Teeth are unique in structure and follow a well-defined sequential developmental pattern. Moreover, teeth are most indestructible components of the body because of its resistivity against most of the environmental abuses. Forensic Age Estimation is an expertise in forensic medicine which aims to define in the most accurate way the chronological age of person of an unknown age involved in judicial or legal proceedings.
Age estimation using the dentition can be grouped into 3 phases (Azaz et al., 1974). Age estimation in prenatal, neonatal and early postnatal child, age estimation in children and adolescents and age estimation in adults (Pretty, 2003). The principal method of age estimation differs in each age group. Thus choice of method is inherently related to whether unidentified remains are those of a juvenile or an adult, the former being primarily based on developmental, and the latter degenerative, morphological features. So the present study, as it is an invasive method, can be used for age estimation in adults with degenerative features (Franklin, 2010).
To the best of our knowledge, this is the first study to estimate age in Kerala population by scoring coronal displacement of cementum in impacted mandibular third molar teeth.
Study done by Bocutog et al. in 1997 showed that there is a significant linear correlation between age and coronal displacement of cementum in impacted teeth (Bocutog and Yakan, 1997). This may be related to continually erupting forces which affect the impacted teeth and may be a mechanism by which the teeth are protected at the cemento enamel junction. In impacted tooth, it was found that as age advances, there is a relative apposition of cementum, coronally. This may be related to continually erupting forces which affect the impacted teeth. As a result of local disruptions in the reduced enamel epithelium that permit follicular cells to come into contact with the enamel surface and differentiate into cementoblasts, such, appositions of cementum on the coronal surface of teeth is possible (Nanci, 2007).
In contradictory to this, a study done by Balwant et al. in 2006 and Raju et al. in 2016 in erupted mandibular third molar teeth, found no significant correlation between age and coronal displacement of cementum in erupted teeth because erupted teeth were found to be directly exposed to external environmental factors (Rai et al., 2006; Raju et al., 2016).
In the present study in Kerala population, the Pearson’s correlation coefficient value between known age and coronal displacement of cementum in impacted mandibular third molar was found to be strongly positive with a correlation coefficient of 0.832 and significant at the 0.001 level. This indicate that coronal displacement of the cementum showed significant increase with age. The study done by Sharma et al. and Rai et al. also supported this (Sharma et al., 2010; Rai and Annad, 2009). But this value is superior to the value observed by Bocutog et al. in impacted maxillary canines in Turkish population (r = 0.69) (Bocutog and Yakan, 1997). This discrepancy may be due to difference in teeth and the ethnicity of the population studied. However the value obtained from the present study was comparable to the value observed by Rai et al. in impacted mandibular third molar in Nepalese population (r = 0.89) (Rai, 2009a). This observations indicated that age and coronal displacement of cementum in impacted teeth also showed a racial difference and validate more studies in different races to establish their influence in coronal displacement of cementum in impacted teeth with increase in age.
In the present study we formulated a regression equation using the scores to estimate age from impacted mandibular third molar teeth in our population.
$$ \mathbf{Age}=\mathbf{2.387}\ \mathbf{x}\ \mathbf{CDC}+\mathbf{20.278} $$
There was significant difference between the present regression formula and the previous equation formulated for North Indian Population. This may be attributed to difference in genetic factors, nutritional factors and geographical factors (Rai, 2009b).
The average age difference between known and estimated age in this study was found to be ±5.28 years. In forensic cases, an error of ±10 years of age is considered as an acceptable range (Talreja et al., 2012). In Gustafson’s method the average error was just ±3.6 years. However when Pillai and Bhaskar applied Gustafson’s method on an Indian population they obtained an average error rate of about ±8 years (Ashith and Acharya, 2014).
