Adherence to the Mediterranean Diet in Association with Self-Perception of Dietary Behavior (Discrepancy between Self-Perceived and Actual Diet Quality): A Cross-Sectional Study among Spanish University Students of Both Genders

Citation: Béjar, L.M. Adherence to the Mediterranean Diet in Association with Self-Perception of Dietary Behavior (Discrepancy between Self-Perceived and Actual Diet Quality): A Cross-Sectional Study among Spanish University Students of Both Genders. Nutrients 2024,16, 3364. https://doi.org/10.3390/nu16193364 Academic Editor: Enbo Ma Received: 16 September 2024 Revised: 30 September 2024 Accepted: 1 October 2024 Published: 3 October 2024 Copyright: © 2024 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). nutrients Article Adherence to the Mediterranean Diet in Association with Self-Perception of Dietary Behavior (Discrepancy between Self-Perceived and Actual Diet Quality): A Cross-Sectional Study among Spanish University Students of Both Genders Luis M. Béjar Department of Preventive Medicine and Public Health, School of Medicine, University of Seville, 41004 Seville, Spain; [email protected]; Tel.: +34-954-551-771 Abstract: Background/Objectives: The Mediterranean diet (MD) is one of the most studied dietary patterns to date and is associated with multiple benefits for health and sustainability. However, paradoxically, adherence to the MD (AMD) has been gradually decreasing in native regions. It is necessary to identify the factors that influence AMD to reverse this trend and to mitigate the negative outcomes (for health and the environment) associated with westernized diets. The objective of this study was to assess how self-perception of dietary behavior influences AMD. Methods: During the 28-day repeated measurement cross-sectional study, participants’ dietary information was obtained from an initial form which established the self-perception of dietary behavior and the e12HR application to establish actual food consumption by individuals. Using the dietary information from both sources, the AMD index was calculated (specifically, the Mediterranean diet Serving Score (MDSS) index). Two categories of self-perception of dietary behavior were defined: Normal/underestimation: difference (MDSS index from initial form—MDSS index from e12HR application) ≤ 0; and Overestimation: difference >0 (with three subcategories: low ( difference = 1–5 ), moderate ( difference = 6–10 ), high ( difference = 11–15 )). Results: 139 ( 111, women ; 28, men ) Spanish university students were studied, with 98.6% (99.1%, women; 96.4%, men) falling into the overestimation category (they overestimated their dietary behavior); these students had significantly lower MDSS indexes, mean = 6.7 , than students in the normal/underestimation category, mean = 12.0 . Within the overestimation category, there were significant differences in the MDSS index: low ( mean = 8.1 ), moderate ( mean = 6.7 ), and high ( mean = 4.9 ) subcategories and also differences that were significant in women but not in men. Conclusions: Overestimation of dietary behavior could be associated with lower AMD in all Spanish university students and women. Keywords: Mediterranean diet; Mediterranean diet adherence; students; eating behavior; university; mobile applications 1. Introduction The Mediterranean diet (MD) is a generic term used to describe the typical dietary pattern found in countries along the coast of the Mediterranean Sea; although there is no single MD, this dietary pattern presents common aspects regardless of the country in question (Crete, Greece, Italy, France, Portugal, Spain, Lebanon, Morocco, Tunisia, Turkey, and elsewhere in the Mediterranean region): It is primarily a plant-based diet (regular intake of olive oil—as the main fat—cereals, fruits, vegetables, legumes, and nuts); as for animal-based products, the intake of fish, poultry and dairy products is moderate and the intake of red or processed meat is low [1–3]. The MD, one of the most studied and well-known dietary patterns worldwide, has been associated with: (1) a wide range of health benefits, and (2) sustainability. Regarding the former, earlier research has provided evidence for the protective role of the MD with Nutrients 2024,16, 3364. https://doi.org/10.3390/nu16193364 https://www.mdpi.com/journal/nutrients Nutrients 2024,16, 3364 2 of 16 regards to cardiovascular disease, cancer, diabetes, excess weight/obesity, hypertension, metabolic syndrome, dyslipidemia, neurodegenerative disorders—particularly Alzheimer’s disease—respiratory diseases such as