The decade under review: Recent trends and challenges in the use of macroscopic age‐at‐death estimation methods in bioarchaeology

Abstract

AbstractAccurate and precise age‐at‐death estimation methods are critical when studying past lifeways. However, adult age‐at‐death estimation is often difficult because of diverse physiologies, preservation, and timing of biological processes in target and reference populations. These challenges can complicate the comparison of results between studies, which can also be impacted by the training and method preference of each bioarchaeologist. In this paper, we first compare the use of two types of age‐at‐death estimation methods, namely, traditional methods (e.g., pubic symphyseal aging) and Transition Analysis. Second, we build upon the work of Falys and Lewis (2011), who reported frequencies of adult age‐at‐death method use between 2000 and 2010, by reporting the frequency of use for traditional methods over the past 40 years with special attention on the last decade. We build further on their work by identifying trends in the minimum age at adulthood, adult age categories, geographic region of institutional affiliation of the first author, and the geographic region of sample origin and interpreting their possible implications on comparability of bioarchaeological literature. Our results show that Transition Analysis, institutional affiliation, and sample origin do not represent major sources of variation in bioarchaeological literature so far. In the case of Transition Analysis, this could result from its limited use thus far, while institutional affiliation and sample origin do not represent major sources of variation because of the relative lack of diversity in both variables. There was, however, substantial variation in the type of traditional method used, the minimum age at adulthood, and adult age categories, which could affect comparability between studies. Our study highlights the need for continued discussion about standardizing bioarchaeological age‐at‐death estimation while respecting the unique needs of diverse target samples.