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# Exploring the preferences of French university students using real-life food sourcing data: A proof-of-concept study

Michel Visalli, Fanny Teil, Lucile Marty

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## To cite this version:

Michel Visalli, Fanny Teil, Lucile Marty. Exploring the preferences of French university students using real-life food sourcing data: A proof-of-concept study. Food Quality and Preference, 2025, 132, pp.105583. 10.1016/j.foodqual.2025.105583. hal-05069960

HAL Id: hal-05069960

https://hal.science/hal-05069960v1

Submitted on 4 Jun 2025

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# Exploring the preferences of French university students using real-life food sourcing data: A proof-of-concept study

M. Visalli<sup>a,b,*</sup>, F. Teil<sup>a</sup>, L. Marty<sup>a</sup>

## ARTICLE INFO

### Keywords:

- Food purchase

- Sensory quality

- Nutritional quality

- Environmental impact

- Liking

## ABSTRACT

Taste and preferences play a crucial role in shaping eating behaviours. However, research on the factors influencing university students' preferences in real-life settings and at the diet level remains limited. This article presents the results of a study conducted with a sample of French students who collected data on the food they personally sourced during one month alongside hedonic scores. Food preferences were compared based on food categories, sourcing locations, consumption frequencies, and the nutritional, environmental, economic, and sensory properties of the foods. The results showed that about 75 % of the sourced foods were highly appreciated, and preferred foods were generally but not systematically consumed more frequently. However, students' diet also included 25 % of moderately liked foods, such as utilitarian and routine foods. Students' preferences often conflicted with higher nutritional quality but not with lower environmental impact. Among the factors influencing preferences, foods with sweet and fatty tastes and ready-to-eat foods were generally preferred, while foods requiring culinary preparation and lower-priced foods within a category were less liked. The context in which food was sourced proved to be the most influential factor, with foods served in collective catering settings being the least liked. Certain food categories, such as fruits, emerged as offering both sensory enjoyment and potential health and sustainability benefits. This research underscores the relationships between food choices, sensory perceptions, preferences, and the context in which foods are sourced and consumed. From a methodological standpoint, it highlights the potential of real-life data collection in better understanding food consumption behaviours in relation to preferences and emphasizes the need to continue developing large-scale, ecological approaches that integrate sensory experiences within a broader context.

## 1. Introduction

Due to the increasing prevalence of diet-related diseases and global environmental challenges, it has become crucial to prioritize diets that both meet individuals' nutritional needs and do not exceed planet environmental boundaries (Willett et al., 2019). These changes require a transformation in eating habits and production systems to ensure a healthier and more sustainable food system for future generations (Garnett et al., 2014). However, there is still limited understanding of how sustainable food choices align with consumer preferences in real-life settings, and to what extent consumers are actually making promises on their preferences in favour of sustainability.

Studying the food choices of young adults and understanding the factors that influence their decisions is essential, as they are the

decision-makers of tomorrow in terms of food sustainability, and they have the potential to drive global changes in society (Eker et al., 2019). Among them, university students represent a particularly interesting population. The student period corresponds to a major food transition, often marked by a first experience of food independence, away from the family home (Kremmyda et al., 2008; Winpenny et al., 2018). This life stage is also crucial for establishing long-term sustainable eating habits (Deliens et al., 2014). In Western societies, however, most studies shown that the diet of the majority of students remains of rather poor nutritional and/or environmental quality (Arrazat et al., 2023; Bernardo et al., 2017; Dharmayani et al., 2024; Horacek et al., 2013; Papadaki et al., 2007; Ramón-Arbués et al., 2021; Roy et al., 2017; Tayhan & Helvacı, 2024; Whatnall et al., 2019).

Numerous studies highlighted that students and young adults

<footnote><sup>a</sup> Centre des Sciences du Goût et de l'Alimentation, L'Institut Agro Dijon, CNRS, INRAE, Université Bourgogne Europe, F-21000 Dijon, France</footnote>

<footnote><sup>b</sup> INRAE, PROBE research infrastructure, ChemoSens facility, F-21000 Dijon, France</footnote>

<footnote>* Corresponding author at: Centre des Sciences du Goût et de l'Alimentation, L'Institut Agro Dijon, CNRS, INRAE, Université Bourgogne Europe, F-21000 Dijon, France.</footnote>

<footnote>E-mail address: michel.visalli@inrae.fr (M. Visalli).</footnote>
consider taste a determining criterion in their food decisions (Arrazat et al., 2023; Block et al., 2013; Deliens et al., 2014; Kourouniotis et al., 2016; Liem & Russell, 2019; Martinez-Perez et al., 2022; Roy et al., 2019; Silva et al., 2020; Tam et al., 2017). Sensory epidemiology approaches indeed demonstrated that the sensory properties of food are key factors in moderating eating behaviours and food intake (Forde & de Graaf, 2022). Therefore, university students should be more likely to adopt and maintain a healthy and sustainable diet if they derive pleasure from its consumption (Kwasnicka et al., 2016). However, there is still a lack of research that specifically documents students' food preferences and the extrinsic product factors that may influence these preferences and shape their food choices in real-life contexts (Conti et al., 2018; Ramsay et al., 2017).

