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: x5, the distance between the inner sides of the open apex of the second premolar divided by the tooth length; s ¼ x1 þ x2 þ x3 þ x4 þ x5 þ x6 þ x7, sum of normalized open apices; N0, 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 ¼ 9:402 0:879 C þ 0:663 N0 0:711 s 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% (R2=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.
Age estimation in children by measurement of open apices in teeth: an Indian formula.
CINGOLANI, MARIANO;
2010-01-01
Abstract
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: x5, the distance between the inner sides of the open apex of the second premolar divided by the tooth length; s ¼ x1 þ x2 þ x3 þ x4 þ x5 þ x6 þ x7, sum of normalized open apices; N0, 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 ¼ 9:402 0:879 C þ 0:663 N0 0:711 s 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% (R2=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.File | Dimensione | Formato | |
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