|Year : 2021 | Volume
| Issue : 6 | Page : 1155-1161
Caries risk assessment among school going young adolescents in Sullia Taluk-Dakshina Kannada
P Jagan1, Radhakrishnan Karthikeyan2, Rajendran Bharathan2, NC Srihari2, Arumugasamy Niranjana2, Minu Suresh3
1 Department of Public Health Dentistry, Sri Ramakrishna Dental College and Hospital, Coimbatore, Tamil Nadu, India
2 Department of Peadodontics and Preventive Dentistry, Sri Ramakrishna Dental College and Hospital, Coimbatore, Tamil Nadu, India
3 Department of Peadodontics and Preventive Dentistry, Coorg Institute of Dental Sciences, Virajpet, Karnataka, India
|Date of Submission||31-Mar-2021|
|Date of Decision||10-Apr-2021|
|Date of Acceptance||18-Apr-2021|
|Date of Web Publication||10-Nov-2021|
Departments of Public Health Dentistry, Sri Ramakrishna Dental College and Hospital, Coimbatore, Tamil Nadu
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Dental caries continue to be one among the major problems related to oral health in developing countries, that affects 60%–90% of school-aged children and adults. According to the WHO Global oral data bank in 2009 the point prevalence was 54% among 12 years old. Studies on prevalence conducted in Dakshina Kannada district reported a caries prevalence ranging from 32.8% to 82.6%. This study was undertaken to assess the risk of among school-going young adolescents using the Cariogram model. Subject and Methods: A cross-sectional descriptive epidemiological study was conducted among school-going young adolescents of Sullia taluk Dakshina Kannada for a period of 3 months (August–October) 2019. From a total of 20 schools, 3 schools were randomly selected and children satisfying inclusion/exclusion criteria were randomly drawn from these schools. Data on parameters of Cariogram model were collected on a specially designed pro forma consisting of four parts, namely Questionnaire, along with a clinical examination, the collection of saliva and microbiological analysis. Descriptive data were recorded and Fischer's Exact test was used to test the significance of the findings. P ≤ 0.05. Results: An analysis of the relative contribution of each cariogram parameter in relation to the caries experience revealed that diet content, frequency of diet, mutans count were statistically significant factors in determining caries risk (P < 0.05). Conclusion: In conclusion, the present study performed with cariogram in young adolescent school-going children revealed that diet content, frequency of diet, mutans count were statistically significant factors in determining caries risk and susceptibility factors were mainly responsible for the aforementioned experience of the school children.
Keywords: Caries risk assessment, cariogram, dental caries
|How to cite this article:|
Jagan P, Karthikeyan R, Bharathan R, Srihari N C, Niranjana A, Suresh M. Caries risk assessment among school going young adolescents in Sullia Taluk-Dakshina Kannada. J Pharm Bioall Sci 2021;13, Suppl S2:1155-61
|How to cite this URL:|
Jagan P, Karthikeyan R, Bharathan R, Srihari N C, Niranjana A, Suresh M. Caries risk assessment among school going young adolescents in Sullia Taluk-Dakshina Kannada. J Pharm Bioall Sci [serial online] 2021 [cited 2022 Aug 10];13, Suppl S2:1155-61. Available from: https://www.jpbsonline.org/text.asp?2021/13/6/1155/330080
| Introduction|| |
Dental caries is a multifactorial disease caused by interactions between acidogenic bacteria, biofilm, and individual caries risk factors such as saliva composition, fluoride exposure, and dietary components.
Looking at a global context, the prevalence of dental caries is still high; especially in children. Comprehensive National Health Survey conducted in 2004 encompassing India has shown a dental caries prevalence of 53.8% in 12-year-old children. The prevention of dental caries has considered an essential task for health professionals for a long time, but preventive programs are not a focal point of services provided at government health centers. In most of developing countries, dental care does not reach the entire population due to high costs. Because caries distribution in the population is remarkably uneven, an accurate assessment of caries risk would permit improved use of limited resources. Adding to this, the key factor for planning any preventive program is to assess with accuracy, a person's risk of developing a disease.
