Univariate sex dimorphism in the Nepalese dentition and the use of discriminant functions in gender assessment

被引:85
作者
Acharya, Ashith B. [1 ]
Mainali, Sneedha
机构
[1] SDM Coll Dent Sci & Hosp, Dept Forens Odontol, Dharwad 580009, Karnataka, India
[2] BP Koirala Inst Hlth Sci, Coll Dent Surg, Dhahran, Saudi Arabia
关键词
forensic odontology; sex determination; odontometrics; Nepal; percentage dimorphism; reverse dimorphism;
D O I
10.1016/j.forsciint.2007.01.024
中图分类号
DF [法律]; D9 [法律]; R [医药、卫生];
学科分类号
0301 ; 10 ;
摘要
Sex dimorphism in the Nepalese dentition is described using univariate and discriminant analyses. Canines showed the greatest univariate sex dimorphism, followed by the buccolingual (BL) dimension of maxillary first and second molars. Overall, the maxillary teeth and BL dimensions showed greater univariate sex differences. However, less than half of the measured variables (46.4%) showed statistically significant differences between the sexes and the magnitude of sex dimorphism was reduced when compared to other populations. Moreover, reverse dimorphism - where females showed larger teeth than males - was observed in the mesiodistal dimension of mandibular second premolars. This reflects reduction in sexual dimorphism observed through human evolution and the consequent overlap of tooth dimensions in modem males and females. A specific purpose of the study was to develop discriminant functions to facilitate sex classification. A group of functions were developed considering the possibility of missing teeth and/or jaws in forensic scenarios. The functions permitted moderate to high classification accuracy in sexing (67.9% using maxillary posterior teeth; 92.5% using teeth from both jaws). The superior expression of sex dimorphism by means of discriminant functions is in contrast to the univariate results. This is due to discriminant analysis utilising the inter-relationship between all teeth within a dentition-these tooth correlations are not utilised in univariate analysis which results in a loss of information. It is inferred that large-scale statistically significant univariate differences are not a prerequisite for sex assessment. (C) 2007 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:47 / 56
页数:10
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