Intake of foods high in saturated fats, vegetarian dietary pattern, and sociodemographic characteristics associated with body weight in Peruvian university students

Introduction

The prevalence of obesity continues to rise among university students and the general population, and although there are several examples of national strategies and policies to address this problem, their effectiveness may vary (1, 2). Since 1980, the prevalence of obesity has doubled, equivalent to almost one third of the world’s population (3). In 2016, the World Health Organization (WHO) published a report stating that 39% of adults over the age of 18 were overweight, while 13% were obese (4). Annual deaths due to obesity amount to approximately 2.8 million (5). In Peru, obesity represents a serious public health problem. According to a report from the Instituto Nacional de Salud, 22.3% of the population over 15 years of age suffers from obesity (6). In particular, the university population is not exempt from this problem; in fact, one study reported that 34.4% of Peruvian university students had a BMI ≥ 25 kg/m² (7). These data were confirmed in another similar study, which reported a higher prevalence of obesity in men than in women (8).

The transition between high school and university is a major change in the lives of university students, which in turn implies a risk of weight gain, especially during the first year of university studies (9). Body weight gain at this critical stage may be due to various factors such as the formation of unhealthy lifestyle habits (10), including low levels of physical activity (11), unhealthy eating habits (12), inadequate sleep habits and patterns (13), as well as alcohol consumption (14). Factors influencing unhealthy lifestyles among university students are multiple, including a sense of independence over their food choices and multiple unhealthy food options, such as those high in saturated fats (15).

Consumption of foods high in saturated fats is undoubtedly one of the main factors that influence the body composition of university students (10). Several studies have reported associations between unhealthy diet practices and obesity in university students. A survey of 300 university students found an association between a high prevalence of fast-food consumption and obesity; in addition, the study showed that the consumption of high-calorie foods is associated with abdominal obesity (16). Other studies report that approximately 30% of high school adolescents and more than 50% of university students consume fast-foods (17, 18), which are rich in saturated fats, trans fats, and cholesterol. In the current study, we did not evaluate fast-food itself; however, most of the foods evaluated, such as hamburgers, french fries, pizza, cakes, and others, are commonly found in fast food restaurants (19).

Prevention of obesity can be achieved by promoting a healthy lifestyle that includes healthy dietary patterns such as vegetarian diets with an emphasis on minimally processed and natural foods such as fruits, vegetables, nuts, whole grains, and seeds and a lower consumption of ultra-processed foods rich in saturated and trans fats (20). Furthermore, other healthy foods, such as fish and fermented or low-fat dairy products, may be beneficial in the prevention of obesity (21). In fact, a study conducted on university students found that those who followed a plant-based diet had lower waist circumference and lower systolic blood pressure (22).

However, dietary patterns that emphasize the consumption of animal products are characterized by high levels of saturated and trans fats (23). Regular meat consumption is associated with alterations in anthropometric parameters and lipid profiles, reflected in increases in body mass index (BMI), waist circumference, and body fat percentage, as well as triglycerides, low-density lipoprotein, and glucose levels (24, 25). These changes contribute to a greater predisposition to cardiometabolic risks and diseases such as obesity, hypertension, diabetes mellitus, and cardiovascular pathologies.

Excess body weight (overweight/obesity) is one of the most important risk factors for noncommunicable diseases such as type 2 diabetes mellitus, cardiovascular disease (CVD), and different types of cancer (26, 27). Moreover, dietary patterns dominated by an intake of saturated fat, trans fats, and cholesterol increase blood cholesterol levels, which, in turn, negatively impact cardiovascular health (26). Considering this reality, the Peruvian government approved the Advertising Warning Manual within the framework of Law No. 30021, the Law for the Promotion of Healthy Eating, whose purpose is to inform the population about the nutritional content of processed and ultra-processed foods to reduce the risk factors associated with obesity and CVD (28). Against this scenario, the national food production industry is required to put a front nutritional warning label on processed foods that are high in sugar, sodium, and saturated fats and eliminate the trans fatty acid content in the products (29).

International organizations such as the American Heart Association recommend that saturated fat intake for apparently healthy adults be limited to less than 7% of total daily calories, trans fat to less than 1% of total daily calories, and cholesterol to less than 300 mg per day (30). In Peru, since March 2021, the Peruvian government requires that no processed and ultra-processed food products such as creams, butter, beef fat (tallow), chicken fat, pork fat (lard), stick margarine and vegetable shortening contain trans fats (28). Substantial changes in student dietary patterns are an important factor in the obesity epidemic and justify the need to evaluate these dietary factors to formulate nutritional intervention programs in this specific population. This study aims to determine the sociodemographic characteristics, dietary pattern, and fat intake associated with excess body weight (overweight/obesity) among Peruvian university students.

Materials and methods

Design and participants

The study was conducted based on an online cross-sectional design. Data from students at a private university in Peru were collected during the months of February and April 2022 through non-probabilistic convenience sampling (31–33). The researchers chose to use this sampling because it was the most practical option for obtaining data from respondents (31, 32). The sample size was calculated using Free Statistic Calculators version 4.0 (34). For the multiple regression analysis, an effect size of 0.02, a statistical power of 0.80, seven explanatory variables and a probability level of 0.05 were considered. According to this calculation, a minimum sample of 721 participants was required. However, a total of 5,608 students voluntarily participated in this study, exceeding the calculated sample size (Figure 1). All participants were recruited through an invitation sent via the university’s virtual platform, in which the purposes of the research and their rights as potential participants were briefly described. The participants then gave their informed consent by clicking on the “I wish to participate” option after reading the approved informed consent form on the preliminary page of the questionnaire. Participation was voluntary and did not offer them any incentive to respond to the survey. The questionnaire was online through the university’s virtual survey system. Students under 18 years of age and those who did not correctly answer the questions on the questionnaire were excluded. Before conducting the investigation, the procedures were reviewed and approval was obtained from the Research Ethics Committee of the Universidad Peruana Unión and registered under the number 2022-CEUPeU-0009. Finally, the study was conducted in accordance with the Declaration of Helsinki.

Figure 1

Figure 1. Study design.

