sciences, Faculty of Pharmacy, University of the Basque Country UPV/EHU, Paseo de la Universidad 7, 01006 Vitoria-Gasteiz, Spain. Email: [email protected] Funding information Erasmus+; Storbyuniversitetet ; Euskal Herriko Unibertsitatea; Eusko Jaurlaritza Abstract: To date, there are no studies that have compared university food environments (FEs) with different sociocultural contexts. Therefore, we analyzed differences in the availability and properties of commercially produced foods, in a northern and a southern European university (located in Norway and Spain, respectively). A cross-sectional observational study was conducted at OsloMet— Oslo Metropolitan University and at the University of the Basque Country UPV/EHU. The nutritional quality of food products was estimated through the following nutrient profiling models (NPMs): those proposed by the Spanish Agency for Consumer Affairs, Food Safety and Nutrition (AECOSAN), the UK nutrient profiling model (UK NPM), the Norwegian Food and Drink Industry Professional Practices Committee (Matbransjens Fagligle Utvalg [MFU]), and a combination of them. In addition, food items were classified using the NOVA system. A total of 251 and 1051 products were identified at OsloMet and the UPV/EHU, respectively. The percentage categorized as low nutritional quality (LNQ) was higher at the UPV/EHU (almost 54.5% of the total products) compared with at OsloMet (almost 40%) (p<0.001). Most of the products were categorized as ultra-processed, and there were no differences in the percentage of ultra-processed foods between the two universities (OsloMet 86.1%, UPV/EHU 83.3%, p>0.05). A higher proportion of LNQ products was found at the UPV/EHU than at OsloMet, probably due to the government policies and actions for creating healthy FEs. Consequently, there is a need to develop interventions to improve the FE at the UPV/EHU, adapted to its sociocultural context. KEYWORDS food environment, food processing level, nutrient profiling model, public health, university food This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2024 The Authors. Journal of Food Science published by Wiley Periodicals LLC on behalf of Institute of Food Technologists. 2494 wileyonlinelibrary.com/journal/jfds J. Food Sci. 2024;89:2494–2511. CAMPUS FOOD ENVIRONMENTS IN EUROPE 2495 Practical Application: This study reveals north–south differences in terms of the availability of low nutritional quality food products. In particular, a higher proportion of this type of product was found at the University of the BasqueCountryUPV/EHUthanatOsloMet—OsloMetropolitanUniversity.Our exploratory hypothesis is that this phenomenon is a consequence of the Nordic government policies that have great potential to create healthy FEs. 1 INTRODUCTION The food environment (FE) has been defined as “the foods available to people in their surroundings as they go about their everyday lives and the nutritional quality, safety, price, convenience, labeling and promotion of these foods” (Food and Agriculture Organization of the United Nations—FAO, 2016). From a socio-ecological perspective, two key domains within the wider FE construct have been identified: the “external domain” and the “personal domain.” The external domain includes food availability, prices, vendor and product properties, and marketing and regulation. The personal domain includes food accessibility, affordability, convenience, and desirability. Interactions between these domains and dimensions determine people´s food acquisition and consumption (Caspi et al., 2012;Turneretal.,2018). Thus, the FE can affect people’s food purchasing and eating choices, as well as the quality of their diets and, in turn, diet-related health outcomes. Over the past decades, energy-dense and nutrient-poor food products and ultra-processed have become more available compared to fresh, minimally processed, or unprocessed foods, fostering obesogenic FEs in Europe and globally (Food and Agriculture Organization of the United Nations—FAO, 2016). Conversely, making the environment more conducive to healthy choices has the potential to be a key aspect of a successful obesity prevention intervention (Lake and Townshend, 2006). In particular, organizational FEs, such as schools and worksites, constitute a strategic setting for the implementation of comprehensive strategies, as they provide an appropriate infrastructure for the prevention of obesity and other nutrition-related diseases (Newton et al., 2016). In this sense, universities manage different food and catering establishments that serve a large number of workers and students (Doherty et al., 2011), where the latter group is at a high-risk period for weight gain. During the transition from high school to university, which coincides with the transition from adolescence to adult life, autonomous decision-making, and personal independencegrow(Holm-Denoma etal., 2008), andsome of the most important behaviors for adult life are modeled. Thus, university FE should positively influence individual food choices by making the healthy choice the easy choice. Studies conducted so far on campus indicate that these FEs are potentially obesogenic due to the high availability and promotion of energy-rich, nutrient-poor foods (Roy et al., 2016). These types of products are mostly commercially produced foods, that is, industrially manufactured foods, such as sweet or savory snack foods, or sweetened beverages. To date, few studies have assessed FE at the university level,andthesehavemainlybeencarriedoutinAustralian, New Zealand, and Latin America universities (Franco et al., 2020; Roy et al., 2019; Tam et al., 2017). There is a lack of research in European universities that evaluates the FE in depth, and none has compared different European universities. As sociocultural factors (that is, culture, economic variables, and political elements, among others) are decisive in food supply and choice (Chen & Antonelli, 2020), the comparison of tertiary education institutions with a different geographical location and sociocultural context can be of great interest to identify similarities and differences. Therefore, through this study, we aimed to analyze differences in the availability and properties (nutritional quality and processing level) of commercially produced foods, in a northern European and a southern European university (located in Norway and Spain, respectively). In discussing North–South differences, we attempted to provide plausible explanations considering the role of sociocultural