Literature DB >> 35017948

Caries Risk Assessment among School Going Young Adolescents in Sullia Taluk-Dakshina Kannada.

P Jagan1, Radhakrishnan Karthikeyan2, Rajendran Bharathan2, N C Srihari2, Arumugasamy Niranjana2, Minu Suresh3.   

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. Copyright:
© 2021 Journal of Pharmacy and Bioallied Sciences.

Entities:  

Keywords:  Caries risk assessment; cariogram; dental caries

Year:  2021        PMID: 35017948      PMCID: PMC8687002          DOI: 10.4103/jpbs.jpbs_304_21

Source DB:  PubMed          Journal:  J Pharm Bioallied Sci        ISSN: 0975-7406


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.[1] Looking at a global context, the prevalence of dental caries is still high; especially in children.[1] Comprehensive National Health Survey conducted in 2004 encompassing India has shown a dental caries prevalence of 53.8% in 12-year-old children.[2] 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.[3] 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.[4] 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.[5] 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.[5] 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.[6] 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.[7] 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.[8] 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.[9] According to the WHO Global oral data bank in 2009 the point prevalence was 54% among 12 years old.[10] Studies on prevalence conducted in Dakshina Kannada district reported a caries prevalence ranging from 32.8% to 82.6%.[9] 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.[11] 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.

Inclusion criteria

Children aged 13–14 years with informed consent and willing to participate in the study.

Exclusion criteria

Children with special needs/dentofacial abnormalities/under medication that could affect parameters considered in the study.

Sampling technique

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 collection

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.[12] 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.

Microbiological analysis

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.[13]

Statistical analysis

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

Parametersn (%)
Gender
 Male40 (53)
 Female35 (47)
Caries severity
 Very low (<1.2)25 (33)
 Low (1.2-2.6)12 (16)
 Moderate (2.7-4.4)18 (24)
 High (>4.4)20 (26)
Distribution of sociodemographic and caries experience among school children 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.
Table 2

Distribution of school children by Cariogram scoring

VariableScoringn (%)
Related diseases0: No74 (98.6)
1: Mild1 (2.4)
2: Severe0
DMFT0: No caries experience8 (10.6)
1: Lower than the age group27 (36)
2: Within the age group range2 (2.6)
3: Higher than the age group range38 (50.6)
Diet content0: Very low amount of sugar7 (9.3)
1: Low amount23 (30.6)
2: Moderate amount31 (41.3)
3: High amount14 (18.6)
Diet frequency0: 0-310 (13.3)
1: 4-550 (66.6)
2: 6-715 (20)
3: >70
Amount of plaquePI 0: No plaque4 (5.3)
PI 1: Seen by probe27 (36)
PI 2: Moderate40 (53.3)
PI 3: Severe4 (5.3)
Streptococcus mutans 0: 0-103 CFU5 (6.6)
1: 103-104 CFU31 (41.3)
2: 104-105 CFU24 (32)
3: >105 CFU15 (20)
Fluoride program0: Maximum fluoride exposure0
1: Additional fluoride measures (other than toothpaste) but infrequent application0
2: Fluoride tooth paste only75 (100)
3: Avoidance of fluorides (i.e., no fluoride exposure)0
Clinical judgment0: More positive0
1: Normal setting75 (100)
2: Worse0
3: Very high caries risk0

CFU: Colony forming units, DMFT: Decayed, missing and filled teeth, PI: Plaque index

Distribution of school children by Cariogram scoring CFU: Colony forming units, DMFT: Decayed, missing and filled teeth, PI: Plaque index 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

VariableScoringVery Low (n=25)Low (n=12)Moderate (n=18)High (n=20) P
Related diseases0: No25(100)12 (100)17 (94)20 (100)0.4
1: Mild0(0)0 (0)1 (6)0 (0)
2: Severe0(0)0 (0)0 (0)0 (0)
Diet content0: Very Low amount of sugar7 (28)0 (0)0 (0)0 (0)<0.05
1: Low amount18 (82)2 (16)2 (11)1 (5)
2: Moderate amount0 (0)9 (76)14 (78)8 (40)
3: High amount0 (0)1 (8)2 (11)11 (55)
Diet frequency0: 0 to 32 (8)6 (50)2 (11)0 (0)<0.05
1: 4 to 522 (88)6 (50)14 (78)8 (40)
2: 6 to 71 (4)0 (0)2 (11)12 (60)
3: More than 70 (0)0 (0)0 (0)0 (0)
Amount of PlaquePI 0: No plaque1 (4)1 (8)2 (11)0 (0)0.1
PI 1: Seen by probe12 (48)3 (25)6 (33)6 (30)
PI 2: Moderate12 (48)8 (67)10 (56)10 (50)
PI 3: Severe0 (0)0 (0)0 (0)4 (20)
Streptococcus mutans0: 0-103 CFU3 (12)1 (8)1 (6)0 (0)<0.05
1: 103-104 CFU19 (76)3 (25)6 (33)3 (15)
2: 104-105 CFU3 (12)8 (67)9 (50)4 (20)
3: >105 CFU0 (0)0 (0)2 (11)13 (65)
Fluoride program0: Maximum fluoride exposure0 (0)0 (0)0 (0)0 (0)1.0
1: additional fluoride measures (other than toothpaste), but infrequent application0 (0)0 (0)0 (0)0 (0)
2: Fluoride tooth paste only25 (100)12 (100)18 (100)20 (100)
3: Avoidance of fluorides (i.e., no fluoride exposure)0 (0)0 (0)0 (0)0 (0)
Clinical judgment0: More positive0 (0)0 (0)0 (0)0 (0)1.0
1: Normal setting25 (100)12 (100)18 (100)20
2: Worse0 (0)0 (0)0 (0)0 (0)
3: Very high caries risk0 (0)0 (0)0 (0)0 (0)
Association between Cariogram patterns and the severity of caries experience among school children 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 Figures 1–4.
Figure 1

