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Introduction
Dentistry is a profession characterized by generating high levels of anxiety in its students, because of which they face a growing academic load that leads to increases in stress levels and reductions in free time [1-5].
This phenomenon causes university students to increase the frequency of unhealthy habits such as prolonged fasting or a predilection for the consumption of processed foods with high glycemic index levels related to cariogenic risk [6-8]. In this sense, carious lesions usually occur as a result of the imbalance in the activity of the oral biofilm [9], where the demineralization and remineralization processes generated in the tooth enamel are frequently associated with the consumption of easily fixed fermentable carbohydrates, whose heterogeneous metabolization, in turn, induces changes in the hydrogen potential (pH), determining this change in environment for the clinical management of dental caries [10-12].
Likewise, this interaction of phenomena inside the oral cavity causes university students to be constantly exposed to a greater risk of cariogenic diseases related to unhealthy eating habits [5,6,13]. In this context, it is interesting to mention that the theoretical-practical knowledge acquired by students of careers linked to the health area is also a determining link in healthy habits, since the educational degree can condition the self-care of both students and health professionals, that is, dentistry, which is a fundamental element when it comes to preventing carious lesions characterized by their high prevalence worldwide [14,15].
Additionally, previous studies have shown that the lifestyle and dietary choices of dental students can significantly impact their oral health outcomes [16-20]. Factors such as the frequency of water and meal intake, plus the choice of snacks along with the overall quality of the diet play a crucial role in maintaining oral health [21,22]. Stress and academic pressures often lead to neglect in these areas, further exacerbating the risk of carious lesions [18,23]. Understanding these patterns is essential for developing targeted interventions aimed at reducing cariogenic risks among dental students [20,24].
For this reason, this work aimed to identify the cariogenic risk in the presence of foods consumed by dentistry students from the Biobio region (Chile).
Methodology
Design
Cross-sectional descriptive observational design study, whose planning was carried out following the guidelines of Strengthening the Reporting of Observational Studies in Epidemiology [25]. The research protocol received approval from the Research Ethics Committee of the Central University of Chile through Minute No. 55/2023, in strict accordance with the Declaration of Helsinki [26].
Context
The evaluation was carried out on dentistry students at the Andrés Bello National University, located in the Biobio region (Chile). A professional specializing in dentistry verified the appropriateness of patient selection, providing each participant with a brief written description of the study, along with its objectives and the reason for selection. This process was accompanied by an informed consent that, once signed, allowed the evaluation of the cariogenic risk and glycemic index of the participants.
Population and Sample
The population was selected through non-probabilistic sampling, choosing 178 dental students who met the established eligibility criteria. The inclusion criteria for participation in the study were the following:
Students enrolled in the professional dentistry career at the Andres Bello National University, located in the Biobio region (Chile), during the year 2023.
In contrast, the exclusion criteria included:
Cariogenic eating habits
Eating habits were obtained through the Lipari and Andrade Cariogenic Food Consumption Survey [27]. This tool evaluates the cariogenic potential of sugars in relation to the patient's diet during and at the end of dental treatment. It allows establishing a closed list of foods classified according to their physical consistency, frequency, and time of consumption. For the classification of cariogenic risk, low (10 to 33 points), medium (34 to 79 points), and high (80 to 144 points) levels are considered.
In addition, the international tables of glycemic index and glycemic load values proposed by Atkinson and collaborators were applied to select the foods to be analyzed [3,4]. This was done based on the description of cariogenic foods provided by Lipari and Andrade [27].
This procedure led to the creation of 18 food groups present in the glycemic index tables, such as fruit juice, milk, white bread, soda crackers, candy, ice cream, jam, chocolate, sweet pie, cake, cookies, donuts, honey, dried fruits, fruits in syrup, nougat, chewy candy, and sugary cereals. Of the 23 food groups, 5 that were not found in these tables were not considered, such as sachet juices, tea, chewing gum, pacifiers, and undiluted powdered juice.
Academic Stress
Academic stress was evaluated using the Academic Stress Inventory (ASI). This questionnaire consists of 11 situations that allow stress to be assessed through a Likert-type scale. The weighting of academic stress is rated in values from 1 to 5, where 1 represents "No stress" and 5 "A lot of stress." The weighting of each dimension is classified as follows: 1-2 = low level; 3 = medium level; 4-5 = high level [28].