aspects. In addition, we analyzed the agreement level between several nutrient profiling models (NPMs) and, among these NPMs andthe processing level of commercially produced food products sold in the universities mentioned. Considering the government’s measures to promote health and prevent disease through a healthier diet in both countries (Spain and Norway) (Pineda et al., 2022), we hypothesized that the percentage of foods of low nutritional quality (LNQ) and ultra-processed would be higher at the Spanish university than at the Norwegian 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2496 CAMPUS FOOD ENVIRONMENTS IN EUROPE university. On the other hand, because of the differences in the criteria of the NPMs, we hypothesized that the percentage of LNQ food products sold at both universities would vary considerably according to the models applied. For this reason, we decided to use a combination of the three selected NPMs. Finally, taking into account the evidence from other studies (Maldonado-Pereira et al., 2022; Martínez Steele et al., 2017) confirming the LNQ of ultra-processed products, we hypothesized that the LNQ food products would be mostly ultra-processed. 2 MATERIALS AND METHODS 2.1 Study design and setting The study is part of a broader investigation in which not only the external but also the personal domain of the FE was analyzed (Martinez-Perez & Arroyo-Izaga, 2021; Martinez-Perez et al., 2022a,2022b). It is a cross-sectional observationalstudyconductedattwoEuropeanpublicuniversities: OsloMet—Oslo Metropolitan University (located in Norway, northern Europe) and the University of the Basque Country UPV/EHU (located in Spain, southern Europe). Data were recorded at the UPV/EHU during the 2016/17 and 2017/18 academic years, and at OsloMet during the 2019/20 academic year. At OsloMet, data were registered before the start of the COVID-19pandemic,at the maincampusesintermsofstudents and staff numbers, which were the Pilestredet and Kjellercampuses. These twocampuseshad19,500 students and 2200 staff in the academic year 2019/20, whereas the campus excluded in the present study, the Sandvika campus, had about 500 students and only 1 employee (Oslo Metropolitan University, 2019). However, at the UPV/EHU, data were registered at its 3 campuses, which had a total of 42,218 students (degree students by campus: Álava/Araba 7163 students, Bizkaia 22,078, Gipuzkoa 10,119; and postgraduate students: Doctoral School located in Bizkaia Campus 2858 students) and 7453 staff (Álava/Araba Campus, 1233; Bizkaia Campus, 4460; and Gipuzkoa Campus, 1760) in the academic year 2016/17. The method used to record data was an audit, which is the most frequently reported method in the literature for measuring consumer FE (Lytle & Sokol, 2017). In the present study specifically, we used it to assess the availability of products and characterize their properties (nutritional quality and processing level). We chose to focus on these indicators for commercially produced food products offered on campus, as they provide essential information on the FE and can contribute to improving the interpretation of data collected in different realities (Ferreira et al., 2021). Permission to conduct the study was obtained from the Foundation for Student Life in Oslo and Akershus (Studentsamskipnaden i Oslo og Akershus— SiO) and Vice Management of Assets and Contracting of the UPV/EHU. 2.2 Registration of data at OsloMet A total of four canteens, three coffee shops, and two vending machines were analyzed at OsloMet. The distribution of food outlets by campus was as follows: eight on the Pilestredet campus (six canteens and two coffee shops) and four on the Kjeller campus (one canteen, one coffee shop, and two vending machines, one for hot drinks, and one for snacks). Thefood outletswithinPilestredetand Kjellercampuses were identified, thanks to the information provided by SiO. SiO is a student welfare organization that operates food services on all campuses of the universities of Oslo and Akershus (Norway). The list of foods and drinks and related information (product description, including flavor or ingredient variations, net weight, and brand) were also obtained through SiO (it should be noted that this list did not include hot drinks such as coffee or chocolate). 2.3 Registration of data at the UPV/EHU During the period in which data were recorded at the UPV/EHU, a total of 21 companies were subcontracted by the UPV/EHU to provide food services, 18 for cafeterias/restaurants/canteens, 2 for vending machines, and 1 for the supermarket service. The distribution of food outlets by campus was as follows: 16 on the Álava/Araba campus (5 cafeterias/restaurants/canteens and 11 vending machines), 37 on the Bizkaia campus (8 cafeterias/restaurants/canteens, 1 supermarket, and 26 vending machines), and 27 on the Gipuzkoa campus (7 cafeterias/restaurants/canteens and 20 vending machines). These subcontracted companies did not change during the study period, and nor did the price of the products, except for the prices for three out of seven cafeterias/restaurants/canteens on the campus of Bizkaia. In total, 203 vending machines, 20 cafeterias/restaurants/canteens, and 1 supermarket were analyzed at the UPV/EHU. In the present study, we did not include 24 vending machines that are not usually accessed by undergraduate students because they are in buildings earmarked for research, and 2 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License CAMPUS FOOD ENVIRONMENTS IN EUROPE 2497 cafeterias/restaurants because the companies in charge of these services were not contracted by the UPV/EHU. Data from cafeterias/restaurants/canteens and the supermarket were obtained through interviews with the staff in charge of these services by a single interviewer, and data from vending machines were recorded by a single observer at the point of sale. In both cases, data were collected through forms developed for this study before data registration (these forms are available from the corresponding author on reasonable request). The following information was recorded: product name (including flavor or ingredient variations, such as barbecue potato chips), brand, net weight, ingredients, and price. However, price data were not included in this manuscript. In the case of vending machines, for the data recording at the UPV/EHU, in addition to the form, photographs also were takeninsitu. 