asthma and sleep apnea, renal disease, and mental disorders such as cognitive decline and depression [ 4 – 8 ]. Regarding the latter, the positive aspects of the MD on sustainability are its relatively low environmental impact in terms of water, nitrogen and carbon footprint; the richness of its biodiversity; and its positive local economic benefits [1,9–13]. Despite these well-known benefits (for health and the environment), paradoxically, adherence to the MD (AMD) has been gradually decreasing within its native region [12,14–17]. Given this context, it is necessary to elucidate the main factors behind the decline in AMD within its native regions to mitigate the negative outcomes (for health and the environment) associated with westernized diets. Empirical research and the theory of planned behavior suggest that behavioral attitude is an important construct associated with behavior intentions [ 18 ]. In this sense, some self-perceived attitudes of the individuals in the Mediterranean region that might influence AMD have been identified (attitudes associated with a lower AMD): attaching higher importance to the sensory appeal factor (e.g., indicating a preference for food that smells nice, has a pleasant texture, and tastes good) [ 19 ]; attaching higher importance to the convenience factor (e.g., indicating a preference for ready-to-eat or easy-to-cook products) [ 19 ]; attaching higher importance to the price factor (e.g., indicating a preference for cheaper food and good value for money) [ 19 – 22 ]; and a picky attitude toward eating (e.g., unwilling to eat unfamiliar foods or try novel foods) [19,23]. In a previous study carried out among cancer survivors in the United States (adults), it was found that the self-perception of dietary behavior (that is, the discrepancy between self-perceived and actual diet quality) was an important attitude that may have influenced the actual diet [ 18 ]. However, to the best of our knowledge, no previous study has explored the self-perception of dietary behavior in association with, specifically, AMD. The primary objective of this study was to assess the influence of self-perception of dietary behavior on AMD in the whole study sample and among both genders. In the previously mentioned study conducted among cancer survivors in the United States [ 18 ], those who overestimated the self-perception of dietary behavior tended to have a lower adherence to the recommendations of the 2010 Dietary Guidelines for Americans. Following this line of thought, the research team has hypothesized that an overestimated self-perception of dietary behavior (that is, self-perceiving greater AMD than that associated with actual dietary behavior) is associated with a lower AMD among Spanish university students. Spanish university students are a particularly interesting group among the younger generations as: (1) They are a subgroup at high risk for having unhealthy dietary habits [ 24 – 29 ]; and (2) they constitute a very large subgroup in Spain, with 1,690,947 students currently enrolled in Spanish universities [ 30 ]. In addition, secondary objectives were to establish AMD and the prevalence of the overestimation of self-perceived dietary behavior in the whole study sample of Spanish university students among both genders. 2. Materials and Methods 2.1. Design Overview The present study is a 28-day repeated measurement cross-sectional descriptive study. 2.2. Setting and Participants The recruitment of participants took place at the Faculties of Pharmacy and Dentistry at the University of Seville (Andalusia, Spain, South of Europe), selecting the three classrooms in which the principal investigator of the study taught (two classrooms at the Faculty of Pharmacy and one classroom at the Faculty of Dentistry); the recruitment of participants took place over two different months of the Academic Year 2023/2024: September 2023 (for the Faculty of Pharmacy) and February 2024 (for the Faculty of Dentistry). In each of the three classrooms selected for the research, the principal investigator of the study showed the project to the students in person, explaining the objectives, risks, and Nutrients 2024,16, 3364 3 of 16 benefits of the research as well as the procedures to properly fill out the different questionnaires used in the study (questionnaires in “Word” document format and questionnaires through the e12HR application (see Section 2.4. e12HR Application subsection)); finally, information was provided on how to participate in the study. Inclusion criteria: Both genders, over 18 years old, student