Citation Information :
Moothedath M. Caries Risk Assessment in Young Adults of South Kerala with Multiple Dental Restorations Using the Cariogram with Salivary Tests. World J Dent 2022; 13 (4):368-374.
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.
Hebbal M, Ankola A V. Caries risk profile of 12-year-old school children in an Indian city using caries risk profile of 12-year-old school children in an Indian city using Cariogram. Med Oral Patol Oral Cir Bucal 2012;17(6):e1054–e1061. DOI: 10.4317/medoral.17880
Garg A, Madan M, Dua P, et al. Validating the usage of Cariogram in 5- and 12-year-old school-going children in paonta sahib, Himachal Pradesh, India: a 12-month prospective study. Int J Clin Pediatr Dent 2018;11(2):110–115. DOI: 10.5005/jp-journals-10005-1495
Karamüftüoğlu N, Ulusu T. Assessment of caries risk in children with “Cariogram”. J Gazi Univ Heal Sci Inst 2021;2:829316.
Peker I, Mangal T, Erten H, et al. Evaluation of caries risk in a young adult population using a computer-based risk assessment model (Cariogram). J Dent Sci 2012;7(2):99–104. DOI: 10.1016/j.jds.2012.03.004
Almosa NA, Lundgren T, Al-mulla A, et al. Caries risk profiles in orthodontic patients: a 4-year follow-up study using the Cariogram model in governmental vs. private clinics. Saudi Dent J 2018;30(2):166–174. DOI: 10.1016/j.sdentj.2018.02.001
Sonbul H, Al-Otaibi M, Birkhed D. Risk profile of adults with several dental restorations using the Cariogram model. Acta Odontol Scand 66(6):351–357. DOI: 10.1080/00016350802325853
Janakiram C, Antony B, Joseph J, et al. Prevalence of dental caries in India among the WHO index age groups: a meta-analysis. J Clin Diagn Res 2018;12:ZE08–13. DOI: 10.7860/JCDR/2018/32669.11956
Naik S, Moyin S, Patel B, et al. Caries risk assessment of 12–13-year-old government and rivate school going children of Mysore city using Cariogram: a comparative study. J Int Soc Prev Communit Dent 2018;8(2):160–167. DOI: 10.4103/jispcd.JISPCD_437_17
Bratthall D, Petersson G. Cariogram–a multifactorial risk assessment model for a multifactorial disease. Community Dent Oral Epidemiol 2005;33(4):256–264. DOI: 10.1111/j.1600-0528.2005.00233.x
Ruiz-Miravet A, Montiel Company J, Almerich-Silla J. Evaluation of caries risk in a young adult population. Med Oral Patol Oral Cir Bucal 2007;12(5):E412–E718.
Almosa N, Al-Mulla A, Birkhed D. Caries risk profile using the Cariogram in governmental and private orthodontic patients at de-bonding. Angle Orthod 2012;82(2):267–274. DOI: 10.2319/040911-253.1
Celik EU, Gokay N, Ates M. Efficiency of caries risk assessment in young adults using Cariogram. Eur J Dent 2012;6(3):270–279.
Mejàre I, Axelsson S, Dahlén G, et al. Caries risk assessment. A systematic review. Acta Odontol Scand 2014;72(2):81–91. DOI: 10.3109/00016357.2013.822548
Featherstone JDB, Crystal YO, Alston P, et al. A comparison of four caries risk assessment methods. Front Oral Heal 2021;2:1–13. DOI: 10.3389/froh.2021.656558
Subashri A, Prabakar J, Ganapathy D. Caries risk assessment using Cariogram profile among 18–20 year old patients attending private dental college, Chennai: a hospital based cross-sectional study. Eur J Mol Clin Med 2020;07(1):1565–1579.
Kumar R, Diwakar M, Shastry S. Effectiveness of Cariogram in assessing caries risk among 12 year old school going children at Puducherry – a cross sectional study. Int J Curr Res 2017;9:48411–48414.
Petersson GH, Isberg PE, Twetman S. Caries risk assessment in school children using a reduced Cariogram model without saliva tests. BMC Oral Health 2010;10:5. DOI: 10.1186/1472-6831-10-5
Tayanin G, Petersson G, Bratthall D. Caries risk profiles of 12–13–year–old children in Laos and Sweden. Oral Heal Prev Dent 2005;3(1):15–23.
van Houte J. Microbiological predictors of caries risk. Adv Dent Res 1993;7(2):87–96. DOI: 10.1177/08959374930070022001
Kühnisch J, Berger S, Goddon I, et al. Occlusal caries detection in permanent molars according to WHO basic methods, ICDAS II and laser fluorescence measurements. Community Dent Oral Epidemiol 2008;36(6):475–484. DOI: 10.1111/j.1600-0528.2008.00436.x
Bellini H, Arneberg P, von der F. Oral hygiene and caries. a review. Acta Odontol Scand 1981;39(5):257–265. DOI: 10.3109/00016358109162287
Reich E, Lussi A, Newbrun E. Caries-risk assessment. Int Dent J 1999;49:15–26. DOI: 10.1111/j.1875-595x.1999.tb00503.x
Campus G, Cagetti MG, Sacco G, et al. Caries risk profiles in Sardinian schoolchildren using Cariogram. Acta Odontol Scand 67(3):146–152. DOI: 10.1080/00016350902740498
Beck J. The epidemiology of root surface caries: north american studies. Adv Dent Res 1993;7(1):42–51. DOI: 10.1177/08959374930070010601
Disney J, Graves R, Stamm J, et al. The University of North Carolina caries risk assessment study: further developments in caries risk prediciton. Community Dent Oral Epidemiol 1992;20(2):64–75. DOI: 10.1111/j.1600-0528.1992.tb00679.x