Variables

Intake of foods high in saturated fats

A food frequency questionnaire created and validated in a previous study was used to assess saturated fat intake (35). The instrument was previously used in the Peruvian population (36) and validated in university students (37). The questionnaire consists of 16 items and is measured with scales that determine the following frequencies: 1 time per month or less = 0 point, 2 to 3 times a month = 1 point, 1 to 2 times a week = 2 points, 3 to 4 times a week = 3 points and 5 or more times a week = 4 points. The sum of the scores corresponding to 0–7 points equals a very low fat intake, 8–14 points equals a medium fat intake, 15–22 points equals a high fat intake, and 23 or more points equal a very high fat intake (Appendix A). The robustness of the questionnaire was demonstrated by coefficients greater than 0.90, with an ordinal alpha of 0.94, an omega of 0.94, and an H of 0.95 (37). These results underscore the high reliability and relevance of the instrument to assess saturated fat intake in the target population.

Vegetarian dietary pattern

The dietary pattern of the students was self-reported through the following question: “What type of diet do you follow?” and classified as non-vegetarian (those who reported consuming red meat and derivatives, poultry, fish, and vegetables), semi-vegetarian (those who consumed red meat, poultry and fish less than once per week and more than once per month) (38, 39), and vegetarian (those who reported consuming milk, eggs, derivatives, and vegetables) (20, 40). In addition, we assessed adherence to the vegetarian dietary pattern using the following single item: How long have you been a vegetarian? The response options were (a) < 3 years, (b) 3–5 years, and (c) > 5 years. To determine these categories, we used the existing literature, considering that a significant effect on body weight is observed in people who have followed a vegetarian diet for at least 5 years (41–44).

Sociodemographic characteristics

To collect sociodemographic data, a registration form was used as part of the survey. Specific information was collected on sex, age, marital status (married and single), place of origin (coast, jungle, and highlands), place of residence (urban and rural), religious affiliation (Adventist, Baptist, Catholic, and Evangelical), area of study (health sciences, engineering and architecture, human sciences, and business), and parents’ level of education (basic, technical, bachelor’s degree, and postgraduate).

BMI

Participants reported their weight and height. BMI was calculated according to the Quetlet index, according to the criteria established by the WHO (45). Likewise, it was classified as follows: (a) underweight, <18.5; (b) normal, 18.5–24.9 kg/m2; (c) overweight, between 25.0–29.9 kg/m2; (d) obesity ≥30 (45).

Statistical analysis

Statistical analyzes were performed using the IBM SPSS statistical program, version 24 (SPSS Inc., Chicago, IL, USA). The results were reported in tables and text by calculating absolute frequencies and percentages. In addition, an analysis of the association between sociodemographic characteristics, dietary pattern, and fat intake with excess body weight (overweight/obesity) was carried out. The Chi-square test was used. A binary logistic regression model was used for the analysis of the association between factors associated with excess body weight (dependent variable). Independent variables such as age, origin, place of residence, faculty, dietary pattern, intake of foods high in saturated fats and adherence to the vegetarian dietary pattern were included. These variables were included in the model because they had a probability value (p-value) less than 0.05 when the bivariate analysis was performed. All analyzes were performed considering a significance level of 5%.

Results

A total of 5,608 university students decided to participate in the study. 2,990 (53.32%) were men and 2,618 (46.68%) were women. The mean age of the participants was 21.5 ± 3.19 in women and 22 ± 3.60 in men. The description of the sociodemographic characteristics of the participants is shown in Table 1. It was observed that 89.6% of the participants were students between 18 and 25 years of age, of which 91.8% were female (p < 0.001). In addition, 94.7% were single and more than half (57.3%) were from the highlands of the country. Similarly, 70.2% lived in urban areas and more than half of the parents of university students had a basic level of education (58.8%). The students were mainly (53.6%) members of the Seventh-day Adventist Church (Seventh-day Adventist Church), with men being more likely to profess that religion than women (54.7% vs. 52.6%, p = 0.013). Finally, students of health science are more likely to be women (44.4%), while 46.6% of those in the faculty of engineering and architecture were male (p < 0.001).

Table 1

Table 1. Sociodemographic characteristics according to the sex of university students.

Table 2 shows the dietary pattern, the intake of saturated fats and the BMI according to the sex of the participants. The intake of saturated fats was higher in men than in women (43.3% vs. 30.9%, p < 0.001). On the other hand, vegetarian diets were represented by 32.2% of men compared to women (24.7%), p < 0.001. The percentage of excess body weight was slightly higher in men (35.8%) than in women (34.7%), however, there were no statistically significant differences (p = 0.410).

Table 2

Table 2. Dietary pattern, saturated fat intake, and BMI according to the sex of the participants.

Table 3 shows that students who were ≥ 26 were more likely to report excess body weight (p < 0.001). Similarly, those who reported high saturated fat intake, who lived in the coastal region of the country and urban areas, those enrolled in engineering faculty, and those who had a non-vegetarian dietary pattern were more likely to have excess body weight (p < 0.05). On the other hand, students who adhered to the vegetarian dietary pattern for more than 5 years reported adequate weight (p < 0.001).

Table 3

Table 3. Analysis of sociodemographic characteristics, dietary pattern, and intake of foods high in saturated fats according to the body weight status of the participants.

The following factors were included in the multivariate analysis: intake of foods high in saturated fats (0 = low intake; 1 = high intake), dietary pattern (0 = vegetarian; 1 = no vegetarian), adherence to the vegetarian dietary pattern (0 = < 5 years; 1 = > 5 years), age (years) (0 = < 26; 1 = ≥ 26), place of origin (0 = other regions; 1 = coast), place of residence (0 = rural; 1 = urban), and faculty (0 = other faculties; 1 = engineering). It was found that high intake of foods high in saturated fats (β = 0.13; OR_B = 1.14; p = 0.02), non-vegetarian dietary pattern (β = 1.01; OR_B = 2.76; p < 0.001), being ≥26 years old (β = 1.18; OR_B = 3.28; p < 0.001), living in urban (β = 0.16; OR_B = 1.68; p = 0.015), and coastal areas of the country (β = 0.52; OR_B = 1.17; p < 0.001), and enrolled in the faculty of engineering (β = 0.17; OR_B = 1.19; p = 0.006), were significantly associated with excess body weight. However, adherence to the vegetarian diet pattern for more than 5 years (β = −0.17; OR_B = 0.842; p = 0.005) was associated with a lower likelihood of having excess body weight (Table 4).

Table 4

Table 4. Multivariable association analysis of factors associated with excess body weight (overweight/obesity) in university students.

