Standardization and quality assurance in skeletal landmark placement and osteometry

Studies revising methodology are essential to the development and standardization of the field of anthropology, especially as the ultimate goal is improved forensic analyses. A series of revisions were made to the Standards for Data Collection Procedures reference manual. This includes changes made to the definitions of several standard measurements ranging from modified landmark placement to variation in the proper orientation of the caliper. The aim of this paper was to compare measurements collected using the different sets of definitions to determine if the measurements would differ significantly. Fifteen measurements were collected from 30 crania and postcrania, first using the original definitions, and then using the modified definitions and/or landmarks. The measurement differences for the 2 sets of definitions were assessed using technical error of measurement and a Kruskal-Wallis test. Results indicate that 8 of the 15 measurements differed significantly when the modified definitions were employed. Therefore, data collected using the different sets of definitions should not be used interchangeably. Forensic practitioners and laboratories making use of the updated reference manual must take into consideration how the current results might influence their standard operating procedures. Furthermore, all databases that currently make use of the original measurements, such as the South African-specific databases used in Fordisc, must be updated to include the modified measurements to stay on par with international data collection standards.http://www.elsevier.com/locate/forsciint2021-03-01hj2020Anatom

Population differences in the postcrania of modern South Africans and the implications for ancestry estimation

The cranium is widely recognized as the most important skeletal element to use when evaluating population differences and estimating ancestry. However, the cranium is not always intact or available for analysis, which emphasizes the need for postcranial alternatives. The purpose of this study was to quantify postcraniometric differences among South Africans that can be used to estimate ancestry. Thirty-nine standard measurements from 11 postcranial bones were collected from 360 modern black, white and coloured South Africans; the sex and ancestry distribution were equal. Group differences were explored with analysis of variance (ANOVA) and Tukey’s honestly significant difference (HSD) test. Linear and flexible discriminant analysis (LDA and FDA, respectively) were conducted with bone models as well as numerous multivariate subsets to identify the model and method that yielded the highest correct classifications. Leave-one-out (LDA) and k-fold (k = 10; FDA) cross-validation with equal priors were used for all models. ANOVA and Tukey’s HSD results reveal statistically significant differences between at least two of the three groups for the majority of the variables, with varying degrees of group overlap. Bone models, which consisted of all measurements per bone, resulted in low accuracies that ranged from 46% to 63% (LDA) and 41% to 66% (FDA). In contrast, the multivariate subsets, which consisted of different variable combinations from all elements, achieved accuracies as high as 85% (LDA) and 87% (FDA). Thus, when using a multivariate approach, the postcranial skeleton can distinguish among three modern South African groups with high accuracy.National Research Foundation of South Africa (NRF)http://www.elsevier.com/locate/forsciint2016-12-31hb201

Evaluating the accuracy of cranial indices in ancestry estimation among South African groups

Historically, population differences were quantified using cranial indices. Even though the application of indices is associated with numerous statistical and methodological problems, the use of cranial indices to estimate ancestry persists as demonstrated by its inclusion in several recent papers and conference presentations. The purpose of this study was to classify 207 South African crania and compare the results of five standard cranial indices to linear discriminant analysis (LDA). New sectioning points were created to contend with low classification accuracies (40% - 79%) and possible secular trends. Although the accuracies of the new sectioning points increased (66% - 87%), the accuracies associated with the stepwise LDA were higher (84%) and could classify the crania into one of the three South African groups. The results of the study demonstrate that indices cannot compete with multivariate techniques and should not be used in forensic anthropological analyses for ancestry estimation.http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1556-40292016-09-30hb201

Postcraniometric analysis of ancestry among modern South Africans

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.Dissertation (MSc)--University of Pretoria, 2015.AnatomyUnrestricte

Postcraniometric sex and ancestry estimation in South Africa : a validation study

With the acceptance of the Daubert criteria as the standards for best practice in forensic anthropological research, more emphasis is being placed on the validation of published methods. Methods, both traditional and novel, need to be validated, adjusted, and refined for optimal performance within forensic anthropological analyses. Recently, a custom postcranial database of modern South Africans was created for use in Fordisc 3.1. Classification accuracies of up to 85% for ancestry estimation and 98% for sex estimation were achieved using a multivariate approach. To measure the external validity and report more realistic performance statistics, an independent sample was tested. The postcrania from 180 black, white, and colored South Africans were measured and classified using the custom postcranial database. A decrease in accuracy was observed for both ancestry estimation (79%) and sex estimation (95%) of the validation sample. When incorporating both sex and ancestry simultaneously, the method achieved 70% accuracy, and 79% accuracy when sex-specific ancestry analyses were run. Classification matrices revealed that postcrania were more likely to misclassify as a result of ancestry rather than sex. While both sex and ancestry influence the size of an individual, sex differences are more marked in the postcranial skeleton and are therefore easier to identify. The external validity of the postcranial database was verified and therefore shown to be a useful tool for forensic casework in South Africa. While the classification rates were slightly lower than the original method, this is expected when a method is generalized.The National Research Foundation (NRF).http://link.springer.com/journal/4142020-01-01hj2018Anatom