Preferences and their role in food choices have been explored through different approaches. The most common involves sensory evaluation studies that assess the acceptability of foods based on their sensory characteristics. This approach has the advantage of examining preferences in conditions of direct exposure to foods. However, as most studies are conducted in laboratories and/or under blind conditions, it is well established that the ecological validity of these measures remains limited (Cardello et al., 2000; Lahne, 2016). In real-life situations, sensory perception and appreciation are influenced by a variety of intrinsic and extrinsic factors related to both the food and the consumer (Symmank, 2019). Thus, studies combining behavioural economics and sensory evaluation, which simulate real-life conditions (e.g., tasting in informed conditions) and involve actual product purchases while remaining in a controlled environment, are also used. However, these studies still raise the issue of balancing internal validity with external validity, which can limit their ability to generalize to real-life situations (Vecchio & Borrello, 2019). A common limitation of both approaches is their focus on a limited range of foods within a specific category. This restriction can be problematic because it may not fully capture the diversity of food preferences and choices that consumers make in real-life situations, where they are exposed to a much broader variety of products across different categories. The use of generic questionnaires that assess overall liking for generic food categories (Carbonneau et al., 2017; Duffy et al., 2009) can help address this limitation by broadening the scope of food preferences beyond a restricted selection of items. However, this approach introduces other issues. In the absence of direct exposure to the foods, the responses can be overly general or influenced by social desirability bias (Cerri et al., 2019), and may not accurately reflect individuals' true preferences.

To better understand the link between preferences and eating behaviours, it is necessary to maximize ecological validity by getting as close as possible to real-life conditions (Galiñanes Plaza et al., 2019; Stelick & Dando, 2018). Dijksterhuis et al. (2022) proposed that, among various methods of collecting consumer-related data, behaviour-based data may be the most suitable for developing predictive models of future consumption patterns. They also emphasized that the most valid insights into food-related consumer choices stem from interactions with real food. When assessing food preferences, this suggests the importance of integrating the best of each approach outlined in the previous paragraph, namely evaluating food liking after the various stages of food selection (thereby considering cognitive, economic, practical, and social dimensions), for a wide range of actually consumed foods that are representative of an individual's overall diet (rather than generic food categories or specific food chosen and provided by the experimenter). In this regard, real-life data collection presents an interesting opportunity, as they enable the gathering of data related to individuals' behaviours and perceptions in natural settings, without direct intervention of experimenters (Leatherdale, 2019).

This article presents a proof-of-concept for a multi-dimensional approach to assessing food preferences based on ecological, real-life data. Over the course of a month, French students provided hedonic ratings for food products they personally sourced. These ratings were analysed in conjunction with detailed information on food categories,

nutritional quality, and environmental impact—considered as sustainability indicators. The analysis also incorporated intrinsic and extrinsic product attributes (e.g., sensory properties, price) as well as consumers' behavioural factors (e.g., consumption frequency, sourcing location), offering a more holistic view of the relationships between students' food preferences and real-life food selection. The specific objectives were to validate the effectiveness of the approach in (i) documenting French students' preferences for the foods they sourced, (ii) identifying foods that provide co-benefits in terms of both sensory pleasure and sustainability, and (iii) gaining a deeper understanding of the competing intrinsic and extrinsic food products attributes and contextual factors that shape food preferences in real-life settings.

## 2. Material and methods

### 2.1. Summary of data collection procedure

This study is a secondary analysis based on data originally collected to validate COD-Appro, a web application designed to gather data on sourced foods, including nutritional composition and environmental impacts, as described in Marty, Dahmani, & Nicklaus, 2024; Marty, Teil, Lange, Bellassen, & Visalli, 2024. The data collection was conducted between November 7 and December 18, 2022. The protocol was approved by the Inserm ethical committee (IRB00003888, reference: 22-884).

Participants for the study were recruited through various channels (social media, posters, flyers, and mailing to individuals registered in the ChemoSens platform's participants database). Eligible participants were university students living in Dijon, aged over 18, fluent in French, and representative of the French student population based on age, sex, and scholarship status. A total of 110 participants were included, and 102 completed the one-month data collection. Among them, 56 % were female, 44 % male; 49 % were aged 18–21, 39 % 22–25, and 12 % over 25; 34 % had a scholarship; 62 % declared to be omnivores, 30 % flexitarian, and 8 % vegetarian. Participants received a 50 € compensation.

The students were briefed (in-person or online) during 30-min sessions about the general objectives of the research, the course of the study, and the use of the COD-Appro web application. They were required to report the food they sourced using the web application over a one-month period. After being assigned a 6-letter personal ID, participants were required to record the date and location for each food sourcing episode, selecting the place from a predefined list. Then, for each item sourced, they have to fill in the label of the food among a predefined list. The items in the list corresponded to the food labels from the Ciqual database, a French resource that provides detailed information on the nutritional composition of food, including nutrient content data for thousands of items (ANSES, 2020). Finally, they had to fill in the quantity, the price and the labels displayed on the packaging, if any, and they could also optionally rate their liking of the current food item on a five-stars scale (Sparling & Sen, 2011). The question was: “How much did you generally like the taste of this food?”. The five-star scale, recognized for its simplicity and ease of use (Waimaleongora-ek & Pri-nyawiwatkul, 2021), was chosen to allow participants to report their liking on the smartphone application while minimizing cognitive effort and enhancing engagement (Chen, 2017). At the end of the study, they had to fill a questionnaire related to their dietary habits (a Food Frequency Questionnaire of 125 items previously used by Arrazat et al., 2023), food choice motives (an adaptation of the Food Choice Questionnaire previously used by Marty et al., 2021), and individual characteristics (e.g., socio-demographics, type of diet, etc.).

