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

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.

Retrospective evaluation of the morphometric properties of intact maxillary sinus using cone-beam computed tomography for sex estimation in an Indian population

Background

Sex estimation is crucial to forensic examinations. In order to estimate sex, intact bones are used if the majority of bones are severely deformed and recovered in fragments. This study aims to analyze sexual dimorphism in intact maxillary sinuses using CBCT scanning to evaluate morphometric properties for sex identification.

Methods

A total of 318 subjects, consisting of 159 males and 159 females, aged between 20 and 60 years without sinus pathology were included in this diagnostic, retrospective cross-sectional study. Bilateral measurements of the volume, height, width, and length of the maxillary sinuses were obtained and compared to evaluate the differences between sexes. Subsequently, a descriptive analysis using mean and standard deviation was performed, followed by a comparison between sexes with a p-value being less than 0.05 and Student's t-test. Finally, a discriminant analysis was performed separately for the right and left maxillary sinuses.

Results

Males and females showed statistically significant variations in the length, width, and volume of the maxillary sinuses. Specifically, on the right side, males had longer maxillary sinuses than females (t = 5.6203, p < 0.0001). Meanwhile, on the left side, females had wider maxillary sinuses than males (t = 8.621, plt0.0001). In addition, males had greater volumes of maxillary sinuses on the right (t = 6.373, p < 0.0001) and left (t = 3.091, p < 0.0001) sides than females. The results of the discriminant analysis showed that the left width parameter had the highest accuracy of sex estimation (74.21%), followed by the Right Length (70.07%) and left volume (66.66%) parameters. The left height parameter had the lowest accuracy of sex estimation (49.37%).

Conclusion

In forensic odontology, the volume of maxillary sinus can serve as a valid radiographic indicator of sex estimation.

Tarsals from the Sima de los Huesos Middle Pleistocene site (Atapuerca, Burgos, Spain)

Here, we provide a complete, updated, and illustrated inventory, as well as a comprehensive study, of the tarsals (rearfoot) recovered from the Middle Pleistocene site of Sima de los Huesos (SH, Atapuerca, Spain) in comparison to other Homo comparative samples, both extant and fossil. The minimum number of individuals (MNI) estimated from the tarsals has been established as 15, which represents 51.7% of the 29 dental individuals identified within the SH sample. Within the SH hominin foot sample, an exclusive combination of primitive or plesiomorphic and derived or autapomorphic traits can be observed when compared with other Homo individuals/populations. Other characters are shared among SH hominins and Neandertals that might represent shared derived or autapomorphic traits for this evolutionary line, and most are likely related to robusticity (e.g., rectangular-like trochlea of the talus, broad calcanei, broad naviculars, and short lateral cuneiforms). Additionally, we observed some exclusive autapomorphic traits in the SH tarsal sample (e.g., narrow head of the talus and short intermediate cuneiforms). A few exclusive traits in SH tarsal remains are even more robust than in Neandertals (e.g., broad lateral malleolar facet in talus, more projected sustentaculum tali, and broad medial cuneiform). These traits could suggest a slightly higher level of gracilization in the tarsal bones of Neandertals compared to the SH sample that is also supported by other anatomical postcranial skeleton elements. Additionally, some paleobiological inferences are made in relation to body size (stature and body mass) and some associations are proposed within the SH sample. In conclusion, the morphology of the SH tarsi confirms an evolutionary relationship of sister groups between this population and Neandertals, probably representing a morphotype similar to the Neandertal ancestors.

Metatarsals and foot phalanges from the Sima de los Huesos Middle Pleistocene site (Atapuerca, Burgos, Spain)

This study provides a complete, updated and illustrated inventory, as well as a comprehensive study, of the metatarsals and foot phalanges (forefoot) recovered from the Middle Pleistocene site of Sima de los Huesos (SH, Atapuerca, Spain) in comparison to other Homo comparative samples, both extant and fossils. This current updated review has established a minimum number of individuals (MNI) of 17, which represent 58.6% of the 29 dental individuals identified within the SH sample. An exclusive or autoapomorphic combination of traits can be recognized within the SH hominin foot sample. A few traits appear primitive or plesiomorphic when compared with earlier Homo individuals and other recent modern humans. There are other metrical and morphological traits that SH hominins and Neandertals have in common that sometimes represent shared derived traits in this evolutionary line, most of which are probably related to robusticity. Furthermore, some exclusive autoapomorphic traits are observed in the SH sample: a very broad first metatarsal, long and broad hallucal proximal foot phalanges and possibly extremely robust lateral distal foot phalanges compared to those of Neandertals and modern humans. In these last traits, the SH metatarsals and pedal phalanges are even more robust than in Neandertals. They are herein named as "hyper-Neandertal" traits, which could suggest a slight gracilization process in this evolutionary line, at least in the hallux toe. Finally, some paleobiological inferences are made in relation to body size (stature and body mass) and some associations are proposed within the SH sample.