2.4 Data processing of commercially produced food supply in outlets of OsloMet and the UPV/EHU From the data registered in both universities, information on ingredients, ingredient percentage (if available), and nutrition labeling information (if available) were obtained by consulting product labeling and/or the manufacturer’s website. Food products sold were categorized according to the document on food in schools developed by the Spanish Agency for Consumer Affairs, Food Safety and Nutrition (AECOSAN) (2010) and the Global Food Monitoring Group food categorization system (Dunford et al., 2012)(TableS1). Each food product offered was counted once, and only the product categories available at both universities were included in the analysis of the current study. Solid foods and beverages were analyzed separately. Hot drinks were not included in this study, not even those from vending machines, because the amount of added sugar could be variable. Table S2 shows the food and drink categories were excluded from the analysis, as they were only sold at UPV/EHU. No product category was only offered at OsloMet. An overview of the methods, recorded data, estimated variables, and data derived related to the food supply in outlets at the UPV/EHU and OsloMet are shown in Table 1. Nutritional information on the products sold in outlets from both universities was also obtained from different sources, as follows (in order of preference): nutrition labeling, the manufacturer’s website, and/or food composition database from each of the countries. As far as food composition databases are concerned, for the products offered at OsloMet, Kostholdsplanleggeren (Norwegian Directorate of Health & Norwegian Food Safety Authority, 2023) was used, and for those offered at the UPV/EHU, the DIAL program 2.12 (Ortega et al., 2016). This last program was completed with the food composition tables of Mataix (2009) whenever necessary. In those products in which trans fatty acid (TFA) data were not available in the nutrition labeling, nor on the manufacturer’s website, or in the food composition databases, they were estimated using the report “Content of Trans Fatty Acids in Foods in Spain, 2015” (Spanish Agency for ConsumerAffairs,FoodSafety and Nutrition[AECOSAN], 2016), and the food composition database of the United States Department of Agriculture, Agricultural Research Service (USDA) (2019). For both universities, from the nutritional information of each product, the energy content and the following nutrients were estimated: proteins, sugars, dietary fiber, total fat, TFA, saturated fatty acids (SFA), and sodium content. In addition, fruit, vegetable, and nut content were estimated. These data were calculated per 100 g of product. 2.5 Analysis of the nutritional quality and processing level of the commercially produced food supply in outlets of OsloMet and the UPV/EHU To indicate the nutritional quality of each food or drink item, the following NPMs were used: those proposed by the Spanish Agency for Consumer Affairs, Food Safety and Nutrition (AECOSAN) (2010), the UK NPM (Department of Health of the United Kingdom, 2011), and those of the NorwegianFoodandDrinkIndustryProfessionalPractices Committee (Matbransjens Fagligle Utvalg—[MFU] [Norwegian Food and Drink Industry Professional Practices Committee], 2013). The former criteria are those designed for the food supply present in vending machines, canteens, and kiosks in education centers. The AECOSAN criteria have six components: energy, total fat, SFA, TFA, sugar, and salt. These criteria set the following limits per 100 g or mL of product: in foods ≤400 kcal, ≤15.6 g total fat, ≤4.4 g SFA, ≤1gTFA,≤30 g sugar, and ≤1 g salt; and in drinks, ≤100 kcal, ≤3.9 g total fat, ≤1.1 g SFA, ≤0.25 g TFA, ≤7.5 g sugar, and ≤0.25 g salt. Products that were over at least one of the cut-offs were considered LNQ. These criteria focus on energy density and nutrients that have the potential to negatively affect health or on “at-risk” nutrients, which can be a limitation when analyzing the nutrient profile. For this reason, we also used the UK NPM, which was developed by the UK Food Standards Agency (Department of Health of the United Kingdom, 2011). This instrument is one of the most frequently validated models 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2498 CAMPUS FOOD ENVIRONMENTS IN EUROPE TABLE 1 Overview of the methods, recorded data, estimated variables, and data derived related to the commercially produced food supply in outlets at OsloMet—Oslo Metropolitan University and the University of the Basque Country UPV/EHU. Data-recording methods Recorded data Estimated variables Data derived from recorded and/or estimated variables Direct recording of data: direct observation and face-to-face interviews, using pre-designed forms, and photographs taken in situa Indirect recording of data through the supplying companies, product labeling and/or manufacturer’s website, using pre-designed forms, and food composition databases Description (including flavor or ingredient variations, such as barbecue or plain potato chips), net weight, brand, ingredients, ingredient percentage (if available), and nutrition labeling information (if available) Energy, protein, total fat, SFA, TFA, fiber, sugar, sodium and fruit, vegetable, and nut content Classification according to the type and subtype of food (Dunford et al., 2012; Spanish Agency for Consumer Affairs, Food Safety and Nutrition—AECOSAN, 2010) NPMs: the Spanish Agency for Consumer Affairs, Food Safety and Nutrition—AECOSAN (2010), the UK NPM (Department of Health of the United Kingdom, 2011), and the Matbransjens Fagligle Utvalg (MFU) (2013) criteria NOVA food classification system (Monteiro et al., 2018a) Abbreviations: AECOSAN, Spanish Agency for Consumer Affairs, Food Safety and Nutrition; MFU, Norwegian Food and Drink Industry Professional Practices Committee; NPM, nutrient profiling model; SFAs, saturated fatty acids; TFAs, trans fatty acids. aThis method was only used in the UPV/EHU. (Labonté et al., 2018). In addition to the “at-risk” nutrients, the UK NPM also includes foods and nutrients considered to have a beneficial effect on health (i.e., fruit, vegetables, nuts, protein, and fiber). The UK NPM uses a simple scoring system wherein points are allocated based on the nutrient content of 100 g of food or drink. To do so, the nutrient content of each food and drink was assessed against a set of published criteria to determine whether it contains certain nutrients aboveorbelow particular thresholds.Thismodelhasseven components—energy, SFA, sugar, sodium, “fruit, vegetables and