Prevalence, Trends, and Associated Risk Factors of Traumatic Dental Injury among Children and Adolescents in India: A Systematic Review and Meta-analysis
1–5Department of Public Health Dentistry, SCB Dental College and Hospital, Cuttack, Odisha, India
Corresponding Author: Sri Priya Narayanan, Department of Public Health Dentistry, SCB Dental College and Hospital, Cuttack, Odisha, India, Phone: +91 9676365683/+91 8919737142, e-mail: email@example.com
How to cite this article: Narayanan SP, Rath H, Panda A, et al. Prevalence, Trends, and Associated Risk Factors of Traumatic Dental Injury among Children and Adolescents in India: A Systematic Review and Meta-analysis. J Contemp Dent Pract 2021;22(10):1206–1224.
Source of support: Nil
Conflict of interest: None
Aim and objective: Traumatic dental injury (TDI) is a significant public health concern. This study aimed to perform a systematic review on the prevalence, trends, and possible risk factors of dental trauma in permanent teeth among children and adolescents in India.
Materials and methods: Literature search was carried out, in PubMed, EMBASE, Web of Science, Cochrane, Google scholar, and Gray literature (MDS dissertation, manuscripts) database up to October 5, 2020, reporting on dental trauma prevalence in India. Meta-analyses were done using random effects model. Pooled estimates were calculated with a confidence interval of 95% (95% CI) both for prevalence and odds ratios (OR). Trend analysis was performed for the included studies. Quality assessment of the included studies was done using the Hoy checklist for prevalence studies. Qualitative synthesis was done for predictors in which meta-analysis could not be performed.
Results: This online searching strategy collected and listed 2,491 articles on this topic. After evaluating their titles and abstracts, only 59 were finally selected for complete review and data collection. All studies had been performed in children and adolescents. The pooled prevalence of dental trauma in permanent teeth was 11%. Positive summary association of dental trauma with male gender (pooled OR = 1.52; 95% CI: 1.37–1.70), inadequate lip coverage (pooled OR = 4.76; 95% CI: 3.18–7.11), and increased overjet of >3.5mm (pooled OR = 4.84; 95% CI: 2.86–8.19) and >5.5 mm (pooled OR = 4.93; 95% CI: 4.32–5.63) was observed. Prevalence of dental trauma showed an increasing trend with time. All of the studies were having moderate–high risk of bias.
Conclusion: Approximately 9–13% of the children and adolescents in India presented some type of TDI in permanent teeth, with an increasing trend. Boys, children, and adolescents presenting inadequate lip coverage, or an increased overjet greater than 3.5 and 5.5 mm are more likely to have traumatic dental injuries.
Clinical significance: Future population-based analytical studies on TDI in India are recommended.
Keywords: Adolescent, Children, Dental trauma, Inadequate lip coverage, Overjet, Permanent teeth, Systematic review.
Traumatic dental injury (TDI) is a significant public health concern. It is presumed to be the fifth most prevalent dental disease in the world and around 20% of people suffer from trauma to teeth at some point in their life. A meta-analysis of the worldwide global burden of TDI reported a prevalence of 15.2% in permanent dentition alone.1 A 12-year review of literature stated that approximately two-thirds of all diagnosed TDIs occurred in children and adolescents.2 Various population-based studies have been conducted in different states of India to quantify TDI and the prevalence ranged from 2.053 to 50%.4 There has been an increase in the number of observational studies carried out on TDI over the past decade.
Previous studies have shown that, as a consequence of dental tissue trauma, bacterial invasion in the exposed dentinal tubules could lead to pulpal inflammation and subsequent necrosis, resulting in discoloration or sometimes even loss of the tooth. Undoubtedly, TDI can thus negatively affect the psychological development in children and adolescents. Moreover, the treatment is expensive and time-consuming.5
TDI is not a disease but a consequence of several unavoidable risk factors in life.6 Published literature has reported host factors like male gender, increased overjet, inadequate lip coverage, along with environmental factors, such as unsafe playgrounds, risk-taking behavior, and violence, to be mostly associated with TDI.1,2,6–12 Some studies have observed obesity and socioeconomic factors to be associated with higher incidence and prevalence of TDI in permanent teeth.10,13
A previous systematic review included studies for TDI in both primary and permanent dentition, before April 2019 in India.14 The review has concluded that there is high degree of variability followed by heterogeneity in the data from primary studies. Also, there is a lack of empirical evidence on the measures of trends over the years and other associated factors, such as obesity and socioeconomic status for TDI across urban and rural India. Such major gaps ultimately hinder careful planning, better decision-making, and the development of an effective intervention for the prevention and management of TDI. Therefore, the present systematic review and meta-analysis of published literature made an attempt to provide a precise pooled estimate by including a greater number of recent studies and comprehensive assessment of TDI prevalence in permanent dentition, trends, and reliable association of various risk factors among Indian children and adolescents.
