Literature DB >> 27373600

A method for sex estimation using the proximal femur.

Francisco Curate1, João Coelho2, David Gonçalves3, Catarina Coelho2, Maria Teresa Ferreira4, David Navega2, Eugénia Cunha2.   

Abstract

The assessment of sex is crucial to the establishment of a biological profile of an unidentified skeletal individual. The best methods currently available for the sexual diagnosis of human skeletal remains generally rely on the presence of well-preserved pelvic bones, which is not always the case. Postcranial elements, including the femur, have been used to accurately estimate sex in skeletal remains from forensic and bioarcheological settings. In this study, we present an approach to estimate sex using two measurements (femoral neck width [FNW] and femoral neck axis length [FNAL]) of the proximal femur. FNW and FNAL were obtained in a training sample (114 females and 138 males) from the Luís Lopes Collection (National History Museum of Lisbon). Logistic regression and the C4.5 algorithm were used to develop models to predict sex in unknown individuals. Proposed cross-validated models correctly predicted sex in 82.5-85.7% of the cases. The models were also evaluated in a test sample (96 females and 96 males) from the Coimbra Identified Skeletal Collection (University of Coimbra), resulting in a sex allocation accuracy of 80.1-86.2%. This study supports the relative value of the proximal femur to estimate sex in skeletal remains, especially when other exceedingly dimorphic skeletal elements are not accessible for analysis.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Biological profile; Forensic anthropology population data; Forensic science; Human identification; Sex diagnosis

Mesh:

Year:  2016        PMID: 27373600     DOI: 10.1016/j.forsciint.2016.06.011

Source DB:  PubMed          Journal:  Forensic Sci Int        ISSN: 0379-0738            Impact factor:   2.395


  2 in total

1.  Getting Rid of Dichotomous Sex Estimations: Why Logistic Regression Should be Preferred Over Discriminant Function Analysis.

Authors:  Bjørn Peare Bartholdy; Elena Sandoval; Menno L P Hoogland; Sarah A Schrader
Journal:  J Forensic Sci       Date:  2020-06-10       Impact factor: 1.832

2.  Let's make a mess, maybe no one will notice. The impact of bioturbation activity on the urn fill condition.

Authors:  Agata Hałuszko; Marcin Kadej; Grzegorz Gmyrek; Maciej Guziński
Journal:  PLoS One       Date:  2022-09-02       Impact factor: 3.752

  2 in total

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