GEOMETRIC MORPHOMETRIC ANALYSES TO QUANTIFY SEXUAL DIMORPHISM IN THE ADULT MANDIBLES IN MODERN MALAYSIAN AND WESTERN AUSTRALIAN POPULATIONS

The adult mandible can be used to estimate sex and ancestry. However, there are limited studies on the degree of sexual dimorphism and population affinity of the mandible, while population-specific anthropological standards are essential for forensic human identification. This study aimed to quantify sexual dimorphism and population affinity in adult mandibles in modern Malaysian and Western Australian populations. A total of 101 CT scans of the mandible were used in this study, consisting of male and female of Malaysian and Western Australian origins. Thirty-two anatomical landmarks were collected, where the centroid size and PCA analysis were used to quantify the size and shape variations between sexes and between populations. Classification accuracy rates were calculated using DFA. There were significant differences between sexes in all groups for centroid size and PCA (p < 0.05), and between populations for PCA (p < 0.001). Classification accuracy rates were higher for sex estimation from centroid size (91-93%) and ancestry estimation from PCA (89-94%). Male mandibles were larger than females, and the mandibular condyles, ramus breadth, and gonial angle were the most sexually dimorphic features. For population affinity, size did not contribute significantly, but Malaysian mandibles tended to display more “feminine” features while Western Australians appeared to be more “masculine”, indicating that different populations have different gradations of sexual dimorphism. Geometric morphometric analyses can be used to estimate sex and ancestry from adult mandibles. The estimations of sex and ancestry are more accurate when performed separately rather than simultaneously, where mandibular size is more accurate for sex estimation, while the shape variations are more accurate for distinguishing between populations. Keywords: ancestry estimation; geometric morphometric; mandible; population variation; sex estimation; sexual dimorphism.