Discussion

Prevalence of obesity continues to increase among university students and the population in general (7, 8, 46). The consumption of foods high in saturated fats constitutes one of the main risk factors influencing obesity in university students (10, 19, 36). Practicing a healthy lifestyle that includes a balanced diet based on the consumption of minimally processed plant foods can prevent negative changes in body composition (22). This study aimed to evaluate the association between saturated fat intake, vegetarian status, sociodemographic characteristics, and excess body weight among Peruvian university students. The relevant findings of this study were: bivariate analysis of factors associated with excess body weight showed a high intake of saturated fat, a non-vegetarian dietary pattern, ≥ 26 years, living in the coastal region and urban areas of the country, and enrolled in the engineering faculty to be statistically significantly associated with excess body weight. After performing a logistic regression analysis, these variables were significantly associated with excess body weight in university students. In contrast, we have found that adhering to a vegetarian dietary pattern for more than 12 months is associated with less likelihood of excess body weight (overweight/obesity) compared to adhering for less than 5 years.

Influence of saturated fats intake

Substantial consumption of foods high in saturated fats among university students represents an elevated risk of long-term weight gain and the development of other health conditions such as metabolic syndrome, insulin resistance, and type 2 diabetes (47). In the current study, high consumption of foods high in saturated fats is associated with excess body weight. These results are in line with the findings of a study in university students in which the consumption of high-fat foods was associated with a poorer health status according to BMI scores (48). In addition, it is important to mention that the type of fat influences obesity. In fact, a study reported that participants who used butter or butter-oil-fat spreads were less likely to have a body weight problem than those who did not apply any on bread, while sausage consumption in women increased the risk (49). It is worth mentioning that the consumption of saturated fats and their relationship with body weight gain remains a controversial issue. For example, there is evidence that fat intake between 18 and 40% of energy intake has little or no effect on adiposity (50), while other studies claim that fat intake energy increases the risk of obesity (51). However, fat intake alone is not the only factor affecting body weight; it is a grouping of different factors such as a low level of physical activity, poor diet, smoking, and heredity, all of which contribute to weight gain (52).

On the other hand, the results of the study indicated that fat intake was more prevalent in men; moreover, they had a slight excess of body weight compared to women. Our findings are consistent with the results of a similar study conducted in US university students that concluded that saturated fat and cholesterol intake was lower in female students (23.5 g/day) than in male students (28.9 g/day) (10). Similarly, findings from an Iranian study of 184 university students showed that female students had a significantly lower intake of saturated fat and a higher intake of monounsaturated fat compared to male students (53). In addition, this same study reported that women perceived themselves as healthy based on body weight (53). These findings were not surprising, considering that women are generally more likely to opt for a healthy diet because they are more concerned about food and body weight, especially during their university years (54). Another study conducted in a group of university students reported that, although female students were stressed, they reported healthy eating habits compared to males, who had a higher level of excess body weight and little interest in dietary advice and health improvement activities (55). Additionally, the study (55) reported that women were more willing to initiate changes in their eating habits than their male counterparts.

Vegetarian dietary pattern

Vegetarian (vegan, lacto-ovo-vegetarian, and pesco-vegetarian) and semi-vegetarian (those consuming red meat, poultry, or fish no more than once a week) diets were more frequent among students without excess body weight. Furthermore, according to binary logistic regression analysis, we found that the non-vegetarian dietary pattern was associated with excess body weight. These findings are supported by the results of previous studies conducted in vegetarians and non-vegetarians in Peru (24, 56), in which vegetarians were found to have a lower BMI compared to non-vegetarians. In addition, Olfert et al. conducted a study of 1,078 vegetarian and non-vegetarian university students and found that those who reported opting for a plant-based diet had a lower BMI compared to meat eaters (22). In addition, the results of two studies carried out in Taiwanese vegetarians (57) and Brazilians (58), found that the BMI of non-vegetarians was >27.0 kg/m2 and > 24.9 kg/m2, respectively, relative to their vegetarian counterparts. These results could be explained by the fact that plant-based diets contain a lower caloric density, due to the presence of a higher content of dietary fiber and bioactive elements (59). The health benefits of vegetarian diets in BMI are well documented in the scientific literature. Current studies have suggested that vegetarian diets, particularly vegan diets, are essentially antiobesogenic compared to diets that include meat and derived products (60). There are several studies that suggest that vegetarianism is significantly associated with lower BMI, total cholesterol concentration, LDL cholesterol, glucose levels, systolic blood pressure, diastolic blood pressure (24, 56, 61, 62), and a lower risk of all-cause mortality (63).

Diets based on animal food consumption are characterized by high caloric density, due to excess saturated and trans fats and added sugars (23). Regular meat intake can have a negative impact on the anthropometric and lipid profile, leading to elevated BMI, waist circumference and fat percentage, higher triglycerides, low-density lipoproteins, and glucose concentrations, which, in turn, increase cardiometabolic risk factors, obesity, hypertension, diabetes mellitus, and cardiovascular disease (24, 25). Therefore, it is important to encourage the adoption of a plant-based diet in university students to reduce risk factors for obesity and other diet-associated diseases based on the consumption of meat and meat products.

The present study has shed light on the significant influence that the duration of adherence to a dietary pattern has on body weight in university students. A striking finding of the study is the association between the prolonged adoption of a vegetarian diet and the reduced prevalence of overweight or obesity. The data suggest that those students who have maintained a vegetarian diet for more than 5 years are less likely to have weight problems than their non-vegetarian peers. These results support the findings of previous studies that vegetarians with less than 5 years of dietary follow-up do not have significant differences in BMI compared to individuals consuming omnivorous diets (41, 64). This underscores that the benefits of maintaining a healthy weight are only realized when the vegetarian diet is followed consistently and regularly over time (42–44, 64). In this sense, the temporary or recent adoption of such a diet does not appear to confer the same protection against overweight or obesity.

