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• Consistent overestimation of age was reported when Demirjian's method was applied. • Use of third molar maturity index (I 3 M) as age marker was tested for first time. • Regression models were derived using I 3 M as independent and age as dependent variable. • Overestimation in age by 0.2 years in boys and 0.13 years in girls was observed. • We conclude by recommending new regression models to estimate age in children and sub-adults. This paper concerns a method to estimate age in children using third molar maturity index (I 3 M) as independent variable and age as the dependent variable. Total of 1283 digital orthopantomograms (OPTs) of south Indian children aged between 7 and 22 years was included. Training sample of 933 OPTs was used to derive regression formulae, and validation sample of 350 OPTs used to verify accuracy of newly derived regression models. Regression analysis performed revealed that cubic function gave the best correlation between the studied variables. The models exhibited a high correlation coefficient for third molar development in both sexes (0.81 for boys and 0.84 for girls). When new models were verified, slight overestimation of dental age i.e., 0.2 years in boys and 0.13 years in girls was observed. Therefore, we conclude by recommending newly derived regression models as they provided better age predicting performances. [ABSTRACT FROM AUTHOR]

• Age of 14 years is set to determine the minimum age for criminal responsibility. • Maturity index (IPM) of mandibular first and second premolars was studied. • Cut-off values of IPM 1 < 0.01 and IPM 2 < 0.02 for both teeth were determined. • The combined predictor IPM 1 + IPM 2 < 0.02 shows the highest specificity and better probability. • Mineralization of first and second premolars could be useful in predicting age over 14 years. Age estimation is an integral part of forensic medical and dental practice. In many countries, the age threshold of 14 years is set to determine the minimum age for criminal responsibility. In the present study, the authors studied the final maturation of the first (IPM 1) and second mandibular premolars (IPM 2) by Cameriere maturity index and determined cut-offs at the age threshold of 14 years, and validate on the test sample. Orthopantomograms of 960 healthy south Indian children and sub-adults (480 boys and 480 girls) aged between 10 and 18 were analysed, 640 as training sample and 320 as a test sample. The results of logistic regression analysis with age (

Providing appropriate legal mechanisms, that evaluate the progression of development from the age of childhood innocence to maturity and full responsibility, considered one of the difficult areas of criminal justice policy. The minimum age of criminal responsibility (MACR) in children varies among countries and differs widely owing to history and culture. Due to rising and brutality of criminal offenses, particularly by juveniles, few countries have lowered the minimum age of criminal responsibility, and many have considered/considering to do the same. India is one such country in which is under the proposal of lowering the age of criminal responsibility to 16 years. As there is lack of useful age assessment methods, that can indicate whether if the individual in question is younger (<16 years) or older than MACR (≥16 years), the present study was undertaken to derive a specific cut-off value of the third molar maturity index (I 3M ) for this purpose. The sample consisted of 1078 orthopantomograms (OPTs) from Andhra Pradesh, India, aged between 11 and 20 years (45.4% males and 54.6% females). The reproducibility of I 3M was calculated by intra-class correlation coefficients, which showed an intra-rater and inter-rater agreement of 0.912 and 0.891, respectively. The sample was divided into training dataset (819 OPTs), to test I 3M and gender as independent variables and MACR as a dependent variable by logistic regression analysis, and test dataset (259 OPTs). A receiver operating curve (ROC) analysis was performed to evaluate the specific cut-off value of I 3M for predicting MACR status. A logistic regression analysis showed that gender was not statistically significant for predicting MACR status while ROC analysis indicated a cut-off value of I 3M  = 0.293 as best for predicting MACR status. The performance of derived cut-off value was tested in a test data set. The sensitivity of the test was 90.6% and 90%, while specificity was 86% and 87.1% in males and females, respectively. The proportion of correctly classified individuals was 88.0% and 88.7% in males and females, respectively. The estimated Bayes post-test probability in males was 87.2% and while in females it was 88.3%. The results highlight the contribution of the derived cut-off value of I3M for discriminating individuals around MACR and should be evaluated in other populations., (Copyright © 2019 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.)

Deliberate falsification of age was considered to be one of the main reasons for forensic age estimation of the living individuals. This posed to be a challenging task during criminal and legal proceedings, and ultimate care must be taken not to classify juveniles as adults. Third molars are the only developing teeth during late adolescence and early adulthood. Our study was designed to analyze the usefulness of the third molar maturity index (I 3M ) specific cut-off value (I 3M  < 0.08) to discriminate adults (≥18 years) and juveniles (<18 years) in South Indian children. 216 panoramic radiographs (114 females and 102 males) of living subjects aged between 14 and 21 years were analyzed. Our results demonstrated high sensitivity (83.3% and 90.2%) and specificity (98.3% and 95.1%) for females and males respectively. The positive likelihood ratios of being adult were 50.00 and 18.35 while the negative likelihood ratios were 0.17 and 0.10 in females and males respectively. The estimated posttest probability was 98.0% in females and 94.8% in males. The obtained results showed that the specific cut-off value of I 3M  < 0.08 may be a useful additional tool in discrimination of individuals who are around 18 years of age., (Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.)

The aim of this paper is twofold: first, to evaluate an Indian sample by Cameriere's European formula; and second, if this formula turns out to be unsuitable, to study a specific formula for Indian children. Orthopantomographs taken from 480 Indian children (227 girls and 253 boys) aged between 3 and 15 years were analyzed. Following the pilot study, subjects' age was modeled as a function of gender (g), region of country (C), and morphological variables (predictors: x (5), the distance between the inner sides of the open apex of the second premolar divided by the tooth length; s=x1+x2+x3+x4+x5+x6+x7, sum of normalized open apices; N (0,) the number of teeth with root development complete. Results showed that all these variables except gender and second premolar contributed significantly to the fit so that all were included in the regression model, yielding the following linear regression formula: Age=9.402-0.879C+0.663 N0-0.711s-0.106s N0 where C is a dummy variable equal to 0 for the center or north of India and 1 for the south. The above equation, with the variables considered, explained 89.7% (R (2) = 0.897) of total deviance. The median of the residuals (observed age minus predicted age) was -0.063 years, with an interquartile range of 1.10 years.