Masculinization of Female Crania: The Effects of Age on Non-Metric Sex Estimation Accuracy of the Skull
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Female skulls are thought to become more masculine in appearance as they increase in age, yet no research has specifically supported this. This study looks at four commonly used morphological traits used for non-metric sex estimation of the skull (nuchal crest, mastoid process, supraorbital margin, and supraorbital ridge) and if their ordinal scores changes with age. A sample of 303 modern American White male and female adult skulls (including the associated mandible if present) between the ages of 30 to 101 years were used. Each skull was placed into one of seven age categories, which were broken down by decade (30-39 years, 40-49 years… 90-101 years). A multiple analysis of variance was run to see if the ordinal scores for each of the four traits changed between the age categories. The results show no statistically significant difference between the age categories for both males and females. Additionally, the sex estimation accuracies for each age category were calculated for both males and females, which revealed changes in the accuracies between age categories. In females, the accuracy rate is lowest (78.26%) in the 40-49 years age category, which may be due sample sizes that are not large enough to capture the complete range of variation. This drop in accuracy could also correspond with changes due to the onset of menopause. In males, the accuracy rate is lowest (85.71%) in the youngest age category used (30-39 years), but then the accuracy rate gradually increases every year. This could be due to the delayed development of more masculinized features in some males until later in life. These findings show that while there may not be a statistically significant change in the ordinal scores for the four morphological traits between the age categories, non-metric sex estimation of the skull accuracy can still vary greatly. Currently, it is not known why this could be, but the research done for this study begins to show the gaps in the knowledge as well as where future research can take place.