Sex assessment with the radius in Portuguese skeletal populations (late 19th - early to mid 20th centuries)

Estimation of sex using dimensions around the metatarsal diaphyseal nutrient foramen: Application of discriminant function analysis and logistic regression models

Sex estimation equations are population-specific, and a wider use of multiple bones to generate equations will increase the accuracy of sex estimation in forensic settings. The metatarsal bones have been used previously, however the dimensions around the diaphyseal nutrient foramen have not been utilised in sex estimation. The current study aimed to determine the utility of the dimensions around the nutrient foramen of metatarsal bones in estimating sex in the South Africans of European descent (SAED). Five measurements around the nutrient foramen were taken from a total of 876 metatarsal bones (first to fifth) from 186 individual skeletons (99 males, 87 females) obtained from the Raymond A. Dart Modern Skeletal Collection. Measurements subjected to direct and stepwise discriminant function (DFA) and logistic regression (LRA) analyses included total length, distance from proximal end to nutrient foramen, circumference, and mediolateral and dorsoplantar diameters at the level of the nutrient foramen. The original classification accuracies for multivariable functions of the stepwise and direct DFA ranged from 83.1-88.3% to 85.5-88.3%, respectively. The original classification accuracies for multivariable functions of the stepwise and direct LRA ranged from 83.3%-88.7% to 86.2%-88.3%, respectively. The cross-validation classifications showed a drop of 0-2.4% for DFA and 0.2-1.1% for LRA. The width measurements were better predictors of sex than length. The dimensions around the metatarsal bone nutrient foramen exhibit sexual dimorphism in the SAED. The generated DFA and LRA functions produced high average classification accuracies which are useful in sex estimation during forensic human identification.

Assigned sex estimation with the clavicle and scapula: A study in a Portuguese reference sample

The estimation of biological sex is a critical step in the assessment of the biological profile of an anonymous skeletonized individual. In certain recovery circumstances, the most dimorphic skeletal areas, such as the pelvis, are absent or fragmented; in that case, other bones of the skeleton, including the clavicle and scapula, can be used to predict sex. The purpose of this research is to generate new models for the estimation of sex with clavicular and scapular measurements using a study-sample of 129 individuals with clavicle (65 males and 64 females) and 112 individuals with scapula (50 males and 62 females) from the Lisbon Identified Skeletal Collection (Portugal). A decision tree classifier (C4.5) and logistic regression (LR) were employed to create univariable and multivariable sex prediction models. Accuracy under cross-validation of the classification models is high (up to 93.8%), with minimal bias (<5%), particularly in the multivariable models. The proposed LR models facilitate the probabilistic estimation of biological sex, accounting for the significant overlap in the expression of sexual dimorphism.

A new method for sex estimation based on femoral cross-sectional geometry measurements and its validation using recent and ancient populations

Estimating sex is a fundamental task in biological and forensic anthropology. This study aimed to develop new methods for sex estimation based on femoral cross-sectional geometry (CSG) variables and to test their applicability in recent and ancient assemblages. The sample was divided into a study group (living individuals, N = 124) for creating sex prediction equations and two test groups: living individuals (N = 31) and prehistoric individuals (N = 34). The prehistoric sample was divided into three subgroups according to subsistence strategy (hunter-gatherers, early farmers that also hunted, and farmers and herders). Femoral CSG variables (size, strength, and shape) were measured from CT images using dedicated software. Discriminant functions for sex estimation were calculated for various bone completeness scenarios and validated using the test groups. Size and strength parameters were sexually dimorphic, while shape was not. Discriminant functions for sex estimation produced success rates in the living sample between 83.9 and 93.5%; the distal shaft yielded the highest results. Success rates were lower among the prehistoric test sample, with better results (83.3%) for the mid-Holocene population (farmers and herders) than for earlier groups (e.g., hunter-gatherers; < 60%). These results were compared with those obtained using other methods for sex estimation based on various skeletal elements. This study provides new, reliable, and simple methods with high success rates for sex estimation based on femoral CSG variables obtained automatically from CT images. Discriminant functions were created for various conditions of femoral completeness. However, these functions should be used carefully in past populations from different settings.

Sex assessment using the radius bone in a French sample when applying various statistical models

Sex estimation of skeletal remains is one of the most important tasks in forensic anthropology. The radius bone is useful to develop standard guidelines for sex estimation across various populations and is an alternative when coxal or femoral bones are not available.The aim of the present study was to assess the sexual dimorphism from radius measurements in a French sample and compare the predictive accuracy of several modelling techniques, using both classical statistical methods and machine learning algorithms.A total of 78 left radii (36 males and 42 females) were used in this study. Sixteen measurements were made. The modelling techniques included a linear discriminant analysis (LDA), flexible discriminant analysis (FDA), regularised discriminant analysis (RDA), penalised logistic regression (PLR), random forests (RF) and support vector machines (SVM).The different statistical models showed an accuracy of classification that is greater than 94%. After selection of variables, the accuracies increased to 97%. The measurements made at the proximal part of the radius (sagittal and transversal diameters of the head, and sagittal diameter of the neck), at distal part (maximum width of the distal epiphysis) and of the entire bone (maximum length) stand out among the various models.The present study suggests that the radius bone constitutes a valid alternative for sex estimation of skeletal remains with comparable classification accuracies to the pelvis or femur and that the non-classical statistical models may provide a novel approach to sex estimation from the radius bone. However, the extrapolation of the current results cannot be made without caution because our sample was composed of very aged individuals.