of Pharmacy or Dentistry (University of Seville) and possess a smartphone. Exclusion criteria: Food intolerances, chronic pathologies, or pregnancy (due to the possibility of requiring specialized dietary recommendations). Confidentiality in the research was guaranteed in accordance with the Organic Law on the Protection of Personal Data (15/1999 of 13 December, OLPPD) and the Law 14/2007 on Spanish Biomedical Research. The steps to participate in the study were as follows: (1) Interested students were provided with a personal alphanumeric code in class; (2) All documents related to the study were available on an educational platform used by the University of Seville. This educational platform is separate for each classroom (with access limited only to the students and professors of each classroom). The documents available to students on the educational platform were as follows: (a) Informed consent; (b) Initial form (see 2.3. Initial Form subsection); (c) User manual with detailed information for downloading and using e12HR, an application that is free to download from the App Store or Play Store. The documents (a) & (b) were to be filled out and submitted on the educational platform; in each of the two documents, each student had to include his or her personal alphanumeric code; (3) The research team reviewed the documents (a) and (b) after these were returned to the educational platform. When both documents were filled out correctly, the research team activated the personal alphanumeric code so that the corresponding student had access to the e12HR application (in this way, students could not start using the e12HR application until they had completed the two documents required for the research). Once the personal alphanumeric code was activated by the research team, the student only had to open the e12HR application to start using it (see Section 2.4. e-12HR Application subsection). To incentivize participation in the present study, taking part in the study was included as one of the class activities for the subjects “Public Health” (Faculty of Pharmacy) and “Epidemiology and Public Health” (Faculty of Dentistry) at the University of Seville; in any case, participation in the study was an optional class activity and was not evaluated for the final marks of the study subjects. 2.3. Initial Form The initial form presented two sections: (1) A section with personal information which allowed the students to provide data such as their date of birth, gender, weight, height, smoking status, faculty, and type of residence; and (2) a section with dietary information which allowed the students to provide information about their self-perception of dietary behavior for certain food groups related to the MD over the previous six months. In this last section, there was information about food groups related to the MD, and consumption recommendations for each food group. The student had to indicate whether or not he or she had met the consumption recommendations for each food group over the previous six months; to do so, the student had to mark one of the two available options in the form: option 1: “Yes; I have complied with the recommendation”; or option 2: “I have not complied with the recommendation” (see Appendix A, Table A1 for the full form with dietary information). As previously mentioned, students filled out and returned the initial form (including their personal alphanumeric code) in a “Word” (Microsoft 365 2020) document format to the educational platform. The research team converted the information from the initial form into “Excel” (Microsoft 365 2020) format for the subsequent statistical analysis. Nutrients 2024,16, 3364 4 of 16 2.4. e12HR Application e12HR is an application that allows for the long-term collection of data on the dietary intake of food groups (related to MD); this application is basically a modified 24-h recall which has been previously validated—using food frequency questionnaires (FFQ) and dietary records as reference methods—for determining the actual consumption of certain food groups related to MD [31,32]. The structure and functions of the version of the e12HR application used in this study have been described in detail by Béjar et al. (in “e12HR App” in Section 2.2.) [ 33 ]. In brief, this version of the e12HR application allowed participants to register the number of servings consumed during the day for each of the nineteen food groups included in the study (see Appendix A, Figure A1 for real images of the e12HR application). After completing the daily form on the application, the