### 2.2. Data analysis

All analyses were performed using R software, version 4.3.1 (R Core & team., 2017). The data and codes used are available online (Visalli et al., 2025).
## 2.2.1. Data selection, pairing with external databases and indicator computation

The 102 students provided a total of 8329 food records over one month.

To ensure that the analysis was based on representative data that reflects consistent eating patterns rather than occasional food entries, it was important to focus on students who demonstrated a substantial level of engagement in the study and provided a sufficiently large and consistent amount of data to minimize the impact of outliers or incomplete data. In statistical terms, 30 is often considered a “sufficiently large” sample size, this is why, as rule of thumb, we decided to include only students who declared at least 30 food records (excluding those related to ingredients such as spices, pie crusts, etc.) associated with liking scores. This resulted in 6178 food records from 84 students being retained for this secondary analysis.

All retained food records were associated with a Ciqual code during their registration (Marty, Teil, et al., 2024), allowing for the determination of nutritional values, food categories and subcategories.

Sourcing locations were manually categorized into “in institutional catering”, “in commercial food service”, and “for home consumption”.

For each food item, the nutrient content (lipids, saturated fatty acids, salt, sugar) in g/100 g was categorized into one of three levels: “low”, “medium”, or “high”, according to the criteria of the FSA’s traffic light system (Department of Health and Food Standards Agency, 2016). The decision to categorize the nutrient content of food items (lipids, saturated fatty acids, salt, sugar) using the FSA’s traffic light system was made to ensure that the classification was both nutrient-based, scientifically grounded and easily interpretable in a way that aligns with public health guidelines.

The pairing with environmental data was done using Agribalyse (ADEME, 2020) using the Ciqual code as the key for matching. For each food, the single EF score, based on 16 impact indicators and expressed in points per 100 g of the finished product, was classified into one of five levels (ADEME, 2024): “A” (low environmental impact), “B”, “C”, “D”, or “E” (high environmental impact).

The items from the food taste database developed by Martin et al. (2014) were manually linked to Ciqual food items by the authors. This database includes mean sensory intensity scores for the five basic tastes (sweet, bitter, sour, salty, umami) and the fat sensation, evaluated by a trained sensory panel using a logarithmic Spectrum scale. For each food item, these scores were classified into one of four levels: “none” ([0–1[]), “low” ([1–3[]), “medium” ([3–5[, or “high” ([5–10[]).

The food items from the Food Frequency Questionnaire were manually linked to Ciqual items by the authors. For each food item, the frequency of consumption was categorized into one of four levels: “monthly”, “weekly”, “daily”, or “high-frequency daily” (more than once a day) frequency.

Finally, for each food, the price, centered and scaled by food category, was calculated and then categorized into one of three levels: “low” (<−0.7), “medium”, or “high” (>0.7).

For the last three variables (taste, frequencies, and prices), the classes were defined to ensure a sufficient number of observations in each category.

## 2.2.2. Distribution of liking scores

The distribution of the students’ liking scores was represented as a stacked barplot. To assess the level of representativeness of preferences, the average and standard deviations of the number of food items with a liking score per student were calculated. To describe the variability in preferences, for each participant, the percentage of each score (from 1 to 5) was calculated, and then the averages of these percentages was computed at the panel level.

The means and standard deviations of the liking scores were compared between levels of variables related to individual characteristics (gender, age group, type of diet, perception of financial situation, place of living, living conditions, responsibility in purchasing,

responsibility in cooking, and importance of taste/health/convenience/ethics/weight control/familiarity/price in food choices) using bootstrapping (1000 iterations). Bootstrapping was employed in this analysis because the data are discrete, follow non-normal distributions, contain missing data, and are unbalanced. This method enabled the estimation of confidence intervals and the testing of differences between means without making strict assumptions about the data distribution, thus providing a robust approach to address these issues (Henderson, 2005). Means computed based on food sourced by fewer than 30 students were not interpreted.

## 2.2.3. Differences in preferences across the different levels of the categorical variables of interest

The liking scores were centered by participant (thereafter denoted CL) to reduce the effect of individual differences in the use of the scale. Then, a screening of preference differences was conducted for each variable: food category, nutritional quality, environmental quality, frequency of consumption, place of purchase, price, and taste intensity. To compare the mean preference levels across the different levels of the categorical variable of interest, the following steps were carried out:

(i) Calculation of the mean of CLs (thereafter denoted MCL) for each participant at each level of the categorical variable of interest.

(ii) Calculation of the mean and 95 % confidence interval of MCLs at each level of the categorical variable of interest by bootstrapping MCLs (1000 iterations), using *smean.cl boot* function of the Hmisc package (Harrell & Dupont, 2025). The mean MCL was considered significantly different from 0 if the confidence interval of the average did not contain 0 (the foods having a mean significantly greater than 0 being the most liked, and the foods having a mean significantly lower than 0 being the least liked).

(iii) Determination of pairwise differences between MCLs at each level of the categorical variable of interest at a 5 % significance threshold by bootstrapping participants’ MCLs (1000 iterations), using *pairwise boot* function of the KefirR package (Masse, 2024).

(iv) Determination of the effect size of the difference between MCLs and assignment to a group: “ns” (not significant), “n” (negligible), “s” (small), “m” (moderate), “l” (large) according to Cohen’s *d* (Cohen, 2008), using *cohens_d* function of the rstatix package (Kassambara, 2023). Cohen’s *d* is a statistical measure used to quantify the magnitude of the difference between two groups, assessing not only statistical significance but also practical significance. It was calculated by subtracting the mean of one group from the mean of the other and dividing the result by the pooled standard deviation.