Vegetarian diets (pesco-vegetarian, lacto-vegetarian, ovo-vegetarian, lacto-ovo-vegetarian, and vegan) showed a significantly higher proportion among men. However, previous studies conducted on vegetarians and non-vegetarians in the general Peruvian population reported that there was a higher percentage of female vegetarians compared to male vegetarians (24, 56). Similarly, studies conducted in another context showed that most women tend to opt for plant-based diets (22). However, in order to contextualize the fact that there is a higher proportion of male vegetarians in the current study, it is important to consider several sociocultural factors that could influence the choice of a vegetarian diet. For example, an aspect to consider is the availability and accessibility of vegetarian options in the environment, as the university where the study took place is part of the SDA Church, a religious denomination whose health philosophy focuses on the consumption of plant-based foods (65). As vegetarian options become more varied and accessible in certain settings, more men may be inclined to try this type of diet.

It is important to note that the fact that there was a higher proportion of vegetarian men than women does not guarantee that fewer men ate foods high in saturated fats. Therefore, it is important to recognize that a vegetarian diet does not automatically equate to a healthy diet. The nutritional quality of a vegetarian diet can vary widely depending on specific dietary choices. Some foods rich in saturated fat, such as chips, cakes, butter, mayonnaise, cheese, whole milk, and cookies, were included in our analysis. It is possible that the men in our sample had a higher preference for these foods compared to the women. This phenomenon highlights the diversity within vegetarian diets and how they can include less healthy choices that are low in certain nutrients (vitamin B12, iron, zinc, and calcium) and/or rich in highly processed and refined foods that contribute to saturated fat consumption (66). This observation is consistent with previous studies that have documented variability in the quality of vegetarian diets (67). Future analyses could further explore how differences in food choices within vegetarian diets affect the overall nutritional profile and long-term health. Our findings underscore the importance of considering not only diet categorization, but also diet quality and nutrient composition when assessing health outcomes.

Sociodemographic characteristics

Another important finding to mention is that students ≥26 years were more likely to have excess body weight. Furthermore, the findings of a cross-sectional study of 2,285 Peruvian university students found that those aged ≥27 years were more likely to be overweight/obese (46). Similarly, a study conducted on 4,201 university students found that the mean BMI of the participants increased with age (68). On the other hand, studies conducted in the general population showed that increasing age was a risk factor for obesity (69). One study revealed that older participants had almost twice the risk of being obese (70). As age increases, due to hormonal and metabolic changes (71), there is an increased risk of obesity. Therefore, permanent and conscious control of food intake and regular physical activity practice is important to prevent weight gain.

Additionally, living in the coastal region and urban areas is associated with excess body weight. The coast of Peru has the highest concentration of urban areas. These cities are home to the people most affected by the presence of overweight and obesity and 1 in 4 people are obese (72). One of the possible justifications for this problem is due to the fact that Peruvian society is experiencing transitional phenomena, characterized by high levels of urbanization, modernization, education, income, access to health facilities, basic sanitation, aspects of technology, among others, which are occurring at an accelerated pace and, as a result, some lifestyle behaviors, such as eating habits, physical activity, and rest, were affected (73). University students living in urban areas could be exposed to significant changes in dietary patterns, which, in turn, could negatively impact body composition (74). The rhythm of life in the city replaces traditional dietary activities, characterized by fishing and agriculture, giving rise to a consumption pattern differentiated by a higher intake of ultra-processed foods (75). However, while previous findings suggest that living in rural areas increases the risk of being overweight, our results contradict this trend by showing that students living in urban areas have a higher prevalence of overweight and obesity (69). Therefore, future research should focus on the development of lifestyle-based interventions for university students, considering the geographic areas of residence to prevent excess body weight.

Finally, we found that students enrolled in the Faculty of Engineering were more likely to be overweight than students in other faculties. This finding is consistent with the existing literature suggesting similar patterns in comparable populations (46, 76). These results may be due to the academic load and lifestyle habits associated with time-intensive fields of study, such as engineering, which can lead to limited physical activity and unhealthy eating, increasing the risk of being overweight (77). The sedentary nature of prolonged study and the tendency to skip meals or resort to fast food options due to time constraints and deadlines have also been cited as contributing to obesity in this student population (78). This study adds to the growing body of literature identifying engineering students as a risk group for overweight and obesity. It reflects the importance of a multidisciplinary approach that involves both educators and health professionals in developing strategies to promote healthy habits among this student population.

Strengths and limitations

This study considered a large sample size (more than 6,000 university students). However, the results of our study should be interpreted considering certain limitations. First, it is a non-randomized sampling of the population studied. Second, although the question assessing the dietary pattern provided a definition of the subgroups of vegetarian diets, however, this variable was self-reported and the information provided may not be accurate. Therefore, future studies should consider the dietary intake to assess the dietary pattern of the participants and not rely on a self-reported pattern. Third, although we have classified the diet into three categories (vegetarian, semi-vegetarian and non-vegetarian), however, we do not know the exact proportion of vegetarian subgroups (pesco-vegetarians, lacto-ovo-vegetarians, and vegans). Finally, although the university where the study was conducted has campuses in three regions of Peru, the findings cannot be generalized to the entire Peruvian population of university students because it is a sampling technique based on a single university.

Conclusion

This cross-sectional study associated the intake of foods high in saturated fats, vegetarian dietary pattern, and sociodemographic characteristics with body weight in university students. It was found that students who reported a high intake of foods high in saturated fat and those with a non-vegetarian dietary pattern were more likely to be overweight. On the contrary, students who reported adherence to the vegetarian diet pattern for more than 12 months were less likely to be overweight or obese. Furthermore, it was found that being ≥26 years old, living in urban areas and coastal areas of the country, and enrolled in the engineering faculty were significantly associated with excess body weight. Furthermore, men were found to have the highest representation among those following vegetarian diets. Fat intake was more prevalent in men; in addition, they were slightly overweight compared to women. Therefore, it is necessary to promote and implement healthy lifestyle programs, considering dietary factors such as saturated fat intake and sociodemographic aspects such as age, place of residence for the control and prevention of obesity in university students.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Research Ethics Committee of the Faculty of Health Sciences of Universidad Peruana Unión: approval number: 2022-CEUPeU-0009. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

JS: Conceptualization, Project administration, Visualization, Writing – original draft, Writing – review & editing. PR: Data curation, Validation, Writing – review & editing. CR-V: Data curation, Visualization, Writing – review & editing. AS-B: Investigation, Supervision, Visualization, Writing – review & editing. SO-G: Investigation, Supervision, Visualization, Writing – review & editing. IL: Formal analysis, Methodology, Writing – review & editing. YC-M: Conceptualization, Project administration, Visualization, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Acknowledgments