MATERIALS AND METHODS
Study Design and Search Strategy
The present systematic review and meta-analysis were undertaken in accordance with the guidelines of the COSMOS-E: Guidance on conducting systematic reviews and meta-analyses of observational studies of etiology.15 A comprehensive literature research of online databases, PubMed Medline, Web of Science, Cochrane Central, EMBASE, and Gray literature (MDS dissertation, manuscripts) from inception to October 5, 2020, was conducted. In addition to these electronic searches, the reference lists of key publications or further material were manually searched. Further articles were manually hand-searched from the citation list of the published literature. The studies from these databases were then imported to Mendeley reference manager software for the removal of duplicate titles.
Keywords Included in the Search Strategy for all Six Databases (Title, Abstract, and MeSH Terms of Papers) (Table 1)
|Study design (AND)||TDI (AND)||Associated factors (AND)||Population (AND)|
|Prevalence||Traumatized teeth||Etiology||School child|
|Cross-sectional study||Dentoalveolar trauma||Etiology||Child|
|Epidemiology||Oral trauma||Caus (cause, causation, causative factors)||Adolescent|
|Point estimate||Permanent anterior||Malocclusion||Minor|
|Cohort analysis||Tooth trauma||Incisor overjet||Young child|
|Cross sectional analysis||Teeth trauma||Anterior overjet||School students|
|Observational analysis||Tooth fractures||Risk factors||School|
|Disease frequency||Teeth fractures||Associated factors|
|Cohort Study||Teeth injuries|
|Cross-sectional studies||Tooth injuries|
|Epidemiologic study Incidence||Traumatic dental injuries|
|Longitudinal study||Dental trauma|
(Prevalence OR incidence OR survey OR epidemiology OR “cross sectional” OR Etiology) AND (dental OR teeth OR tooth) AND (trauma OR injury OR fracture OR avulsion OR dislocation OR luxation) AND (child OR children OR adolescents OR young OR school) AND (India).
Study Eligibility Criteria
Population-based observational studies that evaluated the prevalence of TDI in permanent dentition were eligible. The results from conference proceedings, editorials, letters, reviews, and meta-analysis and publications with incomplete data which could not be obtained from the authors were not included. Studies pertaining to primary dentition as well as those reported from nonrepresentative population (athletes, visually impaired or special needs group, studies done exclusively on male and female population) were also excluded from the present meta-analysis.
Study Selection and Data Collection Process
Two independent reviewers (SPN and RHK) screened all the titles of retrieved records from the databases, followed by a screening of abstracts of relevant titles (Kappa score = 0.81). Abstracts were selected if they fulfilled the selection criteria. Any disagreements about selection were discussed with a third reviewer (HR) for resolution. All duplicates were removed after verifying the most recent and complete version. Full-text studies were retrieved for the selected abstracts and additionally reference lists of these studies were searched. The retrieved full-text studies were assessed further to ensure they satisfied the inclusion criteria.
Assessment of Quality in Included Studies
After the full-text screening, all the articles were subjected to risk of bias assessment using a 10-item checklist adapted from Hoy et al. (2012).16 The selected articles were thus assessed for the representation of the population, sampling, random selection, nonresponse bias, data collected directly from subjects, case definition, reliability and validity of the method used, mode of data collection, and length of shortest prevalence period. Based on the assessment, studies were identified as high, moderate, or low risk.
Data Collection and Extraction
A data collection form was designed in Microsoft Excel to extract and enter the relevant data fields from the selected full-text studies. Data extraction was performed by the two reviewers independently and in duplicate. When needed, authors were contacted to gather missing information. The excel sheet was saved as a comma-separated-values (.csv) file. The data for each included study were then tabulated (Table 2).
|Demographic details||Study methods||TDI prevalence and tooth type||Place of occurrence of TDI||Cause of TDI||Associated factors|
|Author last name||Type of study||TDI number||Home||Fall||Gender|
|Year of publication||Calculated sample size||TDI percentage||Street||Violence||Lip competency|
|Region of the study||Total sample size taken||Tooth type affected: Number and percentages||Playground||Collision||Overjet|
|State where the study was conducted||Sampling strategy||Type of Trauma-based on the classification||School||Biting hard||BMI|
|Journal in which it was published||Evaluation period||School type (Government school/Private school)||Road traffic accidents||Molar relation|
|TDI classification||Cannot remember and others||Socioeconomic status|
Statistical analysis for pooled prevalence and to obtain a forest plot to demonstrate the degree of heterogeneity among the selected articles was performed using R (version 3.0.2) software after extracting data in an excel sheet. Subgroup analyses were further conducted to estimate and verify the influence of studies, by groups, on the pooled results.
Review Manager (Review Manager v. 5.3, The Cochrane Collaboration; Copenhagen, Denmark) was used to obtain forest plots and odds ratio (OR) for associated factors with TDI. The software uses Chi-square, I2, and Tau2 to study heterogeneity. The p-value was set at <0.05 for the results to be significant. Meta-analysis was performed by using a random effects model due to the variation between the studies.
Trend analysis was done in Microsoft Excel. The Statistical analysis for the given dataset was performed using the “Data analysis toolpak” toolbox from Excel in the “Data” section.
