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Estimating body mass from skeletal material: new predictive equations and methodological insights from analyses of a known-mass sample of humans

Authors
  • Elliott, Marina1, 2
  • Kurki, Helen3
  • Weston, Darlene A.4, 5
  • Collard, Mark1, 6
  • 1 Simon Fraser University, Human Evolutionary Studies Program and Department of Archaeology, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada , Burnaby (Canada)
  • 2 University of the Witwatersrand, Evolutionary Studies Institute, Johannesburg, South Africa , Johannesburg (South Africa)
  • 3 University of Victoria, Department of Anthropology, Victoria, BC, V8W 2Y2, Canada , Victoria (Canada)
  • 4 University of British Columbia, Department of Anthropology, Vancouver, BC, V6T 1Z1, Canada , Vancouver (Canada)
  • 5 Max Planck Institute of Evolutionary Anthropology, Department of Human Evolution, Deutscher Platz 6, Leipzig, 04103, Germany , Leipzig (Germany)
  • 6 University of Aberdeen, Department of Archaeology, St Mary’s Building, Aberdeen, AB24 3UF, UK , Aberdeen (United Kingdom)
Type
Published Article
Journal
Archaeological and Anthropological Sciences
Publisher
Springer Berlin Heidelberg
Publication Date
Jun 16, 2015
Volume
8
Issue
4
Pages
731–750
Identifiers
DOI: 10.1007/s12520-015-0252-5
Source
Springer Nature
Keywords
License
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Abstract

Estimating body mass from skeletal material is a key task for many biological anthropologists. As a result, several sets of regression equations have been derived for cranial and postcranial material. The equations have been applied to a wide range of specimens, but several factors suggest they may not be as reliable as generally assumed. Specifically, since many of the equations were derived from small reference samples using proxies for key variables and/or mean data, the nature of the relationship between the skeletal variables and body mass has often not been adequately demonstrated. In addition, few of the equations have been validated on known samples, making their accuracy and precision uncertain. Lastly, because no study has used cranial and postcranial material from the same individuals, the two approaches have never been systematically compared. The present study responded to these issues by deriving new regression equations from cranial and postcranial material using a large sample of modern humans of known-mass and associated skeletal variables measured from CT data. The equations were then tested on an independent sample, also of known mass. The results show that the newly derived equations estimate mass more accurately than existing equations for most variables. However, improvements were modest and accuracy rates remained relatively low. In addition, variables that had previously been argued to be ideal predictors were not the most accurate, and the current criteria used to assess equations did not ensure reliability. Overall, the results suggest that body mass estimates must be used cautiously and that further research is required.

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