The authors thank the subjects for agreeing to participate in the study. We also thank Dr. Varisier Noel for his support in the research development process.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnut.2024.1361091/full#supplementary-material

References

1. Hruby, A, and Hu, FB. The epidemiology of obesity: a big picture. PharmacoEconomics. (2015) 33:673–89. doi: 10.1007/s40273-014-0243-x

PubMed Abstract | Crossref Full Text | Google Scholar

2. Tseng, E, Zhang, A, Shogbesan, O, Gudzune, KA, Wilson, RF, Kharrazi, H, et al. Effectiveness of policies and programs to combat adult obesity: a systematic review. J Gen Intern Med. (2018) 33:1990–2001. doi: 10.1007/s11606-018-4619-z

PubMed Abstract | Crossref Full Text | Google Scholar

3. Chooi, YC, Ding, C, and Magkos, F. The epidemiology of obesity. Metabolism. (2019) 1:6–10. doi: 10.1016/j.metabol.2018.09.005

Crossref Full Text | Google Scholar

4. World Health Organization. Obesity and overweight. (2021) Available at: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight

Google Scholar

5. Hussain, A, Mahawar, K, Xia, Z, Yang, W, and El-Hasani, S. Obesity and mortality of COVID-19. Meta-analysis. Obes Res Clin Pract. (2020) 14:295–300. doi: 10.1016/j.orcp.2020.07.002

Crossref Full Text | Google Scholar

6. INS. Gobierno de Perú. Lima; (2019), Nuestra razón de ser y hacer’ Boletín epidemiológico del Perú. Instituto Nacional de Salud.

Google Scholar

7. Rabanales-Sotos, J, Evangelina Villanueva-Benites, M, Jacinto-Magallanes-Castilla, J, Leitón-Espinoza, ZE, López-González, Á, and López-Torres-Hidalgo, J. Prevalence of overweight and obesity among health sciences students in the Amazonia region of Peru. Healthcare. (2020) 8:538. doi: 10.3390/healthcare8040538

PubMed Abstract | Crossref Full Text | Google Scholar

8. Iparraguirre, RMP, Porras, MM, De La Cruz, AH, and Días Bonilla, ML. Prevalence of overweight and obesity in Young Peruvian students at National University of Center of Peru-Region Junin-Huancayo. Obes Med. (2020) 19:100242. doi: 10.1016/j.obmed.2020.100242

Crossref Full Text | Google Scholar

9. Price, AA, Whitt-Glover, MC, Kraus, CL, and McKenzie, MJ. Body composition, fitness status, and health behaviors upon entering college: an examination of female college students from diverse populations. Clin Med Insights Womens Health. (2016) 9s1:CMWH.S34697. doi: 10.4137/CMWH.S34697

Crossref Full Text | Google Scholar

10. Yahia, N, Brown, CA, Rapley, M, and Chung, M. Level of nutrition knowledge and its association with fat consumption among college students. BMC Public Health. (2016) 16:1–10. doi: 10.1186/s12889-016-3728-z

Crossref Full Text | Google Scholar

11. Nelson, MC, Neumark-Stzainer, D, Hannan, PJ, Sirard, JR, and Story, M. Longitudinal and secular trends in physical activity and sedentary behavior during adolescence. Pediatrics. (2006) 118:e1627–34. doi: 10.1542/peds.2006-0926

PubMed Abstract | Crossref Full Text | Google Scholar

12. Pliner, P, and Saunders, T. Vulnerability to freshman weight gain as a function of dietary restraint and residence. Physiol Behav. (2008) 93:76–82. doi: 10.1016/j.physbeh.2007.07.017

PubMed Abstract | Crossref Full Text | Google Scholar

13. Schlarb, A, Friedrich, A, and Claßen, M. Sleep problems in university students & ndash; an intervention. Neuropsychiatr Dis Treat. (2017) 13:1989–2001. doi: 10.2147/NDT.S142067

PubMed Abstract | Crossref Full Text | Google Scholar

14. Krieger, H, Young, CM, Anthenien, AM, and Neighbors, C. The epidemiology of binge drinking among college-age individuals in the United States. Alcohol Res. (2018) 39:23–30.

Google Scholar

15. Nelson, MC, Kocos, R, Lytle, LA, and Perry, CL. Understanding the perceived determinants of weight-related behaviors in late adolescence: a qualitative analysis among college youth. J Nutr Educ Behav. (2009) 41:287–92. doi: 10.1016/j.jneb.2008.05.005

PubMed Abstract | Crossref Full Text | Google Scholar

16. Mohammadbeigi, A, Asgarian, A, Moshir, E, Heidari, H, Afrashteh, S, Khazaei, S, et al. Fast food consumption and overweight/obesity prevalence in students and its association with general and abdominal obesity. J Prev Med Hyg. (2018) 59:E236–40. doi: 10.15167/2421-4248/jpmh2018.59.3.830

PubMed Abstract | Crossref Full Text | Google Scholar

17. Nixon, H, and Doud, L. Do fast food restaurants cluster around high schools? A geospatial analysis of proximity of fast food restaurants to high schools and the connection to childhood obesity rates. J Agric Food Syst Community Dev. (2011) 2:181–94. doi: 10.5304/jafscd.2011.021.007

Crossref Full Text | Google Scholar

18. Al-Otaibi, HH, and Basuny, AM. Fast food consumption associated with obesity/overweight risk among university female student in Saudi Arabia. Pak J Nutr. (2015) 14:511–6. doi: 10.3923/pjn.2015.511.516

Crossref Full Text | Google Scholar

19. Jiang, Y, Wang, J, Wu, S, Li, N, Wang, Y, Liu, J, et al. Association between take-out food consumption and obesity among Chinese university students: a cross-sectional study. Int J Environ Res Public Health. (2019) 16:1071. doi: 10.3390/ijerph16061071

PubMed Abstract | Crossref Full Text | Google Scholar

20. Saintila, J, Calizaya-Milla, YE, and Javier-Aliaga, DJ. Knowledge of vegetarian and nonvegetarian Peruvian dietitians about vegetarianism at different stages of life. Nutr Metab Insights. (2021) 14:117863882199712. doi: 10.1177/1178638821997123