Flowchart 1 shows a flowchart outlining the number of articles identified at each step of the literature search. The searches resulted in 2,491 references in total. The articles were checked for duplicates using the Mendeley reference manager and 2,039 references were excluded in the process. The titles and abstracts of 452 studies were then screened against the inclusion criteria, independently and in duplicate, discarding 378 studies. Additionally, 15 more studies were excluded after quality assessment. Therefore, 59 records met the inclusion criteria for this review.
A total of 59 studies (58 cross-sectional studies and 1 case–control study) were included in the final analysis. A total of 162,997 participants provided data for the included studies. All the included studies involved the children and adolescent population. The study characteristics extracted from the included observational studies are described in Table 3.
|Author||Year||Region||State||Age||Sample size||Study design||Sampling strategy||Classification|
|Rai and Munshi18||1998||South Kanara||Karnataka||NA||4,500||CS||NA||NA|
|Gupta et al.19||2002||South Kanara||Karnataka||8–14||2,100||CS||Random sampling||Hargreaves and Craig|
|Jose and Joseph20||2003||Vadavucode||Kerala||12–15||1,068||CS||NA||Clinical examination|
|Tangade21||2007||Belgaum||Karnataka||12–15||3,621||CS||Simple random sampling||WHO|
|David et al.22||2009||Trivandrum||Kerala||12||838||CS||Stratified two stage random cluster sampling||O’Brien|
|Bharadwaj23||2009||Coorg||Karnataka||7–15||4,036||CS||Stratified random sampling||Garcia Godoy|
|Ravishankar et al.24||2010||Davangere||Karnataka||12||1,020||CS||Random sampling||WHO|
|Gupta et al.25||2010||Baddi-barotiwala||Himachal Pradesh||4–15||1,059||CS||Simple random sampling||Modified Ellis and Davies|
|Ingle et al.26||2010||Chennai||Tamil Nadu||11–13||687||CS||Random sampling||Ellis and Davies|
|Kumar et al.27||2011||Ambala||Haryana||NA||963||CS||NA||NA|
|Naveen et al.28||2011||Tandoor||Andhra Pradesh||12||1,020||CS||NA||WHO|
|Patel and Sujan29||2012||Vadodara||Gujarat||8–13||3,708||CS||Multistage sampling technique||Andreason|
|Govindarajan et al.30||2012||Chidambaram||Tamil Nadu||3–13||3,200||CS||Simple random sampling||Ellis and Davies|
|Ankola et al.31||2012||Belgaum||Karnataka||6–11||13,200||CS||Random sampling||WHO|
|Sharma and Dua32||2012||Dera bassi||Punjab||7–12||880||CS||NA||Ellis and Davies|
|Rajesh et al.33||2012||4 states||South India||4–16||30,000||CS||Multistage cluster sampling||Modified Ellis and Davies|
|Dhingra et al.34||2012||Faridabad||Haryana||12–15||1,090||CS||Multistage sampling||Ellis and Davies|
|Vijaykumar et al.35||2013||Bengaluru||Karnataka||10–12||858||CS||Simple random sampling||Clinical examination|
|Basavaraj et al.36||2013||Modinagar||Uttar Pradesh||12–15||900||cs||Two stage cluster sampling||WHO|
|Chopra et al.37||2014||Panchkula||Haryana||12–15||810||CS||Multi stage sampling technique||Ellis mod Holland|
|Bansode et al.38||2014||Aurangabad||Maharashtra||>10||1,000||CS||NA||NA|
|Krishna murthy et al.39||2014||Bengaluru||Karnataka||5–16||2,132||CS||Multistage random sampling||Ellis and Davies|
|Prasad et al.40||2014||Gurgaon||Haryana||12–15||671||CS||Multistage sampling technique||Ellis and Davies|
|Chandra41||2014||Greater Noida||New Delhi||NA||9,074||CS||NA||NA|
|Vashisth et al.42||2014||Kangra||Himachal Pradesh||11–14||1,041||CS||NA||Modified Ellis and Davies|
|Gojanur et al.3||2015||Mathura||Uttar Pradesh||5–8||1,657||CS||Stratified cluster random sampling||Ellis and Davies|
