A multivariate model of subadult age estimation

Board Of Regents, Nshe, Obo University Of Nevada, Reno, Reno NV

Investigators

Abstract

This project will explore the relationships among chronological age and dental formation, long bone growth and epiphyseal fusion in modern US children, using full body CT scans and sophisticated statistical models. A better understanding of these relationships is important not only for human biologists interested in childhood growth and life history patterns, but for bioarchaeologists and forensic anthropologists who want more accurate estimates of age at death in skeletal samples. NSF funds will support data collection and statistical consulting for the dental portion of the larger project. The project will result in freely accessible dental and skeletal data for a large, cross-sectional sample of modern children. An age estimation software program, and workshops to introduce the software, will also be developed and will be of interest across a range of research areas within and beyond anthropology. Subadult age estimations are based on documented patterns of growth and development and are considered the most accurate estimation in the subadult biological profile. However, the major limitations of subadult age estimation are the lack of large, modern skeletal reference samples and the reliance on historical, primarily univariate methodological approaches. Most methods utilize a bone-by-bone or tooth-by-tooth approach and do not provide a means to incorporate markers from the entire subadult skeleton. In this project, the investigators will have access to de-identified medical examiner data. They will collect information on dental formation, epiphyseal fusion and long bone growth from multi-slice computed tomography (MSCT) and Lodox Statscan radiographic images for individuals between birth and 15 years (n = 1500), to develop a multivariate age estimation technique. Univariate and multivariate models will be compared in terms of accuracy, bias, and predictive ability, and the data will be incorporated into KidStats software with the goal of providing more accurate, precise, and unbiased age estimates for subadults. The freely accessible data will offer a range of research and collaborative opportunities for undergraduate and postgraduate students as well as researchers in anthropology and allied fields. This project is jointly supported by NSF and the National Institute of Justice.