(v) *Post-hoc* determination of groups of means of MCLs using the Compact Letter Display (CLD) algorithm (Piepho, 2012) with mult-compLetters function from the multcompView package (Graves et al., 2006). The CLD algorithm enabled to display the results of pairwise comparisons in a compact format, by grouping the means that were not significantly different from each other using letters.

(vi) Graphical representation of confidence intervals (green if the lower bound did not contain 0, red if the upper bound did not contain 0, black otherwise), and comparisons of MCLs by level of the categorical variable of interest. Means sharing the same letter (displayed below the confidence interval) are not significantly different at the 5 % significance level, with the number of students indicated above the confidence interval.

# 3. Results

## 3.1. Distribution of liking scores

Fig. 1 shows that the majority of students assigned high ratings (4 or 5) to the foods they selected, suggesting that they primarily choose foods they enjoy the taste of. Specifically, the average number of sourced foods with a liking score per student is 73 (standard deviation: 42), with the following score distribution: <1 % rated 1, 3 % rated 2, 21 % rated 3, 34
<figure><img src="image_5.png" /><figcaption>Fig. 1. Distribution of liking scores in sourced foods among students.</figcaption></figure>

% rated 4, and 42 % rated 5.

The average liking score by participant was 4.22 (confidence interval: [4.11–4.33]). There were significant differences only between genders ($p = 0.008$; moderate effect size; male: [3.91–4.23], $n = 45$; female: [4.21–4.49], $n = 39$) and levels of responsibility in purchasing ($p < 0.001$; small effect size; totally: [4.19–4.46], $n = 52$; partially: [3.94–4.25], $n = 30$).

## 3.2. Preferences by frequency of food consumption

Fig. 2 shows that foods consumed daily were significantly more liked, while foods consumed on a monthly basis were significantly less liked. The large confidence interval for preferences of high-frequency daily consumed foods may be attributed to the fact that this category includes a mix of foods with varying hedonic valence, consumed either out of habit, necessity or pleasure. Indeed, this category encompasses routine foods such as coffee, functional foods such as water and bread, and dessert foods such as yoghurts and apples (see Fig. 3 and Supplementary material for details of preferences by food category).

## 3.3. Preferences by food categories

Fig. 3 shows that beverages, milk products, and sugar and confectionery products were the most significantly liked food categories, while cereal products were significantly less liked. Preferences for starter and dishes, fruits/vegetables/legumes/nuts, and meats/eggs/fish were in between. At the subcategory level (see Supplementary material), it can be observed that within their respective categories, fruits were significantly more liked, while vegetables, potatoes and tubers, legumes, mixed salads, and pasta/rice/grains were significantly less liked.

## 3.4. Preferences by intensity of sensory perception of basic tastes and fat taste

Fig. 4 shows that preferences varied according to the perceived intensity of basic tastes. Overall, foods with the most intense perceived flavours were selected by fewer students (but they were also less numerous, see Martin et al., 2014). For foods with sweet and sour tastes, preferences increased with the intensities of these taste attributes (Figs. 4.A and 4.C). Foods sensorially perceived with no sweet or sour

<figure><img src="image_6.png" /><figcaption>Fig. 2. Mean of centered liking scores by frequency of consumption.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Fig. 3. Mean centered liking scores by food categories.</figcaption></figure>

intensity were significantly less liked than those perceived with medium sweet or sour intensity. Regarding foods with salty taste, preferences followed a U-shaped distribution (Fig. 4.B). Foods perceived with low salty intensity were the least liked, those perceived with medium salty intensity were moderately liked, and foods perceived with no salty intensity were the most liked. A preference for foods perceived with medium bitter intensity can be noted, but only for a small subgroup of students (Fig. 4.D). Preferences for foods followed a decreasing trend with the perceived intensity of umami (Fig. 4.E). Foods perceived with medium umami intensity were less liked than those perceived with medium intensity, but only for a small subgroup of students. No strong trend was observed between preferences and the perceived intensity of fat taste (Fig. 4.F). Foods perceived with low fat intensity were slightly less liked than those perceived with medium fat intensity.

### 3.5. Preferences by sourcing location

Fig. 5 shows that foods consumed at home or outside the home were significantly preferred over foods consumed in institutional catering, which were, on average, less liked. These results were observed across most product categories, but were particularly pronounced in the fruits/vegetables/legumes and cereal products categories (see Supplementary material).

### 3.6. Preferences by food price

Fig. 6 shows that foods with medium prices in their food category were significantly more liked than others. This trend, analysed by food category (see Supplementary material), was particularly pronounced for the fruits/vegetables/legumes category.

### 3.7. Preferences by nutrition and environmental quality of foods

In general, preferences follow a gradient based on levels of content of fat, saturated fat, and sugar. Specifically, foods that are very high in fat were significantly more liked, while foods low in fat were significantly less liked (Figs. 7.A and 7.B). Medium and high sugary foods were very significantly more liked, while foods with low sugar content were very significantly less liked (Fig. 7.C). No link between preferences and salt levels was observed (Fig. 7.D). The absence of significant difference in Fig. 7.E suggests that preferences were not related to the environmental impact of foods.