|Mathur et al.13||2015||NCT||New Delhi||12–15||1,386||CS||Multistage sampling technique||Modified O’ Brien|
|Basha et al.43||2015||Davangere||Karnataka||6–13||1,550||Nested CS||NA||Andreason|
|Hegde and Sajnani44||2015||Mangaluru||Karnataka||14–70||2,000||CS||NA||WHO|
|Kirthiga et al.45||2015||Davangere||Karnataka||11–16||2,000||CS||Two stage random sampling||Ellis and Davies|
|Ramaiah and Maraiah46||2015||Shivamoga||Karnataka||9–14||1,450||CS||Random sampling||WHO|
|Singh et al.47||2015||Lucknow||Uttar Pradesh||3–17||1,112||CS||NA||Ellis and Davies|
|Yadav et al.4||2015||Bhopal||Madhya Pradesh||12–15||200||CS||Snowball sampling||NA|
|Ain et al.48||2016||NA||Kashmir||12||1,600||CS||Multistage sampling technique||Ellis and Davies|
|Gupta et al.49||2016||Bhopal||Madhya Pradesh||11–15||1,518||CS||Stratified cluster sampling||Andreason and WHO codes|
|Prasad et al.50||2016||West Godavari||Andhra Pradesh||NA||5,203||CS||Simple random sampling||NA|
|Hegde and Agrawal51||2017||Kharagpur-Belapur||Navi Mumbai||9–14||3,012||CS||Stratified random sampling||Andreason|
|Garg et al.52||2017||NA||Delhi||7–14||3,000||CS||Multistage random sampling||Andreason and WHO|
|Goyal et al.53||2017||Dhanganagar||Rajasthan||10–17||3,002||case control||Multistage sampling technique||Ellis and Davies|
|Shashikiran et al.54||2017||Bhopal||Madhya Pradesh||6–12||1,204||CS||Random sampling||WHO|
|Sharva et al.55||2017||Bhopal||Madhya Pradesh||12–15||1,100||CS||Three stage sampling||WHO|
|Shah and Jeevanandan56||2018||Chennai||Tamil Nadu||6–15||108||CS||NA||Clinical examination|
|Khandelwal et al.57||2018||Indore||Madhya Pradesh||3–17||5,000||CS||Random sampling||Ellis and Davies|
|Saraswathi and Kumar Rathinavelu58||2018||Rohtak||Haryana||12||2,000||CS||NA||Ellis and Davies|
|Juneja et al.59||2018||Indore||Madhya Pradesh||8–15||4,000||CS||Multistage random sampling||Modified Ellis and Davies|
|Bhagat and Singh60||2018||Ghaziabad||Uttar Pradesh||12–19||1,819||CS||NA||WHO|
|Gupta et al.61||2018||Jabalpur||Madhya Pradesh||6–15||2,671||CS||Stratified cluster sampling||WHO|
|Peter and Narayan62||2018||Kottayam||Kerala||15–18||930||CS||Multistage sampling||WHO|
|Dharmani et al.63||2019||Patiala||Punjab||8–12||3,000||CS||Simple random sampling||Ellis and Davies|
|Priyadarshini et al.64||2019||Chennai||Tamil Nadu||11–13||825||CS||Simple random sampling||Ellis and Davies|
|Prasanna et al.65||2019||Bengaluru||Karnataka||7–14||3,363||CS||Simple random sampling||WHO TDI|
|Nagarajappa et al.66||2019||Kanpur||Uttar Pradesh||12–15||1,100||CS||Two stage stratified random sampling||Ellis and Davies|
|Das et al.67||2019||Lucknow||Uttar Pradesh||5–16||500||CS||Simple random sampling||Clinical examination|
|Prakash and Kumari68||2019||Patna||Bihar||7–14||2,820||CS||NA||WHO|
|Shakuntala and Kalpavriksha69||2019||Bengaluru||Karnataka||9–14||500||CS||Simple random sampling||Andreason with WHO|
|Ramachandran et al.70||2019||Chettinad||Tamil Nadu||20–73||1,562||CS||NA||WHO|
|Basak et al.71||2020||Siliguri||West Bengal||0–14||780||CS||Cluster sampling||WHO|
|Lakshmi et al.72||2020||Chennai||Tamil Nadu||8–15||7,247||CS||Stratified random sampling||Ellis and Davies|
The risk of bias assessment was carried out using the Hoy et al. scale for 59 studies, out of which 47% were at moderate risk and the remaining 53% were at high risk of bias. Low scores were mainly due to lack of representativeness of the sample and proper definition or criteria for TDI. Furthermore, the adjusted odds ratio for associated factors has not been reported adequately. Scores for individual studies are mentioned in Table 4.
