Morphometric analysis of the adult human mastoid process as a sexually dimorphic trait

Thesis (M.S.)--Boston University PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.Sex estimation is a fundamental analysis in the establishment of the biological profile in forensic anthropology. Traditionally, sex estimation of the skull is based on visual interpretation of specific morphological traits and metric analyses (Buikstra and Ubelaker, 1994; Bass 2005; Jantz and Ousley, 2005; Spradley and Jantz, 2011). If morphological traits are large and rugose, the skull is determined to be male, while gracile features and an overall smaller size suggest a female. This type of sex assessment is typically based on ordinal scores of five standard sexually dimorphic traits, including the mastoid process (Buikstra and Ubelaker, 1994). Scores from the visually examined traits are averaged by the analyst to provide a final sex estimate. Recently, legal proceedings in the United States have encouraged quantitative rather than qualitative techniques in scientific fields. As a result, the subjectivity of visual analysis is under scrutiny. The current study aims to determine if metric evaluation of the mastoid process can be utilized as a quantifiable predictor of sex. A modern sample of American Whites and Blacks (n = 157) from the William M. Bass Donated Skeletal Collection was examined. Five bilateral measurements of the mastoid process were recorded and analyzed for accuracy in correct classification of sex. Tests for intraobserver reliability of the measurements were performed on a subsample (n = 24). This study suggests that morphometric analysis of the mastoid process yields reliable, sexually dimorphic values, but with reduced predictive accuracies as compared to visual assessment