UMR 5199-PACEA, Laboratoire d'Anthropologie des Populations du Passé, Université Bordeaux 1, avenue des Facultés, 33405 Talence cedex, France.
Am J Phys Anthropol. 2010 Aug;142(4):655-64. doi: 10.1002/ajpa.21312.
Infracranial sequences of maturation are commonly used to estimate the age at death of nonadult specimens found in archaeological, paleoanthropological, or forensic contexts. Typically, an age assessment is made by comparing the degree of long-bone epiphyseal fusion in the target specimen to the age ranges for different stages of fusion in a reference skeletal collection. While useful as a first approximation, this approach has a number of shortcomings, including the potential for "age mimicry," being highly dependent on the sample size of the reference sample and outliers, not using the entire fusion distribution, and lacking a straightforward quantitative way of combining age estimates from multiple sites of fusion. Here we present an alternative probabilistic approach based on data collected on 137 individuals, ranging in age from 7- to 29-years old, from a documented skeletal collection from Coimbra, Portugal. We then use cross validation to evaluate the accuracy of age estimation from epiphyseal fusion. While point estimates of age can, at least in some circumstances, be both accurate and precise based on the entire skeleton, or many sites of fusion, there will often be substantial error in these estimates when they derive from one or only a few sites. Because a probabilistic approach to age estimation from epiphyseal fusion is computationally intensive, we make available a series of spreadsheets or computer programs that implement the approach presented here.
颅下成熟序列通常用于估计在考古学、古人类学或法医学背景下发现的非成年人标本的死亡年龄。通常,通过将目标标本的长骨骨骺融合程度与参考骨骼集合中不同融合阶段的年龄范围进行比较来进行年龄评估。虽然作为初步估计很有用,但这种方法有许多缺点,包括“年龄模仿”的可能性,高度依赖于参考样本和离群值的样本量,未使用整个融合分布,并且缺乏一种简单的定量方法来结合来自多个融合部位的年龄估计。在这里,我们提出了一种基于在葡萄牙科英布拉的一个有记录的骨骼集合中收集的 137 名年龄在 7 至 29 岁之间的个体的数据的替代概率方法。然后,我们使用交叉验证来评估从骨骺融合估算年龄的准确性。虽然基于整个骨骼或许多融合部位,至少在某些情况下,点估计的年龄可以既准确又精确,但当它们来自一个或只有少数几个部位时,这些估计通常会有很大的误差。由于从骨骺融合估算年龄的概率方法计算量很大,因此我们提供了一系列电子表格或计算机程序,以实现此处介绍的方法。