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Sex determination of a Tunisian population by CT scan analysis of the skull

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Abstract

It is widely accepted that the estimation of biological attributes in the human skeleton is more accurate when population-specific standards are applied. With the shortage of such data for contemporary North African populations, it is duly required to establish population-specific standards. We present here the first craniometric standards for sex determination of a contemporary Tunisian population. The aim of this study was to analyze the correlation between sex and metric parameters of the skull in this population using CT scan analysis and to generate proper reliable standards for sex determination of a complete or fragmented skull. The study sample comprised cranial multislice computed tomography scans of 510 individuals equally distributed by sex. ASIRTM software in a General ElectricTM workstation was used to position 37 landmarks along the volume-rendered images and the multiplanar slices, defining 27 inter-landmark distances. Frontal and parietal bone thickness was also measured for each case. The data were analyzed using basic descriptive statistics and logistic regression with cross-validation of classification results. All of the measurements were sexually dimorphic with male values being higher than female values. A nine-variable model achieved the maximum classification accuracy of 90% with −2.9% sex bias and a six-variable model yielded 85.9% sexing accuracy with −0.97% sex bias. We conclude that the skull is highly dimorphic and represents a reliable bone for sex determination in contemporary Tunisian individuals.

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Acknowledgment

The authors would like to thank Dr. Aycha Ben Miled for her valuable help in the manuscript editing.

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Authors and Affiliations

  1. Faculty of Medicine, University of Tunis El Manar, Tunis, Tunisia

    Malek Zaafrane, Mehdi Ben Khelil, Ines Naccache, Ekbel Ezzedine, Najla Mnif & Moncef Hamdoun

  2. Department of Legal Medicine, Charles Nicolle Hospital, Tunis, Tunisia

    Malek Zaafrane, Mehdi Ben Khelil & Moncef Hamdoun

  3. Laboratoire d’Anthropobiologie AMIS, UMR 5288 CNRS, Université Paul Sabatier, 37 Allées Jules Guesde, 31000, Toulouse, France

    Malek Zaafrane, Frédéric Savall & Norbert Telmon

  4. Department of Radiology, Charles Nicolle Hospital, Tunis, Tunisia

    Ines Naccache, Ekbel Ezzedine & Najla Mnif

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  1. Malek Zaafrane
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  2. Mehdi Ben Khelil
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Correspondence to Malek Zaafrane.

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Zaafrane, M., Ben Khelil, M., Naccache, I. et al. Sex determination of a Tunisian population by CT scan analysis of the skull. Int J Legal Med 132, 853–862 (2018). https://doi.org/10.1007/s00414-017-1688-1

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  • DOI: https://doi.org/10.1007/s00414-017-1688-1

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