A dissertation submitted to the
Faculty of Health Sciences, University of the Witwatersrand,
5 February 2019,
in fulfilment of the requirements for the degree
Master of Science in Medicine / Adult age estimation is of value when creating a biological profile for an unknown set of human remains. Two age estimation methods, the well-known Suchey-Brooks method and the newly introduced Enhanced Computational methods were investigated. Differences between males and females as well as between populations necessitate further research to ascertain whether these methods were accurate enough to be used within a white South African population. A total of 184 well-preserved os coxae were sampled from white South African individuals with known age and sex. The selected os coxae represented male (n=99) and female (n=85) individuals aged 15 to 84 years. The os coxae were subjected to phase analysis, during which the symphyseal surface of the pubis was assigned a phase according to descriptions and pubic symphyseal casts. Following phase analysis, the pubic symphyses were scanned using an Artec Spider 3D scanner. After processing, the laser scans were uploaded into two versions of the forAge program to obtain seven different point estimates for the age-at-death of an individual. The Suchey-Brooks method performed well in a white South African population with statistically significant moderate positive correlations and relatively low biases in both males and females. In contrast, the Enhanced Computational methods performed poorly with weak correlations and higher biases than that observed for the Suchey-Brooks method. The Enhanced Computational methods, however, show a decrease in the intra and inter-observer error typically associated with phase-based methods. Currently, the Suchey-Brooks method can be used in a white South African population, although room for improvement exists. On the other hand, population specific formulae need to be developed for the Enhanced Computational methods before they can used in a white South African population. / E.K. 2019
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/28159 |
| Date | January 2019 |
| Creators | Joubert, Laurette |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | Online resource (112 leaves), application/pdf |
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