Determination of Caries Risk by Your Fingertips – A Mobile Application Based Study

Introduction

Dental caries is a predominant public health predicament and is still a major health problem globally. It is the most widespread chronic disease affecting human race, irrespective of gender, age and socioeconomic strata. It is also a multifactorial disease that involves an interaction between teeth, saliva, and oral microbiota, as the individual’s risk factors, and diet and oral hygiene, as the main external factors.¹ These amendable risk factors are responsive to intervention, whereas the immutable risk factors are equitably challenging to health care professionals. The occurrence of dental caries can be prevented by tackling, modifying and comprehensively studying the risk factors individually.

The search for suitable, accurate, and feasible strategies to identify individuals at high-risk has escalated, and several causative factors and indicators have been documented as targets.¹ Caries risk assessment should therefore be included for the formation of modified preventive measures.¹ The risk profile is an important factor in the decision-making process of prevention and management of dental caries.²

Cariogram, which was presented by Bratthall D in 1996, modified in 1997, is one of the models which illustrates the interactions and collaboration of caries related factors/ parameters of the patient and presents it graphically. The modified version of Cariogram also included the risk prediction in terms of ‘chance of avoiding dental caries’, in addition to caries risk profile.³ The Cariogram predicts caries accretion more precisely than any single factor model. It can be a system or mechanism used for educating the patient about oral hygiene and persuading the patient to maintain oral hygiene, and the Cariogram model could also be used to support the decisions while selecting preventive measures for the patient.³

The present generations are tech-savvy and are governed by the use of mobile apps for day-to-day basic tasks performance. Cell phones have brought a whole new meaning to the term multitasking. Many of these apps aid individual behavioral change towards health and fitness, and one among them is oral health. “Cariogram – Caries Risk Assessment” application is available for android phones and can be installed after downloading from App Store https://play.google.com/store/apps/ details?id=com.appbites.cariogram&hl=en and presents the results graphically in no time. It stipulates the probability of avoiding new carious lesions. The susceptibility rate of caries is higher in children usually due to the casual attitude towards oral hygiene habits and frequent snacking on carbohydrates and sugar. Hence, this study was carried out to assess the caries risk profile among 7–10-year-old school-going children in North Bengaluru, Karnataka using Cariogram application model, available in the play store.

Materials and Methods

A cross-sectional survey was carried out among 7-10 year old school-going children studying in government schools in rural areas of North Bengaluru, Karnataka. Children who were present on the day of the examination were included in the study. The students who were absent on the day of examination, medically compromised children, and uncooperative children were excluded from the study. Many rural areas and circles do not have access to oral health care providers due to geographic isolation and shortages in workforce; so children from rural communities were included. The purpose of the study was explained to the Institutional Review Board and essential permission was taken from the principals of the schools. The purpose and study procedure was then explained to the study subjects and informed consent was obtained from them.

The sample size was determined based on the comparison of mean values of decayed/missing/ filled teeth (DMFT) obtained from the pilot study. This study was conducted among 90 children in the age group of 7-10 years. The sample comprised of 45 males and 45 females. All the study subjects from government schools were selected through stratified cluster random sampling and were recruited for this study resulting in a sample size of 90. The Slovin’s formula was used for the calculation of sample size (n=90).

A survey proforma was designed which consisted of two sections - Section I consisted of general demographic information including name, age, gender, and parent’s name, while Section II consisted of information about the Cariogram parameters - caries experience, related general disease, diet content, diet frequency, plaque amount, fluoride program, and clinical judgment.

Questions were asked to the students and the student’s attendants regarding medical history, brushing technique, and brushing frequency. Also, the history of fluoride use including the application of topical fluoride and use of fluoridated toothpaste was noted and scoring was done. A 24-hour diet recall i.e. recollection of intake of anything consumed in the last 24 hours proceeding in backward fashion was taken through a personal interview by the investigator for all the 90 children selected for the study.

