|Year : 2016 | Volume
| Issue : 3 | Page : 244-248
Caries risk assessment among 12–13 year old school-going children of government and private schools of Tirupur district, Tamil Nadu
Madhu M Mitha, JE Nijesh, Preetha Elizabeth Chaly, Indra Priyadharshini, Mohammed Junaid, S Vaishnavi
Department of Public Health Dentistry, Meenakshi Ammal Dental College, Chennai, Tamil Nadu, India
|Date of Web Publication||25-Jul-2016|
Madhu M Mitha
Department of Public Health Dentistry, Meenakshi Ammal Dental College, Alapakkam Main Road, Maduravoyal, Chennai - 600 095, Tamil Nadu
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Dental caries is as ancient as humankind and has the longest association with the dental profession, an association that is punctuated with agony and ecstasy. The agonizing fact is that despite several efforts toward total eradication, this disease is still prevalent. Nevertheless, an ecstatic success of the profession is the global decline in the incidence compared to the yesteryears' epidemics. Hence, predicting dental caries earlier is a boon. One such model to predict is cariogram developed by Bratthall in 1996. Aim: The aim of this study was to assess the caries risk among 12–13 year old school-going children of government and private schools of Tirupur district in Tamil Nadu using cariogram computer model. Methods: A cross-sectional survey was carried out among 136 study subjects of 12–13 year of age, who fulfilled the inclusion and exclusion criteria. Data were collected using a predesigned questionnaire and scored according to a standardized protocol. The Chi-square test was used to find differences between caries-related factors and cariogram group. The correlation was acquired using Spearman's correlation. Results: Government school study subjects had 56% of chance of avoiding caries whereas the private school study subjects had 66% of chance of avoiding caries in future and the differences were statistically significant (P = 0.001). A negative correlation was observed between the chance to avoid dental caries and cariogram sectors. Conclusion: The majority of the study subjects from government school belonged to medium-risk category and private school subjects belonged to low-risk category which inferred that private school students have high chance to avoid dental caries compared to government study subjects.
Keywords: Caries risk assessment, caries risk model, cariogram, Tirupur
|How to cite this article:|
Mitha MM, Nijesh J E, Chaly PE, Priyadharshini I, Junaid M, Vaishnavi S. Caries risk assessment among 12–13 year old school-going children of government and private schools of Tirupur district, Tamil Nadu. J Indian Soc Pedod Prev Dent 2016;34:244-8
|How to cite this URL:|
Mitha MM, Nijesh J E, Chaly PE, Priyadharshini I, Junaid M, Vaishnavi S. Caries risk assessment among 12–13 year old school-going children of government and private schools of Tirupur district, Tamil Nadu. J Indian Soc Pedod Prev Dent [serial online] 2016 [cited 2023 Feb 6];34:244-8. Available from: http://www.jisppd.com/text.asp?2016/34/3/244/186745
| Introduction|| |
Dental caries is an important public health predicament. The unique characteristic of dental diseases is that they are universally prevalent and do not undergo diminution or termination if untreated and require technically demanding expertise and time-consuming professional treatment. The risk factors should be comprehensively studied, tackled, and modified so that the occurrence of dental caries can be prevented.
The multifactorial etiology of dental caries points to a risk assessment model that would include the different factors or parameters that accompany the development of new carious lesions. Cariogram is one such model which assesses and illustrates a caries risk profile for a personage graphically, simultaneously taking into account the interaction of different caries causing factors/parameters of the patient.,
There are two different approaches described for caries risk assessment models: The risk model and the prediction model. The risk model is used to determine the causative caries factors called risk factors, but it cannot predict the caries outcome. The prediction model estimates the risk of caries progression in the future. Cariogram paradigmatic model has both risk and predictor models in it.