## 4. Discussion

### 4.1. Impact of preferences on French students' sourcing of food

The results of this study confirm previous findings showing that French students, as most populations in affluent regions, place significant importance on the hedonic aspects of their diet (Arrazat et al., 2023; Block et al., 2013; Deliens et al., 2014; Kourouniotis et al., 2016; Liem & Russell, 2019; Roy et al., 2019; Silva et al., 2020; Tam et al., 2017). They primarily sourced foods perceived as pleasant in taste (3/4 of the foods had a liking score of 4/5 or higher in Fig. 1). While this outcome was expected, the study provides insight into the extent to which preferences influence students' food choices in real-life situations, where other considerations—such as cost, availability, convenience, control due to health, environmental concerns or social pressure, and other external influences—also play a role.

The imbalance in favour of pleasure-driven choices suggests that students' eating behaviours are similar to those of children and adolescents, whose food decisions are primarily influenced by the hedonic aspects of taste (Daly et al., 2022; Hebden et al., 2015; Neufeld et al., 2022; Nguyen et al., 2015). Women, on average, assigned higher hedonic values to the foods they sourced, which is in line with the findings of Buczek et al. (2020), who demonstrated sex differences in hedonic eating. Liking scores were also higher among students responsible for food shopping in their household, suggesting that partners may partially experience choices that are not fully aligned with their own preferences. No difference was observed among age groups, but our small sample size did not allow for a detailed investigation of differences between younger and older students.

Food preferences play a crucial role, not only in food choices but also in the frequency of consumption. Foods reported to be consumed daily were the most liked, while foods reported to be consumed monthly were less liked (Fig. 2). These results align with the conclusions of previous studies conducted in the general population (Drewnowski & Hann, 1999) and among young adults (Livingstone et al., 2020). However, some foods consumed multiple times a day received medium-low liking scores. Many of these foods fall under the category of “utilitarian” (Cramer & Antonides, 2011), which are consumed primarily for functional purposes such as nutritional value, health benefits, or energy needs. It is important to note that even for utilitarian foods, taste is generally considered important (Maehle et al., 2015), which may help explain the relatively low proportion of foods rated 3 or lower (Fig. 1). Social norms (Higgs, 2015), habits (Van't Riet et al., 2011), or hedonic adaptation (You et al., 2024) may also explain the consumption of foods
<figure><img src="image_8.png" /><figcaption>Fig. 4. Mean centered liking scores by intensity of sensory perception of basic tastes and fat taste.</figcaption></figure>

with more neutral hedonic valence.

## 4.2. Preferences for sustainable foods

In this study, students' preferences tended to conflict against nutritional recommendations in terms of categories of foods to prioritize (Fig. 3), confirming the findings of several previous studies (Arrazat et al., 2023; Bernardo et al., 2017; Dharmayani et al., 2024; Horacek et al., 2013; Papadaki et al., 2007; Ramón-Arbués et al., 2021; Roy et al., 2017; Tayhan & Helvacı, 2024; Whatnall et al., 2019). There were some exceptions where product categories such as fruits, nuts, seeds and soups demonstrated co-benefits in sensory pleasure and sustainability, at least for certain students (see Supplementary material). This finding suggests that taste may not be a significant barrier to adopting more sustainable eating habits, as it might be possible to make adjustments to the proportion of more beneficial foods without drastically changing the overall diet. However, the fact that, contrary to fruits, nuts, seeds and soups are not more commonly sourced or consumed points to a disconnect between preferences and actual dietary behaviours. This may be due to a

range of factors, including higher cost, limited availability in certain food environments, lack of familiarity with preparation methods, or simply being overlooked in daily meal planning.

The environmental qualities of foods did not seem to have an impact on students' food preferences (Fig. 6.E). This result could be explained by the fact that within each environmental class, there were both liked and less liked foods. This implies that, at the individual dietary level, it is feasible to identify foods that are both low in carbon impact and well-liked.

## 4.3. Preferences for other food product categories

Beverages and sugar-derived products were among the most preferred food categories. The natural craving for sugary foods, which trigger a dopamine response and endorphin release (Liu & Bohórquez, 2022), makes them highly desirable due to their immediate pleasure and quick energy boost. Extensively marketed toward younger audiences, these products are convenient, accessible, and ready-to-consume—attributes that can make them particularly appealing during long
<figure><img src="image_9.png" /><figcaption>Fig. 5. Mean centered liking scores by sourcing location.</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>Fig. 6. Mean centered liking scores by food price.</figcaption></figure>

study sessions, tight schedules, or while on the go, thus contributing to their popularity among students with busy lifestyles.

Milk-based products were liked at the same level as beverages and sugar-derived products. Introduced to people in infancy or early childhood as part of a balanced diet and influenced by cultural traditions (Franzon et al., 2024), this early exposure can lead to lifelong preferences. Moreover, these products are often linked to childhood memories and comfort food, and they are also widely marketed as healthy options due to their nutritional benefits, including calcium, vitamin D, and protein (Jakubowska et al., 2024).

Vegetables, potatoes and tubers, legumes, and mixed salads rank among the least liked food categories (Fig. 3 and Supplementary material), despite European policies focusing on increasing vegetable and legume acceptance. Globally, efforts to promote healthy eating mainly focus on providing nutritious food in public institutions, and raising awareness through education and media campaigns; however, according to the FAO, these interventions generally produce modest, short-term effects and are difficult and expensive to scale to a level that significantly impacts population-wide dietary habits (Gerritsen et al., 2021).

