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Refining Asian Ancestry Classifications via Cranial Macromorphoscopic Traits

NCJ Number
American Journal of Physical Anthropology Volume: 165 Dated: 2018 Pages: 210-210
Date Published
1 page

This study examined biological distance via cranial morphology between Native American (NA), Eskimo, and several Southeast Asian populations.


Forensic anthropologists frequently use 3-group classification models for ancestry estimation; however, delineation of 'Asian' classification is complex, due to human migration patterns and greater variation within these groups, who represent various geographic origins. These groups include mainland Asians, Pacific Islanders, Native Americans, Eskimos, and Hispanics. The current study explored potential refinement of Asian ancestry classifications based on cranial macromorphoscopic traits. The Macromorphoscopic Databank (MaMD) is data repository for cranial macromorphoscopic traits for use with bioarchaeological and forensic human skeletal remains. Canonical Analysis of the Principal Coordinates (CAP) using the chi-square distance metric was used to compare NA, Eskimo, and Asian individuals through canonical and discriminant analysis. Classification accuracies ranged from 83.8 percent (Asian) to 31.6 percent (Eskimo). Previous research has strongly correlated biodistance and geographic barriers; therefore, the current study tested within the NA sample using a pooled sample identifying seven geographic regions. The highest classification accuracies were for the Southeastern sample (58 percent) followed by the Midwest (52 percent). Finally, the study compared several finer levels of resolution to determine the effectiveness of these geographic parameters. Aleut (71.9 percent) had the highest classification, followed by Arikara (60 percent), and Pueblo (59.65 percent). Biodistance analysis will be presented to demonstrated group relatedness for each phase of analysis. These results highlight difficulties distinguishing between groups broadly classified as Asian (Asian/NA/Eskimo), although increased classification rates are possible on a more refined level. Biological distances indicate these traditional 3-group systems of classification are outmoded and require further refinement. (publisher abstract modified)

Date Published: January 1, 2018