Accuracies of discriminant function equations for sex estimation using long bones of upper extremities
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© 2020, Springer-Verlag GmbH Germany, part of Springer Nature. One of the scopes of practice of forensic anthropologists is the estimation of sex from skeletal remains. As a result, population-specific discriminant function equations have been developed from measurements of various bones of the human skeletons. Steyn, Patriquin (Forensic Sci Int 191 (1-3):113, 2009) noted that the lack of skeletal collections and data from most parts of the world has made this process impractical. Previous attempts to develop global discriminant function equations from measurements of the pelvis showed that population-specific equations are not necessary as equations derived from other populations yielded high sex estimation scores when applied to a different population. However, information on the suitability and applicability of generalised equations in sex estimation using long bones is still scarce. It is, therefore, the aim of this study to assess the accuracies of population-specific discriminant function equations derived from measurements of long bones of the upper limb of South African population groups. Data analysed in the current study were obtained from Mokoena, Billings, Bidmos, Mazengenya (Forensic Sci Int 278:404, 2017) and Mokoena, Billings, Gibbon, Bidmos, Mazengenya (Science & Justice 6(59):660–666, 2019) in which a total sample of 988 bones (humeri, radii, and ulnae) of South Africans of African descent (SAAD), South Africans of European descent (SAED) and Mixed Ancestry South Africans (MASA) were measured. Stepwise and direct discriminant function analyses were performed on the pooled data. Each function was used to estimate the sex of cases in each population group separately and average accuracies calculated. Thereafter, population-specific discriminant function equations were formulated for each population group and then applied to other population groups. The average accuracies of functions for pooled data ranged between 80.7 and 86.5%. The cross-validation average accuracies remained unchanged for most functions, confirming the validity of derived functions. A drop in average accuracies (0.8–5.3%) was observed when the functions were tested on a sample of SAAD while increased average accuracy was observed for the SAED and MASA (0.5–6.9%). When population-specific functions for a particular population group were applied to other groups, a wide range of a drop in average accuracies was observed (1.3 to 22.4%). This thereby confirms that population-specific equations should not be applied to other population groups. However, discriminant function equations from the pooled data of South Africans are accurate in the estimation of sex and efforts should be made towards the development and validation of such equations from as many bones of the human skeleton.
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