Geometric morphometric approach to sex estimation of human pelvis

Abstract

Sex estimation of skeletal remains is an important issue in both forensics and bioarchaeology. The chance of attaining a high level of accuracy regarding sex allocations is related to the skeletal component analyzed and the ability of the techniques employed to describe shape and size differences among the sexes. Current opinion regards the hip bone as the most reliable sex indicator because it is the most dimorphic bone, particularly in adult individuals. The aim of this study was therefore to analyze the greater sciatic notch and the ischiopubic complex morphology by employing geometric morphometric techniques, based on semilandmark and multivariate statistical methods, in order to develop a reliable and accurate technique for adult sex estimation. The sample analyzed consisted of 121 adult left hip bones randomly selected from the collection of documented skeletons housed at the Museu Antropologico de Coimbra. Morphometric analysis was based on coordinates of landmarks and semilandmarks of the ilium and ischiopubic regions that were digitized on 2D photographic images. Discriminant analysis with leave-one-out cross-validation and k-means clustering of shape and shape-size variables were used in order to classify individuals by sex. For the greater sciatic notch, average accuracy of 90.9% was achieved with both multivariate analyses based on shape variables. For the ischiopubic complex, the values obtained with shape variables were 93.4% and 90.1% for discriminant and k-means, respectively. Females were misclassified more frequently than males, especially for the ischiopubic complex. When multivariate statistical analyses were performed using shape-size variables, the percentages of correct classifications were lower than those obtained with shape variables. We conclude that the use of geometric morphometrics and multivariate statistics is a reliable method to quantify pelvic shape differences between the sexes and could be applied to discriminate between females and males.