Evaluation of the Usefulness of Some Mandibular Measurements for Sex and Age Prediction in a Sample of Egyptian Population

Document Type : Original Article

Authors

1 Forensic Medicine and Clinical Toxicology Department, Faculty of Medicine, Tanta University, Egypt.

2 Oral Medicine, Periodontology, Oral Diagnosis and Radiology Department, Faculty of Dentistry, Tanta University, Egypt.

Abstract

The mandible is the largest and strongest bone of the face which can play a role n sex and age identification. The aim of the present study was to evaluate the usefulness of some mandibular measurements in digital dental panoramic radiographs for identification of sex and age in a sample of Egyptian population. Digital panoramic radiographs from 150 Egyptian participants of known age and sex were included. They were used to measure the maximum ramus breadth, minimum ramus breadth, coronoid height and mental index. The four studied measurements’ values were higher in males than in females. Among the four measurements, only maximum ramus breadth was found to contribute significantly for sex prediction. A logistic regression equation for prediction of sex was derived. The four studied measurements showed a strong positive, statistically significant correlation with age in both sexes. Multiple regression analysis was conducted to predict age based on the four measurements. However, the contributions of minimal ramus breadth and coronoid height to the model were not statistically significant. Therefore, only the maximum ramus breadth, mental index in addition to sex were included in the regression model to obtain an equation for age prediction.  It was concluded that the mandible exhibits sexual dimorphism and can be used to predict sex with quite satisfactory results based on measuring the maximum ramus breadth according to the derived equation. Furthermore, the four studied parameters showed a strong positive correlation with age and two of them (the maximum ramus breadth and the mental index) contributed significantly to the age prediction equation

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