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ABSTRACT

  • 1Ndlebe TC,
  • 2Adebesin AA
  • 1Department of Human Anatomy and Histology, School of Medicine, Sefako Makgatho Health Sciences University, South Africa
  • 2Department of Human Anatomy and Histology, School of Medicine, Sefako Makgatho Health Sciences University, South Africa

Background

BACKGROUND AND OBJECTIVES:
Accurate sex estimation from fragmentary human remains is a significant challenge in forensic investigations, especially in South Africa with high levels of criminality, including body dismemberment, which contributes to the demand for a reliable identification method of unidentified bodies. Anthropometric measurements, especially of the lower leg and shoulder, offer a non-invasive approach to sex estimation in such contexts. The aim of this study was to investigate the usefulness of anthropometric measurements of the lower leg and shoulder for sex estimation in a black South African population. In
addition, the study also sought to identify the most appropriate statistical method by assessing the accuracy and reliability of the regression equations compared to
alternative techniques.

Method

BACKGROUND AND OBJECTIVES:
Accurate sex estimation from fragmentary human remains is a significant challenge in forensic investigations, especially in South Africa with high levels of criminality, including body dismemberment, which contributes to the demand for a reliable identification method of unidentified bodies. Anthropometric measurements, especially of the lower leg and shoulder, offer a non-invasive approach to sex estimation in such contexts. The aim of this study was to investigate the usefulness of anthropometric measurements of the lower leg and shoulder for sex estimation in a black South African population. In
addition, the study also sought to identify the most appropriate statistical method by assessing the accuracy and reliability of the regression equations compared to
alternative techniques.

Result

RESULTS:
Univariate logistic regression achieved 76.12% accuracy for males and 75.76% for females, with right sitting shoulder height and left sitting knee height as significant
predictors. Multivariate logistic regression identified shoulder breadth and left sitting popliteal height as significant variables (p<0.05). Discriminant function analysis
demonstrated classification accuracy of 79.4% for males and 76.47% for females, with right sitting shoulder height and left sitting knee height as the most influential
parameters.

Conclusion

CONCLUSION:
Anthropometric measurements of the lower leg and shoulder regions provide reliable sex estimation in the South African population. Both logistic regression and discriminant analysis offer comparable accuracy and support their use in forensic identification, especially for fragmented remains.
Author Image

PRESENTING AUTHOR

Mr. Tshepo Ndlebe, MSc in Anatomy (To be completed)
, BSc Hons Psych (completed), BSc (Occupation and Environmental Health Sciences) (completed).

Student, Sefako Makgatho Health Sciences University

Tshepo Ndlebe is a part-time Junior Lecturer and a final-year Master of Science candidate in the Department of Anatomy and Histology at Sefako Makgatho Health Sciences University in Pretoria, South Africa. He holds a Bachelor of Science in Occupational and Environmental Health Sciences as well as an Honours degree in Psychology, equipping him with a strong interdisciplinary background that integrates both the behavioral and biological sciences. His current postgraduate research focuses on the anthropological application of anthropometric data for forensic purposes—specifically investigating the accuracy of lower leg and shoulder breadth measurements in estimating sex within a Black South African population. This study aims not only to explore the forensic utility of these indicators but also to critically evaluate the statistical methods used in biological profiling by comparing the performance of traditional regression analysis with alternative techniques. Through this work, he seeks to contribute toward the development of more population-specific, reliable, and scientifically robust methods for sex estimation in forensic and anthropological contexts.
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