|Year : 2016 | Volume
| Issue : 3 | Page : 266-271
Caries risk assessment among subjects with periodontal disease using cariogram study model
S Hari Krishnam Raju1, Nusrath Fareed2, KM Sudhir3, RV.S Krishna Kumar3
1 Department of Public Health Dentistry, GSL Dental College and Hospital, Rajahmundry, Andhra Pradesh, India
2 Department of Public Health Dentistry, KVG Dental College and Hospital, Sullia, Karnataka, India
3 Department of Public Health Dentistry, Narayana Dental College and Hospital, Nellore, Andhra Pradesh, India
|Date of Web Publication||6-Sep-2016|
S Hari Krishnam Raju
Department of Public Health Dentistry, GSL Dental College and Hospital , Rajahmundry - 533 296, Andhra Pradesh
Source of Support: None, Conflict of Interest: None
Introduction: Root caries (RC) is considered a serious problem affecting the long-term prognosis of both treated and untreated periodontally involved teeth and has become a major public health problem among adults. Aim: The aim of this study is to assess RC risk among subjects with periodontal disease using the cariogram study model. Materials and Methods: A descriptive cross-sectional study was conducted among 220 participants aged ≥35 years who were categorized as cases and controls based on inclusion criteria. Data were collected using the specially designed pro forma. The clinical oral examination was carried out for recording plaque scores (Silness and Loe), periodontal status, and dental caries experience (World Health Organization 1997). The salivary profile was generated by recording stimulated salivary flow rate, buffering capacity, and microbiological status and risk assessment done using the cariogram study model. Results: Cariogram model revealed 39% and 51% chance of avoiding caries for cases and controls, respectively. Mean coronal caries experience among cases and controls was 14.38± 5.52 and 10.88±5.70, and for root caries was 0.87±1.04 and 0.38±9.85 respectively. Subjects categorized as high risk, according to cariogram had higher mean decayed, missed, filled tooth (DMFT) (16.79 ± 4.58) and root decayed, filled tooth (1.47 ± 1.27) than other risk groups. Active periodontal disease and past caries experience were significantly associated with RC through logistic regression analysis. Conclusion: Cariogram can be a useful tool to illustrate caries risk profiles among periodontal disease patients. Along with baseline RC experience, active periodontal disease, plaque, lactobacilli, and mutans streptococci were identified as major risk factors associated with RC.
Keywords: Cariogram, periodontal disease, risk assessment, root caries
|How to cite this article:|
Raju S H, Fareed N, Sudhir K M, Krishna Kumar R. Caries risk assessment among subjects with periodontal disease using cariogram study model. J Indian Assoc Public Health Dent 2016;14:266-71
|How to cite this URL:|
Raju S H, Fareed N, Sudhir K M, Krishna Kumar R. Caries risk assessment among subjects with periodontal disease using cariogram study model. J Indian Assoc Public Health Dent [serial online] 2016 [cited 2020 Dec 4];14:266-71. Available from: https://www.jiaphd.org/text.asp?2016/14/3/266/189838
| Introduction|| |
Oral health is a critical but overlooked component of overall health and well-being among adults. Longer life expectancy and decreased edentulism have resulted in an ever-increasing number of adult patients retaining their natural dentition in advanced age and being in need of special dental service. Studies relating causal factors of tooth extraction have shown that caries is an important reason for the loss of tooth even in older age group. Because of increased life expectancy and greater retention of natural teeth compared with previous generations, root caries (RC) is becoming an important health problem among the dentate elderly.
RC is now being considered as a major public health problem for middle-aged and elderly. The increased prevalence is associated with people keeping their teeth longer and with root surfaces becoming physiologically (aging) or pathologically (periodontal disease) exposed into oral cavity and therefore encountering risk. The prevalence of dental caries, the severity of periodontal disease, and the rate of edentulousness have all come down to an extent that early identification of at risk subpopulation could become an important facet of dental practice in both the private and public health context.
