Department of Anthropology, University of New Mexico, Albuquerque, NM, United States.
Department of Anthropology, University of New Mexico, Albuquerque, NM, United States; New Mexico Office of the Medical Investigator, Albuquerque, NM, United States.
Forensic Sci Int. 2024 Aug;361:112151. doi: 10.1016/j.forsciint.2024.112151. Epub 2024 Jul 16.
Stature estimation is a core component to the biological profile in forensic anthropology casework. Here we provide mathematical equations for estimating stature for contemporary American Indians (AI), which currently are lacking in forensic anthropology. Drawing on postmortem computed tomography data from the New Mexico Decedent Image Database we regressed cadaveric length on four long bone length measures of the tibia, femur, and humerus to produce 11 combinations of models. Separate regression models were calculated for the entire pooled sample, by sex, broad AI language groups, and age + sex subsamples and compared. Sex-specific models were statistically better than general models, which were more accurate than language group and age + sex models. Equations were created for general and sex-specific models. Application to an independent test sample demonstrates the equations are accurate for stature estimation with overestimates of less than 1 cm. The equations provide similar levels of precision to stature estimation programs like the FORDISC 3.0 module and other stature equations in the literature. We provide recommendations for equation use in casework based on our results. These equations are the first for estimating stature in contemporary AI. This paper demonstrates the appropriateness of these newly created stature equations for use in New Mexico and the surrounding region.
身高估计是法医人类学案例工作中生物特征分析的核心组成部分。在这里,我们提供了用于估计当代美洲印第安人(AI)身高的数学方程式,而目前在法医人类学中缺乏这些方程式。我们利用新墨西哥死亡图像数据库中的死后计算机断层扫描数据,将尸体长度与胫骨、股骨和肱骨的四个长骨长度测量值进行回归,得出了 11 种模型组合。为整个 pooled 样本、按性别、AI 语言群体以及年龄+性别子样本分别计算了回归模型,并进行了比较。性别特异性模型在统计学上优于通用模型,而通用模型又比语言群体和年龄+性别模型更准确。为通用和性别特异性模型创建了方程。应用于独立测试样本表明,这些方程在身高估计方面非常准确,估计值的偏差小于 1cm。这些方程与 FORDISC 3.0 模块等其他文献中的身高估计程序具有相似的精度。我们根据研究结果为案件工作中的方程应用提供了建议。这些方程是首次用于估计当代 AI 的身高。本文证明了这些新创建的身高方程在新墨西哥州及周边地区案件工作中的适用性。