PubMed Abstract | Crossref Full Text | Google Scholar

21. Sala-Vila, A, Estruch, R, and Ros, E. New insights into the role of nutrition in CVD prevention. Curr Cardiol Rep. (2015) 17:1–11. doi: 10.1007/s11886-015-0583-y

Crossref Full Text | Google Scholar

22. Olfert, MD, Barr, ML, Mathews, AE, Horacek, TM, Riggsbee, K, Zhou, W, et al. Life of a vegetarian college student: health, lifestyle, and environmental perceptions. J Am Coll Heal. (2020) 70:232–9. doi: 10.1080/07448481.2020.1740231

Crossref Full Text | Google Scholar

23. Vang, A, Singh, P, Lee, J, Haddad, E, and Brinegar, C. Meats, processed meats, obesity, weight gain and occurrence of diabetes among adults: findings from adventist health studies. Ann Nutr Metab. (2008) 52:96–104. doi: 10.1159/000121365

PubMed Abstract | Crossref Full Text | Google Scholar

24. Saintila, J, Lozano, TE, Calizaya-Milla, YE, White, M, and Huancahuire-Vega, S. Nutritional knowledge, anthropometric profile, total cholesterol, and motivations among Peruvian vegetarians and non-vegetarians. Nutricion Clinica y Dietetica Hospitalaria. (2021) 41:91–8. doi: 10.12873/411saintila

Crossref Full Text | Google Scholar

25. Schulze, MB, Martínez-González, MA, Fung, TT, Lichtenstein, AH, and Forouhi, NG. Food based dietary patterns and chronic disease prevention. BMJ. (2018) 361:k2396. doi: 10.1136/bmj.k2396

Crossref Full Text | Google Scholar

26. Neelakantan, N, Seah, JYH, and Van Dam, RM. The effect of coconut oil consumption on cardiovascular risk factors: a systematic review and Meta-analysis of clinical trials. Circulation. (2020) 141:803–14. doi: 10.1161/CIRCULATIONAHA.119.043052

PubMed Abstract | Crossref Full Text | Google Scholar

27. Ramos-Vera, C, Serpa Barrientos, A, Calizaya-Milla, YE, Carvajal Guillen, C, and Saintila, J. Consumption of alcoholic beverages associated with physical health status in adults: secondary analysis of the health information National Trends Survey Data. J Prim Care Community Health. (2022) 13:215013192110662. doi: 10.1177/21501319211066205

Crossref Full Text | Google Scholar

28. Peruano, E . Reglamento de la Ley N° 30021, Ley de Promoción de la Alimentación Saludable-Decreto Supremo - N° 017-2017-SA. Perú: Gobierno del Perú (2019).

Google Scholar

29. Casas-Caruajulca, E, Muguruza-Sanchez, LJ, Calizaya-Milla, YE, and Saintila, J. Percepción del etiquetado frontal de alimentos, compra y consumo de alimentos ultraprocesados durante la cuarentena por COVID-19: Un estudio transversal en la población peruana. Revista Española de Nutrición Humana y Dietética. (2021) 25:1–18. doi: 10.14306/renhyd.25.S2.1473

Crossref Full Text | Google Scholar

30. Mozaffarian, D, Benjamin, EJ, Go, AS, Arnett, DK, Blaha, MJ, Cushman, M, et al. Heart disease and stroke statistics-2015 update: a report from the American Heart Association. Circulation. (2015) 131:e29–e322. doi: 10.1161/CIR.0000000000000152

PubMed Abstract | Crossref Full Text | Google Scholar

31. Jiatong, W, Wang, Z, Alam, M, Murad, M, Gul, F, and Gill, SA. The impact of transformational leadership on affective organizational commitment and job performance: the mediating role of employee engagement. Front Psychol. (2022) 13:13. doi: 10.3389/fpsyg.2022.831060

Crossref Full Text | Google Scholar

32. Althubaiti, A . Sample size determination: a practical guide for health researchers. J Gen Fam Med. (2023) 24:72–8. doi: 10.1002/jgf2.600

PubMed Abstract | Crossref Full Text | Google Scholar

33. Ato, M, López, JJ, and Benavente, A. A classification system for research designs in psychology. Anales de Psicología. (2013) 29:1038–59. doi: 10.6018/analesps.29.3.178511

Crossref Full Text | Google Scholar

34. Software, Soper D . (2022) A-priori sample size calculator for multiple regression. Available at: https://www.danielsoper.com/statcalc/

Google Scholar

35. Block, G, Gillespie, C, Rosenbaum, EH, and Jenson, C. A rapid food screener to assess fat and fruit and vegetable intake. Am J Prev Med. (2000) 18:284–8. doi: 10.1016/S0749-3797(00)00119-7

PubMed Abstract | Crossref Full Text | Google Scholar

36. Lopez-Lopez, DE, Saavedra-Roman, IK, Calizaya-Milla, YE, and Saintila, J. Food addiction, saturated fat intake, and body mass index in Peruvian adults: a cross-sectional survey. Filip R, editor. J Nutr Metab. (2021) 2021:1–7. doi: 10.1155/2021/9964143

PubMed Abstract | Crossref Full Text | Google Scholar

37. Saintila, J, Morales García, WC, Calizaya-Milla, YE, Ruiz Mamani, PG, Huancahuire-Vega, S, and Calizaya-Milla, SE. Psychometric evaluation and invariance of the Spanish version of the Block fat screener (BFS-E) in university students. Front Psychol. (2023) 14:1042. doi: 10.3389/fpsyg.2023.1055468

Crossref Full Text | Google Scholar

38. Le, L, and Sabaté, J. Beyond meatless, the health effects of vegan diets: findings from the Adventist cohorts. Nutrients. (2014) 6:2131–47. doi: 10.3390/nu6062131

PubMed Abstract | Crossref Full Text | Google Scholar

39. Le, LT, Sabaté, J, Singh, PN, and Jaceldo-Siegl, K. The design, development and evaluation of the vegetarian lifestyle index on dietary patterns among vegetarians and non-vegetarians. Nutrients. (2018) 10:542. doi: 10.3390/nu10050542

PubMed Abstract | Crossref Full Text | Google Scholar

40. Dagnelie, PC, and Mariotti, F. Vegetarian diets: definitions and pitfalls in interpreting literature on health effects of vegetarianism In: F Mariotti , editor. Vegetarian and plant-based diets in health and disease prevention. New York, NY: Elsevier (2017). 3–10.

