Sex estimation in a contemporary Turkish population based on CT scans of the calcaneus

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Ekizoglu O., Inci E., Palabiyik F. B., CAN İ. Ö., Er A., Bozdag M., ...More

FORENSIC SCIENCE INTERNATIONAL, vol.279, 2017 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 279
  • Publication Date: 2017
  • Doi Number: 10.1016/j.forsciint.2017.07.038
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: Forensic Anthropology Population Data, Sex estimation, Calcaneus, Turkey, Computed tomography, DIMORPHISM, TALUS, STATURE, GROWTH
  • Dokuz Eylül University Affiliated: Yes


Building a reliable biological profile from decomposed remains depends heavily on the accurate estimation of sex. A variety of methods based on every single skeletal element have been developed over the years for different populations employing both osteological and virtual methods. The latter seem to be a reasonable alternative in countries lacking osteological reference collections. The current study used 3D virtual models of calcanei from CT scans of living adults to develop a sex estimation method for contemporary Turkish. Four hundred and twenty eight calcanei CT scans were analysed. The sample was divided in two subsamples: an original (N = 348) and a validation sample (N = 80) with similar distribution of males and females. Nine classical measurements were taken using the 3D models of the calcanei and two different statistical methods (Discriminant function analysis and Binary logistic regression) were used. Classification accuracy ranged from 82% to 98% for the validation sample and it was consistently high using any of the two methods. Sex bias seems to be lower for most of the logistic regression equations compared to the discriminant functions. These results, however, need further testing to be verified. Based on the results of this study we recommend the use of both methods for sex estimation from the measurements of the calcaneus bone in a Turkish population. (C) 2017 Elsevier B.V. All rights reserved.