An alternative approach for estimating stature from long bones that is not population- or group-specific. (February 2016)

• Record Type: Journal Article
• Authors: Albanese, John; Tuck, Andrew; Gomes, José; Cardoso, Hugo F.V.
• Is Part Of: Forensic science international. Volume 259(2016)
• Page Start: 59
• Page End: 68
• Publication Date: 2016-02
• Subjects: Forensic Anthropology -- Stature equations -- Non-specific -- Terry Collection -- Lisbon Collection; 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.2015.12.011
• Languages: English
• ISSNs: 0379-0738

Abstract

Highlights: Stature estimation equations were developed with a sample from the Terry Collection. Humerus, radius, ulna, femur, tibia and multivariate equations are presented. An unknown does not need to be assigned to a group before the method can be applied. Testing using independent samples demonstrates efficacy in forensic contexts. Methods estimated stature 96.5–98.5% of the time in over 1000 independent trials. Abstract: An accurate and precise estimate of stature can be very useful in the analysis of human remains in forensic cases. A problem with many stature estimation methods is that an unknown individual must first be assigned to a specific group before a method can be applied. Group membership has been defined by sex, age, year of birth, race, ancestry, continental origin, nationality or a combination of these criteria. Univariate and multivariate sex-specific and generic equations are presented here that do not require an unknown individual to be assigned to a group before stature is estimated. The equations were developed using linear regression with a sample ( n = 244) from the Terry Collection and tested using independent samples from the Forensic Anthropology Databank ( n = 136) and the Lisbon Collection ( n = 85). Tests with these independent samples show that (1) the femur provides the best univariate results; (2) the best multivariate equation includes the humerus, femur and tibia lengths; (3) a generic equation that does not require an unknown to first be assigned to a given category provides the best results most often; (4) a population-specific equation does not provide better results for estimating stature; (5) sex-specific equations can provide slightly better results in some cases; however, estimating the wrong sex can have a negative impact on precision and accuracy. With these equations, stature can be estimated independently of age at death, sex or group membership.