Sociodemographic evaluation
Sociodemographic variables included gender (male or female), age (years), weight, and height. These data were obtained through questions incorporated into the questionnaires applied [3,4,27,28], in addition to the classification of nutritional status obtained through the Body Mass Index [29].
Biases
Regarding possible biases, it is relevant to mention that the probability of participant selection could have been affected by the lack of blinding of the evaluators when reviewing the data. This could have influenced the differential treatment between groups, generating a potential risk of information bias. Likewise, the dentistry career is mostly a profession practiced by women, being an indication of a possible selection bias.
Sample size
The 330 students of the dentistry program taught by the Andres Bello National University, located in the Biobio region (Chile), determined the sample size. A 95% confidence interval (CI) and a 5% margin of error were established, obtaining a minimum necessary sample size of 178.
Statistical analysis
The data were analyzed using IBM SPSS Statistics software for Windows operating system, version 27. Normality in the data distribution was evaluated using the Kolmogorov-Smirnov test. Measures of central tendency and dispersion, such as the mean and standard deviation, were used to describe the quantitative variables. In addition, relative and absolute frequencies were used to describe the qualitative variables. In the inferential analysis, Pearson's Chi square test was applied, with the significance level α = 0.05 for all analyses. Additionally, the effect size for the qualitative variables was calculated using Cramer's “V”, considering the classification values based on the degrees of freedom.
Results
A sample of 178 students (60 men and 118 women) was analyzed. In general terms, the students were between 18 and 35 years old, with an average of 22.2 ± 3.1 years, an average nutritional status of overweight (25.2 ± 4.2), an average level of low academic stress (22.8 ± 0.2), and a medium cariogenic risk (63 ± 24.4), as seen in Table 1.
Table 1 Baseline characteristics of the analyzed sample (n = 178).
| Numerical variables | x̅ ± σ |
|---|---|
| Age (years) | 22,2 ± 3,1 |
| Weight (kg) | 69,5 ± 15,1 |
| Size (cm) | 165,6 ± 8,5 |
| BMI (kg/m2) | 25,2 ± 4,2 |
| Academic stress | 2,8 ± 0,9 |
| Cariogenic risk | 63 ± 24,4 |
Note.x̅: Mean, σ: Standard deviation.
Table 2 analyzes the association between cariogenic risk and the study variables, where homogeneity of cariogenic risk is seen depending on gender (gl = 2; p = 0.73; w = 0.06), nutritional status (df = 6; p = 0.19; w = 0.16), and academic stress (df = 4; p = 0.23; w = 0.13). Regarding food intake, white bread (df = 2; p = 0.09; w = 0.17), ice cream (df = 2; p = 0.13; w = 0.15), jam ( df = 2; p = 0.48; w = 0.09), honey (df = 2; p = 0.40; w = 0.10), and dried fruits (df = 2; p = 0.57; w = 0.08) do not present statistically significant differences with small effect sizes.
Table 2 Association of cariogenic risk with the study variables (n = 178).
| Variables | Cariogenic risk classification | Statisticians | Effect size | |||||
|---|---|---|---|---|---|---|---|---|