A systematic review of the available literature reported RC prevalence at baseline, i.e., the past RC experience, the number of teeth and dental plaque as risk indicators for RC. The relationship between periodontal disease and RC, in particular, has been the focus of many research groups. Furthermore, gingival recession changes the oral conditions, which may cause ecological changes, resulting in microbiological changes and attachment of cariogenic bacteria to the supragingival plaque.,
During the past decade, risk assessment and its application to oral diseases has marched to the forepart of the dental health-care policy arena. Much of the recent oral-health-oriented risk assessment research has focused on dental caries. The skewed distribution of caries within the population today calls for risk assessment, and the challenge is to identify and estimate the probability of a patient of developing new caries lesions or progression of existing lesions during a specified period. Many different risk models for caries prediction are available, using different methods for measuring the signs of disease. The risk for a future caries development has been examined using a number of pedagogic models, one of which was a caries risk assessment computer program Cariogram (Malmo University, Malmo, Sweden).
A variety of risk indicators have been associated with RC in cross-sectional and longitudinal studies,,,, but the heterogeneous results of these many studies are difficult to interpret and apply concisely in clinical situations. Research in the field of RC prediction among subjects with periodontal disease by risk modeling is inconclusive and inconsistent. Considering the magnitude of the problem and the paucity of human research regarding RC among periodontal disease subjects, this study was undertaken to assess RC risk among subjects with periodontal disease.
| Materials and Methods|| |
A cross-sectional descriptive epidemiological study was designed and conducted to assess RC risk among subjects with periodontal disease using cariogram study model. The ethical clearance was obtained from the Institutional Review Board of the Narayana Dental College and Hospital.
Data collection was carried out at the Department of Periodontology in Narayana Dental College and Hospital during January 2013–May 2013.
A pilot study was conducted before the main study to standardize the pro forma and methodology planned. The sample size was estimated based on the findings of a pilot study. The estimated sample size was 110 in each group at an accepted minimum possible error of 0.05% with 90% power of two-sided tests.
A total of 480 patients were approached for the study, 300 patients gave informed consent to participate in the study, and 110 subjects who convinced their biological-related individuals to enroll as controls were included in the study.
Subjects aged ≥35 years with active periodontal disease (community periodontal index [CPI] score >2 and loss of attachment [LOA]).
Subjects of similar age who were biological relative of cases with no active periodontal disease (CPI <2 and LOA).
Exclusion criteria for both cases and controls
Subjects who have undergone any therapy for the periodontal disease in the past 18 months. Subjects under medications that effect salivary parameters. Subjects with a history suggestive of systemic diseases and smoking and subjects with the lack of functional dentition (<20 teeth).
The investigator was trained and calibrated for data recording in the Department of Public Health Dentistry, before conducting the study. Intraexaminer kappa statistic scores were calculated pertaining to plaque index, CPI-LOA, and decayed, missed, filled tooth (DMFT) index and were 0.87, 0.85, and 0.84, respectively.
Data were collected using a specially designed pro forma consisting of three parts. The first part recorded sociodemographic details, past medical history, diet history, and the propensity of usage of fluoridated toothpaste and mouth rinses. The second part, clinical oral examination was done for recording plaque scores, periodontal status and dental caries experience (World Health Organization 1997). Finally, the salivary profile was created by recording stimulated salivary flow rate, buffering capacity, and microbiological status. The participants were individually interviewed to record the pro forma followed by a Type III clinical examination according to the ADA  and stimulated saliva was collected from each participant to create their salivary profile. An asepsis protocol was developed, and strict procedures were followed for infection control. The required instruments were autoclaved daily during the study.
Assessment of salivary parameters
Stimulated whole saliva was collected under resting conditions and at the same time to minimize effects of the diurnal variability in salivary composition. The saliva samples were obtained 2 h after breakfast, between 9 a.m and 12 noon. Two hours before the evaluation of stimulated whole saliva production, subjects were instructed not to eat, drink, or rinse their mouths until the test was completed. Thereafter, whole stimulated saliva was collected for about 5 min into a dry, millimetric, and sterilized plastic tube. The flow rate of saliva was estimated by asking participants to spit into the preweighed plastic cylinders for 5 min. These plastic cylinders (containing saliva) were then weighed, and the flow rate was calculated in g/ml which is almost equivalent to ml/min. The saliva collected was divided into two separate mill metric tubes to calculate the buffer capacity of the saliva by Ericsson method (1959) and to determine mutans streptococci and lactobacilli levels. The sample was taken immediately to the Central Laboratory of Narayana Medical College and Hospital for microbiological analysis.