nuts”, fiber and protein—and provides a single score for any given food product, based on calculating the number of points for “negative” nutrients that can be offset by points for “positive” nutrients or ingredients. Points were awarded for energy, SFA, sugar, and sodium (total “A” points =[points for energy] +[points for saturated fat] +[points for sugars] +[points for sodium]) and fruit, vegetable, and nut content, fiber, and protein (total “C” points =[points for % fruit, vegetable & nut content] +[points for fiber] +[points for protein]). The amounts of these components were determined from the food labeling (ingredient list, proportion of the ingredients listed on the label that have the highest percentages, and nutrition labeling), manufacturer’s website, and/or the dietary assessment that was carried out with the above-mentioned food composition database. The score for “C” nutrients and ingredients was subtracted from the “A” nutrient score to give a final score. If the score was <4 for foods or <1 for drinks, the product was classified as HNQ. When scores exceeded these limits, however, the product was classified as LNQ (e.g., high-saturated fat, sugar, and/or salt content). Nonetheless, this model also has limitations, as certain foods with high levels of a particular “at-risk” nutrient (e.g., fat), which are also key sources of some micronutrients, may be classified as LNQ. For example, some cheeses may be classified as LNQ, despite being key sources of dietary calcium and riboflavin. To overcome this limitation, we added other criteria in the evaluation of the nutrient profiling, those that are commonly used to regulate the marketing of products of LNQ to children in Norway, which is a self-regulation scheme operated by the industry through their organization, the MFU criteria (Matbransjens Fagligle Utvalg—[MFU] [Norwegian Food and Drink Industry Professional Practices Committee], 2013). The MFU provides a list of products of LNQ according to their content in one or more of the following components, in most cases per 100 g of product: total fat, SFA, sugar, salt,nutritionaldensity, andenergydensity.Thelimitsestablished for eachofthesecomponents vary according to the type of food. An example is that milk products with more than 15 g added sugar per liter, breakfast cereals with more than 20 g sugar in total per 100 g, and yoghurt with more than 11 g sugar in total per 100 g are classified as LNQ according to the MFU criteria. Finally, theresultingcategoriesafter applying theabovementioned three criteria, the AECOSAN, the UK NPM, and the MFU criteria, were combined as follows: If a product had been classified as LNQ according to the three classifications, itwasconsideredLNQ.The rest of theproducts were categorized as HNQ. This criterion was agreed 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License CAMPUS FOOD ENVIRONMENTS IN EUROPE 2499 to be more rigorous than the one that would be considered LNQ those products that were classified as such according to only one or two classification systems. Table S2 presents the nutritional profile of the foods and drinks only sold at the UPV/EHU that were excluded from the analysis. Moreover, because the results of the analysis were not entirely consistent across NPMs, the LNQ products “with inconsistent classification,” that is, those that were classified as LNQ to only one or two classification systems were analyzed separately. Additionally, the food or drink items were classified using the NOVA system (Monteiro et al., 2018a), which categorizes foods according to their nature, purpose, and degree of industrial processing. This system distinguishes between the following groups: (i) unprocessed or minimally processed foods, (ii) processed culinary ingredients, (iii) processed foods, and (iv) ultra-processed products. This last group, ultra-processed foods, are formulations made mostly or entirely from substances derived from foods (e.g., casein, lactose, whey, gluten, hydrogenated oils, and maltodextrin, among others) and additives (e.g., color stabilizers, flavor enhancers, non-sugar sweeteners, and emulsifiers, among others), with little if any intact unprocessed or minimally processed. In the present study, the category “processed culinary ingredients” was not assessed, because this type of product was only offered in the UPV/EHU supermarket. However, these types of products were part of ready-to-eat foods such as salads with dressing sold in the vending machines that met the criteria to be classified as processed foods. 2.6 Quality management of the data All data were collected by a single researcher (N.M.-P.) and reviewed by another researcher (M.A.-I.). We used unique outlet identification numbers that were attached to each recording sheet. To check for quality data and derived indices (NPMs and level of processing), subsamples of outlets and products were repeatedly examined. The data set was made available for analysis on a protected central data server. Access to the data is restricted to authorized members of the research team. 2.7 Sociocultural factors of Norway and Spain Sociocultural factors of Norway and Spain that could influence food supply and properties of commercially produced food products offered are shown in Table S3. The purpose of this summary is to contextualize the possible influences of these factors on food supply in the universities under study. These sociocultural features were selected based on the Food-EPI monitoring tool (Swinburn et al., 2013; Swinburn et al., nd), which aims to propose a monitoring framework to assess government policies and actions for creating healthy FEs. The key components are classified into “culture,” “economic variables,” “quality of life,” and “political elements.” 2.8 Statistical analysis The data were analyzed using SPSS for Windows version 24.0 (SPSS Inc.). All descriptive statistics were reported in number and percentage. For bivariate analysis, Chi-square or Fisher´s exact test was used to compare categorical variables. All tests were two-sided, and p-values less than 0.05 were considered statistically significant. The κcoefficient was calculated to investigate the degree of agreement between the three NPMs used (the AECOSAN, the UK NPM, and the MFU criteria) and between these models and NOVA classification. The κresults were interpreted as follows: values ≤0 no agreement, 0.1–0.20 none to slight, 0.21–0.40 fair, 0.41–0.60 moderate, 0.61–0.80 substantial, and 0.81–1.00 almost perfect (Landis & Koch, 1977). 