| Low (n = 21) | Medium (n = 103) | High (n = 54) | df | p | w | |||
| Nutritional condition | Under weight | 2 (9,5 %) | 1 (1%) | 2 (3,7 %) | 6 | 0,19 | 0,16 | Medium |
| Healthy | 11 (52,4 %) | 58 (56,3 %) | 25 (46,3 %) | |||||
| Overweight | 7 (33,3 %) | 31 (30,1 %) | 23 (42,6 %) | |||||
| Obesity | 1 (4,8 %) | 13 (12,6 %) | 4 (7,4 %) | |||||
| Academic stress | Low | 12 (57,1 %) | 67 (65,1 %) | 27 (50 %) | 4 | 0,23 | 0,13 | Low |
| Medium | 5 (23,8 %) | 26 (25,2 %) | 15 (27,8 %) | |||||
| High | 4 (19,1) | 10 (9,7 %) | 12 (22,2 %) | |||||
| Gender | Male | 7 (33,3%) | 37 (35,9%) | 16 (29,6%) | 2 | 0,73 | 0,06 | Low |
| Female | 14 (66,7%) | 66 (64,1%) | 38 (70,4%) | |||||
| Fruit juice | Yes | 10 (47,6%) | 72 (69,9%) | 43 (79,6) | 2 | 0,02 | 0,20 | Low |
| Not | 11 (52,4%) | 31 (30,1%) | 11 (20,4%) | |||||
| Milk | Yes | - | 16 (15,5%) | 15 (27,8%) | 2 | 0,01 | 0,22 | Medium |
| Not | 21 (100%) | 87 (84,5%) | 39 (72,2%) | |||||
| White bread | Yes | 13 (61,9%) | 81 (78,6%) | 46 (85,2%) | 2 | 0,09 | 0,17 | Low |
| Not | 8 (38,1%) | 22 (21,4%) | 8 (14,8%) | |||||
| Soda cookies | Yes | 9 (42,9%) | 44 (42,7%) | 36 (66,7%) | 2 | 0,01 | 0,22 | Medium |
| Not | 12 (57,1%) | 59 (57,3%) | 18 (33,3%) | |||||
| Candies | Yes | 5 (23,8%) | 55 (53,4%) | 42 (77,8%) | 2 | <0,001 | 0,33 | Medium |
| Not | 16 (76,2%) | 48 (46,6%) | 12 (22,2%) | |||||
| Ice cream | Yes | 14 (66,7%) | 75 (72,8%) | 46 (85,2%) | 2 | 0,13 | 0,15 | Low |
| Not | 7 (33,3%) | 28 (27,2%) | 8 (14,8%) | |||||
| Jam | Yes | 7 (33,3%) | 48 (46,6%) | 26 (48,1%) | 2 | 0,48 | 0,09 | Low |
| Not | 14 (66,7%) | 55 (53,4%) | 28 (51,9%) | |||||
| Chocolate | Yes | 14 (66,7%) | 81 (78,6%) | 50 (92,6%) | 2 | 0,02 | 0,21 | Medium |
| Not | 7 (33,3%) | 22 (21,4%) | 4 (7,4%) | |||||
| Sweet cake | Yes | 9 (42,9%) | 80 (77,7%) | 48 (88,9%) | 2 | <0,001 | 0,32 | Medium |
| Not | 12 (57,1%) | 23 (22,3%) | 6 (11,1%) | |||||
| Cake | Yes | 8 (38,1%) | 73 (70,9%) | 47 (87%) | 2 | <0,001 | 0,32 | Medium |
| Not | 13 (61,9%) | 30 (29,1%) | 7 (13%) | |||||
| Cookies | Yes | 11 (52,4%) | 88 (85,4%) | 51 (94,4%) | 2 | <0,001 | 0,34 | Medium |
| Not | 10 (47,6%) | 15 (14,6%) | 3 (55,6%) | |||||
| Donuts | Yes | 5 (23,8%) | 59 (57,3%) | 38 (70,4%) | 2 | <0,001 | 0,27 | Medium |
| Not | 16 (76,2%) | 44 (42,7%) | 16 (29,6%) | |||||
| Honey | Yes | 8 (38,1%) | 43 (41,7%) | 28 (51,9%) | 2 | 0,40 | 0,10 | Low |
| Not | 13 (61,9%) | 60 (58,3%) | 26 (48,1%) | |||||
| Dry fruits | Yes | 13 (61,9%) | 58 (56,3%) | 35 (64,8%) | 2 | 0,57 | 0,08 | Low |
| Not | 8 (38,1%) | 45 (43,7%) | 19 (35,2%) | |||||
| Fruits in syrup | Yes | 1 (4,8%) | 20 (19,4%) | 10 (18,5%) | 2 | 0,03 | 0,12 | Low |
| Not | 20 (95,2%) | 83 (80,6%) | 44 (81,5%) | |||||
| Nougat | Yes | 4 (19%) | 25 (24,3%) | 24 (44,4%) | 2 | 0,02 | 0,22 | Medium |
| Not | 17 (81%) | 78 (75,7%) | 30 (55,6%) | |||||
| Chewy candy | Yes | 4 (19%) | 47 (45,6%) | 34 (63%) | 2 | 0,002 | 0,26 | Medium |
| Not | 17 (81%) | 56 (54,4%) | 20 (37%) | |||||
| sugary cereal | Yes | 6 (28,6%) | 61 (59,2%) | 41 (75,9%) | 2 | <0,001 | 0,29 | Medium |
| Not | 6 (75 %) | 21 (47,7 %) | 9 (33,3 %) | |||||
Note. df: degrees of freedom, p: bilateral significance value p, w: Cramer's V statistic.