Scientists are carrying through their research in identifying the best practices for diagnosis, treatment, and prevention of dental caries. Caries risk assessment (CRA) is a cardinal element in the comprehensive management of dental disease and as a result, has gained an immense deal of attention in recent literature. Since dental caries has an etiology which is multifactorial, the procedure necessitates that information on demographic, social, behavior, and biological factors is taken together and caries risk profile or risk category is formed. Cariogram is the sole model which can evaluate various factors, suchlike host response, pathogens, and cariogenicity of the diet involved in the development of caries and consequently, can give an individual explanation of caries risk.
The term “Cariogram” was primarily used by Douglas Bratthall in 1996 at the Dental School in Malmo University (Malmo Sweden) to exhibit the interaction of various caries etiological factors through the means of illustrated graphs. Cariogram is a computer-based program which was developed in recent times to practically carry out caries-risk assessment. It considers the interaction of ten different caries risk factors, assesses the risk for the development of new carious lesions within the next 12 months and presents the caries risk profile of an individual graphically. It further assesses data and illustrates the results in a pie chart with five sectors, which are colored green, dark blue, light blue, and yellow, each representing different groups of factors linked to caries. Therefore, it is useful in assessing the risk of dental caries, identifying high-risk individuals and prescribing appropriate preventive programs based on the risk. Dental caries continue to be one of the major oral health problems in developing countries, it affects 60%–90% of school-aged children and adults. According to the WHO Global oral data bank in 2009 the point prevalence was 54% among 12 years old. Studies on prevalence conducted in Dakshina Kannada district reported a caries prevalence ranging from 32.8% to 82.6%. With this background, this study was carried out to assess the caries risk among school-going young adolescents in Sullia taluk, Dakshina Kannada using the Cariogram model.
| Subject and Methods|| |
A cross-sectional descriptive epidemiological study was conducted among school-going young adolescents of Sullia taluk Dakshina Kannada, South India for a period of 3 months (August–October) 2019. Ethical clearance was obtained by the institutional review board (SS/15/14KVGMC) and from the concerned authorities, permission to conduct the study was obtained. Informed consent for the participation of children was obtained by the parents through the headmasters/headmistresses. Based on the previous study, the estimated sample was 65, an additional 10% was added to compensate for sampling loss if any. Thus, the final sample accounted for 70 subjects. A sample proportionate to size was drawn from three randomly selected schools. Stratified cluster sampling methodology was employed for sample selection.
Children aged 13–14 years with informed consent and willing to participate in the study.
Children with special needs/dentofacial abnormalities/under medication that could affect parameters considered in the study.
A list of schools was obtained by Block Education Office, Sullia town and all schools were invited to participate in the study. From a total of 20 schools, 3 schools were randomly selected and children satisfying inclusion/exclusion criteria were randomly drawn from these schools.
Data on parameters of Cariogram model was collected on a specially designed proforma consisting of four parts, namely questionnaire, clinical examination, collection of saliva, and microbiological analysis. All the examinations were carried out by a single trained examiner chief investigator. The oral examinations took place in the school under good illumination. First demographic data, related diseases, fluoride exposure were recorded by the investigator followed by the recording of visible plaque using Silness and Loe plaque index. Then, the tooth surfaces were cleaned after which dental caries were recorded. Children were trained in the maintenance of diet diary and dietary information was collected from a 7 day diet diary which was maintained by the children. Clinical judgment was based on examiners own clinical and personal score for the individual patient. A score of 1 for clinical judgment was given irrespective of the status. Caries experience was assessed by decayed, missing and filled teeth of the patients. Investigator had been calibrated for clinical parameters in department of public health dentistry.
Salivary samples were collected by the investigator himself at the school premises between 10:00 and 10:30 a.m. to maintain circadian rhythm. Children were refrained to eat or drink 1 h before the collection of samples Whole unstimulated saliva was collected with the participant sitting quietly for 15 min, then allowing saliva to drain between the open lips directly into a collecting jar near the mouth, 2 ml of unstimulated saliva was collected in a sterile calibrated plastic cup; using sterile disposable syringe 0.5 ml aliquot of saliva was transferred from the cup to the previously labeled and coded vials containing 1 ml of RTF media and transported to Department of Molecular Biology and Immunology within 48 h.
