Worldwide Population Variation in Pelvic Sexual Dimorphism: A Validation and Recalibration of the Klales et al. Method ☆

Research paper by Michael W. Kenyhercz, Alexandra R. Klales, Kyra E. Stull, Kyle A. McCormick, Stephanie J. Cole

Indexed on: 13 May '17Published on: 08 May '17Published in: Forensic Science International


Sex estimation is an integral aspect of biological anthropology. Correctly estimating sex is the first step to many subsequent analyses, such as estimating living stature or age-at-death. Klales et al. (2012) provided a revised version of the Phenice (1969) method that expanded the original three traits (ventral arc, subpubic concavity/contour, and medial aspect of the ischio-pubic ramus) into five character states to capture varying degrees of expression within each trait. The Klales et al. (2012) method also provided associated probabilities with each sex classification, which is of particular importance in forensic anthropology. However, the external validity of this method must be tested prior to applying the method to different populations from which the method was developed. A total of 1,915 innominates from four diverse geographic populations: 1) U.S. Blacks and Whites; 2) South African Blacks and Whites; 3) Thai; and 4) unidentified Hispanic border crossers were scored in accordance with Klales et al. (2012). Trait scores for each innominate were entered into the equation provided by Klales et al. (2012) for external validation. Additionally, recalibration equations were calculated with logistic regression for each population and for a pooled global sample. Validation accuracies ranged from 87.5–95.6% and recalibration equation accuracies ranged from 89.6% − 98% total correct. Pooling all samples and using Klales’ et al. (2012) equations achieved an overall validation accuracy of 93.5%. The global recalibration model achieved 95.9% classification accuracy and can be employed in diverse worldwide populations for accurate sex estimation without the need for population specific equations.