A new comprehensive quantitative approach for the objective identification and analysis of linear enamel hypoplasia (LEH) in worn archaeological dental assemblages
Publication date: January 2020
Source: Journal of Archaeological Science, Volume 113
Author(s): Alejandra Cares Henriquez, Marc F. Oxenham
We present a new comprehensive approach for the objective microscopic identification and quantitative analysis of linear enamel hypoplasia defect chronology and duration that is specifically designed for use on worn archaeological samples when there is an absence of visible perikymata. We use the anterior dentition of three individuals that were assessed for LEH using perikymata spacing and depth profiles in a previous study to demonstrate and validate the methodology. The approach draws upon two recently published methods for the identification and estimation of LEH defect chronology and combines these with new developments for objectively matching stress events across multiple teeth of the same individual. Defects on individual teeth are initially identified using the Micro Polynomial method, which relies on surface depth profiles. Defects from multiple teeth of the same individual are then used to construct a common cycle of defects that can then be more confidently attributed to episodes of systemic stress. The chronology of stress events is estimated using exponential regression equations that provide precise age estimates based on the defect distance from the CEJ. These same equations are then also used to estimate the overall duration, as well as separate stress and recovery duration for each episode. Additionally, the overall period of growth disruption that is represented by the various defects identified for each individual is also estimated. Our results indicate that the approach outlined in this paper is not only capable of replicating previous results, but that minor differences, when observed, are due to the improvement in precision and accuracy that the more objective methods employed here are able to generate. This approach not only reduces the potential for observer bias, when compared to commonly used subjective methods, but also increases the accuracy, replicability, and comparability of results while allowing for multiple aspects of LEH to be explored.