| Autor: |
Yousef Majed Almugla, Guna Shekhar Madiraju, Rohini Mohan, Sajith Abraham |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Applied Sciences, Vol 13, Iss 16, p 9326 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2076-3417 |
| DOI: |
10.3390/app13169326 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