Google Scholar

41. Teixeira, RDCMDA, del CB, MM, Flor, DS, Zandonade, E, and Mill, JG. Estado nutricional e estilo de vida em vegetarianos e onívoros - Grande Vitória-ES. Rev Bras Epidemiol. (2006) 9:131–43. doi: 10.1590/S1415-790X2006000100016

Crossref Full Text | Google Scholar

42. Quiles, L, Portolés, O, Sorlí, J, and Corella, D. Efectos a corto plazo en el perfil lipídico y la glucemia de una dieta vegetariana baja en grasa. Nutr Hosp. (2015) 32:156–64. doi: 10.3305/nh.2015.32.1.8892

Crossref Full Text | Google Scholar

43. Marsh, K, Zeuschner, C, and Saunders, A. Health implications of a vegetarian diet: a review. Am J Lifestyle Med. (2012) 6:250–67. doi: 10.1177/1559827611425762

Crossref Full Text | Google Scholar

44. Tonstad, S, Butler, T, Yan, R, and Fraser, G. Type of vegetarian diet, body weight, and prevalence of type 2 diabetes. Diabetes Care. (2009) 32:791–6. doi: 10.2337/dc08-1886

PubMed Abstract | Crossref Full Text | Google Scholar

45. WHO. Constitution of the World Health Organization, basic documents. 48th ed. Geneva: WHO (2014).

Google Scholar

46. Quiliche, RB, Turpo-Chaparro, J, Torres, JH, Saintila, J, and Ruiz Mamani, PG. Overweight and obesity, body fat, waist circumference, and Anemia in Peruvian university students: a cross-sectional study. J Nutr Metab. (2021) 2021:1–9. doi: 10.1155/2021/5049037

PubMed Abstract | Crossref Full Text | Google Scholar

47. Heidal, KB, Colby, SE, Mirabella, GT, Al-Numair, KS, Bertrand, B, Gross, KH, et al. Cost and calorie analysis of fast food consumption in college students. Food Nutr Sci. (2012) 3:942–6. doi: 10.4236/fns.2012.37124

Crossref Full Text | Google Scholar

48. Santos, SJ, Hurtado-Ortiz, MT, Armendariz, M, Van Twist, V, and Castillo, Y. Obesity-related dietary patterns and health status of diabetes among at-risk Latino college students. J Hispanic High Educ. (2017) 16:291–313. doi: 10.1177/1538192716653504

Crossref Full Text | Google Scholar

49. Lahti-Koski, M, Pietinen, P, Heliövaara, M, and Vartiainen, E. Associations of body mass index and obesity with physical activity, food choices, alcohol intake, and smoking in the 1982-1997 FINRISK studies. Am J Clin Nutr. (2002) 75:809–17. doi: 10.1093/ajcn/75.5.809

PubMed Abstract | Crossref Full Text | Google Scholar

50. Willett, WC, and Leibel, RL. Dietary fat is not a major determinant of body fat. Am J Med. (2002) 113:47–59. doi: 10.1016/S0002-9343(01)00992-5

Crossref Full Text | Google Scholar

51. Satia-Abouta, J, Patterson, RE, Schiller, RN, and Kristal, AR. Energy from fat is associated with obesity in U.S. men: results from the prostate Cancer prevention trial. Prev Med. (2002) 34:493–501. doi: 10.1006/pmed.2002.1018

Crossref Full Text | Google Scholar

52. Chiolero, A, Faeh, D, Paccaud, F, and Cornuz, J. Consequences of smoking for body weight, body fat distribution, and insulin resistance. Am J Clin Nutr. (2008) 87:801–9. doi: 10.1093/ajcn/87.4.801

PubMed Abstract | Crossref Full Text | Google Scholar

53. Alipour, B, Abbasalizad Farhangi, M, Dehghan, P, and Alipour, M. Body image perception and its association with body mass index and nutrient intakes among female college students aged 18–35 years from Tabriz, Iran. Eat Weight Disord. (2015) 20:465–71. doi: 10.1007/s40519-015-0184-1

Crossref Full Text | Google Scholar

54. Yahia, N, El-Ghazale, H, Achkar, A, and Rizk, S. Dieting practices and body image perception among: Lebanese university students. Asia Pac J Clin Nutr. (2011) 20:21–8.

PubMed Abstract | Google Scholar

55. von Bothmer, MIK, and Fridlund, B. Gender differences in health habits and in motivation for a healthy lifestyle among Swedish university students. Nurs Health Sci. (2005) 7:107–18. doi: 10.1111/j.1442-2018.2005.00227.x

PubMed Abstract | Crossref Full Text | Google Scholar

56. Saintila, J, Lozano, TE, Ruiz, PG, White, M, and Huancahuire-Vega, S. Health-related quality of life, blood pressure, and biochemical and anthropometric profile in vegetarians and nonvegetarians. J Nutr Metab. (2020) 2020:1–8. doi: 10.1155/2020/3629742

PubMed Abstract | Crossref Full Text | Google Scholar

57. Chiu, YF, Hsu, CC, Chiu, THT, Lee, CY, Liu, TT, Tsao, CK, et al. Cross-sectional and longitudinal comparisons of metabolic profiles between vegetarian and non-vegetarian subjects: a matched cohort study. Br J Nutr. (2015) 114:1313–20. doi: 10.1017/S0007114515002937

PubMed Abstract | Crossref Full Text | Google Scholar

58. de Pimentel, CVMB, Philippi, ST, Simomura, VL, and Teodorov, E. Nutritional status, lifestyle and lipid profile in vegetarians. Int J Cardiovas Sci. (2019) 32:623–34. doi: 10.5935/2359-4802.20190044

Crossref Full Text | Google Scholar

59. Davey, GK, Spencer, EA, Appleby, PN, Allen, NE, Knox, KH, and Key, TJ. EPIC–Oxford: lifestyle characteristics and nutrient intakes in a cohort of 33 883 meat-eaters and 31 546 non meat-eaters in the UK. Public Health Nutr. (2003) 6:259–68. doi: 10.1079/PHN2002430

PubMed Abstract | Crossref Full Text | Google Scholar

60. Agarwal, U, Mishra, S, Xu, J, Levin, S, Gonzales, J, and Barnard, N. A multicenter randomized controlled trial of a nutrition intervention program in a multiethnic adult population in the corporate setting reduces depression and anxiety and improves quality of life: the GEICO study. Am J Health Promot. (2015) 29:245–54. doi: 10.4278/ajhp.130218-QUAN-72

