Abstract:
Subadult age estimation is considered the most accurate parameter estimated in a
subadult biological profile, even though the methods are deficient and the samples from which
they are based are inappropriate. The current study addresses the problems that plague subadult
age estimation and creates age estimation models from diaphyseal dimensions of modern
children.
The sample included 1,310 males and females between the ages of birth and 12 years.
Eighteen diaphyseal length and breadth measurements were obtained from Lodox Statscan
radiographic images generated at two institutions in Cape Town, South Africa between 2007 and
2012. Univariate and multivariate age estimation models were created using multivariate
adaptive regression splines (MARS). K-fold cross-validated 95% prediction intervals (PIs) were
created for each model and the precision of each model was assessed.The diaphyseal length models generated the narrowest PIs (two months to six years) for
all univariate models. The majority of multivariate models had PIs that ranged from three months
to five and six years. Mean bias approximated zero for each model, but most models lost
precision after 10 years of age. While univariate diaphyseal length models are recommended for
younger children, multivariate models are recommended for older children where the inclusion
of more variables minimized the size of the prediction intervals. If diaphyseal lengths are not
available, multivariate breadth models are recommended. The present study provides applicable
age estimation formulae and explores the advantages and disadvantages of different subadult age
estimation models using diaphyseal dimensions.