After the interview, intraoral examination of the study subjects was conducted outside the classrooms (ADA Specification Type IV clinical examinations).⁴ On average, the examination was conducted for a maximum of 15 subjects per day. Caries prevalence, decayed, missing, and filled teeth (DMFT) index were recorded using World Health Organization (WHO) standard criteria for oral health surveys.⁵ Oral hygiene was estimated by employing Silness and Löe plaque index.⁶ Both the indices were recorded by a single skilled examiner with proper guidelines. The degree of reliability of the examiner was set and was standardized by examining 20 children, and the procedure was repeated after four weeks.

Once the information was collected regarding the caries-related factors, scores were entered according to a predetermined scale in the application from 0-2 or 0-3 for each criterion.

For all the entities in this study, the “Clinical Judgment Factor” was scored as 1, which meant that the other value entered evaluated the risk. In Cariogram, the sets for the country/area were established to the standard as the standard set is appropriate to those countries which does not have water fluoridation and India comes under this category.

The scores were entered into the Cariogram app and automatically a pie diagram was generated expressing five different sectors as percentages, i.e.

1. “Diet,” established on an amalgamation of sugar intake (dark-blue sector);

2. “Bacteria,” which is an amalgamation of plaque score (red sector);

3. “Susceptibility,” comprising the fluoride program, (light blue sector);

4. “Circumstances,” previous caries experience and associated general disease (yellow sector); and

5. “Chance of avoiding new caries/cavities”(green sector)³

There are five caries risk groups that the participants can be classified into based on the percentage achieved by the application,

Cariogram:

• Very low risk: 81–100%

• Low risk: 61–80%

• Moderate risk: 41–60%

• High risk: 21–40%

• Very high risk: 0–20%1

The data that was obtained were compiled systematically. The results were analysed comparing male and female students and also based on the age of the students. Results The results of the current study are expressed as caries risk according to Petersson et al.,⁷ to obtain greater scope for statistical analysis, as it is believed to be a more extensive, all-inclusive and useful value, derived by summing up the circumstances, bacteria, partial caries risks of susceptibility and diet, which allows correlations to be established.⁷

The present study was carried out among 90 children in the age group of 7-10 years comprising 45 males and 45 females (Table 1). Among the study subjects, the dominant sector was ‘avoid new caries’ sector in both male and female subjects with 38.422 ± 16.263 and 51.067 ± 40.305, respectively (Table 1) (Figure 1, 2]. The least sector was ‘circumstances’ with 5.177 ± 3.536 in males and 3.844 ± 4.95 in female study subjects (Table 1) (Figure 1, 2). The chance of avoiding new caries in females was higher in comparison to chance of avoiding new caries in male population Table 2 represents the average caries-risk profiles of 7-10-year-old study participants. Results revealed that there was a minor difference in caries risk among different age groups, where 7 and 9-year-old school children showed 49% caries development risk, with 51% chance to avoid caries in the future, while 8-yearold children showed 51% caries development risk, with 49% chance to avoid caries in future, and 10-year-old children showed 67% caries development risk, with 33% chance to avoid caries in future, according to Cariogram (Figure 3, 4, 5, 6). Final result was established based on the category, “chance to avoid new caries”. It was noted that when all the school children were classified according to the above-mentioned criteria, the majority of school children were in the category of ‘medium risk’.

Discussion

A steadfast and reliable caries risk assessment is crucial for preventive dentistry as the most important challenge is to maintain healthy teeth in daily practice, and it could benefit a clinical practitioner immensely as caries prevention and management is based on the patient’s risk of developing caries.⁸ The old-fashioned method of being dependent on a single factor to dictate the development of a multifactorial disease often would lead to inaccurate predictions.⁹ Various caries risk assessment tools (CAT) have been developed previously. American Academy of Pediatric Dentistry has developed CAT10 to monitor the caries risk based on the exposure to fluoride, clinical findings, presence, or absence of caries.¹⁰ Another system used to assess the caries risk of patients is Cariogram, which was introduced in 1976 and modified in 1977 by Bratthall.¹¹ This examines the caries risk based on the multifactorial nature of dental caries. However, these former applications developed are for professional use and could only be operated by the practitioner for primary level of caries prevention. In this regard, ‘Cariogram’ application was developed to increase the cooperation and involvement of patients in caries prevention. Cariogram can be useful on a day to day basis for caries prevention. In regular diet counselling, physical presence of the dentist is not always feasible as a constant reminder and reinforcement.¹²

