Testing of morphological sex estimation traits with a sex‐known collection

Ottoman period skulls

Bibliographic Data

ID12371610
AuthorsBerkay Yaşar (0000-0002-3977-3532, Faculty of Languages, History and Geography, Department of Anthropology Ankara Ankara University 06100 Sıhhiye Turkey, corresponding author), Mustafa Sagir (0000-0003-3057-0648, Faculty of Languages, History and Geography, Department of Anthropology Ankara Ankara University 06100 Sıhhiye Turkey)
Year2023
Volume33
Issue6
Pages1042-1051
Publication date2023-10-30
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Osteoarchaeology (JOURNAL)
Journal identifiersISSN: 1047-482X • E-ISSN: 1099-1212
PublisherWiley (PUBLISHER • GB)
DOI10.1002/oa.3265
OpenAlexW4388015643
LanguageEN
References cited40

Sexual dimorphism patterns vary across geographic regions due to the influence of genetic characteristics and environmental factors. Therefore, sex estimation models are being developed specifically for each population or group. The applicability of morphological sex estimation methods has not been tested in Turkey. Hence, by using skulls, the present study aims to analyze the reliability of the visual morphological method and test the equations developed in different populations. The study material consists of 192 skulls (96 male, 96 female) with known sexes, excavated from Istanbul's Karacaahmet cemetery in 1925. In the present study, glabella, mastoid process, supraorbital margin, and nuchal crest traits were scored on a scale of 1 to 5 according to the instructions provided in standard protocols. Intra‐observer and inter‐observer agreements were analyzed by two experts having the same level of experience. When equations derived from other populations were applied to our samples, they exhibited high sex biases (up to 50%). Therefore, new equations were derived through binary logistic regression analysis. Glabella had the highest performance in terms of repeatability (0.83) and reproducibility (0.74), whereas the nuchal crest showed the lowest performance (0.60–0.52). The most significant sexual dimorphism was observed in the glabella. Based on cross‐validated results using a single criterion, it accurately classified 80% of females and 84% of males. The nuchal crest was not significantly affecting the sex discriminative equations ( p > 0.05). Multivariate equations achieved an accuracy of over 90% and cross‐validated results ranged between 80% and 90%. The results obtained from present study support the hypothesis that sexual dimorphism patterns vary under different conditions and highlight the importance of population variation in sex estimation. The models derived from the present study were found to be suitable for sex estimation from skulls and demonstrated high performance

Biology · Crest · Estimation · Glabella · Multivariate statistics · Population · Sexual dimorphism · Statistics · Zoology · Demography · Forensic and Genetic Research · Forensic Anthropology and Bioarchaeology Studies · Mathematics · Paleopathology and ancient diseases · Anatomy

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