The accuracy of age estimation using transition analysis in the Hamann‐Todd collection

Abstract

Objectives: Reconstructing demography of past populations using skeletal data is challenging when analyzing adults because the process of biological aging does not always reflect the individual's chronological age. A proposed solution to address the limitations of traditional age estimation methods is transition analysis (TA), a multifactorial method of age estimation. However, despite its methodological refinement, TA has varying degrees of accuracy when applied to different known-age skeletal samples. This study assesses TA's accuracy by comparing age estimates to known age at death in the Hamann-Todd Collection.Materials and Methods: We contrasted the maximum likelihood age estimates generated by the ADBOU program to the known ages of 221 individuals. The absolute error was calculated for the entire sample, and compared between sex and ancestry. Results:The mean absolute error in the sample is 11.6 (SD = 10.3) years, with white individuals' errors (14.1 years) being significantly higher than black individuals' (9.1 years; p < 0.001). No significant differences were found between sexes (p = 0.621). A weak to moderate positive correlation was found between known age and absolute error for white males (R = 0.607; p < 0.001), white females (R = 0.509; p < 0.001), and black males (R = 0.371; p = 0.006). The accuracy of TA age estimates varied when each anatomical region was analyzed independently, but the combination of all three anatomical regions yielded the most accurate age estimates.Discussion: These findings further support that TA accuracy depends on the prior distribution used and, in the Hamann-Todd Collection, the accuracy for white individuals is more influenced by this limitation than when black individuals are analyzed.

Estimating adult age categories in commingled skeletons with Transition Analysis 3

“…To further illustrate the difference in old-age estimation between traditional methods and TA3, the maximum mean estimated age of one bone for this sample using Suchey-Brooks/Hartnett (male) was 61.2 years (individual U2.37.512), compared with the maximum likelihood point estimate using TA3 (also pubic symphysis) of 85.9 years (individual U2.37.619) (see Table S1). While imperfect (see Hurst, 2010;Simon & Hubbe, 2021), TA has been observed to be more useful in general age-at-death distribution analyses (such as examining population-level mortality profiles) than specific and accurate individual age estimation (Milner & Boldsen, 2012). Further, TA programs have been useful for age estimation in different contexts, requiring some research and practice but not any more inaccessible or difficult than traditional methods (see Fojas et al, 2018; also confirmed by our own observations).…”

Temporal, spatial and gender-based dietary differences in middle period San Pedro de Atacama, Chile: A model-based approach

“…Demographic characteristics of the individuals included in this study (age at death and sex) were estimated based on the analysis of skulls and pelvis, following traditional bioarchaeological methods of analysis [ 65 ]. However, as mentioned before, for most of the samples only skulls are available, which makes the estimates of age at death unreliable [ 66 , 67 ]. For this reason, the age distribution of the local populations cannot be estimated properly, and this demographic aspect was not explored in the current study.…”

The Black Death in Hereford, England: A demographic analysis of the Cathedral 14th‐century plague mass graves and associated parish cemetery

“…Age estimates were generated via transition analysis using the Anthropological Database, Odense University (ADBOU) program Transition Analysis 2 (TA2), version 2.1.046 (Ousley et al, 2016). For each skeleton, pubic symphysis and auricular surface degeneration were scored alongside cranial suture obliteration (Kim & Algee‐Hewitt, 2022; Milner & Boldsen, 2012; Simon & Hubbe, 2021). This method generates a maximum likelihood point estimate (MLPE) for age‐at‐death, with a 95% confidence interval, from the scored pelvic and skull traits (Getz, 2020).…”