Rib biomechanical properties exhibit diagnostic potential for accurate ageing in forensic investigations

Bonicelli, Andrea; Xhemali, Bledar; Kranioti, Elena F.; Zioupos, Peter

Abstract

Age estimation remains one of the most challenging tasks in forensic practice when establishing a biological profile of unknown skeletonised remains. Morphological methods based on developmental markers of bones can provide accurate age estimates at a young age, but become highly unreliable for ages over 35 when all developmental markers disappear. This study explores the changes in the biomechanical properties of bone tissue and matrix, which continue to change with age even after skeletal maturity, and their potential value for age estimation. As a proof of concept we investigated the relationship of 28 variables at the macroscopic and microscopic level in rib autopsy samples from 24 individuals. Stepwise regression analysis produced a number of equations one of which with seven variables showed an R2 = 0.949; a mean residual error of 2.13 yrs ±0.4 (SD) and a maximum residual error value of 2.88 yrs. For forensic purposes, by using only bench top machines in tests which can be carried out within 36 hrs, a set of just 3 variables produced an equation with an R2 = 0.902 a mean residual error of 3.38 yrs ±2.6 (SD) and a maximum observed residual error 9.26yrs. This method outstrips all existing age-At-death methods based on ribs, thus providing a novel lab based accurate tool in the forensic investigation of human remains. The present application is optimised for fresh (uncompromised by taphonomic conditions) remains, but the potential of the principle and method is vast once the trends of the biomechanical variables are established for other environmental conditions and circumstances.

Citation

Bonicelli, A., Xhemali, B., Kranioti, E. F., & Zioupos, P. (2017). Rib biomechanical properties exhibit diagnostic potential for accurate ageing in forensic investigations. PLoS ONE, 12(5), Article e0176785. https://doi.org/10.1371/journal.pone.0176785

• Journal Article Type: Article
• Acceptance Date: Apr 17, 2017
• Online Publication Date: May 17, 2017
• Publication Date: May 1, 2017
• Deposit Date: Oct 24, 2023
• Publicly Available Date: Nov 7, 2023
• Journal: PLoS ONE
• Print ISSN: 1932-6203
• Publisher: Public Library of Science
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 5
• Article Number: e0176785
• DOI: https://doi.org/10.1371/journal.pone.0176785
• Public URL: https://hull-repository.worktribe.com/output/4424639