The main goal of a forensic anthropological analysis of unidentified human remains is to
establish an accurate biological profile. The largest obstacle in the creation or validation of
techniques specific for subadults is the lack of large, modern samples. Techniques created for
subadults were mainly derived from antiquated North American or European samples and thus
inapplicable to a modern South African population as the techniques lack diversity and ignore
the secular trends in modern children. This research provides accurate and reliable methods to
estimate age and sex of South African subadults aged birth to 12 years from long bone lengths
and breadths, as no appropriate techniques exist.
Standard postcraniometric variables (n = 18) were collected from six long bones on 1380
(males = 804, females = 506) Lodox Statscan-generated radiographic images housed at the
Forensic Pathology Service, Salt River and the Red Cross War Memorial Children’s Hospital in
Cape Town, South Africa. Measurement definitions were derived from and/or follow studies in
fetal and subadult osteology and longitudinal growth studies. Radiographic images were
generated between 2007 and 2012, thus the majority of children (70%) were born after 2000 and
thus reflect the modern population.
Because basis splines and multivariate adaptive regression splines (MARS) are
nonparametric the 95% prediction intervals associated with each age at death model were
calculated with cross-validation. Numerous classification methods were employed namely linear,
quadratic, and flexible discriminant analysis, logistic regression, naïve Bayes, and random
forests to identify the method that consistently yielded the lowest error rates. Because some of
the multivariate subsets demonstrated small sample sizes, the classification accuracies were
bootstrapped to validate results. Both univariate and multivariate models were employed in the
age and sex estimation analyses.
Standard errors for the age estimation models were smaller in most of the multivariate
models with the exception of the univariate humerus, femur, and tibia diaphyseal lengths.
Univariate models provide narrower age estimates at the younger ages but the multivariate
models provide narrower age estimates at the older ages. Diaphyseal lengths did not demonstrate
any significant sex differences at any age, but diaphyseal breadths demonstrated significant sex
differences throughout the majority of the ages. Classification methods utilizing multivariate
subsets achieved the highest accuracies, which offer practical applicability in forensic
anthropology (81% to 90%). Whereas logistic regression yielded the highest classification
accuracies for univariate models, FDA yielded the highest classification accuracies for
multivariate models. This study is the first to successfully estimate subadult age and sex using an
extensive number of measurements, univariate and multivariate models, and robust statistical
analyses. The success of the current study is directly related to the large, modern sample size,
which ultimately captured a wider range of human variation than previously collected for
subadult diaphyseal dimensions. / Thesis (PhD)--University of Pretoria, 2013. / gm2014 / Anatomy / unrestricted
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/40263 |
| Date | January 2013 |
| Creators | Stull, Kyra Elizabeth |
| Contributors | L'Abbe, Ericka Noelle, kstullster@gmail.com, Ousley, Stephen D. |
| Publisher | University of Pretoria |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Rights | © 2013 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. |
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