collected data was automatically sent to the research team’s website. The research team converted the information from the website into “Excel” format for subsequent statistical analysis. The study protocol in the present study (which combined two assessment processes using the form with dietary information and the e12HR application) is shown in Figure 1. Nutrients 2024, 16, x FOR PEER REVIEW 4 of 17 dietary behavior for certain food groups related to the MD over the previous six months. In this last section, there was information about food groups related to the MD, and consumption recommendations for each food group. The student had to indicate whether or not he or she had met the consumption recommendations for each food group over the previous six months; to do so, the student had to mark one of the two available options in the form: option 1: “Yes; I have complied with the recommendation”; or option 2: “I have not complied with the recommendation” (see Appendix A, Table A1 for the full form with dietary information). As previously mentioned, students filled out and returned the initial form (including their personal alphanumeric code) in a “Word” document format to the educational platform. The research team converted the information from the initial form into “Excel” format for the subsequent statistical analysis. 2.4. e12HR Application e12HR is an application that allows for the long-term collection of data on the dietary intake of food groups (related to MD); this application is basically a modified 24-h recall which has been previously validated—using food frequency questionnaires (FFQ) and dietary records as reference methods—for determining the actual consumption of certain food groups related to MD [31,32]. The structure and functions of the version of the e12HR application used in this study have been described in detail by Béjar et al. (in “e12HR App” in Section 2.2.) [33]. In brief, this version of the e12HR application allowed participants to register the number of servings consumed during the day for each of the nineteen food groups included in the study (see Appendix A, Figure A1 for real images of the e12HR application). After completing the daily form on the application, the collected data was automatically sent to the research team’s website. The research team converted the information from the website into “Excel” format for subsequent statistical analysis. The study protocol in the present study (which combined two assessment processes using the form with dietary information and the e12HR application) is shown in Figure 1. Figure 1. Assessment processes using the form with dietary information and e12HR application. 2.5. Adherence to Mediterranean Diet Assessment In this study, the data from the initial form (specifically, the form with dietary information) and the e12HR application were compared. With the dietary information from both sources, AMD was calculated following the original rules of the Mediterranean diet Serving Score (MDSS) index [34]: (1) Selection of a series of key food groups (compatible with the MD); (2) establishment of dietary intake recommendations for each key food group; (3) a numerical score assigned to each item in the case of compliance with the recommendations (if the indicated recommendations were not followed, a value of zero was Figure 1. Assessment processes using the form with dietary information and e12HR application. 2.5. Adherence to Mediterranean Diet Assessment In this study, the data from the initial form (specifically, the form with dietary information) and the e12HR application were compared. With the dietary information from both sources, AMD was calculated following the original rules of the Mediterranean diet Serving Score (MDSS) index [ 34 ]: (1) Selection of a series of key food groups (compatible with the MD); (2) establishment of dietary intake recommendations for each key food group; (3) a numerical score assigned to each item in the case of compliance with the recommendations (if the indicated recommendations were not followed, a value of zero was assigned for that item). However, it was necessary to make some modifications in order to adapt them to the characteristics of the form with dietary information and the e12HR application (Table 1). With the dietary information from both sources (the form with dietary information and the e12HR application), scores for the MDSS index were calculated manually by the research team (using the rules shown in Table 1and the documents in “Excel” format generated from each source). To complete the