The 81st Annual Meeting of the American Association of Physical Anthropologists (2012)


New techniques for estimating stature and body mass in European skeletal samples

CHRISTOPHER B. RUFF1, BRIGITTE HOLT2, MARKKU NISKANEN3 and VLADIMIR SLADEK4.

1Center for Functional Anatomy and Evolution, Johns Hopkins University School of Medicine, Baltimore, 2Department of Anthropology, University of Massachusetts, Amherst, 3Department of Archaeology, University of Oulu, 4Department of Anthropology, Charles University, Prague

Thursday Afternoon, Forum Suite Add to calendar

Previous methods for estimating stature and body mass from European skeletal remains have generally relied on small and/or possibly unrepresentative reference samples. Here we develop new equations based on a very large, temporally and geographically wide sampling of European skeletal material. Anatomical (Fully) statures were calculated for 501 individuals spanning the Neolithic through 20th century, and from Scandinavia to the Mediterranean region. Sex-specific RMA regressions of anatomical stature on femoral, tibial, humeral, and radial maximum lengths were derived, with %SEE’s of less than 2% for the femur and about 2.5% for the humerus and radius. Region-specific (northern and southern European) equations are more accurate for the tibia, but other bones show no marked geographic trends. There are no marked temporal trends in prediction accuracy. Body mass was calculated based on reconstructed stature and bi-iliac (maximum pelvic) breadth for 1170 individuals using currently available equations based on a world-wide sample. Sex-specific RMA prediction equations from the femoral head were then generated from these body mass estimates. Average directional prediction errors for the femoral head equations are small (<1%), as are average random errors (7%). These new equations are broadly applicable to Holocene European skeletal material and provide a more accurate means to estimate and compare body size in past populations from this region.

This study was funded by the National Science Foundation, grant numbers 0642297 and 1124775.

Tweet
comments powered by Disqus