Cariogram software can be downloaded from the internet. The outcomes are presented graphically to the patient, indicating the probability of avoiding new carious lesions. Cariogram is anchored in a set of pathological and protective factors, namely, caries experience, systemic diseases, diet contents and frequency, the amount of plaque, mutans streptococci, fluoride sources, saliva secretion, and buffer capacity in addition to the professional clinical judgment. As some other factors are considered more relevant than others regarding caries development, different weights are given to different factors.,
Children have a greater incidence of carious lesions as they reach school age, mostly due to irregular and ineffective oral hygiene habits and of course not to say the least frequent snacking rich in carbohydrate and sugar. It becomes pragmatic to find ways to predict new carious lesions so that we can prevent their progression and occurrence.,
In a country like India, which needs the emphasis on assessing the caries risk and a profound acumen in identifying high-risk individuals who will develop caries. so, that preventive measures can be beleaguered to that group, thereby not only plummeting the encumbrance of the restorative care but also eliminating pain and refining the quality of life. Moreover, preventive measures can then be beleaguered at this group, thereby not only plummeting the encumbrance of the restorative care but also eliminating pain and refining the quality of life., Hence, this study was conducted to assess the caries risk among 12–13 year old school-going children in Tirupur district, Tamil Nadu using cariogram computer model.
| Methods|| |
A cross-sectional survey was carried out among the 12–13 years old school-going children in both private and government schools in Tirupur district, Tamil Nadu. Only children who were 12–13 years of age as per school records and present on the day of the examination were included in the study. Medically compromised subjects, children who were not present on the day of examination and uncooperative subjects were excluded from the study. The nature and purpose of the study were explained to the Institutional Review Board (MADC/IRB/2015/103) and ethical clearance was obtained. The study subjects were then explained about the purpose and study procedure, following which informed consent was obtained from them.
A sample size of 130 was determined based on the comparison of mean values of decayed/missing/filled teeth (DMFT) obtained from the pilot study. All the study subjects from both private and government schools were selected through stratified cluster random sampling and were recruited for this study resulting in a sample size of 136.
The clinical examination and laboratory analysis were carried out by a single examiner. The risk assessment included (1) a questionnaire, (2) estimation of oral hygiene, (3) saliva sampling, (4) clinical examination and (5) creating a risk profile for each child using a cariogram. Interview-based Questionnaire was employed to collect data pertaining to diet, frequency of eating (snacks/meals) per day, related general diseases, the use of fluoride toothpaste, and other fluoride supplements. The examination was conducted outside the classrooms of the study subject, (ADA Specification Type III clinical examination). On an average, examination was conducted for a maximum of ten subjects per day. Caries prevalence and DMFT were recorded using the WHO standard criteria for oral health status and treatment needs (2013). Oral hygiene was estimated using plaque index by SilnessP and Loe H (1967).
Simplified techniques of salivary assessments were used to make them cost effective and applicable for the field study. The study subjects were instructed to place the sterilized rubber band in the mouth and start chewing it for 30 seconds and stimulated saliva was collected. All the saliva samples were labeled with a number before sending them for microbiological processing. To ensure blinding, the number was given by an assistant who was unaware of the purpose of the study. The number given by the assistant ensured that the investigator who inoculates processes and reads the plates was unaware of which sample belongs to the study subjects. Stimulated whole saliva was collected from all children to measure the
- Saliva secretion rate (expressed as ml/min)
- Buffering capacity of saliva
- Lactobacillus and Streptococcus mutans count.
Salivary pH was measured by electronic pH meter. Assessment of diet frequency was obtained by intake frequency questionnaire, the interview method (24 h recall questionnaire).
When all the information was available, they were scored according to the predetermined scale as 0–2 or 3. The scores were entered into the cariogram computer program to calculate the “caries risk” and conversely “chance of avoidance of caries” for each child. The subjects were classified into three caries risk groups according to the percentage shown by the cariogram: 61–100% - low risk, 21–60% - medium risk and 0–20% - high risk.
The data so-obtained were compiled systematically and analyzed using SPSS (Version 16, SPSS Inc., Chicago, USA) software. Descriptive statistics were obtained for all demographic variables. Caries risk profile among the study subjects was obtained using the Chi-square test. The correlation between caries risk and cariogram sectors was obtained using Pearson's correlation and the significance level was set at P < 0.05.
| Results|| |
This study was conducted among 136, 12–13 years old children comprising 69 males and 67 females [Table 1]. Among the study subjects, the dominant sector was bacteria sector in both government and private schools with 18.0725 ± 8.48583 and 13.4776 ± 7.03316, respectively, and the differences noted between the two groups were statistically significant (P = 0.001). The least sector is circumstance having 6.0580 ± 3.01898 in government sector and 4.4776 ± 2.88863 in private sector study subjects and the differences found between the two groups were statistically significant (P = 0.002) [Table 2]. The difference noted between male and female study subjects for average caries risk profile were not found to be statistically significant [Table 3].