process, the value of each food group was added up and a score on the MDSS index was generated, which could vary between zero and twenty-four. In addition, the score on the MDSS index was related with one of three levels of MDSS [35]: low (0–8 points), moderate (9–15 points) or high (16–24 points). In order to calculate the MDSS index, the daily dietary data from the e12HR application were processed as follows: (1) For each food group, the sum of the daily rations was recorded; (2) the previous sum was then divided by the number of days for which the task was completed (to obtain the average number of servings/day for each food group); and (3) for food groups which used the weekly recommendations, as opposed to daily, the Nutrients 2024,16, 3364 5 of 16 result from the previous operation was multiplied by seven (to obtain the average number of servings/week). Table 1. Mediterranean diet Serving Score index for the form with dietary information and e12HR. Food Group Recommendation Score (Form with Dietary Information and e-12HR) Scoring of Food Groups Calculated on a daily basis Fruits ≥3 serving/day 3 Vegetables ≥3 serving/day 3 Cereals 3–6 serving/day 3 Olive oil 3–4 serving/day 3 Milk and dairy products 2–3 serving/day 2 Fermented beverages 1–2 serving/day 1 Scoring of food groups calculated on a weekly basis Nuts 3–7 serving/week 2 Potatoes ≤3 serving/week 1 Legumes ≥2 serving/week 1 Eggs 3–4 serving/week 1 Fish ≥2 serving/week 1 White meat 2–3 serving/week 1 Red and processed meat ≤2 serving/week 1 Sweets ≤2 serving/week 1 Total maximum score 24 Cereals: breakfast cereals, pasta, rice and bread. Olive oil: used on salads or bread or for frying. Milk and dairy products: milk, yogurt and cheese. Fermented beverages: wine and beer. White meat: poultry. Red meat: pork, beef and lamb. Sweets: sugar, candies, pastries, sweetened fruit juices and soft drinks. 2.6. Self-Perception of Dietary Behavior by Students: Overestimation or Normal/Underestimation In this study, two categories have been defined for the self-perception of dietary behavior by students (overestimation or normal/underestimation), considering the following criteria [ 18 ]: (1) normal/underestimation category: MDSS index calculated from the data obtained from the form with dietary information—MDSS index calculated from the data obtained from the e12HR application ≤ 0. For the students in this category, the research team interpreted that they self-perceived equal or lower AMD than that associated with their actual dietary behavior; (2) overestimation category: MDSS index calculated from the data obtained from the form with dietary information—MDSS index calculated from the data obtained from the e12HR application >0. For the students in this category, the research team interpreted that they self-perceived greater AMD than that associated with their actual dietary behavior. For the overestimation category, three subcategories were established: low (difference from 1 to 5); moderate (difference of 6–10), and high (difference of 11–15). No differences greater than 15 were observed in the present study. 2.7. Statistical Analysis Discrete variables are presented as a number followed by percentages. Continuous variables are presented using means and standard deviations (SD) and median and interquartile range (IQR). The data were tested for normality using the nonparametric Kolmogorov–Smirnov test. For paired samples: (1) Student’s t-test or the nonparametric Wilcoxon test were used for the analysis of quantitative variables; and (2) Wilcoxon test was used for the comparison of ordinal qualitative variables. Nutrients 2024,16, 3364 6 of 16 For unpaired samples: Student’s t-test or the nonparametric Mann–Whitney U-test was used for the analysis of quantitative variables, penalizing p-values with Bonferroni adjustment for multiple comparisons. The results were considered significant if p-value < 0.05, except for multiple comparisons using Bonferroni penalization: p-value < 0.017 (0.05/3). Statistical analyses were performed using the SPSS statistical software package version 29.0 (SPSS Inc.; Chicago, IL, USA). 3. Results 3.1. Sample and Adherence to the Study In the three classrooms selected for the study (two classrooms at the Faculty of Pharmacy and one classroom at the Faculty of Dentistry) there were a total of 205 students, of whom 162 signed the informed consent forms. However, two students were excluded (one due to diabetes and another due to anorexia). Of those who fulfilled the inclusion requirement for the study, 21 were considered non-responsive (as they completed the task on the app for fewer than 20 days); therefore, the study response rate was 86.9% (139/160). The data for the non-responsive individuals was not included in the later statistical analysis. No significant statistical differences were observed in the variables studied between responsive and non-responsive participants. 