Postcraniometric analysis of ancestry among modern South Africans

Abstract

The primary role of a physical anthropologist is to provide sufficient information to assist in the individualisation of unknown skeletal remains. This is often achieved in establishing a biological profile of the deceased, of which ancestry is an essential aspect. Several successful osteometric and morphological approaches have been developed to facilitate the estimation of ancestry from the cranium. However, the cranium is not always available for analysis, emphasising a need for postcranial alternatives. The postcranial skeleton is frequently labelled as too variable and unreliable to provide an accurate assessment of ancestry. Yet, numerous studies utilise the postcrania for sex and stature estimation, where the a priori knowledge of ancestry results in higher accuracy. Thus, the presence of postcranial differences among populations when investigating other biological parameters inherently demonstrates the potential for the estimation of ancestry. The purpose of this study was to quantify postcranial variation among modern, peer-reported black, white and coloured South Africans. A series of 39 standard measurements were taken from 11 postcranial bones, namely the clavicle, scapula, humerus, radius, ulna, sacrum, pelvis, femur, tibia, fibula and calcaneus. The sample consisted of 360 modern South African individuals (120 black, 120 white, 120 coloured) from the Pretoria Bone and Kirsten Collections housed at the University of Pretoria and the University of Stellenbosch, respectively. Group differences were explored with ANOVA and Tukey’s honestly significant difference test (HSD). Group means were used to create univariate sectioning points for each variable indicated as significant with ANOVA. Where two of the three groups had similar mean values, the groups were pooled for the creation of the sectioning points. Multivariate classification models were employed using linear and flexible discriminant analysis (LDA and FDA, respectively). Classification accuracies were compared to evaluate which model yielded the best results. The results demonstrated variable patterns of group overlap. Black and coloured South Africans displayed similar means for breadth measurements, and black and white South Africans showed similar means for the maximum length of distal limb elements. The majority of group variation is attributed to differences in size and robusticity, where white South Africans are overall larger and more robust than black and coloured South Africans. Accuracies for the univariate sectioning points ranged from 43% to 87%, with iliac breadth performing the best. However, the majority of the univariate sectioning points can only classify individuals into two groups rather than three because of similar group means. Multivariate bone models created using all measurements per bone resulted in accuracies ranging from 46% to 62% (LDA) and 41% to 66% (FDA). Multivariate subsets consisting of numerous different measurement combinations from several skeletal elements achieved accuracies as high as 85% (LDA) and 87% (FDA). Ultimately the best results were achieved using combinations of different variables from several skeletal elements. Overall, the multivariate models yielded better results than the univariate approach, as the inclusion of more variables is generally better for maximising group differences. Furthermore, FDA achieved higher accuracies than the more traditional approach of LDA. Despite the significant overlap among the groups, the postcranial skeleton has proven to be proficient in distinguishing the three groups. Thus, even in a heterogeneous population, a multivariate postcraniometric approach can be used to estimate ancestry with high accuracy.