Subadult sex estimation from diaphyseal dimensions.

Abstract

Many studies on subadult sex estimation focus on elements that express sexually dimorphic features in adults. In contrast, diaphyseal dimensions have been shown to display sex-specific differences prior to adolescence. The current study evaluates the use of diaphyseal dimensions in subadult sex estimation. Eighteen postcranial measurements from six long bones were collected on Lodox Statscan radiographic images of 1,310 modern South African children between birth and 12 years of age. Linear (LDA) and flexible discriminant analysis (FDA) and logistic regression were employed with single and multiple variable models with age both included and excluded from the model. Bootstrapped cross-validation was employed because some of the multiple variable subsets had small sample sizes. Each of the bootstrapped accuracies has an associated 95% confidence interval demonstrating the ranges in classification. Classification methods utilizing multiple variables achieved the highest bootstrapped classification accuracies (70% to 93%). The inclusion of age in the models did not consistently increase or decrease the classification accuracies. Proximal and distal breadth measurements were consistently recognized as important measurements in model creation. FDA yielded the highest overall accuracies, but the logistic regression presented with overall smaller bootstrapped 95% confidence intervals. Quantifiable sex differences were discovered in the appendicular skeleton of children between birth and 12 years of age. The high classification accuracies were likely due to using numerous predictor variables from multiple skeletal elements, which were optimized for classification using FDA. To facilitate application, a graphical user interface, KidStats, was developed.