Pasta, rice, and grains, associated with less pronounced taste

intensities, were significantly less liked than vegetables, potatoes and tubers, and legumes. This result aligns with the findings of Forde and de Graaf (2022), who highlight that these foods often have relatively low hedonic value, possibly due to their use as staple foods. For pasta-based foods, a recent decrease in consumption has been observed in several countries, which may be attributed to several factors, including growing awareness of high-quality foods and increasing health consciousness, the globalization of food production and consumption, and the emergence of new formulations such as gluten-free, plant-based, or whole-grain pasta (Mandolesi et al., 2023). It is also possible that pasta is too frequently consumed among student populations, as it is inexpensive and easy to prepare. This could lead to a saturation effect, particularly if there is little variety in preparation methods or if the pasta is poorly cooked.

Finally, meat, eggs, or fish products, received medium-low preference scores. These results contrast with literature data, which report a high appreciation of meat among students (Cripps & Thiagarajah, 2018; Ruby et al., 2016). The increasing popularity of plant-based diets, particularly among younger and more educated populations, more attuned to environmental and ethical concerns and susceptible to influenced by their social environment whom they perceive avoiding
<figure><img src="image_11.png" /><figcaption>Fig. 7. Mean centered liking scores by nutrition and environmental quality of foods.</figcaption></figure>

meat as a social norm, could be a factor in the relatively low liking scores for meat, eggs, and fish products (Sedová et al., 2016). It could also reflect a more balanced acceptance of vegetarian and non-vegetarian dishes (Marty, Dahmani and Nicklaus, 2024).

4.4. Different influences of nutrient composition versus taste perception on preferences

It is well established that the sensory appeal and appreciation of
foods are largely determined by their perceived physical and chemical
properties before and during consumption (Forde & de Graaf, 2022).
The results on preferences by food nutrient composition (Fig. 6.A-6D)
are overall consistent with the literature. Preferences for fatty and
sugary foods are well-documented (Drewnowski & Almiron-Roig,
2010). In this regard, students' preferences seem to align with those of
adolescents, who are known for their attraction to foods rich in fats and
sugar (Forde & de Graaf, 2022; Hoffman et al., 2016). Preferences for
salty foods, however, are more variable depending on individuals
(Bobowski, 2015; Proserpio et al., 2025), which may explain why no
clear trend emerges on average.

While the results regarding preferences for sugary foods are consis-
tent between their composition and sensory perception (Figs. 6.C and 4.
A), a relative dissociation between the objective nutritional composition
of foods and the sensory perception of the fatty (Figs. 6.A/B and 4.F) and
salty foods (Figs. 6.D and 4.B) can be observed. This result is not

unexpected, as modern processed foods often contain a complex mixture
of ingredients, including flavour enhancers, stabilizers, emulsifiers, and
various additives, which interact with one another and the natural
components of the food to create a distinct sensory experience (Huang
et al., 2024). Lower preferences were also observed for foods with a
medium level of umami flavour (Fig. 4.E), which goes against the
literature, as umami is typically described as enhancing the palatability
of foods (Wang et al., 2020). These findings, therefore, point to the
importance of considering not just the nutritional breakdown of foods,
but also the complex interactions between ingredients and how they
shape sensory experiences.

Beverages, sweets, fruits, and dairy products were the most liked
categories (Fig. 3 and Supplementary material). These foods are pri-
marily dominated by sweet, sweet/fatty, or salty/fatty flavours (Martin
et al., 2014), Sweet and fatty flavours are recognized for their universal
appeal (Drewnowski & Almiron-Roig, 2010; Drewnowski & Hann,
1999). The U-shaped distribution of preferences for foods perceived as
salty (Fig. 4.B) suggests complex preference patterns (Bobowski, 2015).
However, it is important to note that in this study, behaviours such as
adding salt or sauce before food consumption were not recorded.

Vegetable and legumes foods are generally perceived as low in
sweetness and fat, with some of them exhibiting sour or bitter flavours
(Martin et al., 2014). Bitterness is frequently cited as a cause of rejection
for these foods (Amoah et al., 2023). However, in this study, medium
bitter foods were not less liked than those with low or no bitterness
(Fig. 4.D). Unlike sweet and fatty flavours, students seem to deviate from children's preferences, as children generally reject bitter flavours (Forde & de Graaf, 2022). This divergence could be explained by the fact that those who truly disliked these products simply did not purchase them, or by a learning process (Stein et al., 2003) during student life, which involves "social consumption" of bitter beverages like coffee or beer.

## 4.5. Other factors associated with French students' preferences

The location of the food sourcing (and, by extension, the context of consumption) was the factor that had the most significant impact on French students' preferences (Fig. 5). Several reasons may explain the lower liking scores in collective catering as compared to food sourced in commercial food services or for home consumption. The choices may have been influenced by the variety of foods available at the time of sourcing. Foods intended to be consumed at home were mostly purchased in supermarkets, a setting offering a wide variety of hyperpalatable commercial products, allowing students to align their choices with their personal tastes. In contrast, the food offerings in dining facilities are inherently more limited. In commercial restaurants, menus are typically designed to meet the expectations and preferences of customers. However, in collective catering, menus are standardized and designed with economic and nutritional constraints in mind (Barić et al., 2003). For students, this resulted in a reduction of hedonic choice opportunities. Pechey et al. (2022) showed that offering a variety of vegetables increased the probability of finding a food that is liked in the assortment. Similarly, Arrazat et al. (2023) demonstrated that doubling the offer of vegetarian dishes in a university cafeteria significantly improved their average appreciation. These studies emphasize the importance of satisfying various individual preferences when designing menus for large audience, as pointed out by (Ueland et al., 2020) and Briazu et al. (2024).