|Author||Risk of bias score|
|Gojanur et al.3||6|
|Yadav et al.4||7|
|Mathur et al.13||5|
|Ramachandran et al.70||7|
|Prakash and Kumari68||7|
|Das et al.67||7|
|Khandelwal et al.57||5|
|Garg et al.52||7|
|Gupta et al.49||6|
|Prasad et al.40||7|
|Chopra et al.37||6|
|Basak et al.71||6|
|Patel and Sujan29||6|
|Krishna Murthy et al.39||7|
|Ravishankar et al.24||6|
|Lakshmi et al.72||6|
|Gupta et al.19||6|
|Sharma and Dua32||8|
|Nagarajappa et al.66||7|
|Juneja et al.59||6|
|Shashikiran et al.54||8|
|Peter and Narayan62||7|
|Basavaraj et al.36||7|
|Sharva et al.55||6|
|Priyadarshini et al.64||7|
|Dhingra et al.34||6|
|Gupta et al.61||7|
|Kirthiga et al.45||7|
|Dharmani et al.63||6|
|Basha et al.43||6|
|Govindarajan et al.30||8|
|Hegde and Agrawal51||6|
|Ain et al.48||6|
|Goyal et al.73||7|
|Saraswathi and Kumar Rathinavelu58||7|
|Ankola et al.31||6|
|Gupta et al.25||6|
|Ramaiah and Maraiah46||7|
|Shakuntala and Kalpavriksha69||7|
|Anegundi et al.60||6|
|Bhagat and Singh60||6|
|Singh et al.47||7|
|David et al.22||6|
|Vijaykumar et al.35||6|
|Prasanna et al.74||6|
|Hegde and Sajnani44||7|
|Shah and Jeevanandan56||6|
|Rai and Munshi18||8|
|Jose and Joseph20||7|
|Ingle et al.26||6|
|Kumar et al.27||7|
|Naveen et al.28||8|
|Bansode et al.38||6|
|Vashisth et al.42||7|
|Prasad et al.50||7|
Pooled Prevalence of TDI in Permanent Teeth in India
The result of the meta-analysis for pooling the proportion of TDI is graphically represented in Figure 1A. Forest plot of meta-analysis of studies in the prevalence of traumatic dental injuries in permanent teeth (all studies included n = 59) revealed a pooled prevalence of 11% with 95% CI of 9–13% using random effect model.
Sensitivity Analysis for the Pooled Prevalence of TDI in Permanent Teeth in India
The result of the meta-analysis for pooling the proportion of TDI by removal of outlier studies4,67,68,70 on visual inspection of the forest plot is graphically represented in Figure 1B. No significant change in the heterogeneity was observed after excluding four outlier studies.
Subgroup analysis was performed based on various study level covariates contributing to clinical and methodological heterogeneity. Probable covariates were identified before analysis. The subgroup analysis was conducted by the state where the study was carried out as well as by the criteria used to classify TDI.
Subgroup analysis based on the state where the study was conducted: Figure 2A depicts subgroup analysis by state with Karnataka subgroup including 14 studies and non-Karnataka including 45 studies. The forest plot revealed a nonsignificant effect of the moderator using mixed model analysis (random effects model within subgroups and fixed effects model between subgroups) suggesting that the study state does not modify the prevalence of TDI.
Subgroup analysis based on the criteria used to classify TDI: Subgroup analysis by criteria used to classify TDI has been projected in Figure 2B. The forest plot revealed a nonsignificant effect of the moderator using mixed model analysis (random effects model within subgroups and fixed effects model between subgroups) implying that classification does not modify the prevalence of TDI.
Meta-regression of the Study Level Covariates
Among the study level covariates considered for meta-regression, both sample size and year of publication significantly explain the percentage of heterogeneity variation (18.15 and 4.89%) found on the prevalence proportion (Table 5).
|Study level covariate||β coefficient||R2||p value|
|Risk of bias||0.0545||0.01%||0.6906|
|Year of publication||0.0253||4.89%||0.0534|
Association between Gender and TDI in Permanent Teeth
Figure 3A is a forest plot of 38 studies reporting the association between gender and traumatic dental injuries in permanent teeth. The study-specific odds ratio was 1.52 and summary effect estimates of 1.37–1.70. There are 1.52 times increased odds of experiencing traumatic dental injury among males as compared to females.
Association between Inadequate Lip Coverage and TDI in Permanent Teeth
Figure 3B depicts that the overall effect estimate of 17 studies was 4.76 (3.18–7.11), thus indicating that there are 4.76 times increased odds of experiencing traumatic dental injury among those with inadequate lip coverage as compared to those with adequate lip coverage.
Association between Geographic Area and TDI in Permanent Teeth
As explained in Figure 3C, the overall effect estimate of six studies was 1.30 (0.88–1.91) indicating that there are 1.30 times increased odds of experiencing traumatic dental injury among those from the rural area as compared to those from the urban region. However, this finding was not statistically significant.
Association between Increased Overjet of >3.5 mm, >5.5 mm with TDI in Permanent Teeth
Figure 3D illustrates that the overall effect estimate from 13 studies was 4.84 (2.86–8.19), thus indicating that there are 4.84 times increased odds of experiencing traumatic dental injury among those with increased overjet (>3.5 mm) as compared to those with normal overjet. Figure 3E shows the overall effect estimate of nine studies as 4.93 (4.32–5.63), thus indicating that there are 4.84 times increased odds of experiencing traumatic dental injury among those with increased overjet (>5.5 mm) as compared to those with normal overjet.
Trends in Prevalence of Dental Trauma in Permanent Teeth in India
Figure 4A depicts the trends of prevalence for TDI in the percentage of the studies included over the years. The first study was conducted in 1967. Out of the 59 mentioned studies, the maximum number of prevalence studies (n = 32) has been done in the last 6 years. Figure 4B depicts the trend line of TDI prevalence in permanent teeth in India which denotes an upward trend. Figure 4C reveals the forecast of prevalence for TDI by average for the next 10 years that suggests an increasing pattern over the coming years. An estimate of the prevalence percentage for the corresponding year can be deduced. Figure 4D depicts the forecast of prevalence for TDI by average for the next 10 years broadly based on studies classified under the three most commonly used classifications that suggest a steeper pattern of TDI% when using clinical examination compared to WHO75 and Ellis and Davies classification.76
Assessment of Publication Bias
The funnel plot (Fig. 5) for the current review is a simple scatter plot of the intervention effect estimates from individual studies against each study’s precision (standard error) that is depicting considerable asymmetry with scattered studies depicting heterogeneity.