3RESULTS 3.1 Availability of commercially produced foods In total, 251 foods and drinks were identified at OsloMet. The most common products were sweet snacks (48.5% of the solid foods and 32.7% of the total products) and sugarsweetened carbonated drinks (23.2% of the cold drinks and 7.6% of the total products) (Table 2). 3.2 Nutritional quality of commercially produced foods Approximately half of the products did not meet the AECOSAN criteria (53.0%) and the UK NPM criteria (47.4%). Moreover, nearly three quarters (72.9%) did not meet the MFU criteria. The AECOSAN criterion that was most frequently unfulfilled was the SFA (43.2%) content in solid foods and the sugar (31.7%) content in drinks. The combination of the three criteria above-mentioned, the AECOSAN criteria, the UK NPM criteria, and the MFU criteria, showed that 40.2% of the products were classified as LNQ. The percentage of LNQ was higher in solid foods than in drinks for the three NMPs (p<0.001). 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2500 CAMPUS FOOD ENVIRONMENTS IN EUROPE TABLE 2 Differences in nutritional profile of commercially produced food products sold in food outlets at OsloMet—Oslo Metropolitan University and the University of the Basque Country UPV/EHU. Type of product n(%)a pb Percentage not meeting the criteria, LNQ AECOSAN criteriac,% pb UK NPMd,% pb MFUe,% pb AECOSAN +UK NPM +MFUf,% pb OM EHU OM EHU OM EHU OM EHU OM EHU Solid foods Fruit and fruit derivatives 8(3.2) 56 (5.3) 0.158 50.0 16.1 0.047 37.5 12.5 0.102 37.5 12.5 0.102 37.5 12.5 0.102 Dairy products Yogurts 18 (7.2) 23 (2.2) <0.001 – – – 5.9 8.7 1.000 52.9 56.5 0.051 – – – Other dairy productsg 18 (7.2) 37 (3.5) <0.001 –78.4<0.001 16.7 83.8 <0.001 83.3 83.8 1.000 – 67.6 <0.001 Nuts 6(2.4) 56 (5.3) 0.050 83.3 72.7 1.000 – 29.1 0.326 83.3 87.3 1.000 – 29.1 0.326 Salty snacks 19 (7.6) 185 (17.6) <0.001 68.4 95.3 <0.001 21.1 66.5 <0.001 36.8 89.2 <0.001 21.1 63.8 <0.001 Sandwiches 3(1.2) 31 (2.9) 0.116 100.0 90.3 1.000 100.0 41.9 0.094 100.0 96.8 1.000 100.0 41.9 0.094 Sweet snacks 82 (32.7) 384 (36.5) 0.250 81.7 95.3 <0.001 84.1 88.8 0.239 96.3 100.0 0.005 76.8 86.7 0.023 Sweets and chewing gums With added sugars 11 (4.4) 14 (1.3) <0.001 90.9 92.9 1.000 90.9 85.7 1.000 100.0 100.0 – 90.9 85.7 1.000 With sweeteners 5(2.0) 37 (3.5) 0.219 40.0 –0.012 40.0 –0.012 100.0 100.0 –40.0 –0.012 Total of solid foods 169 (67.3) 822 (78.2) <0.001 61.5 81.0 <0.001 56.2 66.3 0.013 81.1 88.7 0.007 50.3 63.7 <0.001 Drinks Bottled water 3 (1.2) 18 (1.7) 0.562 – – – – – – – – – – – – Carbonated drinks With added sugars 19 (7.6) 29 (2.7) <0.001 84.2 82.8 1.000 89.5 89.7 1.000 100.0 100.0 – 84.2 82.8 1.000 With added sugars and sweeteners 1 (0.4) 9 (0.9) 0.453 –55.6 1.000 100.0 66.7 1.000 100.0 100.0 – – – 1.000 With sweeteners 16 (6.4) 11 (11.0) <0.001 – – – – – – 100.0 100.0 – – – – (Continues) 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License CAMPUS FOOD ENVIRONMENTS IN EUROPE 2501 TABLE 2 (Continued) Type of product n(%)a pb Percentage not meeting the criteria, LNQ AECOSAN criteriac,% pb UK NPMd,% pb MFUe,% pb AECOSAN +UK NPM +MFUf,% pb OM EHU OM EHU OM EHU OM EHU OM EHU Without added sugars or sweeteners (soda) 2 (0.8) 2 (0.2) 0.119 – 50.0 1.000 – 50.0 1.000 – 100.0 0.333 – 50.0 1.000 Dairy drinks 18 (7.2) 47 (4.5) 0.078 66.7 80.9 0.323 22.2 70.2 <0.001 –36.2 0.002 –34.0 0.003 Juices 10 (4.0) 71 (6.8) 0.103 10.0 69.0 0.001 10.0 36.6 0.153 – 19.7 0.197 – 1.4 1.000 Milk 2 (0.8) 15 (1.4) 0.429 –100.0 – – 33.3 1.000 – – – – – – Non-carbonated drinks With added sugars 9(3.6) 19 (1.8) 0.082 –15.8 0.530 11.1 47.4 0.098 100.0 100.0 – – 10.5 1.000 With sweeteners 1 (0.4) 1 (0.1) 0.271 – – – – – – 100.0 100.0 – – – – Vegetable drinks 1 (0.4) 7 (0.7) 0.624 – – – – 14.3 1.000 – – – – – – Total of drinks 82 (32.7) 229 (21.8) <0.001 35.4 52.4 0.008 29.3 46.7 0.006 56.1 44.5 0.072 19.5 21.4 0.719 Total of products 251 1051 <0.001 53.0 74.8 <0.001 47.4 62.0 <0.001 72.9 79.1 0.035 40.2 54.5 <0.001 Abbreviations: AECOSAN, Spanish Agency for Consumer Affairs, Food Safety and Nutrition; EHU, University of the Basque Country UPV/EHU; LNQ, product of low nutritional quality; MFU, Norwegian Food and Drink Industry Professional Practices Committee; NPM, nutrient profiling model; OM, OsloMet—Oslo Metropolitan University. aPercentages with respect to the total of products for each university (only the product categories available at both universities are included in this table). bχ2test or the Fisher exact test was used to assess differences between universities, significant p-values are highlighted in bold. cSpanish Agency for Consumer Affairs, Food Safety and Nutrition—AECOSAN (2010). dDepartment of Health of the United Kingdom (2011). eMatbransjens Fagligle Utvalg (MFU) (2013). fThe three NPMs were combined as follows: If a food or drink had been classified as LNQ according to the Spanish Agency for Consumer Affairs, Food Safety and Nutrition—AECOSAN (2010), the UK NPM (Department of Health of the United Kingdom, 2011) and the Matbransjens Fagligle Utvalg (MFU) criteria (2013), it was considered LNQ. g“Other dairy products”: custard, cream caramel, cheese, pudding, and so on. 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2502 CAMPUS FOOD ENVIRONMENTS IN EUROPE A total of 1051 foods and drinks were identified at the UPV/EHU. The most common products were sweet snacks (46.7% of the solid foods and 36.5% of the total products), followed by salty snacks (22.5% of the solid foods and 17.6% of the total products), and juices (31.0% of the drinks and 6.8% of the total products) and sugar-sweetened carbonated drinks (12.7% of the drinks and 2.7% of the total products). At the UPV/EHU, nearly three quarters of the total commercially produced food products were classified as LNQ according to the AECOSAN criteria (74.8%), the UK NPM criteria (62.0%), and the MFU criteria (79.1%). The combination of the three criteria above-mentioned showed that 54.5% of the products were classified as LNQ. Similar to the offerat OsloMet, thepercentageof LNQ washigher in solid foods than in drinks for the three NMPs (p<0.001). The AECOSAN criteria that solid foods most frequently did not meet were the energy (53.8%) and total fat content (55.1%); and in drinks, the sugar content (50.7%). The analysis of differences in the nutritional profile of commercially produced foods offered in the two universities showed that the percentage of products classified as LNQ was higher at the UPV/EHU compared to at OsloMet (p<0.001). Specifically, the subcategories in