Estimation of sex from metatarsals using discriminant function and logistic regression analyses

Abstract

South Africa has one of the highest crime rates in the world and the discovery of dismembered bodies for human identification process poses a greater challenge. The South African Africans (also known as South African blacks) population group is often the victims of crimes as they are the largest group. While measurements of several bones of the human skeleton have been used for sex estimation, the potential of metatarsals have not been explored in this population group. Metatarsal bones are usually well-preserved since they are recovered in shoes protected from scavengers and they are able to withstand environmental degradation and taphonomy. This study investigated the potential of measurements of metatarsals in sex estimate amongst South African Africans using logistic and discriminant function analysis. Six measurements of metatarsals from 100 individuals of known sex and population affinity from the Raymond Dart Collection of Human skeletons were analysed. Various combinations of measurements of metatarsal bones yielded suitably high average accuracies (79% to 84%) for sex estimation and are comparable to functions derived from other skeletal elements of South African Africans. Metatarsals of South African Africans are therefore useful as alternatives to highly sexual dimorphic bones in the forensic estimation of sex.

Sex prediction with morphometric measurements of first and fifth metatarsal and phalanx obtained from X-ray images by using machine learning algorithms

“…Although the methods used for sex prediction in length measurements performed on dry metatarsal bones and foot phalanx bones are different, it has been found that length measurements show significant difference between genders. As a result of the analysis of these studies, a mean accuracy range varying between 70% and 84% has been shown and it has been found that the results are in parallel with the results of our study [7,8,10,36]. All metatarsal bones show sex based biomechanical differences.…”

“…In another study, the lengths of the metatarsal bones of 100 individuals were used by using Vernier calliper. The measurements were evaluated by using discriminant function and logistic regression analysis and as a result of the evaluation, various combinations of metatarsal bones have been shown to give high mean Acc (between 79% and 84%) for sex prediction [7]. In a study conducted with dry metacarpal and metatarsal bones by using digital calliper for sex prediction, as a result of discriminant functions it was found that the accuracy of metacarpal bones varied between 79% and 85%, while the Acc of metatarsal bones varied between 77% and 83% [41].…”

Evaluasi Perbandingan Performansi LVQ 1, LVQ 2, Dan LVQ 3 Dalam Klasifikasi Jenis Kelamin Menggunakan Tulang Tengkorak

“…Teknik klasifikasi yang paling sering digunakan pada penentuan jenis kelamin adalah Discriminant Function Analysis (DFA) oleh (Omar et al, 2021), dan Logistic Regression (LR) oleh (Bidmos et al, 2021). Dalam beberapa tahun terakhir, identifikasi jenis kelamin juga diterapkan menggunakan Machine Learning (ML) (Toneva et al, 2021).…”

Calculation of likelihood ratios for inference of biological sex from human skeletal remains

“…Use of classification models is common, and binary classification models have long been used to draw inferences with respect to biological sex, e.g., [ [8] , [9] , [10] , [11] , [12] , [13] ]. Commonly used models such as linear discriminant analysis, quadratic discriminant analysis, and logistic regression can output posterior probabilities, but in the forensic-anthropology literature a threshold is usually applied in order to obtain a classification.…”