SEX DETERMINATION USING THE TIBIA IN AN ANCIENT ANATOLIAN POPULATION


Koca Özer B., Özer İ., Sağır M., Gulec E.

MEDITERRANEAN ARCHAEOLOGY & ARCHAEOMETRY, cilt.14, sa.2, ss.313-320, 2014 (AHCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 14 Sayı: 2
  • Basım Tarihi: 2014
  • Dergi Adı: MEDITERRANEAN ARCHAEOLOGY & ARCHAEOMETRY
  • Derginin Tarandığı İndeksler: Arts and Humanities Citation Index (AHCI), Scopus
  • Sayfa Sayıları: ss.313-320
  • Anahtar Kelimeler: Human skeletons, discriminant function analysis, tibia, sex determination, ancient Anatolia, DISCRIMINANT FUNCTION-ANALYSIS, FEMUR, DIMORPHISM, JAPANESE, CHINESE, SCAPULA, SKULLS
  • Ankara Üniversitesi Adresli: Evet

Özet

Sex determination is an important issue of anthropological and forensic sciences. Determination of sex is a priority issue for further analysis of unidentified ancient human remains, because all techniques of identification are markedly different for males and females. The present study provides sex determination using discriminant analysis from tibia measurements in an ancient Anatolian population. In this study, a total of 7 tibia measurements were taken from 123 adults of known sex (62 males and 61 females) in Medieval Dilkaya population (A.D. 10th century). Osteometric measurements included were the length, circumference of midshaft and minimum, transverse and sagittal diameters of midshaft and nutrient foramen levels. Data were analyzed by student t-test and discriminant analysis using Statistical Package for the Social Sciences (SPSS) version 13.0 program. Results showed that grouping due to sex differentiations was accurate by tibia metric values between 73.5% and 90.2% in Dilkaya population. The midshaft circumference was the best single discriminating variable and results of this study compare with other studies. It is suggested that discriminant formulas developed by tibia measurements in this study can be used for sex determination accurately on fragmentary skeletal remains in ancient Anatolian populations.