Determining The Sex of a Person by Odontometric Parameters Using Logistic Regression Equations

Abstract

The development of personal identification methods based on bone remains, which are used to diagnose the population of Azerbaijan, is a priority task due to the unresolved issue. In this scenario, a new method for quickly determining sex by teeth is in demand, as it should increase the efficiency of the work of forensic experts. The purpose of this study was to develop modern methods for diagnosing human sex using odontometric studies. At the craniological collection of Azerbaijanis, the sizes of teeth were studied. On 7 teeth of the upper and 7 teeth of the lower jaw, 3 parameters were measured (in this case, symmetrical teeth were considered as a single array). Each of the 14 anatomical teeth was represented by 80 male and 80 female teeth. For odontometric procedures, a Mutitouyo digital caliper (accuracy 10 microns) was used. The results of odontometry were analyzed by statistical methods using ROC analysis. Mathematical modeling was carried out using the MATLAB statistical software package. With the help of ROC-analysis, the data obtained during odontometry were considered. 6 odontometric signs were established, which are interconnected with gender. The most correlated with gender were the bucco-lingual diameter of the upper canine, as well as the heights of the crowns – the second lower molar, lower incisors, lower canine and upper medial incisor. Using mathematical modeling, we have developed 6 logistic regression equations that can be used to determine the gender of a person by the size of his teeth. The predictive potential of the equations was also evaluated using ROC analysis procedures. As a result of the study, based on odontometric indicators and by using ROC analysis, diagnostic equations were obtained to determine the sex of a person by the size of the teeth. The equations have not yet been verified on independent samples, so they cannot yet be unconditionally recommended for practice. Nevertheless, the authors count on the high legitimacy of their own models due to the fact that they used a fairly powerful mathematical apparatus.