Surface texture analyses complement scale sensitive fractal analyses in an in vivo human dental microwear study

Abstract

The study of dental microwear, the microscopic patterns left on teeth from interactions with food, has become instrumental in examining the diets of past societies. This approach gained prominence with the advent of dental microwear texture analysis (DMTA), an automated method that minimises observer error. Nevertheless, interpreting microwear patterns remains challenging due to limited knowledge about which foods and processing methods produce specific markings. Given the subtle variations in human diets compared to other species, there is a pressing need for more comprehensive in vivo data on microwear production.

In this study, we improved our understanding of DMTA by employing multivariate analyses to combine parameters from surface texture analyses (STA) with the more common parameters derived from scale sensitive fractal analyses (SSFA). We collected dental impressions from five Kenyan communities: El Molo, Turkana (Kerio), Luhya (Webuye), Luhya (Port Victoria), and Luo (Port Victoria), representing a range of subsistence strategies – fishing, pastoralism, and agriculture. Regrettably, the presence of oral biofilm – a bacterial layer covering teeth in living individuals – often hampers the accurate moulding of dental microwear in vivo. Despite the constraint imposed by the presence of biofilm, which limited our sample to only 37 usable surfaces, we found that while SSFA variables failed to distinguish between populations, combining them with STA parameters in multivariate analyses successfully differentiated the El Molo from the other populations, as well as the groups from Port Victoria.

Our findings suggest that this approach offers a more comprehensive understanding of microwear variation. To ensure the continued relevance of dental microwear studies in understanding the diets of past societies, we must improve our understanding of the relationship between dental microwear patterns and the complex, mixed diets of humans, and overcome the current limitations of the technique. Consistently incorporating ISO 25178 in our analyses represents a promising avenue for achieving this objective.