Technology has become an ultimate part of our daily life. It has been delivered to our fingertips since the introduction of the android system. In this regard, Cariogram has been developed to bring caries prevention to the fingertips. This study was conducted to validate the caries risk profiles in school children (aged 7 -10 years) using Cariogram in rural areas of North Bengaluru so that preventive measures can be enforced in this group. This particular caries assessment method was selected for the study as it 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.¹³ Studies regarding dietary assessment based on the type of food consumed showing the calorie intake have been done using a mobile application; however, no application measured the dietary score based on the weighted mean on the cariogenic risk of food items individually. This provides uniqueness to the application.¹² Another vital advantage is that it provides a series of recommendations for preventive action according to the caries risk. The presentation of pie chart with its different sectors intrigues the patient making it interestingly easier for patients to understand caries risk profile which can be effectually used to motivate them. When validated among both children and elderly, Cariogram predicted caries increment more accurately than any single factor model.¹³ The results obtained showed that children aged 10 years had comparatively less chance to avoid new caries than those in the age groups 7, 8, and 9 years. When the comparison was made between male and female subjects, females had more chances of avoiding new caries as compared to males, even though they did not have a significant difference in their oral hygiene practices, dietary practices, and socioeconomic background.

Certain variables like country/area, and groups were scored as a regular set and clinical judgment was scored as 1 in the Cariogram app for the present study, as the previous studies on the efficacy of Cariogram. The efficacy of the program was increased by using these options. A comparison of the results with other studies was not possible because of the disparity between the results. The limitation of the study is the relatively smaller sample size, which could be a consequence of the factors for inclusion in the study. Cariogram does not require laboratory tests, it is easily applicable, and many researches have validated it in several studies.^8,13,14 Cariogram application was used in this study to achieve rapid results regarding the oral hygiene status of the children so that early preventive measures can be established, thereby increasing the chances of avoiding new caries.

The Cariogram model is truly widespread and elucidates the relative importance of various caries-related factors in an individual risk profile, but the inclusion of salivary tests with microbiological cultivations, such as mutans streptococci and lactobacilli enumeration and chair-side microbial tests usage which are expensive and laborious, eventually delaying the process from a patient-motivating point of view may convey its limited use.

This complies with the study conducted among 12-year old children in an Indian city piloted by Hebbal et al. ¹⁴ Since the disparity between the results exists, comparison of all results with other studies was not possible. Thus, the cariogram model is effective and has several advantages in making recommendations for preventive care and increasing patient motivation. In scientific studies, the cariogram program has been evaluated both in children and adult populations. It is a useful pedagogic tool for dentists, pediatric dentists, dental hygienists, and assistants to discuss with patients about their caries risk. The computerized record-keeping and management are the current trends which the cariogram enables thereby making it unique.¹⁴ The results obtained from the study conducted by Kemparaj et al.,¹⁵ also exhibited highest percentage of individuals (83.2%) developing new caries lesions in the category of very high-risk children and lowest percentage of individuals (10.8%) developing new caries lesion in the category of very low-risk children.15 Petersson et al⁷ also reported that those children with increased risk compared with baseline developed significantly more caries than those with unchanged category.⁷

There are very few experimental studies conducted similar to ours, in which a questionnaire was prearranged and application of mobile phone was used for the intervention. Thus, more research focused on this platform can be conducted at later stages for data evaluation, analysis, and interpretation. However, it might be possible to develop simpler models for the determination of caries risk. The use of Cariogram in paediatric patients seems to be less time consuming and a more economic method. However, these models must be evaluated in further longitudinal clinical studies.

Conclusion

The application named "Cariogram- Caries Risk Assessment" is published which is packaged with a questionnaire to help estimate the caries risk. It is an attempt to employ technology to every household to assist in the prevention of dental caries. The results obtained from the application “Cariogram – Caries Risk Assessment” enables the classification of school children as low, moderate and high caries risk, and the moderate risk group was predominant in this study. “Cariogram – Caries Risk Assessment” mobile dental app is more comfortable and portable to the users as compared to the standard operating systems such as personal computers, which gives this app an edge over them for use in prospective clinical studies.