Sex prediction according to digital analysis of the morphological characteristics of maxillary posterior teeth in a Pakistani population

• Main Authors: Riaz, Samiya, Atif, Saira, Syed, Sadia, Rafi Chaudhry, Asma, Zahid, Erum
• Format: Article
• Language: English; English
• Published: Elsevier Ltd 2024
• Subjects: K Law (General); K5000 Criminal Law; RK Dentistry
• Online Access: http://irep.iium.edu.my/114754/7/114754_Sex%20prediction%20according%20to%20digital%20analysis.pdf; http://irep.iium.edu.my/114754/13/114754_Sex%20prediction%20according%20to%20digital%20analysis_SCOPUS.pdf; http://irep.iium.edu.my/114754/; https://www.sciencedirect.com/science/article/pii/S1658361224001100/pdfft?md5=684cd26ad7d63d6fa022e836cf018149&pid=1-s2.0-S1658361224001100-main.pdf; https://doi.org/10.1016/j.jtumed.2024.09.002

Objective Researchers have examined several dental characteristics to identify differences in tooth morphology between males and females in various populations. Nevertheless, no research has been undertaken to ascertain sexual dimorphism and develop a sex prediction model by using the groove pattern, cusp number and occlusal pattern in any population group. Therefore, this study accessed the sexual differences and the ability to predict sex according to these characteristics of maxillary teeth in the Pakistani community. Method A total of 130 dental casts were selected (65 each from males and females). Digital images of the occlusal surface of the maxillary first premolar, second premolar and first molar were captured with a Canon Powershot A2200 14.1 MP digital camera with 4× optical zoom. Cusp number, groove pattern and occlusal pattern were recorded for each tooth type. Data were analysed with chi-square tests and logistic regression analysis. Results The groove pattern and occlusal pattern of the maxillary first premolar and first molar showed significant sexual dimorphism (p < 0.05). The cusp number of the maxillary first molar also displayed a statistically significant difference between males and females (p < 0.05). The sex prediction accuracy was 76.7% for the training samples and 70% for the test samples. Conclusion We observed significant sexual dimorphism in the groove pattern and the occlusal pattern of the maxillary first premolar and maxillary first molar teeth, as well as the cusp number of the maxillary first molar teeth. The prediction model demonstrated good accuracy, at 76.7%, and hence can be used for sex prediction in the Pakistani population.