which these differences were observed were: salty snacks, sweet snacks, dairy products other than yogurt, and dairy drinks(p<0.05).Theonlysubcategoryinwhichtheresults were the other way around, that is, the percentage of products classified as LNQ was higher in OsloMet than in the UPV/EHU, was sweets and chewing gums with sweeteners (p<0.05). However, this result was not confirmed when the less rigorous criterion was applied, that is, in separate analyses for LNQ products with inconsistent classification (Table S4). In contrast, the percentage of sweets and chewing gums with sweeteners classified as LNQ “with inconsistent classification” was higher in the UPV/EHU than in OsloMet. In any case, the results related to the offer of salty snacks and sweet snacks classified as LNQ at the UPV/EHU compared to those of OsloMet were confirmed in separate analyses for LNQ products “with inconsistent classification.” Moreover, employing this less rigorous criterion, the following differences in subcategories were observed, in favor of the UPV/EHU: sandwiches, sweets and chewing gums with added sugars, carbonated drinks with added sugars, and juices. On the other hand, a comparison of the results obtained with the three NPMs for food supply at OsloMet showed substantial agreement between the results obtained with the UK NPM and the AECOSAN criteria and a moderate agreement between the UK NPM and the MFU criteria (Table 3). The agreement between the AECOSAN and the MFU criteria was fair. However, in the case of the food supply at the UPV/EHU, the agreement between the results obtainedwith the UKNPMandthe AECOSANcriteriawas moderate, and between the UK NPM and the MFU criteria, and between the AECOSAN and the MFU criteria were fair. 3.3 Processing level of commercially produced foods According to the NOVA system, most of the products offered were categorized as “ultra-processed,” which was the case for 87.6% of the solid foods and 82.9% of drinks of OsloMet, and 85.5% of the solid foods and 75.5% of drinks of the UPV/EHU (Table 4). No differences were found between the two universities analyzed regarding the share of ultra-processed foods, neither for total of products, for solid foods, nor for drinks. In any case, the product subcategory that presented a higher percentage of products of LNQ was dairy products other than yogurt at OsloMet compared to the UPV/EHU (p<0.001), and juices at the UPV/EHU in comparison with OsloMet (p<0.05). 3.4 Comparison between the nutritional profile and processing level of commercially produced foods Regarding the comparisonbetweenthe NPMsandprocessing level classification, at both universities, there was from none to fair agreement between the NOVA classification and the three NPMs combined. For each of the NPMs separately, at OsloMet, there was a none-to-slight agreement between the NOVA system and the AECOSAN criteria, whereas, at the UPV/EHU, there was a fair agreement between these two criteria. At both universities, there was fair agreement when comparing the processing level classification with the UK NPM and moderate agreement with the MFU criteria (Table 5). In general, drinks presented a lower agreement compared to solid foods when comparing the NOVA system with the three NPMs combined and separately, except for the comparison with the AECOSAN criteriaat OsloMet, andthe UKNMP at UPV/EHU. Inboth cases, solid food presented a lower agreement. 4DISCUSSION The present study aimed to assess differences in the nutritional profile and processing level of commercially produced foods offered at food outlets at the UPV/EHU and OsloMet, as well as discrepancies between the 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License CAMPUS FOOD ENVIRONMENTS IN EUROPE 2509 application of healthiness indicators for commercial establishments that sell foods for immediate consumption. Foods,10(6), 1434. https://doi.org/10.3390/foods10061434 Food and Agriculture Organization of the United Nations — FAO. (2016). Influencing food environments for healthy diets. FAO. https://www.fao.org/3/i6484e/i6484e.pdf Franco, A. D. S., Canella, D. S., Perez, P. M. P., Bandoni, D. H., & Castro, I. R. R. D. (2020). University food environment: Characterization and changes from 2011 to 2016 in a Brazilian public university. Revista de Nutrição,33, e200058. https://doi.org/10. 1590/1678-9865202033e200058 Holm-Denoma, J. M., Joiner, T. E., Vohs, K. D., & Heatherton, T. F. (2008). The "freshman fifteen" (the "freshman five" actually): Predictors and possible explanations. Health Psychology,27(1S), S3–S9. https://doi.org/10.1037/0278-6133.27.1.S3 Horacek, T. M., Erdman, M. B., Byrd-Bredbenner, C., Carey, G., Colby, S. M., Greene, G. W., Guo, W., Kattelmann, K. K., Olfert, M., Walsh, J., & White, A. B. (2013). Assessment of the dining environment on and near the campuses of fifteen post-secondary institutions. Public Health Nutrition,16(7), 1186–1196. https://doi. org/10.1017/S1368980012004454 Horacek, T. M., Yildirim, E. D., Matthews Schreiber, M., ByrdBredbenner, C., Colby, S., White, A. A., Shelnutt, K. P., Olfert, M. D., Mathews, A. E., Riggsbee, K., Franzen-Castle, L., Morrell, J. S., & Kattelmann, K. (2019). Development and validation of the Vending Evaluation for Nutrient-Density (VEND)ing audit. International Journal of Environmental Research and Public Health, 16(3), 514. https://doi.org/10.3390/ijerph16030514 Huseinovic, E., Winkvist, A., Slimani, N., Park, M. K., Freisling, H., Boeing, H., Buckland, G., Schwingshackl, L., Weiderpass, E., Rostgaard-Hansen, A. L., Tjønneland, A., Affret, A., BoutronRuault, M. C., Fagherazzi, G., Katzke, V., Kühn, T., Naska, A., Orfanos, P., Trichopoulou, A., ... Forslund, H. B. (2016). Meal patterns across ten European countries—Results from the European prospective investigation into cancer and nutrition (EPIC) calibration study. Public Health Nutrition,19(15), 2769–2780. https://doi. org/10.1017/S1368980016001142 Labonté, M. È., Poon, T., Gladanac, B., Ahmed, M., Franco-Arellano, B., Rayner, M., & L’Abbé, M. R. (2018). Nutrient profile models with applications in government-led nutrition policies aimed at health promotion and noncommunicable disease prevention: A systematicreview.Advances in Nutrition,9(6),741–788.https://doi. org/10.1093/advances/nmy045 Lake, A., & Townshend, T. (2006). Obesogenic environments: Exploring the built and food environments. The Journal of the Royal Society for the Promotion of Health,126(6), 262–267. https://doi. org/10.1177/1466424006070487 Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics,33(1), 