Qualitative Synthesis of Other Factors in Which Meta-analysis Could Not Be Performed
Out of 59 included studies, 50 studies10–13,44–78,79 could provide data for causes of trauma. The most common cause mentioned was falls.10–13,19,22,24,25,27,31–36,43–47,49,51,54,55,58–64,66,69,73,74,77–79 Twenty-five11,19,24,30,32,34,36,37,39,43,45,49,52,54,55,57,59,61–66,72,77 studies provided information about the geographical place where the TDI occurred. The most common places mentioned were home (12 studies)11,24,36,43,49,52,54,57,63,64,66,72,77 followed by the school (six studies).39,43,55,62,63,72 Eight studies13,24,43,49,57,62,66,69 evaluated socioeconomic status that was categorized to upper, middle, and lower socioeconomic status. Three studies13,57,72 mentioned that participant of middle socioeconomic status experienced greater TDI. In the other five studies,43,49,62,66,69 lower socioeconomic status groups experienced greater TDI. BMI was categorized as overweight/obese, normal, and underweight. There were four35,52,63,77 studies that could be included in this analysis. A greater prevalence of TDI in overweight or obese participants was reported in three studies.35,63,77 In one study, underweight participants were associated with TDI.52 A total of six studies48,49,51,57,59,63 assessed molar relations and all of them reported greater TDI prevalence among participants with class 2 molar relation. The affected tooth type was mentioned in 2013,23,24,31,32,36,43,47,48,51,56,58,59,62,64,66,77,80–82 studies. In 19 studies, maxillary central incisors were most commonly affected teeth. Out of the 247,11,13,22,24,30,31–33,35,37,43,45,47-49,51,55,57,63,66,78,81 studies that reported the nature of the injury, enamel fracture was the most common findings in 18 studies.7,11,13,30,31,33,35,37,43,45,47–49,51,55,57,66
The present systematic review was undertaken to evaluate the prevalence, trends, and associated factors of TDI in permanent teeth of children and adolescents in India. The overall prevalence of TDI from a total of 59 studies meeting the inclusion criteria in permanent teeth was 11% (0.11) (95% CI 0.09–0.13) with high heterogeneity among studies conducted in different geographic areas in India using the random effects model. A previous systematic review has reported 13% overall prevalence of TDI in India for 48 included studies.14 The difference may be due to inclusion of studies pertaining to primary dentition and high-risk groups such as athletes. The systematic reviews conducted in different countries reported a pooled prevalence of 18.6%9 in Latin American and Caribbean countries and 17.5%7 in Iran. This difference may be because of variation in the actual prevalence in the different study populations from different countries. By visual inspection, four outlier studies4,67,68,70 was noted indicating the varying prevalence of TDI in the studies conducted. Sensitivity analysis was done removing the outlier studies; however, no significant changes in the pooled result were observed.
There is a high degree of heterogeneity between studies, which can likely be explained by clinical, methodological, and statistical reasons. Although the study population included children and adolescents, factors that contributed to clinical heterogeneity include participants in the studies who differed in their age, gender, risk factors assessed, evaluation period, definition, and criteria used for TDI. There was considerable variability in the region where studies were conducted. Out of the 59 studies, 17 were done in the Southern state of Karnataka. Hence, a subgroup analysis was performed based on Karnataka and non-Karnataka studies. The moderator effect was not statistically significant as there were a varying number of studies in each group. No subgroup analysis was able to explain the heterogeneity.
The commonly used criteria were WHO classification.75 The WHO classification of oral trauma describes injuries to the internal structures of the mouth. Luxation injuries are grouped as one and not divided into intrusive, extrusive, and lateral luxation. Injuries to the alveolar socket and fractures of the mandible or maxilla are not grouped under oral injuries, but rather are classified separately as fractures of facial bones.
The Ellis classification76 is a modification of the WHO system which has been used most commonly by various authors for recording dental trauma. This system is a simplified classification which groups many injuries and allows for subjective interpretation by including broad terms such as “simple” or “extensive” fractures. However, injuries to the alveolar socket and fractures of the mandible and maxilla have not been classified here, which can underestimate the actual prevalence percentage. Unlike the WHO classification, Andreasens80 is a more comprehensive system having 19 groups including injuries to the teeth, supporting structures, gingiva, and oral mucosa that allows for minimal subjective interpretations. Nevertheless, this is the least commonly used criterion in Indian studies. Although the best option to evaluate TDI could not be narrowed down, a universal classification can be used to facilitate further comparisons between survey results. Subgroup analysis based on classification used could not prove heterogeneity statistically.
