Title 

Sex Estimation from the Shaft Fragment of Humerus bone from Samples of Central Indian Skeletal Remains.

Authors

Mohammad Nasir Ahmad, Ruma Purkait

 Abstract

Introduction: In medico-legal and disaster distress scenarios, the chances to get fragmentary body/bones are very common. Establishing the biological identity is quite challenging task for the authorities. Assessment of sex from fragmentary bones is one of the important task for medico legal investigators in during the disasters. Therefore, there is an urgent need to develop a population-specific discriminant function (DFA) which can be applied to the Fragmentary region of the bone. Material & Methods: A total of 402 (254 male and148 female) humerus bones were included in the study. The survival of the shaft region found higher compare to the upper and lower epiphysis due to various external factors. In present study only Shaft specific parameters i.e. Least Girth of Shaft, and Circumference at Deltoid Tuberosity were measured. One additional parameter developed i.e. Maximum diameter at deltoid tuberosity was measured and was tested for its efficacy. The statistical analysis done with SPSS version 16.0 and univariate statistics and discriminant function was calculated for all the parameters to reach the best estimation possible. Results: The univariate accuracy percentage to classify the male and female was found 90.1% for Circumference at deltoid tuberosity and 76.2% for least girth of the Shaft. In the non-conventional parameters, maximum diameter at deltoid tuberosity gives 84.4% per cent accuracy. In Stepwise discriminant function analysis, the measured combinations give an accuracy of 88.6 % for male and 94.0% for female whereas in the cross-validation they give 90.5%. Conclusion: The study shows that the parameters on fragmentary shaft of humerus may one of the best indicator for determining the sex of an unknown when no other bones are present.

keywords 

Forensic Science, Forensic Anthropology, Sexual Dimorphism, Deltoid Tuberosity, Mass Disaster, Discriminant Function Analysis.

DOI