In relation to the behavior of the overweight/obesity condition as a function of cariogenic risk, statistically significant differences with medium to large effect sizes are only observed on milk intake (df = 2; p = 0.01; w = 0 .33), cookies (df = 2; p < 0.001; w = 0.42), soda crackers (df = 2; p = 0.03; w = 0.29), candies (df = 2; p = 0.03; w = 0.30), and sweet cake (df = 2; p = 0.02; w = 0.31), as seen in Table 3.
Table 3 Association of cariogenic risk in variables of the overweight/obesity subgroup (n = 79).
Note. df: degrees of freedom, p: bilateral significance value p, w: Cramer's V statistic.
Discussion
The findings of this study reveal a complex relationship between food consumption and cariogenic risk among dentistry students at Andrés Bello National University in the Biobío region, Chile. The prevalence of overweight and obesity in this population exceeds that observed in the general population of Chilean university students [30], suggesting an obesogenic environment in higher education where diet and physical inactivity play determining roles [30-32].
A possible explanation for this behavior is that cariogenic risk does not necessarily depend on educational level. In fact, a high risk has been observed despite students' awareness and knowledge of good oral hygiene habits [18,19]. Instead, factors such as food consumption, nutritional status, and physical activity levels modulate cariogenic risk. Diet and dietary habits are key determinants in the occurrence of dental caries in adults who attend tertiary health centers [19,33].
The study highlights a high prevalence of cariogenic risk associated with the intake of foods such as fruit juices, white bread, sweets, ice cream, chocolates, pastries, cakes, cookies, donuts, nuts, and cereals. These foods, rich in carbohydrates (glucose and fructose), contribute to the development of anabolic effector systems responsible for the lipogenesis process [3,4,34]. Dental plaque exposed to sugars like sucrose can rapidly produce acids, causing a rapid drop in pH followed by a gradual recovery towards the initial oral pH. This pH instability generates an oral environment conducive to the growth of the bacteria S. mutans [10,11].
The exopolysaccharide matrix produced by bacteria such as S. mutans is a key factor in the virulence of the cariogenic biofilm. The metabolism of these exopolysaccharides is considered a potential preventive strategy for the formation of cariogenic biofilms. However, this approach contradicts the results of the study, which indicate a low consumption of foods such as honey (55.6%), a phenomenon possibly attributed to marketing and public policies that directly influence consumer habits, regardless of the nutritional quality of the products [35,36].
Moreover, it is known that academic stress, often related to anxiety, can modulate the consumption of sugary drinks, fast food, and pastries [37-39]. This behavior aligns with the low to moderate stress classification observed in the present study. In relation to cariogenic risk, significant differences are observed in the frequency of consumption of fruit juice, milk, soda crackers, candy, chocolate, sweet cake, cake, cookies, donuts, nougat, and sugary cereals. A cariogenic diet characterized by a high sugar content, such as sucrose, can adhere to the tooth surface, generating dysbiosis that favors enamel demineralization and the formation of dental caries [40-42].
The analysis of the overweight/obesity subgroup shows significant differences in the consumption of sugar-rich foods (milk, candy, sweet cake, cookies, and soda crackers), indicating that these can modulate cariogenic risk. Although the etiology of dental caries is determined by multiple intrinsic and extrinsic factors, the frequency of food consumption, time of ingestion, concentration of sugars, and pH of food contribute to varying degrees to cariogenic risk [42].
Regarding the limitations of the study, it is important to note that the self-perception of healthy foods by each student could have altered the results. The absence of validated dietary surveys for food recording is also a limitation. Although a report was made based on food categories according to the international table of glycemic index and load values published in 2008 and 2021, it is suggested for future research to apply validated questionnaires that include typical Chilean preparations or to conduct a 24-hour recall with a food consumption trend survey. To date, there are no validated questionnaires on the glycemic index with typical Chilean preparations. However, the use of international tables of glycemic index and load values proved to be a useful tool for classifying the glycemic index of the food products consumed by the subjects in the cariogenic risk survey.
Conclusion
The findings of the present study suggest the possibility of an association between the frequency of consumption of foods rich in sugars with nutritional status, academic stress, and cariogenic risk in dental students. Nevertheless, it is important to highlight that future research should focus on the use of instruments that allow a precise assessment of intake to obtain more robust conclusions.