Statistical analysis was performed by means of IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY, USA: IBM Corp. Descriptive data was recorded; Fischer's exact test was conducted to test the significance of the findings. P value was set ≤ 0.05.
| Results|| |
Analysis of gender distribution revealed approximately equal number of school children in both the genders. Severity of dental caries revealed 25 (33%) had very low scores and 20 (26%) had high scores as shown [Table 1].
|Table 1: Distribution of sociodemographic and caries experience among school children|
Click here to view
Assessment of school children based on parameters used in cariogram model showed that the majority of school children (98.6%) had no related disease associated. Majority (38%) of school children had caries experience higher than the age group. Analysis of diet revealed school children had moderate amount of sugar intake with a diet frequency of 4–5 times a day. A moderate amount of plaque (53.3%) and mutans count of 104–105 (31%) was observed in the majority of studied school children. All the studied children reported to be using fluoridated dentifrice to clean their teeth as shown in [Table 2].
Further analysis of the relative contribution of each cariogram parameter in relation to the caries experience revealed that diet content, frequency of diet, mutans count were statistically significant factors in determining caries risk (P < 0.05) as shown in [Table 3].
|Table 3: Association between Cariogram patterns and the severity of caries experience among school children|
Click here to view
A detailed analysis of school children in all the caries experience groups identified susceptibility factors to dental caries is the most important factor among all the parameters given in the cariogram. In the very low, low, and moderate caries experience group bacteria and diet were equally contributory, where as in the high caries experience group bacteria was the most contributing factor. As shown in [Figure 1], [Figure 2], [Figure 3], [Figure 4].
|Figure 1: Cariogram of the school children belonging to very low caries experience group (decayed, missing and filled teeth score less than 1.2)|
Click here to view
|Figure 2: Cariogram of the school children belonging to low caries experience group (decayed, missing and filled teeth score 1.2 to 2.6)|
Click here to view
|Figure 3: Cariogram of the school children belonging to moderate caries experience group (decayed, missing and filled teeth score 2.7 to 4.4)|
Click here to view
|Figure 4: Cariogram of the school children belonging to high caries experience group (decayed, missing and filled teeth > 4.4)|
Click here to view
Assessment of caries risk profile using cariogram model was analyzed for each participant according to the predetermined scales for each factor. High risk was entered under country, as India is a developing country where children are prone to caries. These scores were then entered into the cariogram computer program to obtain the individual caries risk profile. The chance of avoiding caries was obtained from the pie diagram. The chance of avoiding caries for very low, low, moderate, and high groups were 61%, 32%, 33%, 19% as shown in [Figure 1], [Figure 3] and [Figure 5].
| Discussion|| |
A study done by Simon AK et al. in 2014 concluded that the availability of dentists decreased dental services alarmingly low which makes CRA an important tool to establish dental caries risk. CRA is the clinical process of establishing the probability for an individual patient to develop caries lesions in the near future and thereby an essential component in the decision-making process for adequate prevention and management of dental caries.
Cariogram considers the interaction between various caries risk factors and assesses the risk of development of the new carious lesion. The data were collected and entered into the Cariogram software. As soon as information is entered, the program automatically generates a pie chart, which shows a green area of the chart indicating the actual chance to avoid new cavities, that is expressed as a percentage of the pie chart.
Although the Cariogram software includes defined parameters to use in filling the instrument, in the present study we have excluded two parameters, i.e. saliva secretion and saliva buffer.
In the present study, the school children were segregated into four groups based on the caries severity as recommended by WHO for 12-year-old and the association between cariogram patterns and the severity of caries experience among schoolchildren were analyzed. The subjects with the highest chance of caries avoidance were seen in very low caries experience group and the least chance of avoiding caries was seen in the high caries risk group which was similar to the findings of the study conducted by Petersson et al., and Tayanin et al.,
Higher chances of avoiding caries were concurrent with low caries experience and similarly, lower chances of avoiding caries were seen in high caries experience group in accordance to studies conducted by Sakeenabi and Hiremath and Ali et al.,
In the present study, diet content and diet frequency were the major contributing factors among high caries experience group when compared with that of very, low, and moderate caries experience group which is similar to the finding s of studies conducted by Kowalczyk DO, Sudha P et al. and Al-Darwish et al.,,
The findings of the present study that reported the use of fluoridated dentifrice and its inverse relationship with caries experience are similar to findings of Mafuvadze et al. and Krasse.,
The measures for very low caries experience group as given by cariogram were reduction in intake of fermentable carbohydrates and to reduce the amount of plaque by improving oral hygiene measures whereas for High caries experience group recommended measures were reduction in intake of fermentable carbohydrates, improving oral hygiene and repeated professional cleaning and chlorhexidine gel treatment for reduction of mutans streptococci.
