DETERMINATION OF INTRAVITAM BODY TYPE IN MEN DRAWING ON THE OSTEOMETRIC CHARACTERISTICS OF SKELETONISED CLAVICLES
- 作者: Smirnov A.V.1, Sundukov D.V.1
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隶属关系:
- Peoples’ Friendship University of Russia
- 期: 卷 6, 编号 1 (2020)
- 页面: 27-32
- 栏目: 原创研究
- ##submission.dateSubmitted##: 26.03.2020
- ##submission.dateAccepted##: 26.03.2020
- ##submission.datePublished##: 26.03.2020
- URL: https://for-medex.ru/jour/article/view/299
- DOI: https://doi.org/10.19048/2411-8729-2020-6-1-27-32
- ID: 299
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One of the major challenges faced by a forensic medical expert when performing the examination of bone remains for the purposes of personal identification is the determination of group characteristics, which include the person’s body type. The present study focuses on a new method for determining the intravitam body type when considering skeletonised remains.
Aim. To develop diagnostic mathematico-statistical models that allow the intravitam body type in men to be determined, drawing on the osteometric characteristics of skeletonised clavicles.
Material and methods. We studied clavicles from the osteological collection held at the Department of Anthropology, Lomonosov Moscow State University (62 adult male skeletons) according to the expanded osteometric program (15 characteristics). The obtained data were processed by StatSoft STATISTICA 10 using multivariate stepwise discriminant analysis (MDA).
Results. We have developed diagnostic models allowing the intravitam body type (ectomorph, mesomorph and endomorph) to be determined on the basis of skeletonised clavicles with an accuracy of 62.9–79 %. Using the proposed models, a more accurate determination of ectomorphs and mesomorphs (90 %) than endomorphs (41–58.8 %) is observed. In order to increase the objectiveness of the expert’s conclusion, we used function Pl showing the probability of correct body type classification in every single case.
The diagnostic models were successfully verified using the skeletal samples held at the Peter the Great Museum of Anthropology and Ethnography, with the maximum accuracy level reaching 80 %.
作者简介
A. Smirnov
Peoples’ Friendship University of Russia
编辑信件的主要联系方式.
Email: ascold20@yandex.ru
ORCID iD: 0000-0001-6017-5310
Askold V. Smirnov, Research Assistant, Department of Forensic Medicine, Medical Institute
Moscow
俄罗斯联邦D. Sundukov
Peoples’ Friendship University of Russia
Email: sudmed.rudn@yandex.ru
ORCID iD: 0000-0001-8173-8944
Dmitry V. Sundukov, Dr. Sci. (Med), Assoc. Prof., Departmental Head, Department of Forensic Medicine
Moscow
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