Sex estimation using measurements of the proximal femur in a historical population from Poland

Sex estimation is one of the most important components in assessing the biological profile of an individual. In an archaeological context, the pelvis, which is the most dimorphic part of the skeleton, is often poorly preserved, which can cause an inability to use morphological sex estimation methods. Therefore, alternative methods are required in such cases. Because the utility of the metric methods based on the femur measurement has been confirmed, and the bone is usually available for examination due to its good preservation, developing methods using the landmarks of the femur could have important implications in sex estimation.   This study aimed to derive a discriminant function equation for a Polish archaeological population based on measurements of the proximal end of the femur.   The study sample included individuals from a medieval cemetery in Milicz (n = 62) and an early modern necropolis at Czysty Square in Wrocław, Poland (n = 162). The analysis included seven measurements collected from the right and left proximal femora. To estimate the reproducibility of the measurements, intra-and interobserver errors and reliability coefficients were calculated. Subsequently, univariate and stepwise discriminant analyses were performed, and the sex sectioning points and equations were proposed.   No differences were observed between measurements of the right and left femora. The results indicated a high utility and reproducibility of the FHD measurement (regardless whether left or right femur was measured). The discriminant equations for sex estimation reached an accuracy of 83.0–92.3%, which implies the utility of the function on Polish historical populations when the other methods for sex estimation cannot be used. 

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

It is common in forensic anthropology to draw inferences (e.g., inferences with respect to biological sex of human remains) using statistical models applied to anthropometric data. Commonly used models can output posterior probabilities, but a threshold is usually applied in order to obtain a classification. In the forensic-anthropology literature, there is some unease with this "fall-off-the-cliff" approach. Proposals have been made to exclude results that fall within a "zone of uncertainty", e.g., if the posterior probability for "male" is greater than 0.95 then the remains are classified as male, and if the posterior probability for "male" is less than 0.05 then the remains are classified as female, but if the posterior probability for "male" is between 0.05 and 0.95 the remains are not classified as either male or female. In the present paper, we propose what we believe is a simpler solution that is in line with interpretation of evidence in other branches of forensic science: implementation of the likelihood-ratio framework using relevant data, quantitative measurements, and statistical models. Statistical models that can implement this approach are already widely used in forensic anthropology. All that is required are minor modifications in the way those models are used and a change in the way practitioners and researchers think about the meaning of the output of those models. We explain how to calculate likelihood ratios using osteometric data and linear discriminant analysis, quadratic discriminant analysis, and logistic regression models. We also explain how to empirically validate likelihood-ratio models.

Accuracies of discriminant function equations for sex estimation using long bones of upper extremities

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.

Missing Value Imputation in Stature Estimation by Learning Algorithms Using Anthropometric Data: A Comparative Study

Estimating stature is essential in the process of personal identification. Because it is difficult to find human remains intact at crime scenes and disaster sites, for instance, methods are needed for estimating stature based on different body parts. For instance, the upper and lower limbs may vary depending on ancestry and sex, and it is of great importance to design adequate methodology for incorporating these in estimating stature. In addition, it is necessary to use machine learning rather than simple linear regression to improve the accuracy of stature estimation. In this study, the accuracy of statures estimated based on anthropometric data was compared using three imputation methods. In addition, by comparing the accuracy among linear and nonlinear classification methods, the best method was derived for estimating stature based on anthropometric data. For both sexes, multiple imputation was superior when the missing data ratio was low, and mean imputation performed well when the ratio was high. The support vector machine recorded the highest accuracy in all ratios of missing data. The findings of this study showed appropriate imputation methods for estimating stature with missing anthropometric data. In particular, the machine learning algorithms can be effectively used for estimating stature in humans.