Blast injury to the human skeleton: recognition, identification and differentiation using morphological and statistical approaches.
type: CreativeWork
description: Anthropologists are increasingly called upon to assess trauma to the skeleton and contextualising the nature of this trauma. Blast injury is a type of trauma which is increasingly seen in a variety of contexts, such as terrorism, human rights violations, combat and accidents. The purpose of this study was to examine blast injury in the human skeleton and apply robust multivariate statistical methods, alongside morphological methods, to identify blast trauma based on the distribution of injury in the skeleton. The objectives of the study were to identify patterns in a sample of cases from mass graves in Bosnia and to determine differences between the blast injury cases and gunshot wound cases which can identify indicators of blast injury for future use. This was done using Pearson‘s χ2, cluster analysis and multiple correspondence analysis. Secondly, the identified indicators were applied to two methods of binary logistic regression model to test prediction of the presence or absence of blast injury in the sample, as well as assessing the results of the two methods. Lastly, the results of these analyses were subsequently compared with clinical literature to identify similarities and differences which can aid anthropologists in determining presence of blast injury in large assemblages. This also served to address the specific argument that the injuries seen in the Bosnia sample are combat related, as claimed in court proceedings in ongoing cases at the International Criminal Tribunal for the Former Yugoslavia. It was found that cluster analysis was not useful for the sample examined in the research, however multiple correspondence analysis permitted graphical differentiation between the blast injury and gunshot cases, identifying variables which contributed to the variance and could be used as indicators of blast injury. Binary logistic regression was employed to test the significant contribution of these variables to a model predicting the presence of blast injury in…
abstract: Anthropologists are increasingly called upon to assess trauma to the skeleton and contextualising the nature of this trauma. Blast injury is a type of trauma which is increasingly seen in a variety of contexts, such as terrorism, human rights violations, combat and accidents. The purpose of this study was to examine blast injury in the human skeleton and apply robust multivariate statistical methods, alongside morphological methods, to identify blast trauma based on the distribution of injury in the skeleton. The objectives of the study were to identify patterns in a sample of cases from mass graves in Bosnia and to determine differences between the blast injury cases and gunshot wound cases which can identify indicators of blast injury for future use. This was done using Pearson‘s χ2, cluster analysis and multiple correspondence analysis. Secondly, the identified indicators were applied to two methods of binary logistic regression model to test prediction of the presence or absence of blast injury in the sample, as well as assessing the results of the two methods. Lastly, the results of these analyses were subsequently compared with clinical literature to identify similarities and differences which can aid anthropologists in determining presence of blast injury in large assemblages. This also served to address the specific argument that the injuries seen in the Bosnia sample are combat related, as claimed in court proceedings in ongoing cases at the International Criminal Tribunal for the Former Yugoslavia. It was found that cluster analysis was not useful for the sample examined in the research, however multiple correspondence analysis permitted graphical differentiation between the blast injury and gunshot cases, identifying variables which contributed to the variance and could be used as indicators of blast injury. Binary logistic regression was employed to test the significant contribution of these variables to a model predicting the presence of blast injury in…
author: Dussault, Marie Christine
language: en
keywords: Medicine and Health
date published: 2013-05
date modified: 2026-07-24T01:12:33Z
provider: University of Bournemouth
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Bournemouth University, School of Applied Sciences.