159–174. Lee, J. J., Srebot, S., Ahmed, M., Mulligan, C., Hu, G., & Lȷbbé, M. R. (2023). Nutritional quality and price of plant-based dairy and meat analogs in the Canadian food supply system. Journal of Food Science,88(8), 3594–3606. https://doi.org/10.1111/1750-3841.1669 1 Luiten, C. M., Steenhuis, I. H., Eyles, H., Ni Mhurchu, C., & Waterlander, W. E. (2016). Ultra-processed foods have the worst nutrient profile, yet they are the most available packaged products ina sampleofNewZealandsupermarkets.Public Health Nutrition, 19(3), 530–538. https://doi.org/10.1017/S1368980015002177 Lytle, L. A., & Sokol, R. L. (2017). Measures of the food environment: A systematic review of the field, 2007–2015. Health & Place,44, 18–34. https://doi.org/10.1016/j.healthplace.2016.12.007 Mackenbach, J. P., Stirbu, I., Roskam, A. J., Schaap, M. M., Menvielle, G., Leinsalu, M., Kunst, A. E., & European Union Working Group on Socioeconomic Inequalities in Health. (2008). Socioeconomic inequalities in health in 22 European countries. The New England Journal of Medicine,358(23), 2468–2481. https://doi.org/10.1056/ NEJMc081414 Maldonado-Pereira, L., Barnaba, C., de Los Campos, G., & MedinaMeza, I. G. (2022). Evaluation of the nutritional quality of ultraprocessed foods (ready to eat +fast food): Fatty acids, sugar, and sodium. Journal of Food Science,87(8), 3659–3676. https://doi.org/ 10.1111/1750-3841.16235 Martinez-Perez, N., & Arroyo-Izaga, M. (2021). Availability, nutritional profile and processing level of food products sold in vending machines in a Spanish public university. International Journal of Environmental Research and Public Health,18(13), 6842. https:// doi.org/10.3390/ijerph18136842 Martinez-Perez, N., Telleria-Aramburu, N., Insúa, P., Hernández, I., Telletxea, S., Ansotegui, L., Rebato, E., Basabe, N., de Pancorbo, M. M., Rocandio, A., & Arroyo-Izaga, M. (2022a). On-campus food purchase behaviors, choice determinants, and opinions on food availability in a Spanish university community. Nutrition,103–104, 111789. https://doi.org/10.1016/j.nut.2022.111789 Martinez-Perez, N., Torheim, L. E., Castro-Díaz, N., & Arroyo-Izaga, M. (2022b). On-campus food environment, purchase behaviours, preferences and opinions in a Norwegian university community. Public Health Nutrition,25(6), 1619–1630. https://doi.org/10.1017/ S136898002100272X Martínez Steele, E., Popkin, B. M., Swinburn, B., & Monteiro, C. A. (2017). The share of ultra-processed foods and the overall nutritional quality of diets in the US: Evidence from a nationally representative cross-sectional study. Population Health Metrics, 15(1), 6. https://doi.org/10.1186/s12963-017-0119-3 Martinez Perez, N. (2022). On-campus food environment in two European public universities: food purchasing behaviours, choice determinants and opinions on the food availability among the university community [Doctoral Thesis, University of the Basque Country UPV/EHU]. http://hdl.handle.net/10810/55642 Mataix,J. (2009).Tabla decomposiciónde alimentos,5ªedición[Food composition table] (5th ed.). University of Granada. Matbransjens Fagligle Utvalg — MFU [Norwegian Food and Drink Industry Professional Practices Committee]. (2013). Complete Product List.https://nye.mfu.as/complete-product-list/ Matthews, M., Horacek, T. M., Olfert, M. D., Koenings, M. M., Shelnutt, K. P., Stocker, C., Golem, D. L., Kattelmann, K. K., Colby, S., Franzen-Castle, L., Brown, O. N, & Morrel, J. S. (2014). Development, validation and implementation of the Health Density Vending Machine Audit Tool (HDVMAT). Journal of the Academy of Nutrition and Dietetics,114,A65.https://doi.org/10.1016/j.jand. 2014.06.217 Mithril, C., Dragsted, L. O., Meyer, C., Blauert, E., Holt, M. K., & Astrup, A. (2012). Guidelines for the new Nordic diet. Public Health Nutrition,15(10), 1941–1947. https://doi.org/10.1017/ S136898001100351X Monroy-Parada, D. X., Prieto-Castillo, L., Ordaz-Castillo, E., Bosqued, M. J., Rodríguez-Artalejo, F., & Royo-Bordonada, M. Á. (2021). Mapa de las políticas nutricionales escolares en España 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2510 CAMPUS FOOD ENVIRONMENTS IN EUROPE [Map of school nutritional policies in Spain]. Gaceta Sanitaria, 35(2), 123–129. https://doi.org/10.1016/j.gaceta.2019.10.005 Monteiro, C. A., Cannon, G., Moubarac, J. C., Levy, R. B., Louzada, M. L. C., & Jaime, P. C. (2018a). The UN decade of nutrition, the NOVA food classification and the trouble with ultraprocessing. Public Health Nutrition,21(1), 5–17. https://doi.org/10. 1017/S1368980017000234 Monteiro, C. A., Moubarac, J. C., Levy, R. B., Canella, D. S., Louzada, M. L. D. C., & Cannon, G. (2018b). Household availability of ultra-processed foods and obesity in nineteen European countries. Public Health Nutrition,21(1), 18–26. https://doi.org/10.1017/ S1368980017001379 Newton, J., Dooris, M., & Wills, J. (2016). Healthy universities: An example of a whole-system health-promoting setting. Global Health Promotion,23(1 Suppl), 57–65. https://doi.org/10.1177/ 1757975915601037 Norwegian Directorate of Health & Norwegian Food Safety Authority. (2023). Kostholdsplanleggeren (Diet planner). Norwegian Directorate of Health & Norwegian Food Safety Authority. https:// www.kostholdsplanleggeren.no/ Norwegian Ministries. (2017). Norwegian National action plan for a healthier diet (Nasjonal handlingsplan for bedre kosthold 2017–2021). Norwegian Ministries. https://www.regjeringen.no/ contentassets/fab53cd681b247bfa8c03a3767c75e66/norwegian_ national_action_plan_for_a_healthier_diet_an_outline.pdf Ortega, R. M., López-Sobaler, A. M., Andrés, P., Requejo, A. M., Aparicio, A., & Molinero, L. M. (2016). Programa DIAL para valoración de dietas y cálculos de alimentación, versión 2.12 [DIAL program for diet assessment and feeding calculations, 2.12]., Department of Nutrition (Complutense University of Madrid) & Alce Ingeniería, S.L. Oslo Metropolitan University. (2019). Årsrapport 2019 [Annual report 2019]. Oslo Metropolitan University. https://ansatt.oslomet.no/ documents/585743/54495365/%C3%85rsrapportþ2019/ Pineda, E., Poelman, M. P., Aaspõllu, A., Bica, M., Bouzas, C., Carrano, E., De Miguel-Etayo, P., Djojosoeparto, S., Blenkuš, M. G., Graca, P., Geffert, K., Hebestreit, A., Helldan, A., Henjum, S., Huseby, C. S., Gregório, M. J., Kamphuis, C., Laatikainen, T., Løvhaug, A. L., ... Vandevijvere, S. (2022). Policy implementation and priorities to create healthy food environments using the Healthy Food Environment Policy Index (Food-EPI): A pooled level analysis across eleven European countries. The Lancet Regional Health. Europe,23,100522.https://doi.org/10. 