3.2. Personal Information of the Participants Table 2shows the personal information of the participants. Table 2. Characteristics of study participants. Characteristics n (%) Mean (SD) Median (IQR) Participants who completed the study 139 (100) - * - Gender - - Females 111 (79.9) - - Males 28 (20.1) - - Age (Years) 21.3 (4.5) 19.9 (2.7) <20 70 (50.4) - - ≥20 69 (49.6) - - Studies - - Pharmacy 89 (64.0) - - Dentistry 50 (36.0) - - BMI (kg/m2)22.2 (3.7) 21.5 (3.7) <25 118 (84.9) - - ≥25 21 (15.1) - - Smoking Status - - No 114 (82.0) - - Yes 25 (18.0) - - Physical activity status (m/w) - - ≥150 93 (66.9) - - <150 46 (33.1) - - * Not applicable. SD: standard deviation. IQR: interquartile range. BMI: body mass index. m/w: minutes/week. The 139 participants who completed the study (28-day follow-up period) registered their daily consumption for the nineteen food groups included in the study. This represents a collected total of 73,948 data points on daily consumption for the food groups (139 participants, a 28-day follow-up period, and 19 food groups included). Nutrients 2024,16, 3364 7 of 16 3.3. Scores and Levels of the Mediterranean Diet Serving Score Index Table 3shows the scores of the MDSS index and Table 4shows the levels of the MDSS index (in the whole study sample and by gender), calculated from the data obtained from the two sources used in the study: the form with dietary information (filled out by participants at the beginning of the study) versus the e12HR application (used by participants for the 28-day follow-up period) (see Figure 1). Table 3. Scores of the Mediterranean diet Serving Score index (form with dietary information versus e12HR application). Form with Dietary Information e12HR Application Mean (SD) Median (IQR) Mean (SD) Median (IQR) p-Value * All 14.3 (3.4) 14.0 (5.0) 6.8 (2.7) 7.0 (3.0) <0.001 Females 14.3 (3.4) 15.0 (5.0) 6.8 (2.8) 7.0 (3.0) <0.001 Males 14.3 (3.4) 14.0 (5.0) 7.0 (2.1) 7.0 (3.0) <0.001 MDSS: Mediterranean diet Serving Score. SD: standard deviation. IQR: interquartile range. p-value: differences from the data from the form with dietary information versus the e12HR application. * Paired Student t-test. A p-value < 0.05 is considered significant. Table 4. Levels of the Mediterranean diet Serving Score index (form with dietary information versus e12HR application). Form with Dietary Information e12HR Application n (%) n (%) High Moderate Low High Moderate Low p-Value * All 69 (49.6) 64 (46.0) 6 (4.3) 0 (0.0) 33 (23.7) 106 (76.3) <0.001 Females 56 (50.5) 50 (45.0) 5 (4.5) 0 (0.0) 27 (24.3) 84 (75.7) <0.001 Males 13 (46.4) 14 (50.0) 1 (3.6) 0 (0.0) 6 (21.4) 22 (78.6) <0.001 MDSS: Mediterranean diet Serving Score. p-value: differences from the data from the form with dietary information versus e12HR application. * Paired Wilcoxon test. A p-value < 0.05 is considered significant. For the whole study sample and both genders, there were significant statistical differences between the indices calculated using the form with dietary information versus the e12HR application, with higher a MDSS index calculated from the data obtained from the form with dietary information. From the form with dietary information, the MDSS index was ≥ 14.0 (mean and median); from the e12HR application, the MDSS index was ≤ 7.0 (mean and median) (Table 3). For the whole study sample and both genders, there were significant statistical differences between the indices calculated using the form with dietary information versus the e12HR application. A higher percentage of participants with a high/moderate MDSS index was calculated using the from data obtained from the form with dietary information: From the form with dietary information, the percentage of participants with a high/moderate MDSS index was >46.0 and ≥ 45.0, respectively. From the e12HR application, the percentage of participants with a high MDSS index was 0.0, and the percentage of participants with a moderate MDSS index was <25.0 (Table 4). 