Caries Risk Assessment in Young Adults of South Kerala with Multiple Dental Restorations Using the Cariogram with Salivary Tests

Abstract

Aim: The aim of this study was to determine the caries risk of young adults by using the Cariogram software and explore the interactions between the various caries-related factors and their associated caries risk determined by the Cariogram. Materials and methods: A cross-sectional comparative study was undertaken among 120 young adults (60 undergraduates and 60 postgraduates) aged 18–25 years. Clinical and radiographic examinations, salivary sampling, and a questionnaire on a diet were used to collect data from the study sample. The 10 distinct parameters of the Cariogram for each individual were obtained according to a preset scale of 0–2 or 0–3. The examiner gathered the data for each variable from the clinical examination or from laboratory tests, as well as from the completed questionnaire and dietary record. The favorable score was 0, while the unfavorable score was 3 or 2 in some circumstances. For each of the students studied, a caries risk profile was created, with the appropriate score assigned to each of the criteria to be considered by the software. The Cariogram model was then used to determine the caries risk profile of each individual in the study sample. Results: The study results depicted that most of the undergraduates (31.67%) and postgraduates (46.67%) had a good plaque index score. 36.67% had a Streptococcus count of 103,4 and 56.67% had a Lactobacillus count of less than 10.3 The salivary secretion rate of 41.67% of undergraduates and 38.33% of postgraduates was essentially normal at 0.9–1.1 ml/min. It was observed that 58.33% of the postgraduates had acceptable pH ≥6, and 3.33% of undergraduates had salivary pH between 4.5 and 5.5. Enumeration of salivary Streptococcus mutans and Lactobacillus, decayed missing filled teeth (DMFT), decayed missing filled surface (DMFS) score, salivary buffer capacity, plaque level, and use of fluoride supplementation were found to have a significant correlation with the caries risk determination. Conclusion: The Cariogram model can detect caries-related factors that may contribute to the anticipated caries risk. Streptococcus mutans count is the most important predictive factor in the model, followed by the DMFS, fluoride program, DMFT, Lactobacillus counts, buffer capacity, and plaque index. Preventive strategies can also be developed using these profile analyses to reduce or eliminate the risk of caries prevailing in the community.