The samples were processed on the same day by trained personnel in the central laboratory. Mitis Salivarius Agar supplemented with potassium tellurite, and Rogosa SL was used as culture media for isolation of total salivary streptococci and lactobacilli, respectively, and incubated anaerobically using anaerobic gas pack system (Hi-media) at 37°C for 48 and 72 h, respectively. Colony counting was done manually and represented as the number of the colonies which were multiplied by the number of times the original ml of the sample was diluted (the dilution factor of the plate counted) and expressed as the number of colony forming units per milliliter of saliva.
Creation of cariogram model
Relevant information regarding the subjects was collected, scored according to a standardized protocol mentioned in the manual, and then entered into the computerized software program, Cariogram 3.0 version (Malmo University, Sweden) to calculate the caries risk and conversely chance of avoidance of caries in the future for each individual.
Data were computerized into SPSS 20, IBM, Armonk, NY, United States of America software. Chi-square test and t-test were used to compare study parameters, the periodontal status, and caries-related factors between two groups. Logistic regression analysis was performed to identify the impact of various independent cariogram-related risk factors on RC. Statistical significance was set at P < 0.05.
| Results|| |
A total of 480 participants were examined, of which 220 participants are included in the study as 110 each in case and control groups. There was no statistically significant difference in gender distribution and sociodemographic characteristics among cases and controls.
[Table 1] shows the distribution of subjects in relation to their periodontal condition, 32.73% of subjects from cases had an LOA of 6–8 mm, followed by 49.09% with LOA of 4–5 mm. In contrast, only 5.45% of subjects from controls had an LOA of 6–8 mm and majority of them, 54.55% were in the range of 0–3 mm.
|Table 1: Distribution of study subjects in relation to their periodontal condition|
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[Table 2] shows the distribution of cases and controls into different cariogram risk groups expressed as a percentage chance of avoiding caries according to cariogram. The majority of the subjects in cases (36.36%) were categorized as high risk, followed by 30.91% subjects at high medium risk for developing future caries. In contrast, only 12.73% of subjects in the control group were categorized as high risk, followed by 27.27% in high medium for developing future caries. Cariogram model revealed 39% and 51% chance of avoiding caries for cases and controls, respectively, and the difference between the two groups was found to be statistically significant [Figure 1]. When the caries risk profile was plotted among two groups with and without RC. Subjects with RC showed a 17% compared to 48% chance of avoiding caries among subjects without RC.
|Table 2: Distribution of cases and controls into cariogram risk groups expressed as percent chance of avoiding caries according to cariogram model|
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|Figure 1: Caries risk profiles of cases and controls as obtained through cariogram model|
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[Table 3] depicts the prevalence of coronal and RC among studied subjects in different cariogram risk groups. Subjects categorized as high risk according to cariogram had higher mean DMFT and root decayed, filled tooth (RDFT) than other risk groups among cases (DMFT 16.79 ± 4.58, RDFT 1.47 ± 1.27) and controls (DMFT 12.34 ± 5.45, RDFT 1.64 ± 0.89). The difference between two groups was found to be statistically significant.
|Table 3: Comparison of coronal and root caries experience among cases and controls|
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Logistic regression analysis was performed to identify the impact of various independent cariogram-related variables and periodontal status on RC prevalence. Subjects with past caries experience (DMFT) had highest odds 2.94 times chance of developing RC followed by a high Lactobacillus count (1.65), the amount of plaque (1.43), Streptococcus mutans count (1.39), and low-buffering capacity (1.25). Subjects with active periodontal disease and LOA had 1.28 and 1.02 times odds of developing RC. Active periodontal disease and past caries experience were significantly associated with RC [Table 4].
|Table 4: Logistic regression analysis of impact different cariogram related variables and periodontal status on root caries prevalence|
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| Discussion|| |
Despite the evidence linking periodontal disease to RC development is well established, it seems that the implications of the interrelationship between these two clinical entities have not been routinely seen in the course of RC investigations. It is considered a serious problem affecting the long-term prognosis of both treated and untreated periodontally involved teeth by Krasse and Fure. Hence, this study was planned to assess RC and its risk factors among subjects with periodontal disease using cariogram study model.