3.4. Distribution of Self-Perception of Dietary Behavior by Students: Overestimation or Normal/Underestimation Table 5shows the distribution of the participants and the scores of the MDSS index (calculated from the data obtained from the e12HR application) by overestimation (low, moderate, and high subcategories) and normal/underestimation categories. Table 6shows a comparison of the MDSS across the same categories/subcategories. Nutrients 2024,16, 3364 8 of 16 Table 5. Distribution of the participants and scores of the Mediterranean diet Serving Score index by overestimation (low, moderate and high subcategories) and normal/underestimation categories. MDSS Index (from e12HR Application) Category n (%) Mean (SD) Median (IQR) All Normal/underestimation 2 (1.4) 12.0 (1.4) 12.0 (- *) Overestimation 137 (98.6) 6.7 (2.6) 7.0 (3.0) Within overestimation category Low 41 (29.5) 8.1 (2.8) 8.0 (4.0) Moderate 67 (48.2) 6.7 (2.2) 7.0 (3.0) High 29 (20.9) 4.9 (2.2) 5.0 (3.0) Gender Female Normal/underestimation 1 (0.9) 13.0 (-) 13.0 (-) Overestimation 110 (99.1) 6.7 (2.8) 7.0 (3.0) Within overestimation category Low 35 (31.5) 8.2 (2.9) 8.0 (4.0) Moderate 51 (45.9) 6.7 (2.3) 7.0 (3.0) High 24 (21.6) 4.5 (2.1) 4.0 (3.0) Male Normal/underestimation 1 (3.6) 11.0 (-) 11.0 (-) Overestimation 27 (96.4) 6.8 (2.0) 7.0 (3.0) Within overestimation category Low 6 (21.4) 7.7 (2.2) 7.0 (4.0) Moderate 16 (57.1) 6.6 (1.9) 7.0 (3.0) High 5 (17.9) 6.6 (2.3) 7.0 (4.0) * Not applicable. MDSS: Mediterranean diet Serving Score. SD: standard deviation. IQR: interquartile range. Table 6. Mediterranean diet Serving Score index: comparison across overestimation (and low, moderate, and high subcategories) and normal/underestimation categories. MDSS Index (from e12HR Application) Category Mean (SD) p-Value All Normal/underestimation Overestimation 0.008 ** 12.0 (1.4) 6.7 (2.6) Multiple comparisons within overestimation category Low overestimation 8.1 (2.8) Moderate overestimation 6.7 (2.2) 0.004 *** Low overestimation 8.1 (2.8) High overestimation 4.9 (2.2) <0.001 *** Moderate overestimation 6.7 (2.2) High overestimation 4.9 (2.2) <0.001 *** Nutrients 2024,16, 3364 9 of 16 Table 6. Cont. MDSS Index (from e12HR Application) Category Mean (SD) p-Value Females Normal/underestimation 13.0 (−*) Overestimation 6.7 (2.8) 0.018 ** Multiple comparisons within overestimation category Low overestimation 8.2 (2.9) Moderate overestimation 6.7 (2.3) 0.010 *** Low overestimation 8.2 (2.9) High overestimation 4.5 (2.1) <0.001 *** Moderate overestimation 6.7 (2.3) High overestimation 4.5 (2.1) <0.001 *** Males Normal/underestimation 11.0 (−)Overestimation 6.8 (2.0) 0.071 ** Multiple comparisons within overestimation category Low overestimation 7.7 (2.2) Moderate overestimation 6.6 (1.9) 0.260 *** Low overestimation 7.7 (2.2) High overestimation 6.6 (2.3) 0.449 *** Moderate overestimation 6.6 (1.9) High overestimation 6.6 (2.3) 0.486 *** * Not applicable. MDSS: Mediterranean diet Serving Score. SD: standard deviation. ** Unpaired Mann–Whitney U-test. *** Unpaired Student’s t-test. A p-value < 0.05 is considered significant, penalizing p-value with Bonferroni adjustment for multiple comparisons: p-value < 0.017 (0.05/3). For the whole study sample and both genders, most students were in the overestimation category (with percentages >96.0%), mainly in the moderate subcategory (with percentages >45.0%) (Table 5). For the whole study sample and for women, there were significant statistical differences in the MDSS index in the normal/underestimation category (with mean values of 12.0 and 13.0) as compared to the overestimation category (with mean values of 6.7); within the overestimation category, there were significant statistical differences in the MDSS index comparing low (with mean values of 8.1 and 8.2), moderate (with mean values of 6.7) and high (with mean values of 4.5 and 4.9) subcategories. No significant statistical differences were observed for men (Table 6). 4. Discussion 4.1. Principal Findings The main findings of the study were: (1) The actual dietary behavior in the sample was poor: The mean score of the MDSS index was 6.8 for all students (6.8 for women and 7.0 for men) (Table 3), with 76.3% of all students at the low level of the MDSS index (75.7% for women and 78.6% for men) (Table 4); (2) The self-perception of dietary behavior in the sample was significantly higher: the mean score of the self-perceived MDSS index was 14.3 for all students (14.3 for women and men) (Table 3), with 95.7% of all students at the moderate-high level of self-perceived MDSS index (95.5% for women and 96.4% for men) (Table 4); Nutrients 2024,16, 3364 16 of 16 32. Béjar, L.M.; García-Perea, M.D.; Reyes, Ó.A.; Vázquez-Limón, E. Relative Validity of a Method Based on a Smartphone App (Electronic 12-Hour Dietary Recall) to Estimate