Beyond food diversity, the context of consumption could have also influenced preferences. In addition to being associated with negative stereotypes, collective catering can suffer from lack of conviviality (Galiñanes Plaza et al., 2022). This may be due to additional constraints such as fixed hours, limited meal durations, and unappealing environments (Edwards et al., 2019; Meiselman, 2006). In contrast, foods consumed at home may have benefited from a positive association with an intimate and familiar setting, while meals consumed in commercial restaurants incorporated a social and convivial dimension, thereby enhancing satisfaction (Galiñanes Plaza et al., 2022). These observations support the findings of Edwards et al. (2003), who showed that the same foods were significantly less liked when consumed in collective catering compared to a restaurant.

Another characteristic that distinguishes the most liked foods from the least liked ones (Fig. 3) is that the former were mostly sourced ready-to-eat, whereas the latter typically required culinary preparation. All food categories were significantly less liked when consumed in collective catering, but this effect was particularly pronounced for vegetables and legumes, as well as pasta, rice, and cereals. When these food categories are prepared in advance and in large quantities, they may lose sensory quality due to cooking, storage, presentation, or seasoning processes that are not optimal (Galiñanes Plaza et al., 2022). In contrast, lower-quality foods (such as junk food) often have taste profiles that remain appealing (Tetens et al., 2019), even when preparation quality is suboptimal, particularly in a collective catering setting. This suggests that the issue is not a general preference for low-nutritional-quality foods over high-quality ones, but rather a more specific culinary challenge related to food preparation and handling.

The food sourcing context is also closely linked with the food price. A relationship between food prices and preferences was observed (Fig. 6), suggesting that the least expensive foods within a given food category were significantly less liked. From a sensory perspective, cheaper products may be of lower quality due to differences in the ingredients used or manufacturing processes. For example, inexpensive fruits and

vegetables may have been harvested before reaching full maturity, resulting in lower taste quality. Psychologically, price may also have played a role in shaping the subjective perception of food quality (Galiñanes Plaza et al., 2022; Just et al., 2014), with a direct effect on liking (Plassmann et al., 2008).

## 4.6. Strengths and limitations of real-life data collection to investigate the relationships between sensory properties, preferences and food choices

This study stands out for its ecological approach to evaluating contextualized food preferences, based on data collected from foods sourced in real-life settings. In most traditional sensory evaluations, participants assess their liking for a subjective selection of foods including a limited number of items chosen by the experimenter, in a blind test, during a single controlled laboratory session. In contrast, participants in this study rated their liking in informed conditions, for a wide variety of foods from different categories, which they freely selected over a one-month period. Unlike most behavioural economics approaches, they assessed foods they actually purchased and consumed in various contexts, taking into account factors such as price, availability, and the occasion for consumption. The inclusion of proof of purchase helped ground the evaluations in concrete behaviours, rather than declarative intentions. In comparison to traditional food surveys, this method questioned consumers about specific foods rather than food categories, and allowed for more precise longitudinal tracking, with the collection of exact sourcing dates, rather than relying on a monthly recall based on memory. This enabled a more accurate and dynamic reconstruction of eating patterns, ensuring a better representation of consumers' actual diets, in line with recommendations to collect evidences based on actual food consumption (Krasovskaia & Just, 2024). Additionally, this approach integrates directly with existing databases, enriching the information collected on foods, such as nutritional, environmental, and sensory properties, for a more comprehensive analysis.

The findings of this study regarding students' preferences align with several well-established results in the literature, thereby supporting the external validity of the approach. However, the approach has limitations that could restrict the generalization of the conclusions. Although the student population was recruited using a quota sampling method, a significantly larger sample, recruited from a broader geographic area than Dijon and its surroundings, would be necessary to draw more robust conclusions and to study the combined effects of several variables (interactions) on preferences, or to make cluster analyses. The data collection procedure used presents conceptual and methodological challenges (Taillie et al., 2017). In particular, it suffers from the absence of control over both observed and unobserved variables, and confounding biases may complicate the interpretation of main effects and limit the scope of the conclusions (Leatherdale, 2019). Moreover, in this study, a high level of participant involvement was required to report and evaluate sourced food thus limiting the data collection period to one month. Biases related to seasonal effects may have been introduced. The delayed measurement of liking, not necessarily concurrent with the food consumption, may have been affected by memory bias or simplification of the participants' actual preferences. Nevertheless, this study serves as a proof of concept, demonstrating the feasibility and value of measuring preferences based on real-life data collection of sourced foods.

Several approaches could be considered to collect more accurate data on food products. Sourced data were recorded by asking participants to select a food item from a pre-established list of food names corresponding to the Ciqual reference to facilitate matching with nutrient composition and environmental impacts but disregard intra-food variability. By collecting sourced data at the level of a commercial designation (e.g., scanning food barcodes, or automatically extracting product names from invoices or receipts), and matching these data with databases like Open Food Facts (Open Food Facts, 2024), it would be possible to obtain more precise information on food compositions, environmental impacts, brands, associated labels, packaging,
etc. Basic taste intensities could also be directly assessed by consumers using adapted measures to better capture the subjective nature of sensory perceptions. Additionally, modalities such as appearance and texture could be integrated in the evaluation process. Finally, participants could be asked to describe more precisely the context in which the products were consumed (meal type, preparation mode, social context, etc.). Given the level of investment this would require, participatory science approaches could be considered (Espinosa-Brisset & Saint-Eve, 2024).

