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Gender Dimorphism in Maxillary Permanent Canine Odontometrics Based on a Three-Dimensional Digital Method and Discriminant Function Analysis in the Saudi Population.

Authors :
Almugla, Yousef Majed
Madiraju, Guna Shekhar
Mohan, Rohini
Abraham, Sajith
Source :
Applied Sciences (2076-3417); Aug2023, Vol. 13 Issue 16, p9326, 11p
Publication Year :
2023

Abstract

The present study aimed to analyze the gender dimorphism in odontometrics of permanent maxillary canines using a three-dimensional digital method and to test the accuracy in gender estimation using discriminant function analysis in a sample of the Saudi population. A total of 120 diagnostic dental casts of patients aged 16–29 years were used in the present study. Plaster models of their maxillary dentition obtained from the archives were scanned and digitally measured using a three-dimensional digital method. The mesiodistal width of the right and left maxillary canines and intercanine distance were measured. Gender dimorphism was established using the Garn method. Data were statistically analyzed using descriptive statistics, the Mann–Whitney U test and discriminant analyses. Males showed larger mean dimensions of canines than females with regard to both mesiodistal width and intercanine distance, and the difference was statistically significant (p < 0.05). The right maxillary canine mesiodistal width showed a higher percentage of gender dimorphism (3.5%). Discriminant function analysis showed that the overall accuracy of gender prediction was 80.5% for the multivariate analysis. The univariate discriminant function equation revealed that intercanine distance was the most accurate predictor of gender (78%), followed by the right canine mesiodistal width (76.3%). The use of three-dimensional technology for odontometrics presents a promising method, and permanent maxillary canine parameters can be used as an acceptable ancillary tool for gender estimation in forensic science. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
13
Issue :
16
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
170711457
Full Text :
https://doi.org/10.3390/app13169326