The present study has excluded two parameters i.e. saliva secretion and saliva buffer. This may have reduced the predictive capability of the cariogram in the school children which could be the limitation of the present study. Data regarding the related diseases and fluoride exposure as reported by the school children have an element of inherent response error.
| Conclusion|| |
In general, cariogram provides caries risk in a graphic form, which is expressed as the chance to avoid new caries in the near future. It exemplifies to what extent different factors affect the chance of avoiding new caries based on which preventive measures can be implemented before new cavities could develop. This important CRA tool can be used in clinics and in educational programs.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Cabral RN, Hilgert LA, Faber J, Leal SC. Caries risk assessment in schoolchildren – A form based on Cariogram®
software. J Appl Oral Sci 2014;22:397-422.
Ingle NA, Dubey HV, Kaur N, Gupta R. Prevalence of dental caries among school children of Bharatpur city, India. J Int Soc Prev Community Dent 2014;4:52-5.
Simon AK, Rao A, Rajesh G, Shenoy R, Pai MB. Oral health care availability in health centers of mangalore taluk, India. Indian J Community Med 2014;39:218-22.
] [Full text]
Giacaman RA, Miranda Reyes P, Bravo León V. Caries risk assessment in Chilean adolescents and adults and its association with caries experience. Braz Oral Res 2013;27:7-13.
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.
Peker I, Mangal T, Erten H, Alp G, Avci E, Akca G. Evaluation of caries risk in a young adult population using a computer-based risk assessment model (Cariogram). J Dent Sci 2012;7:99-104.
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.
Alian AY, McNally ME, Fure S, Birkhed D. Assessment of caries risk in elderly patients using the Cariogram model. J Can Dent Assoc 2006;72:459-63.
Petersen PE, Bourgeois D, Ogawa H, Estupinan-Day S, Ndiaye C. The global burden of oral diseases and risks to oral health. Bull World Health Organ 2005;83:661-9.
World Health Organization. Oral Health Surveys: Basic Methods. Geneva, Switzerland: World Health Organization; 2013.
Lalić M, Aleksić E, Gajić M, Milić J, Malešević Ð. The efficacy of the interventional health education program for oral health improvement in school children. Stomatol Glas Srb 2012;59:27-34.
Silness J, Loe H. Periodontal disease in pregnancy. II. Correlation between oral hygiene and periodontal condtion. Acta Odontol Scand 1964;22:121-35.
Köhler B, Pettersson BM, Bratthall D. Streptococcus mutans
in plaque and saliva and the development of caries. Scand J Dent Res 1981;89:19-25.
Hänsel Petersson G, Ericson E, Isberg PE, Twetman S. Caries risk assessment in young adults: A 3-year validation of clinical guidelines used in Public Dental Service. Acta Odontol Scand 2013;71:1645-50.
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.
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.
Sakeenabi B, Hiremath SS. Dental caries experience and salivary Streptococcus mutans
, lactobacilli scores, salivary flow rate, and salivary buffering capacity among 6-year-old Indian school children. J Int Soc Prev Community Dent 2011;1:45-51.
Ali YA, Chandranee NJ, Wadher BJ, Khan A, Khan ZH. Relationship between caries status, colony forming units (cfu) of Streptococcus mutans
and Snyder caries activity test. J Indian Soc Pedod Prev Dent 1998;16:56-60.
Olczak-Kowalczyk D, Turska A, Gozdowski D, Kaczmarek U. Dental caries level and sugar consumption in 12-year-old children from Poland. Adv Clin Exp Med 2016;25:545-50.
Sudha P, Bhasin S, Anegundi RT. Prevalence of dental caries among 5-13-year-old children of Mangalore city. J Indian Soc Pedod Prev Dent 2005;23:74-9.
] [Full text]
Al-Darwish M, El Ansari W, Bener A. Prevalence of dental caries among 12–14 year old children in Qatar. Saudi Dent J 2014;26:115-25.
Mafuvadze BT, Mahachi L, Mafuvadze B. Dental caries and oral health practice among 12 year old school children from low socio-economic status background in Zimbabwe. Pan Afr Med J 2013;14:164.
Krasse B. The caries decline: Is the effect of fluoride toothpaste overrated? Eur J Oral Sci 1996;104:426-9.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2], [Table 3]