The cariogram is regarded as a useful tool for assessing and predicting caries risk and has been validated for predicting future coronal and RC among elderly individuals. In this study, cariogram-multifactorial caries risk assessment model has been used to predict RC risk among individuals with or without active periodontal disease in an attempt to identify the risk factors associated with RC. Remarkably, we used both coronal and RC experience as one of the predictors for future RC. Since both coronal and RC have common risk factors with root exposure being the only additional requirement for the development of RC.
Subjects who were categorized as a high-risk group according to cariogram had higher mean DMFT and RDFT compared to other groups in subjects with active periodontal disease. The high caries experience, i.e. DMFT and RDFT can be considered as a risk factor for development of future caries in this study, which was found similar to studies reported by Zero et al., Fontana and Zero, where DMFT was considered as a strong predictor for future caries. This study findings were also similar to studies conducted by Powell et al., Vehkalahti, Fure and Zickert, establishing baseline coronal caries as the best predictor for RC incidence.
The prevalence of RC among cases and controls was 50.9% with a mean of 0.87 ± 1.04 and 21.8% with a mean of 0.38 ± 0.85, respectively. The prevalence was higher than the findings of a study conducted by Fadel et al. in Saudi Arabia and lower than reports of studies conducted by Ravald and Hamp  and Ravald and Birkhed, which ranged from 58% to 87%. This low prevalence in this study may be due to the initial exclusions of patients with fewer than 20 teeth from the current investigation who may also have exhibited root lesions in their remaining teeth.
The caries risk profile was plotted among cases with or without RC. Subjects with RC showed a 17% compared to 48% chance of avoiding caries among subjects without RC. Subjects with RC were at higher risk of developing future caries compared to subjects without RC among cases and controls. Red (plaque and mutans streptococci) followed by dark blue (diet) sectors occupied larger area difference under cariogram with and without RC indicating the amount of plaque, mutans streptococci, and Lactobacillus counts as the major risk factors for RC. This study findings were in accordance with studies reported by Saotome et al.
Logistic regression analysis to assess the impact different cariogram-related variables and periodontal status on RC prevalence revealed subjects with past caries experience had highest odds 2.94 followed by a high Lactobacillus count (1.65), plaque amount (1.43), and active periodontal disease (1.21). The odds of past caries experience in this study was significantly associated with RC prevalence and was in accordance with the study conducted by Joshi et al. and Scheinin et al.
| Conclusion|| |
Our results suggest that high-risk patients for RC can be identified by estimating past caries experience and active periodontal disease. Cariogram can be a useful tool to illustrate caries risk profiles among periodontal disease patients. The study was hospital-based study which may not represent the general population. Longitudinal studies should be conducted to endorse the risk of periodontal disease severity on RC incidence.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Petersen PE. The World Oral Health Report 2003: Continuous improvement of oral health in the 21st
century – The approach of the WHO Global Oral Health Programme. Community Dent Oral Epidemiol 2003;31 Suppl 1:3-23.
Preston AJ. Dental management of the elderly patient. Dent Update 2012;39:141-3.
Fure S, Zickert I. Incidence of tooth loss and dental caries in 60-, 70- and 80-year-old Swedish individuals. Community Dent Oral Epidemiol 1997;25:137-42.
Ritter AV, Shugars DA, Bader JD. Root caries risk indicators: A systematic review of risk models. Community Dent Oral Epidemiol 2010;38:383-97.
Quirynen M, Gizani S, Mongardini C, Declerck D, Vinckier F, Van Steenberghe D. The effect of periodontal therapy on the number of cariogenic bacteria in different intra-oral niches. J Clin Periodontol 1999;26:322-7.