Habitual Dietary Intake in Adults. JMIR Mhealth Uhealth 2019,7, e11531. [CrossRef] 33. Bejar, L.M. Weekend–Weekday Differences in Adherence to the Mediterranean Diet among Spanish University Students. Nutrients 2022,14, 2811. [CrossRef] 34. Monteagudo, C.; Mariscal-Arcas, M.; Rivas, A.; Lorenzo-Tovar, M.L.; Tur, J.A.; Olea-Serrano, F. Proposal of a Mediterranean Diet Serving Score. PLoS ONE 2015,10, e0128594. [CrossRef] [PubMed] 35. Vasiloglou, M.F.; Lu, Y.; Stathopoulou, T.; Papathanail, I.; Fäh, D.; Ghosh, A.; Baumann, M.; Mougiakakou, S. Assessing Mediterranean Diet Adherence with the Smartphone: The Medipiatto Project. Nutrients 2020,12, 3763. [CrossRef] [PubMed] 36. Béjar, L.M.; García-Perea, M.D.; Mesa-Rodríguez, P. Evaluation of an Application for Mobile Telephones (e-12HR) to Increase Adherence to the Mediterranean Diet in University Students: A Controlled, Randomized and Multicentric Study. Nutrients 2022, 14, 4196. [CrossRef] [PubMed] 37. Béjar, L.M.; Mesa-Rodríguez, P.; Quintero-Flórez, A.; Ramírez-Alvarado, M.D.M.; García-Perea, M.D. Effectiveness of a Smartphone App (e-12HR) in Improving Adherence to the Mediterranean Diet in Spanish University Students by Age, Gender, Field of Study, and Body Mass Index: A Randomized Controlled Trial. Nutrients 2023,15, 1688. [CrossRef] [PubMed] 38. Béjar, L.M.; Mesa-Rodríguez, P.; García-Perea, M.D. Short-Term Effect of a Health Promotion Intervention Based on the Electronic 12-Hour Dietary Recall (e-12HR) Smartphone App on Adherence to the Mediterranean Diet Among Spanish Primary Care Professionals: Randomized Controlled Clinical Trial. JMIR Mhealth Uhealth 2024,12, e49302. [CrossRef] 39. Rodríguez, I.T.; Ballart, J.F.; Pastor, G.C.; Jordà, E.B.; Val, V.A. Validación de un cuestionario de frecuencia de consumo alimentario corto: Reproducibilidad y validez [Validation of a short questionnaire on frequency of dietary intake: Reproducibility and validity]. Nutr. Hosp. 2008,23, 242–252. 40. Willett, W. Nutritional Epidemiology, 3rd ed.; Oxford University Press: New York, NY, USA, 2013; p. 552. 41. Rosso, N.; Giabbanelli, P. Accurately inferring compliance to five major food guidelines through simplified surveys: Applying data mining to the UK National Diet and Nutrition Survey. JMIR Public Health Surveill. 2018,4, e56. [CrossRef] 42. Tucker, K.L.; Smith, C.E.; Lai, C.; Ordovas, J.M. Quantifying diet for nutrigenomic studies. Annu. Rev. Nutr. 2013,33, 349–371. [CrossRef] 43. Gibson, R. Principles of Nutritional Assessment, 2nd ed.; Oxford University Press: New York, NY, USA, 2005. 44. Solera, A.; Gamero, A. Healthy habits in university students of health sciences and other branches of knowledge: A comparative study. Rev. Esp. Nutr. Hum. Diet 2019,23, 271–282. [CrossRef] 45. Cancela-Carral, J.M.; Ayán-Pérez, C. Prevalencia y relación entre el nivel de actividad física y las actitudes alimenticias anómalas en estudiantes universitarias españolas de ciencias de la salud y la educación [Prevalence and relationship between physical activity and abnormal eating attitudes in Spanish women university students in Health and Education Sciences]. Rev. Esp. Salud. Publica 2011,85, 499–505. [CrossRef] 46. Yahia, N.; Achkar, A.; Abdallah, A.; Rizk, S. Eating habits and obesity among Lebanese university students. Nutr. J. 2008,7, 32. [CrossRef] [PubMed] 47. Yolcuo˘glu, I.Z.; Kızıltan, G. Effect of Nutrition Education on Diet Quality, Sustainable Nutrition and Eating Behaviors among University Students. J. Am. Nutr. Assoc. 2022,41, 713–719. [CrossRef] [PubMed] 48. Forster, H.; Fallaize, R.; Gallagher, C.; O’Donovan, C.B.; Woolhead, C.; Walsh, M.C.; Macready, A.L.; Lovegrove, J.A.; Mathers, J.C.; Gibney, M.J.; et al. Online dietary intake estimation: The Food4Me food frequency questionnaire. J. Med. Internet Res. 2014, 16, e150. [CrossRef] [PubMed] 49. Rutishauser, I.H. Dietary intake measurements. Public Health Nutr. 2005,8, 1100–1107. [CrossRef] 50. Martín-Moreno, J.M.; Gorgojo, L. Valoración de la ingesta dietética a nivel poblacional mediante cuestionarios individuales: Sombras y luces metodológicas [Assessment of dietary intake at the population level through individual questionnaires: Methodological shadows and lights]. Rev. Esp. Salud Publica 2007,81, 507–518. [CrossRef] 51. Dhurandhar, N.V.; Schoeller, D.; Brown, A.W.; Heymsfield, S.B.; Thomas, D.; Sørensen, T.I.; Speakman, J.R.; Jeansonne, M.; Allison, D.B. Energy balance measurement: When something is not better than nothing. Int. J. Obes. 2015,39, 1175–1176. [CrossRef] Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.