An Examination of Variability in Dental Development Across the State of North Carolina
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Eddleman, Liam Gray
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East Carolina University
Abstract
Contemporary research suggests that dental development is biologically stable across human populations. However, research examining trends in dental developmental variation tends to focus on broad population trends and often lacks nuanced information about small-scale relationships at the city and community level. As a result, these studies may gloss over localized genetic and/or environmental trends that may influence variation in dental development. Addressing this gap, tooth mineralization scores were collected from dental radiographs associated with subadult individuals (6–16 years of age) from Community Service Learning Centers (CSLC) affiliated with the East Carolina University School of Dental Medicine (SoDM) with a total sample size of n = 976. The CSLC locations are geographically and demographically diverse and include populations across North Carolina, such as Ahoskie, Lumberton (Robeson County), Ross Hall (Greenville, NC), Spruce Pine, and Sylva. Results were compared against previously published research associated with the Subadult Virtual Anthropology Database (SVAD) and contextualized within demographic factors such as geographic location, biological sex, self-described race, and ethnicity. The results demonstrate that the timing of tooth mineralization is similar across North Carolina regardless of geography or demographic composition. CSLC Sylva shows a high degree of delay in mineralization timing for age with most teeth scoring below their counterparts across North Carolina and within the SVAD sample. This delay is most severe during root development and may be a product of local environmental factors in western North Carolina (CSLC Sylva). Early forming teeth notably exhibit more extreme degrees of delay compared to their later forming counterparts. The results do corroborate the stability shown in previous research, but also capture the variation that may be missed when pooling samples by broad geographic or environmental categories.