Testing the Validity of Metacarpal Use in Sex Assessment of Human Skeletal Remains

Abstract

To assess the potential of employing metacarpals in assessing sex of human skeletal remains, previous investigators have generated regression equations (Scheuer & Elkington, 1995) and linear discriminant functions (Falsetti, 1995; Stojanowski, 1999) based upon measurements from metacarpals. Results have varied in overall accuracy and which metacarpal produces the greatest accuracy. Using a contemporary sample, this study seeks to evaluate the validity of using metacarpals to assign sex by testing methodologies of previous studies. Measurements defined by previous authors were repeated on metacarpals from 23 adult cadavers and data were subjected to regression equations and linear discriminant analysis according to previous methodologies. Accuracy in sex determination from methods of Scheuer & Elkington (1993) and Falsetti (1995) were lower than originally reported while accuracy from methods of Stojanowski (1999) were higher than previously reported. These results suggest that the use of metacarpals in sex determination may be limited and should be applied cautiously.

Estimation of sex from the metric assessment of digital hand radiographs in a Western Australian population

“…Misclassification may have a flow on effect that reduces the accuracy of the estimation of other biological attributes and ultimately compromise the identification of an individual. Population specific sex estimation standards afford the most accurate possible classification [11,21,28]. Within a forensic context it is particularly important to subject results to statistical interrogation and supply the end-user with a measure of sexual dimorphism and a quantification of the accuracy of the sex estimation standards developed.…”

“…Standards used to analyse morphometric data are thus most accurate when applied to the population from which they are derived [10,11]. Although the pelvis is highly sexually dimorphic, and therefore the preferred element for sex estimation, recent research has worked towards quantifying the sex estimation potential of other skeletal elements [12].…”

“…Previous research has demonstrated that the sternum [9], femur [13], metatarsals [14] and metacarpals [15] can be used to correctly classify sex with a high degree of expected accuracy (above 80%). However, and with specific reference to the hand bones, Burrows et al [11] demonstrated that the application of skeletal standards for metacarpals formulated for one population can be less accurate when applied to another that is geographically removed; this can be attributed to population and temporal differences between the samples specific to each study. When standards are applied inappropriately, the errors highlighted by Burrows et al [11] have a potentially significant impact on the value of anthropological evidence in legal proceedings.…”

“…However, and with specific reference to the hand bones, Burrows et al [11] demonstrated that the application of skeletal standards for metacarpals formulated for one population can be less accurate when applied to another that is geographically removed; this can be attributed to population and temporal differences between the samples specific to each study. When standards are applied inappropriately, the errors highlighted by Burrows et al [11] have a potentially significant impact on the value of anthropological evidence in legal proceedings. It is therefore crucial that population-specific standards are applied.…”

Chacarita Project: Conformation and analysis of a modern and documented human osteological collection from Buenos Aires City – Theoretical, methodological and ethical aspects

“…While the application of these methods has produced satisfactory results in many cases, it is widely recognised that bone manifestations of sex and age are dependent on specific phenotypic and behavioural characteristics in each population (e.g. Alunni-Perret et al, 2003;Asala, 2001;Burrows et al, 2003;Bruzek and Murail, 2006;Ferembach et al, 1980;Kemkes and Göbel, 2006;Mays and Cox, 2000;Ríos Frutos, 2003;Spradley et al, 2008;Ubelaker, 1974Ubelaker, , 2008Wiredu et al, 1999). This means that they are influenced by factors such as ethnicity, physical activity patterns, nutrition, health and socio-economic status (Hamilton, 1982;Luna, 2008;Pucciarelli et al, 1996;Trancho et al, 1997).…”