The aim of the present paper was to improve and expand research with a larger number of children from various European countries and to provide a common formula useful for all these countries. Orthopantomographs taken from 2,652 European Caucasian children (1,382 boys, 1,270 girls) aged between 4 and 16 years were analyzed. The children came from Croatia, Germany, Kosovo, Italy, Slovenia, Spain, and the UK. Following the pilot study, subjects' age was modeled as a function of gender (g), morphological variables (predictors) x 5(second premolar), s (sum of normalized open apices) N 0, and the first-order interaction between s and N 0. The results showed that all these variables contributed significantly to the fit, so that all were included in the regression model, yielding the following linear regression formula: Age = 8.387 + 0.282 g - 1.692 x 5 + 0.835 N 0 - 0.116 s - 0.139 s x N 0, where g is a variable, 1 for males and 0 for females. The equation explained 86.1% (R2 = 0.861) of total deviance. The median of the residuals (=observed age minus predicted age) was -0.114 years, with (RefB.2) interquartile range = 1.22 years.

Age estimation in children by measurement of open apices in teeth : a European formula / R. Cameriere, D. De Angelis, L. Ferrante, F. Scarpino, M. Cingolani. - In: INTERNATIONAL JOURNAL OF LEGAL MEDICINE. - ISSN 0937-9827. - 121:6(2007 Nov), pp. 449-453.

Age estimation in children by measurement of open apices in teeth : a European formula

D. De Angelis
Secondo
;
2007

Abstract

The aim of the present paper was to improve and expand research with a larger number of children from various European countries and to provide a common formula useful for all these countries. Orthopantomographs taken from 2,652 European Caucasian children (1,382 boys, 1,270 girls) aged between 4 and 16 years were analyzed. The children came from Croatia, Germany, Kosovo, Italy, Slovenia, Spain, and the UK. Following the pilot study, subjects' age was modeled as a function of gender (g), morphological variables (predictors) x 5(second premolar), s (sum of normalized open apices) N 0, and the first-order interaction between s and N 0. The results showed that all these variables contributed significantly to the fit, so that all were included in the regression model, yielding the following linear regression formula: Age = 8.387 + 0.282 g - 1.692 x 5 + 0.835 N 0 - 0.116 s - 0.139 s x N 0, where g is a variable, 1 for males and 0 for females. The equation explained 86.1% (R2 = 0.861) of total deviance. The median of the residuals (=observed age minus predicted age) was -0.114 years, with (RefB.2) interquartile range = 1.22 years.
age estimation ; dental age ; forensics
Settore MED/43 - Medicina Legale
nov-2007
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/212192
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