Population overlap and the variation within and among populations have been globally observed but is often difficult to quantify. To achieve this, numerous different methods need to be explored and validated to assist with the creation of an accurate biological profile. The current lack of databases for postcranial macromorphoscopic traits indicates the need to further investigate if the method can be employed repeatably in a forensic context. The current study aimed to assess the prevalence of eleven postcranial macromorphoscopic traits in a South African sample. A total of 271 postcrania of adult black, coloured, and white South Africans were assessed. The intra- and inter-observer agreement ranged from fair to almost perfect except for the accessory transverse foramen of C1, which had poor agreement between observers. Only seven traits differed significantly between at least two of the groups. Univariate and multivariate random forest models were created to test the positive predictive performance of the traits to classify population affinity. The classification accuracies for the univariate models ranged from 33.3% to 53.0% and ranged from 54.6% to 62.1% for the multivariate models. Based on the variable importance, the traits assessing spinous process bifurcation were the most discriminatory variables. The results indicate that the postcranial MMS approach does not outperform current methods employed to estimate population affinity. Further research needs to be done for the method to have practical applicability for medicolegal casework in South Africa.
Keywords: Classification accuracy; Forensic anthropology; Observer agreement; Population affinity; Random Forest Modelling; Variable importance.
Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.