PubMed Abstract | Crossref Full Text | Google Scholar

61. Parra-Fernández, ML, Manzaneque-Cañadillas, M, Onieva-Zafra, MD, Fernández-Martínez, E, Fernández-Muñoz, JJ, Prado-Laguna, MDC, et al. Pathological preoccupation with healthy eating (orthorexia nervosa) in a Spanish sample with vegetarian, vegan, and non-vegetarian dietary patterns. Nutrients. (2020) 12:3907. doi: 10.3390/nu12123907

PubMed Abstract | Crossref Full Text | Google Scholar

62. Paslakis, G, Richardson, C, Nöhre, M, Brähler, E, Holzapfel, C, Hilbert, A, et al. Prevalence and psychopathology of vegetarians and vegans – results from a representative survey in Germany. Sci Rep. (2020) 10:6840. doi: 10.1038/s41598-020-63910-y

PubMed Abstract | Crossref Full Text | Google Scholar

63. Orlich, M, Singh, P, Sabate, J, Jaceldo-siegl, K, Jing, F, Knutsen, S, et al. Vegetarian dietary patterns and mortality in Adventist health study 2. JAMA Intern Med. (2014) 173:1230–8. doi: 10.1001/jamainternmed.2013.6473

Crossref Full Text | Google Scholar

64. Yen, CE, Yen, CH, Huang, MC, Cheng, CH, and Huang, YC. Dietary intake and nutritional status of vegetarian and omnivorous preschool children and their parents in Taiwan. Nutr Res. (2008) 28:430–6. doi: 10.1016/j.nutres.2008.03.012

PubMed Abstract | Crossref Full Text | Google Scholar

65. Saintila, J, Calizaya-Milla, YE, Brañes-Ruiz, DE, Nunura-Figueroa, PR, Chávez-Hernández, TC, Bautista-Mayuri, VA, et al. Relationship between dietary self-efficacy and religiosity among seventh-day Adventists in Peru. J Multidiscip Healthc. (2022) 15:259–69. doi: 10.2147/JMDH.S350990

PubMed Abstract | Crossref Full Text | Google Scholar

66. Ancka-Iglesias, CV, Flores-Albino, YA, Calizaya-Milla, YE, and Saintila, J. Sociodemographic characteristics and consumption of ultra-processed foods in vegetarians and non-vegetarians: a cross-sectional study in the Peruvian population. Nutricion Clinica y Dietetica Hospitalaria. (2022) 42:186–96. doi: 10.12873/421ancka

Crossref Full Text | Google Scholar

67. Wang, T, Masedunskas, A, Willett, WC, and Fontana, L. Vegetarian and vegan diets: benefits and drawbacks. Eur Heart J. (2023) 44:3423–39. doi: 10.1093/eurheartj/ehad436

PubMed Abstract | Crossref Full Text | Google Scholar

68. Desai, MN, Miller, WC, Staples, B, and Bravender, T. Risk factors associated with overweight and obesity in college students. J Am Coll Heal. (2008) 57:109–14. doi: 10.3200/JACH.57.1.109-114

Crossref Full Text | Google Scholar

69. Huot, I, Paradis, G, and Ledoux, M. Factors associated with overweight and obesity in Quebec adults. Int J Obes. (2004) 28:766–74. doi: 10.1038/sj.ijo.0802633

Crossref Full Text | Google Scholar

70. Omar, SM, Taha, Z, Hassan, AA, Al-Wutayd, O, and Adam, I. Prevalence and factors associated with overweight and central obesity among adults in the eastern Sudan. PLoS One. (2020) 15:e0232624. doi: 10.1371/journal.pone.0232624

PubMed Abstract | Crossref Full Text | Google Scholar

71. Seth, B, Arora, S, and Singh, R. Association of obesity with hormonal imbalance in infertility: a cross-sectional study in north Indian women. Indian J Clin Biochem. (2013) 28:342–7. doi: 10.1007/s12291-013-0301-8

PubMed Abstract | Crossref Full Text | Google Scholar

72. Pajuelo, J, Torres, L, Agüero, R, and Bernui, I. El sobrepeso, la obesidad y la obesidad abdominal en la población adulta del Perú. Anales de la Facultad de Medicina. (2019) 80:21–7. doi: 10.15381/anales.v80i1.15863

Crossref Full Text | Google Scholar

73. Huynen, MMTE, Vollebregt, L, Martens, P, and Benavides, BM. The epidemiologic transition in Peru. Rev Panam Salud Publica. (2005) 17:51–9. doi: 10.1590/s1020-49892005000100010

Crossref Full Text | Google Scholar

74. Lissock, C, Sobngwi, E, Ngassam, E, and Ngoa, L. Rural and urban differences in metabolic profiles in a Cameroonian population. Pan Afr Med J. (2011) 10:10. doi: 10.4314/pamj.v10i0.72204

Crossref Full Text | Google Scholar

75. Wate, JT, Snowdon, W, Millar, L, Nichols, M, Mavoa, H, Goundar, R, et al. Adolescent dietary patterns in Fiji and their relationships with standardized body mass index. Int J Behav Nutr Phys Act. (2013) 10:45. doi: 10.1186/1479-5868-10-45

PubMed Abstract | Crossref Full Text | Google Scholar

76. Tapera, R, Merapelo, MT, Tumoyagae, T, Maswabi, TM, Erick, P, Letsholo, B, et al. The prevalence and factors associated with overweight and obesity among University of Botswana students. Cogent Med. (2017) 4:1357249. doi: 10.1080/2331205X.2017.1357249

Crossref Full Text | Google Scholar

77. AlJohani, S, Salam, M, Bani Mustafa, A, Zaidi, ARZ, Aljohani, AA, Almutairi, A, et al. Dietary habits of students enrolled in faculties of health sciences: a cross-sectional study. Cureus. (2019) 11:e6012. doi: 10.7759/cureus.6012

Crossref Full Text | Google Scholar

78. Montero, A, Ubeda, N, and Gonzales, A. Evaluación de los hábitos alimentarios de una población de estudiantes universitarios en relación con sus conocimientos nutricionales. Nutr Hosp. (2015) 21:466–73.

Google Scholar