Validation of anthropological measures of the human femur for sex estimation in Brazilians

Exploratory analysis of new craniometric measures for the investigation of biological sex using open-access statistical and machine-learning tools on a cone-beam computed tomography sample

Investigation of the biological sex of human remains is a crucial aspect of physical anthropology. However, due to varying states of skeletal preservation, multiple approaches and structures of interest need to be explored. This research aims to investigate the potential use of distances between bifrontal breadth (FMB), infraorbital foramina distance (IOD), nasal breadth (NLB), inter-canine width (ICD), and distance between mental foramina (MFD) for combined sex prediction through traditional statistical methods and through open-access machine-learning tools. Ethical approval was obtained from the ethics committee, and out of 100 cone beam computed tomography (CBCT) scans, 54 individuals were selected with all the points visible. Ten extra exams were chosen to test the predictors developed from the learning sample. Descriptive analysis of measurements, standard deviation, and standard error were obtained. T-student and Mann-Whitney tests were utilized to assess the sex differences within the variables. A logistic regression equation was developed and tested for the investigation of the biological sex as well as decision trees, random forest, and artificial neural networks machine-learning models. The results indicate a strong correlation between the measurements and the sex of individuals. When combined, the measurements were able to predict sex using a regression formula or machine learning based models which can be exported and added to software or webpages. Considering the methods, the estimations showed an accuracy rate superior to 80% for males and 82% for females. All skulls in the test sample were accurately predicted by both statistical and machine-learning models. This exploratory study successfully established a correlation between facial measurements and the sex of individuals, validating the prediction potential of machine learning, augmenting the investigative tools available to experts with a high differentiation potential.

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-moderated relationship between the 2D:4D ratio and circulating hormones in an adult Ghanaian population

The second-to-fourth digit ratio (2D:4D) is the putative marker of prenatal hormone exposure. The 2D:4D ratio or the right-left difference (Dr-l) are said to be negative and positive correlates, respectively, of circulating testosterone and estrogen in both adult males and females. However, previous studies on the subject have reported mixed results. This study aimed to determine the sex-moderated relationship between the 2D:4D ratio and adult circulating testosterone, estradiol, testosterone-to-estradiol ratio and the free androgen index. This was a cross-sectional study from January to June 2021 at the University for Development Studies, Ghana. The study involved 62 participants (Female = 28; Male = 34), aged between 20 and 26 years. The right (2D:4DR), the left (2D:4DL), and their difference (Dr-l) were measured by computer-assisted analysis. Fasting venous samples were assayed for total testosterone (T), estradiol (E2 ), and sex hormone-binding globulin (SHBG) using ELISA. The free androgen index (FAI) was then calculated (T/SHBG) and the data were analyzed using moderated and/or weighted regression. Males had significantly higher T and FAI than females while females had significantly higher E2 than males, which were independent of age and body mass index (p < 0.001). There was a significant SEX*Dr-l interaction on FAI (p = 0.007). The Dr-l correlated negatively with FAI in males but positively in females and accounted for about 94.0% of the variability of FAI in males (adjR2  = 0.940) and only 0.2% in females (adjR2  = 0.002). The 2D:4D ratio, a putative marker of prenatal hormone exposure, may have an impact on sex differences in adult free androgen index.

Testing the validity of population-specific sex estimation equations: An evaluation based on talus and patella measurements

Sex estimation is essential for forensic scientists to identify human skeletal remains. However, the most sexually dimorphic elements like pelvis or skull are not always assessable. Osteometric analyses have proven useful in sex estimation, but also to be population specific. The main purpose of this study was to test the validity of contemporary Greek and Spanish discriminant functions for the talus and the patella, respectively, on a Swiss skeletal sample and to quantify the utility of the measurements as a novel approach in osteometric sex assessment. Four talus and three patella measurements on dry bone were obtained from 234 individuals of the modern cemetery SIMON Identified Skeletal Collection. The previously derived discriminant functions were applied, accuracies determined, the utility of the different measurements was assessed and new multivariable equations constructed. Accuracies varied between 67% and 86% for talus and 63% and 84% for patella, similar to those reported by the original studies. Multivariable equations should be preferred over equations based on single measurements and combining the most significant measurements rather than using several variables obtained the best possible accuracy. The new discriminant functions did not provide a substantial improvement to the original ones. The overall utility of talus and patella is limited, allowing sex estimation with sufficient certainty only in a small proportion of individuals. Discriminant functions developed in contemporary Greek or Spanish populations are in principle applicable also to Swiss contemporary populations. We recommend that at present existent studies of this type should be validated and tested rather than developing new formulas.

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

The assessment of sex is of immense relevance in the analysis of human skeletal remains, as other parameters of the biological profile are usually sex-specific (e.g., age at death or stature). The radius can be used to estimate sex when more dimorphic bones are not available or in the case of incomplete and fragmentary remains. Ten radius measurements collected in a sample of 364 individuals (166 females and 198 males) from the Coimbra Identified Skeletal Collection (late 19th - early 20th centuries) were employed to generate univariable and multivariable models for sex estimation. All models were evaluated with a 10-fold cross-validation method and an independent holdout sample from the Luís Lopes Collection (late 19th - mid 20th centuries) encompassing 50 individuals (25 females and 25 males). Univariable models show an accuracy ranging from 77.7% to 89.8% (cross-validation), and from 70% to 86% (test sample), while accuracy in the multivariable models varies from 88.7% to 93.4% (cross-validation), and 84.0% to 90.0% (test sample). Results suggest that measurements of the radius are useful to develop standard guidelines for sex estimation of anonymous skeletal remains.

Advancements in sex estimation using the diaphyseal cross-sectional geometric properties of the lower and upper limbs

This paper introduces an automated method for estimating sex from the lower and upper limbs based on diaphyseal CSG properties. The proposed method was developed and evaluated using 389 femurs, 412 tibias, and 404 humeri of adult individuals from a modern Greek reference sample, the Athens Collection. The skeletal properties, which were extracted with the CSG-Toolkit, were analyzed with step-wise DFA (evaluated with LOOCV) and subsequently with RBF kernel SVM supervised learning. SVM cross-validation was based on a 20-fold stratified random sample splitting as well as a chronological split based on year of birth to further assess the effect of secular change in sex estimation capacity. Maximum cross-validated classification accuracy from step-wise DFA reached 94.8% for the femur, 94.7% for the tibia, and 97.3% for the humerus, whereas SVM cross-validated results were similar although slightly lower, mainly due to the more strict cross-validation scheme. Our results suggest that the proposed sex estimation method is reasonably robust to secular change, since there was limited loss in classification accuracy between different chronological groups, despite the presence of secular change in stature of the Greek population during the examined period. The proposed method has been implemented as a function for the GNU Octave environment, named estimate_sex, which comprises a self-intuitive graphical user interface for facilitating sex estimation and is freely available under a suitable license.