Methodologically the included studies varied in the sampling technique, sample size, and geographic location. Qualitative appraisal of the studies revealed that 42 studies reported sampling method and only 22 studies reported the evaluation period and sample size calculation. The sample size included in the meta-analysis ranged from 10856 to 30,000.33 There were also differences in the quality of the studies with the majority of them having moderate-to-high risk of bias. Both methodological and clinical sources of heterogeneity contribute to the occurrence and magnitude of statistical heterogeneity.81
When gender was assessed as a risk factor for TDI, boys were reported to have about two times greater odds of TDI compared to girls (OR = 1.52; 95% CI: 1.37–1.70). This finding was compatible with reports from similar systematic reviews in other countries like the Latin America and Caribbean countries9 and Iran.7 A possible explanation for this finding might be due to boys engaging more actively in sports, fights, and outdoor activities than girls.
The meta-analysis from the forest plot could not deduce a significant association of the rural population with TDI (OR = 1.30; 95% CI: 0.88–1.91). A possible explanation could be that only six studies had assessed this variable. Individuals raised in rural areas are exposed to considerably different environmental risk factors than those living in urban regions such as household and school setting, play area, and lifestyle behaviors, which have all been implicated as potential environmental risk factors for TDI.57
The studies that evaluated socioeconomic status reported the greatest prevalence of TDI among adolescents in lower socioeconomic status. Meta-analysis could not be conducted because the data was not extractable. This was in contrast to a systematic review which proved that the scientific evidence indicates no association between socioeconomic indicators and TDI.82 Socioeconomic differences in the prevalence of TDI in adolescents are likely due to differential exposure to environmental factors of the neighborhood, parental education level and employment status, and the level of social capital in the community.13,43 This difference could be partly explained by the fact that there is no single measure of socioeconomic status, and the studies for the systematic review did not include observations from the Indian population. The standardization of a measure, particularly in the Indian scenario which is a lower-middle-income country, is needed for the acquisition of scientific evidence of such an association.
The association between obesity and the occurrence of TDI in the present systematic review was doubtful. Although results suggest that there was an increased chance of TDI among overweight/obese individuals,35,63,77 inconsistencies exist among the four studies35,52,63,77 reported. In a systematic review by Gottems et al.,10 the evidence favors no significant association between dental trauma and physical activity and nutritional status. However, the authors were inconclusive of the results due to the relatively low level of current evidence especially because of obesity. Consequently, prospective cohort studies are needed to address this issue further.
The current systematic review indicates that fall injuries were most commonly associated with dental trauma followed by sports and collision. This was a common finding in other reviews as well.7,8 Besides the present systematic review also suggested that TDI most frequently occurs at home than in school, street, or playgrounds. Previous studies with similar findings suggested that this could be because the children and adolescents spend more time at home and the parents are unaware of preventing TDI.2,6,7,11
In the present review, overjet was classified as studies reporting an overjet of >3.5mm (OR = 4.84; 95% CI: 2.86–8.19) and >5.5mm (OR = 4.84; 95% CI: 4.32–5.63). In both cases, a positive association of as much as five times greater with TDI than normal overjet was found in the meta-analysis. An Australian systematic review conducted by Arraj82 reported that an increased overjet was significantly associated with higher odds of developing trauma in all dentition stages and age-groups. A similar study by Soriano EP in Brazil also suggested that an overjet size greater than 5 mm and inadequate lip coverage were predisposing factors related to the occurrence of traumatic dental injuries.83 Increased overjet due to the proclination of anterior teeth leaves them vulnerable and less protected by lips. Thus, when the lips do not cover the entire tooth, they do not absorb any impact and all force is applied to the tooth.
The present review showed that participants with inadequate lip coverage were three times as likely to be associated with TDI compared to those without TDI (OR = 4.76; 95% CI: 3.18–7.11). The finding was in accordance with other systematic reviews as well.7–9,12 Even before orthodontic treatment is started, such patients should be periodically monitored and educated about TDI prevention. The use of mouthguards should also be promoted in these groups.2
In addition, increased association of Angle’s class 2 malocclusion (particularly division 1 molar relation) with TDI is inferred from the qualitative synthesis. It has been well documented that malocclusion is associated with less masticatory efficiency and a poorer quality of life. As such, clinical factors of malocclusion associated with a higher chance of suffering TDI (such as greater overjet, inadequate lip sealing, class II division I molar relation) should be prevented and treated not only because of their association with TDI but also due to their impact on children and adolescents.8
Based on the qualitative synthesis of the studies, maxillary central incisors account for most of the TDI followed by maxillary lateral incisors, which was in agreement with other studies.2,7 This could be partly explained by the fact that the anterior teeth are more prone to injures due to their obvious placement in the arch and also maxillary central incisors are positioned to receive the maximum impact during a fall or collision. The nature of injury involved maximum enamel fracture followed by enamel and dentine fractures. This finding was supported by other review articles as well.6,7,11
There is noticeable fluctuation in the trends of TDI prevalence over the years. An increasing pattern for trend line with a positive slope can be observed suggesting that TDI could pose a significant dental public health issue in permanent dentition. In addition to the trend line, a forecast plot for the next 10 years based on different classifications used was generated to further understand the variation in the prevalence of TDI. All the three most commonly used classification indicated an increasing pattern with a positive slope. A steep gradient was observed in the case of TDI classified by mere clinical examination and a considerably moderate rise in the case of Ellis and Davies and WHO criteria. A possible explanation for the overestimation of TDI by clinical examination could be inability to follow a specific set of standard criteria. Inconsistencies of outcome assessment by different examiners can thus add more to the reason why the observations were more scattered resulting in a steep forecast line. As for Ellis and Davies and WHO criteria, most of the observations were almost in line with the forecast trend suggesting a proper estimation for TDI. Nevertheless, it is worth to state that this trend analysis does not reflect exact data from all regions of India. Further studies should be conducted to map possible different scenarios nationwide considering different geographic locations for more prediction.