Reiker J, van der Velden U, Barendregt DS, Loos BG. A cross-sectional study into the prevalence of root caries in periodontal maintenance patients. J Clin Periodontol 1999;26:26-32.
Petersson GH, Ericson E, Isberg PE, Twetman S. Caries risk assessment in young adults using public dental service guidelines and the Cariogram – A comparative study. Acta Odontol Scand 2013;71:534-40.
Bratthall D, Hänsel Petersson G. Cariogram – A multifactorial risk assessment model for a multifactorial disease. Community Dent Oral Epidemiol 2005;33:256-64.
Drake CW, Beck JD. Models for coronal caries and root fragments in an elderly population. Caries Res 1992;26:402-7.
Lundgren M, Emilson CG, Osterberg T. Root caries and some related factors in 88-year-old carriers and non-carriers of Streptococcus sobrinus in saliva. Caries Res 1998;32:93-9.
Luan W, Baelum V, Fejerskov O, Chen X. Ten-year incidence of dental caries in adult and elderly Chinese. Caries Res 2000;34:205-13.
Takano N, Ando Y, Yoshihara A, Miyazaki H. Factors associated with root caries incidence in an elderly population. Community Dent Health 2003;20:217-22.
Silness J, Loe H. Periodontal disease in pregnancy. II. Correlation between oral hygiene and periodontal condtion. Acta Odontol Scand 1964;22:121-35.
World Health Organization. Oral Health Surveys, Basic Methods. 4th
ed. Geneva: World Health Organization; 1997.
Dawes C. Physiological factors affecting salivary flow rate, oral sugar clearance, and the sensation of dry mouth in man. J Dent Res 1987;66:648-53.
Edgar WM. Saliva: Its secretion, composition and functions. Br Dent J 1992;172:305-12.
Sanchez-Garcia S, Gutierrez-Venegas G, Juarez-Cedillo T, Reyes-Morales H, Solorzano-Santos F, Garcia-Pena C. A simplified caries risk test in stimulated saliva from elderly patients. Gerodontology 2008;25:26-33.
Krasse B, Fure S. Root surface caries: A problem for periodontally compromised patients. Periodontol 2000 1994;4:139-47.
Hänsel Petersson G, Fure S, Bratthall D. Evaluation of a computer-based caries risk assessment program in an elderly group of individuals. Acta Odontol Scand 2003;61:164-71.
Vehkalahti MM. Relationship between root caries and coronal decay. J Dent Res 1987;66:1608-10.
Zero D, Fontana M, Lennon AM. Clinical applications and outcomes of using indicators of risk in caries management. J Dent Educ 2001;65:1126-32.
Fontana M, Zero DT. Assessing patients' caries risk. J Am Dent Assoc 2006;137:1231-9.
Powell LV, Leroux BG, Persson RE, Kiyak HA. Factors associated with caries incidence in an elderly population. Community Dent Oral Epidemiol 1998;26:170-6.
Fadel H, Al Hamdan K, Rhbeini Y, Heijl L, Birkhed D. Root caries and risk profiles using the Cariogram in different periodontal disease severity groups. Acta Odontol Scand 2011;69:118-24.
Ravald N, Hamp SE. Prediction of root surface caries in patients treated for advanced periodontal disease. J Clin Periodontol 1981;8:400-14.
Ravald N, Birkhed D. Prediction of root caries in periodontally treated patients maintained with different fluoride programmes. Caries Res 1992;26:450-8.
Saotome Y, Tada A, Hanada N, Yoshihara A, Uematsu H, Miyazaki H, et al.
Relationship of cariogenic bacteria levels with periodontal status and root surface caries in elderly Japanese. Gerodontology 2006;23:219-25.
Joshi A, Papas AS, Giunta J. Root caries incidence and associated risk factors in middle-aged and older adults. Gerodontology 1993;10:83-9.
Scheinin A, Pienihäkkinen K, Tiekso J, Holmberg S, Fukuda M, Suzuki A. Multifactorial modeling for root caries prediction: 3-year follow-up results. Community Dent Oral Epidemiol 1994;22:126-9.
[Table 1], [Table 2], [Table 3], [Table 4]