A method for sex estimation using the proximal femur. (September 2016)

• Record Type: Journal Article
• Authors: Curate, Francisco; Coelho, João; Gonçalves, David; Coelho, Catarina; Ferreira, Maria Teresa; Navega, David; Cunha, Eugénia
• Is Part Of: Forensic science international. Volume 266(2016)
• Page Start: 579.e1
• Page End: 579.e7
• Publication Date: 2016-09
• Subjects: Forensic anthropology population data -- Forensic science -- Human identification -- Biological profile -- Sex diagnosis; Medical jurisprudence -- Periodicals; Chemistry, Forensic -- Periodicals; Forensic Medicine -- Periodicals; Médecine légale -- Périodiques; Chimie légale -- Périodiques; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; Chemistry, Forensic; Medical jurisprudence; Electronic journals; Periodicals; Electronic journals; 614.1
• DOI: 10.1016/j.forsciint.2016.06.011
• Languages: English
• ISSNs: 0379-0738

Abstract

Highlights: Models to estimate sex in incomplete and fragmentary human skeletal remains. Simple and straightforward measurements in the proximal portion of the femur. Femoral neck axis length and femoral neck width show sexual dimorphism. A decision tree with both variables gives the most accurate and less biased results. 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.