|Table 1: Distribution of study subject based on government and private schools|
Click here to view
|Table 2: The average caries risk profile of 12-13-year-old study subjects among government and private schools|
Click here to view
|Table 3: The average caries risk profile of 12-13-year-old study subjects among male and female study subjects|
Click here to view
The government and private school study subjects were divided into groups according to the chance of avoiding caries ranging from high- to low-risk group. Of 69 government school study subjects, 52.1% (n = 36) belonged to medium-risk category, 44.9% (n = 31) belonged to low-risk category, and 2.9% (n = 2) belonged to high-risk category [Table 4].
|Table 4: Caries risk among government and private school children made by cariogram|
Click here to view
Of 67 study subjects among private school, 27.3%(n=19) belonged to medium-risk category, 72.7% (n = 48) belonged to low-risk category, and none of them belonged to high-risk category. The difference noted between these two groups were statistically very highly significant (P = 0.001) [Table 4].
Chance to avoid dental caries was found to have a very highly significant moderate negative correlation with diet, bacteria, susceptibility and circumstance [Table 5].
|Table 5: Correlation between caries risk and cariogram sectors among study subjects belonging to both schools|
Click here to view
| Discussion|| |
The present study was conducted among 12–13 years old school children of government and private schools of Tirupur district to compare and evaluate their caries profile using cariogram model which was introduced by Bratthall et al. in 1997. Schools were profoundly selected for this study because it provided a unique platform for the promotion of oral health and overall health not only for the students but also for the benevolent staff, families, and members of the community as a whole.
The WHO has certain index ages out of which age group belonging to 12 years is chosen. The WHO considers 12-years age as the global indicator age for monitoring dental caries. Children with permanent dentition were selected to avoid discrepancies between mixed and permanent dentition with regard to microbial counts as stated by Schlagenhauf and Rosendahl.
The present study used cariogram, which is considered one of the most reliable models as reported by many authors ,, for predicting caries risk in an individual since it is an amalgamation of objective, quantitative methods that uses a computer program to calculate the data, results that can be printed out and saved. Another imperative advantage is that it makes a series of recommendations for preventive action according to the caries risk. The pie chart presentation with its different sectors makes it interestingly easier for patients to understand caries risk profile which can be effectively used to motivate the patient. When validated among both children and elderly, cariogram predicted caries increment more accurately than any single-factor model.,,,
The chance to avoid caries was finally grouped into three levels: Low chance 0–20% (high caries risk), moderate chance 21–60% (moderate caries risk), and high chance 61–100% (low caries risk) which was similar to the study conducted by Kavvadia et al. among 2–6-year-old Greek children.
In the present study, the majority of the study subjects from government schools belonged to medium risk category and private school subjects belonged to low-risk category which inferred that private school students have high chance to avoid dental caries compared to government study subjects. This is due to the fact that the susceptibility, bacteria, diet, and circumstances sector were dominant in government study subjects when compared with private school study subjects.
Exposure to fluoride is one of the most important protective factors when evaluating caries risk is the cause of the considerable fall in caries levels in western countries. None of the children in this study used fluoride supplements, and the only source of fluoride was fluoridated toothpastes, use of which was confirmed by asking the brand name. The circumstances that lead to an individual caries risk, according to cariogram, emphasize the experience of caries and the presence of diseases that may directly impact on the increase of caries and in the weakness of the individual. In the present study, no interferences were observed. All children were found healthy, without any systemic changes. This is in accordance with the study conducted by Hebbal et al. among 12-year-old children in an Indian city.
Significant negative correlation was obtained between the sectors and chance to avoid dental caries. This result was found to be contrast with the study conducted by Hebbal et al. among 12-year-old children in an Indian city  because correlation was obtained between the different variables and the risk obtained for each sector.
Petersson et al.,,, expressed the results of their studies with the cariogram as a chance to avoid caries which is similar to this study. For statistical analysis purposes, the results of the present study are expressed as caries risk, which the authors consider a more comprehensible and useful value; obtained by adding up the partial caries risks of susceptibility, circumstances, bacteria, and diet, it allows correlations to be established and gives greater scope for analysis.
