dc.contributor.advisor |
L'Abbe, Ericka Noelle |
|
dc.contributor.coadvisor |
Jantz, Richard L. |
|
dc.contributor.postgraduate |
Krüger, Gabriele Christa |
|
dc.date.accessioned |
2024-02-13T09:47:40Z |
|
dc.date.available |
2024-02-13T09:47:40Z |
|
dc.date.created |
2024-05-03 |
|
dc.date.issued |
2024-02-13 |
|
dc.description |
Thesis (PhD (Anatomy))--University of Pretoria, 2024 |
en_US |
dc.description.abstract |
Constant re-evaluation of standards used in forensic anthropological analyses are necessary,
particularly as new methods are explored or populations change. Even though Indian South
Africans are not a new addition to the South African population, the lack of skeletal material
available for analysis has resulted in a lack of information on the variation present in the crania
of this group. Furthermore, although black, white and coloured South African crania have been
previously researched and standards created, by similarly making use of three-dimensional
(3D) models created from computed tomography (CT) scans, the data are comparable to the
Indian South African data collected and all four groups could be explored simultaneously.
The aim of this project was to use 3D CT models to explore cranial variation in Indian South
Africans when compared to current black, coloured and white South Africans to distinguish
among the groups when estimating sex and population affinity from the cranium.
3D cranial models were created from 409 head CT scans of black, coloured, white and
Indian South Africans (equal sex and population distribution). A total of 42 landmarks were
recorded on each skull. The coordinates were used to assess shape differences using geometric
morphometrics, generalized Procrustes analysis and principal component analysis. Standard
and non-standard interlandmark distances (ILD) were also created from the landmark
coordinate data and assessed using analysis of variance for significant sex and population
differences, and symmetric percent differences for comparisons of the degree of sexual
dimorphism among the different population groups. Furthermore, linear discriminant analysis
(LDA) was used to assess the classification potential of the various ILDs to estimate sex and
population affinity. Four morphoscopic traits were also scored on each cranium according to
the methodology by Walker (2008). The scores were then assessed for their ability to separate between the sexes in each of the population groups using ordinal logistic regression and random forest modelling.
Indian South Africans obtained the highest correct classification rates for sex using morphoscopic traits (95.7%) and demonstrated substantial differences between Indian South African males and females for the ILDs. Similarly, the remaining three population groups had excellent correct classification rates for the morphoscopic traits (88.0% - 91.5%) and sex could be estimated with high rates using ILDs (90.7%). Furthermore, acceptable classification rates were obtained when estimating population affinity for the four South African populations when the ILDs (up to 62.2%) and 3D coordinates (up to 63.8%) were assessed, indicating cranial differences among the four groups. Even though population affinity could be estimated, substantial overlap between coloured, Indian and white South Africans was noted, most likely due to the similarities in genetic influences that have contributed to the various populations.
The assessment of current Indian South Africans as well as the exploration of the cranial variation present in the other three larger current South African populations, was only possible through the use of 3D cranial models created from head CT scans, and was able to provide novel information that can be applied in both biological and forensic anthropology.
Keywords: computed tomography, sex estimation, population affinity, Indian South Africans, cranial variation, morphoscopic, random forest modelling, geometric morphometrics, linear discriminant analysis, interlandmark distances. |
en_US |
dc.description.availability |
Unrestricted |
en_US |
dc.description.degree |
PhD (Anatomy) |
en_US |
dc.description.department |
Anatomy |
en_US |
dc.description.faculty |
Faculty of Health Sciences |
en_US |
dc.description.sdg |
SDG-09: Industry, innovation and infrastructure |
en_US |
dc.identifier.citation |
* |
en_US |
dc.identifier.doi |
10.25403/UPresearchdata.25211171 |
en_US |
dc.identifier.other |
A2024 |
en_US |
dc.identifier.uri |
http://hdl.handle.net/2263/94536 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
University of Pretoria |
|
dc.rights |
© 2023 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
|
dc.subject |
UCTD |
en_US |
dc.subject |
Computed tomography |
en_US |
dc.subject |
Sex estimation |
|
dc.subject |
Interlandmark distances |
|
dc.subject |
Linear discriminant analysis |
|
dc.subject |
Indian South Africans |
|
dc.subject |
Random forest modelling |
|
dc.subject |
Geometric morphometrics |
|
dc.subject |
Population affinity |
|
dc.subject |
Cranial variation |
|
dc.subject |
Morphoscopic |
|
dc.subject |
Sustainable Development Goals (SDGs) |
|
dc.subject |
SDG-09: Industry, innovation and infrastructure |
|
dc.subject.other |
SDG-09: Industry, innovation and infrastructure |
|
dc.subject.other |
Health sciences theses SDG-09 |
|
dc.title |
An evaluation of the cranial variation of Indian South Africans in comparison to other modern South Africans |
en_US |
dc.type |
Thesis |
en_US |