1016/j.lanepe.2022.100522 Roy, R., Hebden, L., Kelly, B., de Gois, T., Ferrone, E. M., Samrout, M., Vermont, S., & Allman-Farinelli, M. (2016). Description, measurement and evaluation of tertiary-education food environments. The British Journal of Nutrition,115(9), 1598–1606. https://doi.org/ 10.1017/S0007114516000568 Roy, R., Soo, D., Conroy, D., Wall, C. R., & Swinburn, B. (2019). Exploring university food environment and on-campus food purchasing behaviors, preferences, and opinions. Journal of Nutrition Education and Behavior,51(7), 865–875. https://doi.org/10.1016/j. jneb.2019.03.003 Shen, J., Wilmot, K. A., Ghasemzadeh, N., Molloy, D. L., Burkman, G., Mekonnen, G., Gongora, M. C., Quyyumi, A. A., & Sperling, L. S. (2015). Mediterranean dietary patterns and cardiovascular health. Annual Review of Nutrition,35, 425–449. https://doi.org/ 10.1146/annurev-nutr-011215-025104 Spanish Agency for Consumer Affairs, Food Safety and Nutrition— AECOSAN. (2005). Estrategia para la Nutrición, Actividad Física, prevención de la Obesidad y Salud (NAOS). Invertir la tendencia de la obesidad [Strategy for nutrition, physical activity, obesity pervention and health. Reverse the trend of obesity]. AECOSAN. https://www.aesan.gob.es/AECOSAN/docs/ documentos/nutricion/estrategianaos.pdf Spanish Agency for Consumer Affairs, Food Safety and Nutrition— AECOSAN. (2010). Consensus document on food in educational centres. AECOSAN. https://www.aesan.gob.es/AECOSAN/docs/ documentos/nutricion/educanaos/Consensus_document.pdf Spanish Agency for Consumer Affairs, Food Safety and Nutrition— AECOSAN. (2012). Código de corregulación de la publicidad de alimentos y bebidas dirigida a menores, prevención de la obesidad y salud (código paos) [Co-regulation code for food and beverage advertising aimed at minors, obesity prevention and health (paos code)]. AECOSAN. http://www.aesan.gob.es/AECOSAN/docs/ documentos/nutricion/Nuevo_Codigo_PAOS_2012_espanol.pdf Spanish Agency for Consumer Affairs, Food Safety and Nutrition— AECOSAN. (2016). Contenido de Ácidos Grasos Trans en los Alimentos en España, 2015 [Content of trans fatty acids in foods in Spain, 2015]. AECOSAN. https://www.aesan.gob.es/AECOSAN/ docs/documentos/nutricion/Informe_AGT2015.pdf Spanish Agency for Consumer Affairs, Food Safety and Nutrition— AECOSAN. (2020a). Collaboration PLAN for the improvement of the composition of food and beverages and other measures 2020. AECOSAN. https://www.aesan.gob.es/AECOSAN/ docs/documentos/nutricion/EN_DOSSIER_PLAN_2020.pdf Spanish Agency of Consumer Affairs, Food Safety and Nutrition. (2020b). Intervención de promoción de hábitos saludables en el ámbito laboral: Programa IPHASAL [Intervention to rpomote healthy habits in the workplace: IPHASAL program]. AECOSAN. http://www.aesan.gob.es/AECOSAN/docs/ documentos/nutricion/IPHASAL.pdf Spanish Agency for Consumer Affairs, Food Safety and Nutrition—AECOSAN. (nd). Información alimentaria facilitada al consumidor [Food information provided to the consumer]. AECOSAN. http://www.aesan.gob.es/AECOSAN/ web/seguridad_alimentaria/detalle/etiquetado_informacion_ alimentaria.htm SpanishStatistics NationalInstitute.(2016).Encuesta deCondiciones de Vida (ECV). Año 2015. [Survey of life conditions. Year 2015]. Spanish Statistics National Institute. https://www.ine.es/prensa/ np969.pdf Sturm, R. (2008). Disparities in the food environment surrounding US middle and high schools. Public Health,122(7), 681–690. https://doi.org/10.1016/j.puhe.2007.09.004 Swinburn, B., Mackay, S., Garton, K., Vandevijvere, S., & INFORMAS. (nd). Benchmarking food environments. INFORMAS. https://www.informas.org/food-epi/ Swinburn, B., Vandevijvere, S., Kraak, V., Sacks, G., Snowdon, W., Hawkes, C., Barquera, S., Friel, S., Kelly, B., Kumanyika, S., L’Abbé, M., Lee, A., Lobstein, T., Ma, J., Macmullan, J., Mohan, S., Monteiro, C., Neal, B., Rayner, M., ... INFORMAS. (2013). Monitoring and benchmarking government policies and actions to improve the healthiness of food environments: A proposed Government Healthy Food Environment Policy Index. Obesity Reviews,14(Suppl 1), 24–37. https://doi.org/10.1111/obr.1207 3 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License CAMPUS FOOD ENVIRONMENTS IN EUROPE 2511 Tam, R., Yassa, B., Parker, H., O’Connor, H., & Allman-Farinelli, M. (2017). University students’ on-campus food purchasing behaviors, preferences, and opinions on food availability. Nutrition,37, 7–13. https://doi.org/10.1016/j.nut.2016.07.007 The Ministry of Health and Care Services. (2017). Norwegian National Action Plan for a Healthier Diet—An outline. The Ministry of Health and Care Services. https://www.regjeringen.no/ contentassets/fab53cd681b247bfa8c03a3767c75e66/norwegian_ national_action_plan_for_a_healthier_diet_an_outline.pdf Torheim, L. E., Løvhaug, A. L., Huseby, C. S., Terragni, L., Henjum, S., & Roos, G. (2020). The Healthy Food Environment Policy Index (FOOD-EPI). Evidence document for Norway (FOODEPI 2020). INFORMAS. https://www.jpi-pen.eu/images/reports/ Food-EPI-Evidence-Norway-2020.pdf Turner, C., Aggarwal, A., Walls, H., Herforth, A., Drewnowski, A., Coates, J., Kalamatianou, S., & Kadiyala, S. (2018). Concepts and critical perspectives for food environment research: A global frameworkwith implications for action in lowand middleincome countries. Global Food Security,18, 93–101. https://doi.org/ 10.1093/advances/nmz031 United States Department of Agriculture, Agricultural Research Service. (2019). FoodData Central. United States Department of Agriculture, Agricultural Research Service. https://fdc.nal.usda. gov/ Vaz Velho, M., Pinheiro, R., & Rodriguez, A. S. (2016). The Atlantic Diet—Origin and features. International Journal of Food Studies, 5, 106–119. https://doi.org/10.7455/ijfs/5.1.2016.a10 SUPPORTING INFORMATION Additional supporting information can be found online in the Supporting Information section at the end of this article. How to cite this article: Martinez-Perez, N., Torheim, L. E., & Arroyo-Izaga, M. (2024). Availability and properties of commercially produced food products offered in European public universities: A North–South comparison. Journal of Food Science,89, 2494–2511. https://doi.org/10.1111/1750-3841.17022 17503841, 2024, 4, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.17022 by Universidad Del Pais Vasco, Wiley Online Library on [30/04/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License