Cariogram of the school children belonging to very low caries experience group (decayed, missing and filled teeth score less than 1.2)

Figure 4

Cariogram of the school children belonging to high caries experience group (decayed, missing and filled teeth > 4.4)

Cariogram of the school children belonging to very low caries experience group (decayed, missing and filled teeth score less than 1.2) Cariogram of the school children belonging to low caries experience group (decayed, missing and filled teeth score 1.2 to 2.6) Cariogram of the school children belonging to moderate caries experience group (decayed, missing and filled teeth score 2.7 to 4.4) Cariogram of the school children belonging to high caries experience group (decayed, missing and filled teeth > 4.4) 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 Figures 1, 2 and 5.
Figure 2

Cariogram of the school children belonging to low caries experience group (decayed, missing and filled teeth score 1.2 to 2.6)

Figure 5

Cariogram of the school children

Cariogram of the school children

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.[3] 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.[14] 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.[1516] 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.[1718] 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.[192021] 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.[2223] 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

Nil.

Conflicts of interest

There are no conflicts of interest.
  20 in total

1.  Prevalence of dental caries among 5-13-year-old children of Mangalore city.

Authors:  P Sudha; S Bhasin; R T Anegundi
Journal:  J Indian Soc Pedod Prev Dent       Date:  2005-06

2.  Assessment of caries risk in elderly patients using the Cariogram model.

Authors:  Anna Y Alian; Mary E McNally; Solveig Fure; Dowen Birkhed
Journal:  J Can Dent Assoc       Date:  2006-06       Impact factor: 1.316

3.  The caries decline: is the effect of fluoride toothpaste overrated?

Authors:  B Krasse
Journal:  Eur J Oral Sci       Date:  1996-08       Impact factor: 2.612

4.  Cariogram Model in Assessment of Dental Caries among Mentally Challenged and Visually Impaired Individuals of Udaipur, India.

Authors:  Hemasha Daryani; Ramesh Nagarajappa; Archana J Sharda; Kailash Asawa; Mridula Tak; Sudhanshu Sanadhya; Mehak Batra
Journal:  J Clin Diagn Res       Date:  2014-01-12

5.  The global burden of oral diseases and risks to oral health.

Authors:  Poul Erik Petersen; Denis Bourgeois; Hiroshi Ogawa; Saskia Estupinan-Day; Charlotte Ndiaye
Journal:  Bull World Health Organ       Date:  2005-09-30       Impact factor: 9.408

6.  Caries risk profiles of 12-13-year-old children in Laos and Sweden.

Authors:  G L Tayanin; G Hänsel Petersson; D Bratthall
Journal:  Oral Health Prev Dent       Date:  2005       Impact factor: 1.256

7.  Dental Caries Level and Sugar Consumption in 12-Year-Old Children from Poland.

Authors:  Dorota Olczak-Kowalczyk; Anna Turska; Dariusz Gozdowski; Urszula Kaczmarek
Journal:  Adv Clin Exp Med       Date:  2016 May-Jun       Impact factor: 1.727

8.  Streptococcus mutans in plaque and saliva and the development of caries.

Authors:  B Köhler; B M Pettersson; D Bratthall
Journal:  Scand J Dent Res       Date:  1981-02

9.  Caries risk profiles in 2- to 6-year-old Greek children using the Cariogram.

Authors:  Katerina Kavvadia; Andreas Agouropoulos; Sotiria Gizani; Lisa Papagiannouli; Svante Twetman
Journal:  Eur J Dent       Date:  2012-10

10.  Dental caries and oral health practice among 12 year old school children from low socio-economic status background in Zimbabwe.

Authors:  Brighton Tasara Mafuvadze; Lovemore Mahachi; Benford Mafuvadze
Journal:  Pan Afr Med J       Date:  2013-04-29
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