Accuracy of methods of age estimation in predicting dental age of preadolescents in South Indian children

Balla, Sudheer B.; Baghirath, P Venkat; Vinay, B Hari; Kumar, Jatin; Babu, Dara Balaji Gandhi

doi:10.1016/j.jflm.2016.07.004

Cited by 28 publications

(12 citation statements)

References 12 publications

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“…Cameriere's European formula was tested in different regions of the world. 7,18,[26][27][28][29][30] The European formula was compared to Willems and Haavikko methods on a sample of 1098 OPTs within age range between 6 and 13 years in the previous study from Bosnia and Herzegovina, DA overestimated for 0.09 years for girls (MAE, 0.53 years) and underestimated by -0.02 years for boys (MAE, 0.55 years), very close to our results of the same age range. 18 Contrary to our study in which we analyzed digital OPTs from a single institution, Galić et al 18 used analog OPTs which were photographed by the digital camera.…”

Section: Discussionsupporting

confidence: 81%

Cameriere’s European formula for age estimation: A study on the children in Bosnia and Herzegovina

Latić-Dautović

Nakaš

Jelešković

et al. 2017

sejodr

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Section: Discussionsupporting

confidence: 81%

Cameriere’s European formula for age estimation: A study on the children in Bosnia and Herzegovina

Latić-Dautović

Nakaš

Jelešković

et al. 2017

sejodr

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“…Age estimation using teeth was studied in India widely [65][66][67][68] . Recently, a study was conducted on South Indian children, where in which the author has tested the accuracy of three age estimation methods 65 .…”

Section: Discussionmentioning

confidence: 99%

“…Recently, a study was conducted on South Indian children, where in which the author has tested the accuracy of three age estimation methods 65 . Despite its slight underestimation of real age, Cameriere's method 69 was proved to be the best method over Willems 70 and Acharya's method 62 .…”

Section: Discussionmentioning

confidence: 99%

Validation of third molar maturity index (I 3M ) for discrimination of juvenile/adult status in South Indian population

Balla

Galić

Karunakar

et al. 2017

Journal of Forensic and Legal Medicine

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Abstract: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 (I3M) specific cut-off value (I3M <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 I3M <0.08 may be a useful additional tool in discrimination of individuals who are around 18 years of age.

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“…The Willems I method’s over/underestimation of age has been well reported worldwide. overestimation of chronological age was validated in a variety of counties or regions such as India [ 33 ],Turkey [ 34 ], Thailand [ 35 ], Spain [ 36 ],Kenya [ 37 ] and Poland [ 38 ]. Elsewhere, there were also reports of underestimation in north China [ 24 ], Tunisia [ 30 ], and Sri Lanka [ 39 ].…”

Section: Discussionmentioning

confidence: 99%

“…They concluded that both methods were appropriate when applied to a French population, although the Willems I method was more accurate according to their data. Another similar study from an Indian population with the Willems II method revealed that the mean values were 0.06 ± 0.80, − 0.11 ± 0.79, and − 0.01 ± 0.80 years for boys, girls, and the total sample, respectively [ 33 ]. Among Tunisian sub-adults [ 34 ], the Willems II method tended to underestimate age by 0.91, and 0.64 years for boys and girls, respectively.…”

Section: Discussionmentioning

confidence: 99%

Comparative assessment of the Willems dental age estimation methods: a Chinese population-based radiographic study

et al. 2022

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Background The comparison of the two Willems dental age estimation methods (gender-specific (Willems I) and non-gender-specific (Willems II)) has not been fully investigated. Here we aimed to explore the applicability of the Willems dental age estimation in an Eastern Chinese population, which may cast light on the field of dental age estimation. Methods A total of 1211 oral panoramic radiographs (582 boys and 629 girls) of the Chinese Han population aged 11–16 years old were collected. Dental ages (DAs) were calculated using the Willems method. Statistical significance was set at a p-value < 0.05. Age differences between chronological age (CA) and dental age were analyzed by paired t-tests and mean absolute error (MAE). Results The differences between CA and DA determined by the Willems I method were + 0.44 and + 0.09 years for boys and girls, respectively. When using the Willems II method, these differences were + 0.57 and − 0.09. The MAEs of the Willems I method between DA and CA were 0.95 and 1.00 years in boys and girls, respectively. For Willems II, MAEs were 1.02 and 1.00 years in boys and girls. Conclusions This study showed that the Willems I method was more accurate than the Willems II method in the boys’ group for predicting age from a whole scale. In comparison, Willems II is more competitive in the girls' group. Neither method may be satisfactory for 11-to-16-year-old teenagers in Eastern China.

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Accuracy of methods of age estimation in predicting dental age of preadolescents in South Indian children

Cited by 28 publications

References 12 publications

Cameriere’s European formula for age estimation: A study on the children in Bosnia and Herzegovina

Cameriere’s European formula for age estimation: A study on the children in Bosnia and Herzegovina

Validation of third molar maturity index (I 3M ) for discrimination of juvenile/adult status in South Indian population

Comparative assessment of the Willems dental age estimation methods: a Chinese population-based radiographic study

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