## 4.7. Implications

Promoting sustainable food choices cannot rely solely on prescriptive or proscriptive approaches; as consumer preferences play a central role in eating behaviours and directly influence individuals' adherence to nutritional and environmental recommendations, it is essential to integrate them into the development of public health policies (Irz et al., 2016). Health-focused messages often conflict with individuals' immediate sensory preferences at the moment of food choices, limiting their effectiveness in shaping actual eating behaviour, and highlighting the need for approaches that emphasize the tasty and enjoyable aspects of healthier foods (Turnwald et al., 2019).

The findings of this study demonstrate that food choices and preferences are intricately linked, yet not fully correlated. Indeed, food choices are influenced by a complex interplay of factors that interact with preferences in sometimes unexpected ways. In this regard, it would be valuable to compare how different populations (e.g., young vs. older adults, or low-income vs. high-income groups) rate their liking for the foods they sourced. Such comparisons could help determine whether the 25 % threshold of medium-liked foods is specific to students or reflects a broader trend across various demographic groups.

While controlled environment experiments and questionnaires offer valuable insights into the impact of individual factors, they cannot capture the full range of influences that shape consumer preferences in real-life contexts. The goal of the presented approach was not to identify sensory determinants for guiding new product development (which can be achieved through traditional sensory evaluation) nor to assess the theoretical impact of information (which can be done through discrete choice experiments) on food choices. Instead, by combining sensory and behavioural measurements grounded in the real-life context of food selection, this approach aimed to open new avenues for food sensory and consumer research by providing a more information of how contextual factors influence preferences, and how, in turn, preferences shape food choices and sourcing decisions. The study's results allowed us to generate hypotheses about the interactions between intrinsic factors (e. g., nutritional composition, flavours) and extrinsic factors (e.g., preparation methods, consumption context, availability, price) that modulate food preferences.

The findings of this study suggest that encouraging healthy choices depends not only on availability but also on enhancing the taste of healthy foods. For home consumption, this can be achieved through taste or cooking training interventions targeted at young adults (Hersch et al., 2014). In the specific context of collective catering, adapting culinary practices – such as making sustainable foods more flavourful to better align with consumer expectations (Fritts et al., 2018) – could be more effective and easier to-implement than modifying the food offering itself. Further research could explore strategies for optimizing food offerings in collective catering by increasing choice diversity to account for individual differences in liking, while still achieving nutritional, environmental, and economic goals, with the challenge of not increasing waste. Practical approaches might include designing more flexible meal plans leveraging technology to anticipate (e.g., through reservations) or predict demand (e.g., using models based on previous consumption patterns).

More broadly, the results support the idea that promoting sustainability in diets doesn't necessarily involve sacrificing taste or making a

complete switch of diet, and that sustainable food choices may be better aligned with students' preferences through more targeted or personalized recommendations rather than relying primarily on generic public health messages. In this regard, it may be beneficial to dissociate fruits from vegetables in general recommendations to place greater emphasis on these products (Tru徒au et al., 1998), and focus could be made on certain fruits, such as citrus and berries, which appear to possess functional properties that may offer additional health benefits (Wallace et al., 2020). Future research could explore whether it is possible to encourage students to incorporate more sustainably sourced foods they enjoy into their diets through more individualized intervention strategies. Recent studies suggest that strategies using taste as a "nudge" could be promising (Kokkorou et al., 2024; Visalli et al., 2024).

## 5. Conclusion

This study highlights the importance of sensory preferences on the food sourced by French university students. The majority of the sourced foods were highly appreciated, leading to more frequent consumption. Among these, foods with sweet and fatty tastes were generally preferred. However, it is important to note that the sensory perception of fat and salty tastes did not always align with their nutritional content, revealing a disconnect between sensory appeal and nutritional value. Furthermore, students' preferences often conflicted with nutritional recommendations but not with lower environmental impacts. The context in which foods were sourced emerged as the most influential factor on preferences, with foods sourced in collective catering settings being the least liked. Additionally, ready-to-eat foods were preferred over those requiring culinary preparation, and lower-priced foods within a category were less liked. Finally, certain food categories, such as fruits or nuts, offer both sensory enjoyment and potential health and sustainability benefits.

More generally, this research highlights the need for more individualized approaches in intervention strategies to support the food transition toward sustainability, taking both individual preferences and the subjective, holistic dimensions of eating pleasure into account. In this regard, it is crucial to continue developing large-scale, ecological approaches that integrate measurements of food choices and sensory experiences in real-life settings. Such approaches should consider individual factors (motivations, representations, expectations, etc.), behavioural factors (eating habits, purchase and consumption contexts, preparation methods, etc.), and contextual influences (economic, social, temporal, etc.). Ultimately, understanding and integrating these diverse factors will be key to fostering lasting and meaningful changes in dietary behaviours that meet sustainability goals without altering individual consumption patterns beyond their threshold for acceptance.

### CRediT authorship contribution statement

**M. Visalli:** Writing – original draft, Software, Methodology, Formal analysis, Data curation, Conceptualization. **F. Teil:** Methodology, Investigation, Data curation. **L. Marty:** Writing – review & editing, Project administration, Methodology, Funding acquisition, Conceptualization.

### Ethical statement

The research was carried out following the Declaration of Helsinki. The consumers were informed of the conditions for participating and they gave informed consent validating a written form. They were able to withdraw from the study at any time without giving a reason. The protocol was approved by the by the Inserm ethical committee (IRB00003888, reference: 22–884).
# Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

# Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.foodqual.2025.105583.

# Data availability

Data and codes are shared on a public repository

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