The 87th Annual Meeting of the American Association of Physical Anthropologists (2018)

Subadult age estimation of Taiwanese populations using long bone dimensions from radiographs


1Department of Anthropology, University of Illinois at Urbana-Champaign, 2Department of Anthropology, University of Nevada, Reno, 3Department and Graduate Institute of Forensic Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan, 4Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan

April 12, 2018 , Zilker 1/2/3 Add to calendar

Age estimation from the skeletons in subadults is based on growth and development of the skeleton. Long bone length and width have been shown to have a strong positive correlation with age and therefore a good predictor of chronological age. However, populations will likely have different standards for age estimation because long bone dimensions are susceptible to environmental influences and lifestyle differences. Currently, most subadult ageing methods have not been tested in Asian populations and it is necessary to quantify the external validity and if necessary, develop population-specific standards.

This study analyzed 250 computed tomography scans of males and females between 1 and 15 years old from National Taiwan University Hospital. Measurements of diaphyseal and epiphyseal dimensions of humerus and femur were collected and multivariate adaptive regression splines were used to build models and construct prediction intervals for the sample. As age increases, the accuracy of the Stull et al. (2014) method decreases. Thus we built population specific models in order to capture the entirety of the variation in the Taiwanese sample. Similar to previous findings, single variable models with diaphyseal length generated the narrowest age prediction intervals for the youngest ages, but as age increased, the incorporation of additional variables was beneficial to prediction. The results of this study are consistent with previous studies on subadult age estimation but shed light on the potential of universal models for younger age periods and stress the need for population-specific standards for older age periods.

NIJ Award 2017-DN-BX-0144