Gender classification model
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The main purpose of this work is to investigate the application of dental morphological features as a potential qualitative method of sex classification in medico-legal identification. The classification of 16 non-metric dental traits was... more
The main purpose of this work is to investigate the application of dental morphological features as a potential qualitative method of sex classification in medico-legal identification. The classification of 16 non-metric dental traits was performed by ASUDAS (Arizona State University Dental Anthropology System) method. The traits displayed exclusively by the crowns of permanent teeth were analyzed on dental casts of a Portuguese population sample consisting of 53 male and 57 female individuals.
No significant differences (p<0.05) were found between males and females for all investigated traits, except for the dental tubercle of tooth 13, for the metaconule of tooth 27 and the canine distal accessory ridge of teeth 33 and 43. Based on the method applied, tooth 43 has proven to be the most dimorphic among the Portuguese population. Further, a gender classification model using significant different traits between both sexes of the teeth 13, 27 and 43 was developed, and it proved to have a reasonable gender classification reliability (with 76.4 percent of correct classification, Cox & Snell’s pseudo R2 equals to 0.344 and Nagelkerke’s pseudo R2 equals to 0.458) although with a significant probability of misclassification.
No significant differences (p<0.05) were found between males and females for all investigated traits, except for the dental tubercle of tooth 13, for the metaconule of tooth 27 and the canine distal accessory ridge of teeth 33 and 43. Based on the method applied, tooth 43 has proven to be the most dimorphic among the Portuguese population. Further, a gender classification model using significant different traits between both sexes of the teeth 13, 27 and 43 was developed, and it proved to have a reasonable gender classification reliability (with 76.4 percent of correct classification, Cox & Snell’s pseudo R2 equals to 0.344 and Nagelkerke’s pseudo R2 equals to 0.458) although with a significant probability of misclassification.