Association between salivary /microbiological parameters, oral health and eating habits in young athletes

Abstract

Background: Athletes' oral health can impact overall well-being and sports performance. This study aimed to evaluate the interactions between eating habits and oral health of 120 young athletes as compared to 30 age-matched individuals not practicing sports based on a questionnaire and the analysis of saliva.

Methods: One hundred twenty subjects practicing various sports activities (test group) and 30 subjects not practicing sports (control group) were selected. A self-administered questionnaire was used to obtain personal data, hours and frequency of weekly training, complete pathological history, history of hard and soft tissues of the oral cavity, family history, and oral hygiene practices. The eating habits of the young participants were analyzed by investigating the number of daily meals; use and frequency in sports practice of supplements/energy drinks, fruit/juices, snacks, chocolate; daily diet; and differences between usual diet and pre-competition diet. At baseline (T0), each participant was clinically assessed for the determination of the number of decayed, missing, and filled teeth (DMFT), Silness & Löe Plaque Index (PI), and the Löe & Silness Gingival Index (GI) and qualitative analysis for the presence/absence of stains and dental erosions. At T0, before (T1) and after training sessions (T2), saliva was collected to determine resting pH, Streptococcus mutans, and Lactobacillus spp counts.

Results: Test groups were trained more than 2 h, 5 times a week. Soccer players and skiers had a high percentage of caries; water polo players demonstrated the highest percentage of erosions and dental stains. Salivary resting pH showed statistically different values in three different observations between the groups. S. mutans was harbored by 60% of soccer and 70% of water polo players, while Lactobacillus spp in 43.33% of the swimmers and soccer players. Combining all the 56 variables including the clinical examination, self-reported parameters, and salivary analysis, we have identified water polo players as a distinct at-risk group for developing dental defects, expressed as an aggregate disease score. In particular, we have found that energy snacks/chocolate intake is strongly associated with ratio of S. mutans/Lactobacillus spp and that S. mutans is linked to dental defects (R = 0.88). Linear regression analysis indicates that energy snacks/chocolate intake in the study population represents a strong driver for oral dysbiosis and dental disease.

Conclusions: Our study clearly shows that athletes should follow a balanced diet that not only satisfies their nutritional needs but also avoids oral dysbiosis and subsequent dental damage.

Keywords: Saliva; adolescent health; food habits; nutrition; sport.

Figure 1.

Clinical dental scores, oral pH, and oral hygiene habits across sports group and controls. (a) Bar plot showing the aggregate disease score including DMFT index, active caries, PI, GI, dental erosions, and dental stains per group. (b) Correlation matrix for sports group and control identifies effects of dental hygiene on clinical parameters. (c) Bar chart showing the change in pH at baseline (T0), before training (T1) and after training (T2). Au = arbitrary units, DMFT = decayed, missing, filled teeth index, PI = periodontal inflammation, GI = gingival inflammation. Significant associations in the correlation plot are indicate by p values in red.

Figure 2.

Presence of cariogenic bacteria and relation to clinical parameters across groups and dental hygiene habits in sportsmen. (a) Bar plot showing the ratio of S. mutans and lactobacillus spp across sports group and controls. (b) Correlation matrix for sports group identifies potential associations between microbial cariogenic species and clinical scores. (c) Correlation matrix for sports group inquires the effect of brushing on the microbial load. Au = arbitrary units, DMFT = decayed, missing, filled teeth index, PI = periodontal inflammation, GI = gingival inflammation. Significant associations in the correlation plots are indicated by p values in red.

Figure 3.

Connecting eating habits to dental hygiene practices, clinical scores, and cariogenic species in sportsmen. (a) Correlation matrix for sports group identifies potential associations between eating behavior and dental hygiene practices. (b) Correlation matrix for sports group identifies potential associations between eating habits and clinical scores. (c) Correlation matrix for sports group inquires the effect of eating habits on the microbial load. Au = arbitrary units, DMFT = decayed, missing, filled teeth index, PI = periodontal inflammation, GI = gingival inflammation. Significant associations in the correlation plots are indicate by p values in red.

Figure 4.

Intake of functional food and its effect on clinical parameters and oral biosis in sporstmen in sportsmen. (a) Bar plot showing the aggregate score for functional food in all study group. (b) Correlation matrix for sports group identifies potential associations between functional food types and clinical scores. (c) Correlation matrix for sports group inquires the effect of functional food on the microbial load. Au = arbitrary units, DMFT = decayed, missing, filled teeth index, PI = periodontal inflammation, GI = gingival inflammation. Significant associations in the correlation plots are indicated by p values in red.

Figure 5.

Attitude to functional beverages before, during, and after training. (a) Supplements/energy drinks intake with respect to training competition. Paired comparison, T-test: p < 0.05: soccer before and after. (b) Fruit/juices intake with respect to training competition. Paired comparison, T-test, p < 0.05: before training; swimming vs water polo; swimming vs skiing; soccer vs water polo; soccer vs skiing, paired comparison, T-test, p < 0.01: water polo, before versus during and during versus after; p < 0.05 = skiing, before versus during.

Figure 6.

Attitude to functional food before, during, and after training. (a) Snack intake with respect to training competition. Paired comparison, T-test, p < 0.05: Soccer, before versus during, p < 0.01: skiing: during vs after; p < 0.001: waterpolo, before versus during and during versus after. (b) Chocolate intake with respect to training-competition. Paired comparison, T-test p < 0.01, b = swimming vs water polo, p < 0.001: water polo before vs during, and during vs after.

Figure 7.

Effect of the intake of breakfast food, mid-morning snack, and afternoon snack on clinical parameters and oral biopsy in sportsmen. Correlation matrices investigating the interactions among breakfast food and (a) clinical parameters, (b) oral biosis. Correlation matrices investigating the interactions among mid-morning snacks, (c) clinical parameters and (d) oral biosis. Correlation matrices investigating the interactions among afternoon snacks, (e) clinical parameters and (f) oral biosis. DMFT = decayed, missing, filled teeth index, PI = periodontal inflammation, GI = gingival inflammation. Significant associations in the correlation plots are indicate by p values in red.

Figure 8.

Effect of the intake of lunch and dinner food on clinical parameters and oral biosis in sportsmen. Correlation matrices investigating the interactions of lunch food on (a) clinical parameters and (b) oral biosis and dinner food on (c) clinical parameters and (d) oral biosis. DMFT = decayed, missing, filled teeth index, PI = periodontal inflammation, GI = gingival inflammation. Significant associations in the correlation plots are indicated by p values in red.

Figure 9.

Diversity of study groups and identification of oral dysbiosis drivers. (a) Similarity plot showing how sports type differ considering all 56 variable. (b) Radar plot showing distinctive variables per sport group and as compared to controls (dotted line). (c) Correlation plot investigating the interactions among selected variables. (d) Representation of directional dependencies and their weight. Significant associations in the correlation plots are indicate by p values in red.