Three variables of cariogram were not used in this trial, such as country/area, and groups were scored as a standard set and clinical judgment was scored as 1, similar to the previous studies on the efficacy of cariogram., Using these options may increase the efficacy of this program. Comparison of all results with other studies was not possible, as the disparity between the results exists.
Thus, cariogram program is effective and has some advantages such as making recommendations for preventive care and increasing patient motivation. The cariogram model has been evaluated in scientific studies both children and adult population. It is a useful pedagogic tool for dentists, dental hygienists, and assistants in discussion with patients about their caries risk. The cariogram complements the current trends toward computerized record keeping and management.
| Conclusion|| |
The accuracy of caries prediction in school children was significantly impaired when cariogram model was applied. However, the results of the study will serve as the baseline data, which will be used to plan a preventive program for the school children in Tirupur district.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Kemparaj U, Chavan S, Shetty NL. Caries risk assessment among school children in Davangere city using cariogram. Int J Prev Med 2014;5:664-71.
Hänsel Petersson G, Twetman S, Bratthall D. Evaluation of a computer program for caries risk assessment in schoolchildren. Caries Res 2002;36:327-40.
Hebbal M, Ankola A, Metgud S. Caries risk profile of 12 year old school children in an Indian city using cariogram. Med Oral Patol Oral Cir Bucal 2012;17:e1054-61.
Anup N, Vishnani P. Cariogram – A multi-factorial risk assessment software for risk prediction of dental caries. Int J Sci Study 2014;1:58-62.
Cabral RN, Hilgert LA, Faber J, Leal SC. Caries risk assessment in schoolchildren – A form based on Cariogram software. J Appl Oral Sci 2014;22:397-402.
World Health Organization, editor. Design of a basic oral health survey. In: Oral Health Surveys Basic Methods. 5th
ed. Geneva: AITBS Publishers and Distributors; 2013. p. 18-21.
Peter S, editor. Dental caries. In: Essentials of Public Health Dentistry. 5th
ed. New Delhi: Arya Medi Publishing House Pvt. Ltd.; 2015. p. 275-8.
Bratthall D, Petersson GH, Stjernsward JR. Cariogram manual, a new and interactive way of illustrating the interaction of factors contributing to the development of dental caries. Cariogram, Internet Version 2.01; 2004.
Schlagenhauf U, Rosendahl R. Clinical and microbiological caries-risk parameters at different stages of dental development. J Pedod 1990;14:141-3.
Petersson GH, Twetman S. Caries risk assessment in young adults: A 3 year validation of the Cariogram model. BMC Oral Health 2015;15:17.
Tayanin GL, Petersson GH, Bratthall D. Caries risk profiles of 12-13-year-old children in Laos and Sweden. Oral Health Prev Dent 2005;3:15-23.
Zukanovic A, Kobaslija S, Ganibegovic M. Caries risk assessment in Bosnian children using Cariogram computer model. Int Dent J 2007;57:177-83.
Petsi G, Gizani S, Twetman S, Kavvadia K. Cariogram caries risk profiles in adolescent orthodontic patients with and without some salivary variables. Angle Orthod 2014;84:891-5.
Daryani H, Nagarajappa R, Sharda AJ, Asawa K, Tak M, Sanadhya S, et al
. Cariogram model in assessment of dental caries among mentally challenged and visually impaired individuals of Udaipur, India. J Clin Diagn Res 2014;8:206-10.
Kavvadia K, Agouropoulos A, Gizani S, Papagiannouli L, Twetman S. Caries risk profiles in 2- to 6-year-old Greek children using the Cariogram. Eur J Dent 2012;6:415-21.
Al Mulla AH, Kharsa SA, Kjellberg H, Birkhed D. Caries risk profiles in orthodontic patients at follow-up using Cariogram. Angle Orthod 2009;79:323-30.
Petersson GH, Carlsson P, Bratthall D. Caries risk assessment: A comparison between the computer program “Cariogram,” dental students and dental instructors. Eur J Dent Educ 1998;2:184-90.
Celik EU, Gokay N, Ates M. Efficiency of caries risk assessment in young adults using Cariogram. Eur J Dent 2012;6:270-9.
Renuka P, Pushpanjali K. Cariogram as an educational tool for reducing the caries risk among the differently abled children-case series. J Dent Med Sci2015;14:60-7.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]