Considerable asymmetry was observed in the funnel plot for the present systematic review. This may be due to several reasons, including true heterogeneity (i.e., smaller studies differ from larger ones in terms of the study population, exposure levels of risk factors, etc.), selection bias and bias in design or analysis, or chance.
There were several limitations in this systematic review. It should be noted that the data for Indian studies are weighted toward Southern and Northern India with only 1 of the 59 studies reporting data from West Bengal. Therefore, the data presented should be interpreted as pertaining mainly to some regions of India. Moreover, the literature search was restricted to studies published in permanent teeth, which may have introduced bias into the study. However, there were only a few studies that were excluded for this reason. Meta-analysis could not be performed for several predictors as data were not extractable for each study level covariate. Subgroup analysis could not be relied upon because of the high disparity in the number of studies under each subgroup. Varying criteria for assessing TDI as well as lack of longitudinal studies could have underestimated the actual prevalence.
Despite these limitations, this systematic review provides a comprehensive overview of prevalence, associated risk factors of TDI across time and geography compared to other published review in India without any language restriction in the included studies. The burden of TDI varies by geography and appears to be increasing over time. Definitive reasons for the increasing incidence rates of TDI are largely unknown and may be attributed to a greater number of studies being conducted in the last 5 years. Despite several Indian surveys conducted for TDI in the literature, the present systematic review highlights the need for incidence and prevalence data in many regions of India, particularly from the Eastern and North Eastern and Western regions. Future studies in these regions are required for additional insight into the geographic patterns and time trends of TDI that will provide important perceptions into the etiology and may well serve as a foundation for the formulation of an objective universal classification for TDI that would facilitate judging the actual prevalence.
Public Health Significance and Recommendation
This review will help researchers estimate the public health burden of TDI and assist policymakers in the allocation of appropriate healthcare resources and research in specific geographic regions. Simple measures such as identifying high-risk groups and prompting them for orthodontic treatment can curb the incidence of TDI. Parents, teachers, and supervisors must be educated particularly about the potential risk factors of TDI and safeguarding home by padding sharp furniture or corners, carpeting the play area or hall so that the children can be careful at home when left unattended. Further, they must be made aware of consequences of deleterious oral habits, such as chewing on hard objects like pencils or pens that can be preventable. Children and adolescents, especially males, should be informed about risk-taking behavior and to watch out for possible obstruction while playing so that they do not trip down. Also, they must be advised to practice safe and responsible playing without pushing or knocking each other with heavy objects. Maintenance of certain harmonized movement measures in the school classrooms, corridors, or staircases where the children are more likely to get injured due to collision and falls can prevent sudden impact injuries to the teeth. The play area of the schools should be preferably covered with grass and children involved in sports activities should be informed about using mouthguards. Therefore, the results of this study should be considered in the adoption of public health policies and inform further research to the same end preferably with a universal classification for assessing TDI.
The present systematic review reported that the prevalence of dental trauma in permanent teeth among children and adolescents in India was 11% (0.11) (95% CI 0.09–0.13), with a high degree of heterogeneity among studies. Most of the studies presented a moderate–high risk of bias. Male gender, increased overjet, and inadequate lip coverage were observed to be significantly associated with TDI. Also, a qualitative synthesis revealed a positive association of sociodemographic factors, such as rural population, low socioeconomic status, and environmental factors, like place of occurrence and cause of TDI, with TDI. However, the data could not be pooled under the criteria required for meta-analysis. Trends for TDI seem to be increasing with years among children and adolescent population in India. To advance the understanding of the key determinants of TDI, future population-based analytical studies should focus on reporting the incidence and/or prevalence of TDI among marginalized communities.
Author would like to thank Dr Ankit Chandra (Senior Resident, Centre for Community Medicine, AIIMS, New Delhi) for retrieving articles from EMBASE, Dr. Naga Naveena N (Post graduate trainee, Dept. of Oral and Maxillofacial Pathology, SCBDCH, Odisha) for her continuous support and Mr. Shriram Muthuswamy (Lead Data Analyst, SUBEX, Bengaluru) for providing me with all the technical and statistical assistance through every phase of this research.
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