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Objective:To evaluate diets in terms of nutritional characteristics and quality from the perspectives of health, greenhouse gas emissions (GHGE) and possible associations with each other in a representative sample of students at a public university.Design:Cross-sectional. Dietary intake was evaluated with a validated FFQ, and diet quality was assessed through the Healthy Eating Index (HEI-2010) and MedDietScore (MDS). GHGE data were obtained from the literature. In addition, sex, socio-economic status (SES) and body fat (BF) status were analysed as covariates.Setting:Basque Autonomous Community, Spain.Participants:Totally, 26 165 healthy adults aged 18–28 years.Results:Student diets were characterised by low consumption of carbohydrates (38·72 % of total energy intake (TEI)) and a high intake of lipids (39·08 % of TEI). Over half of the participants had low dietary quality. The low-emitting diets were more likely to be consumed by subjects with low HEI-2010 scores (β: 0·039 kg eCO2/1000 kcal/d) and high MDS scores (β: −0·023 kg eCO2/1000 kcal/d), after controlling for sex, SES and BF status. Both the low-emitting and healthy diets were more likely to be consumed by women and by those with normal BF percentage.Conclusions:UPV/EHU university students’ diets were characterised by moderate quality from a nutritional perspective and moderate variation in the size of carbon footprints. In this population, diets of the highest quality were not always those with the lowest diet-related GHGE; this relationship depended in part on the constructs and scoring criteria of diet quality indices used.

Objective:To assess the food environment at OsloMet, through the nutritional profile and processing level of available commercial foods and drinks, as well as to determine food-purchasing behaviours, preferences and opinions on the food environment, in order to identify whether interventions on campus need to be conducted.Design:Cross-sectional descriptive study.Setting:Pilestredet and Kjeller campus of OsloMet (Norway).Participants:To analyse the nutritional profile of products offered at all food outlets (seven canteens, three coffee shops and two vending machines) at the main campuses three criteria were applied: those proposed by the Spanish Agency for Food Safety and Nutrition, the UK nutrient profiling model and those of the Food and Drink Industry Professional Practices Committee Norway. In addition, products were classified by processing level, using the NOVA system. Food purchasing, food choice behaviours and opinions were analysed through a survey online, in which 129 subjects participated.Results:With regard to the first of the objectives, the combination of the above-mentioned criteria showed that 39·8 % of the products were ‘unhealthy’ and 85·9 % were ‘ultra-processed’. Regarding the second objective, the most important determinants of food choice were taste, convenience, and cost and nutrition/health value. The most common improvements suggested were lowering the cost, improving the allergen information on labelling and increasing the variety of fresh and healthy foods.Conclusions:A high proportion of the products offered were considered ‘unhealthy’ and highly processed. Interventions that improve food prices, availability and information on labelling would be well-received in this community.

The objective of the present study was to compare different methods for evaluating body fat percentage (BF%) (anthropometric methods and bioelectrical impedance analysis) in university students. Subjects were 653 healthy students whose mean age, body height, body weight and BMI were 21·1 (SD 2·5) years, 166·0 (SD 8·4) cm, 62·8 (SD 11·0) kg and 22·7 (SD 3·1) kg/m2, respectively. Results showed that BMI is a poor predictor of body fatness since the sensitivity was low in comparison with the reference method (Siri equation). The lowest values of BF% were obtained using the reference method (Siri equation) (21·8 (SD 6·8)%). The two methods with the highest agreement were Siri and Lean (mean difference, −0·5), followed by Brozek (mean difference, −1·4) and Deurenberg (mean difference, −1·5). The largest mean difference for BF% was between Siri and impedance (−4·5). Although the methods and/or equations used in the present study have been commonly utilised to estimate BF% in young adults, the results must be interpreted with caution in the diagnosis and monitoring of overweight and obesity.