A multivariate model of subadult age estimation

该项目将利用全身CT扫描和复杂的统计模型，探索现代美国儿童年龄与牙齿形成、长骨生长和骨骺融合之间的关系。更好地理解这些关系不仅对对童年成长和生活史模式感兴趣的人类生物学家很重要，对希望更准确地估计骨骼样本的死亡年龄的生物考古学家和法医人类学家也是如此。NSF基金将支持更大项目的牙科部分的数据收集和统计咨询。该项目将为现代儿童的大量横断面样本提供免费的牙科和骨骼数据。还将开发一个年龄估计软件程序和介绍该软件的研讨会，并将在人类学内外的一系列研究领域引起人们的兴趣。亚成体年龄估计是基于记录在案的生长和发育模式，并被认为是亚成体生物学概况中最准确的估计。然而，亚成人年龄估计的主要局限性是缺乏大的、现代的骨骼参考样本，以及依赖历史的、主要是单变量的方法学方法。大多数方法采用逐骨或逐牙的方法，不提供结合整个亚成人骨骼的标记的方法。在这个项目中，调查人员将可以访问未确认身份的法医数据。他们将从出生至15岁(n=1500)的个人的多层计算机断层扫描(MSCT)和Lodox统计扫描X射线图像中收集有关牙齿形成、骨骺融合和长骨生长的信息，以开发一种多变量年龄估计技术。单变量和多变量模型将在准确性、偏差和预测能力方面进行比较，数据将被纳入KidStats软件，目的是为亚成人提供更准确、准确和公正的年龄估计。这些免费访问的数据将为本科生和研究生以及人类学和相关领域的研究人员提供一系列研究和合作机会。该项目由NSF和国家司法研究所联合支持。

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.