The utility of mandibular canine index and its components for sex and ancestry determination: a medicolegal perspective

Abstract

Abstract Background Identification is a challenging mission in civil and legal contexts. Teeth, that are resilient to high temperatures and various assaults, hold promise for improved forensic identification methods. While sex identification using canine dental measurements has been extensively studied, more research is needed on ancestry-related variations. Subjects and methods This was a cross-sectional study to assess the role of mandibular canine measurements as sex and ancestry discriminators in 328 subjects (Egyptians and Malaysians). A Medit i700 intraoral scanner device was used to assess the mandibular canine index (MCI), lower canine mesiodistal (MD) width, and lower inter-canine distance (ICD). Results Males exhibit wider MD widths and higher ICDs than females of the same ancestry ( p < 0.001). In contrast, there were no significant sex differences in the MCI in both ancestries. Two proposed sex-predicting models were introduced as follows: $$\widehat{log-odds\ of\ being\ male\ in\ Egyptians }=-49.525+1.4 \left(ICD\right)+53.857\left(Rt. MCI\right)$$ $$\widehat{log-odds\ of\ being\ male\ in\ Malaysians}=-111.578+3.452 \left(ICD\right)+75.524 \left(Rt. MCI\right)$$ The proposed sex-predicting models demonstrated high accuracy, with an area under the curve (AUC) above 0.867. On validation, these models outperformed the standard MCIs in sex prediction. The sex predictive models achieved an overall accuracy of 81.1% in Egyptians and 90.2% in Malaysians, surpassing the standard MCIs in the validation cohort. The model for predicting Egyptian ancestry in males performed well (AUC = 0.839, sensitivity = 88.0, and specificity = 60.8). However, the suggested ancestry predictive model in females showed modest discrimination and lower specificity. Conclusions When considered as individual predictors, the components of MCI demonstrated better sexual dimorphism and improved ancestry discrimination than MCIs. While the introduced models showed promise in determining sex, it is important to note that the ancestry discrimination models should be interpreted cautiously. Further research is needed to generalize these findings and improve the accuracy of ancestry prediction.