Graduation Year

2011

Document Type

Thesis

Degree

M.A.

Degree Granting Department

Anthropology

Major Professor

Erin H. Kimmerle, Ph.D.

Committee Member

David A. Himmelgreen, Ph.D.

Committee Member

Lorena Madrigal, Ph.D.

Keywords

Transition Analysis, Bayesian Analysis, Forensic Anthropology, Human Variation, Age Estimation

Abstract

Due to the strong genetic component of dental development, research has shown that mineralization patterns of the human dentition are relatively buffered against environmental influences that normally affect bone growth and development. It is because of this resistance to environmental factors and the continuous growth of the permanent dentition throughout childhood and adolescence that the evaluation of dental development patterns has become the preferred method of age estimation in living and deceased children.

Researchers (Harris and Mckee 1990; Tompkins 1996; Blankenship et al. 2007; Kasper et al. 2009) have suggested that the timing of dental development varies by ancestral descent and geographic populations. However, further evaluations of these perceived differences in the timing of dental development among populations are necessary as classical statistical methods result in age estimations that are biased toward the age structure of the reference population. However, the Bayesian approach is beneficial since it incorporates relevant prior knowledge into the analysis and formalizes the relationship between assumptions and conclusions (Buck et al. 1996). Therefore, the purpose of this research is to incorporate methods in Bayesian analysis to compare the timing of dental development between two contemporary populations of the Southeastern United States, as well as test the accuracy of dental development age parameters devised by Moorrees et al. (1963) on a contemporary Florida Population.

For this study, 51 panoramic radiographs of individuals from a contemporary Florida population ranging in age from 7.7-20.4 years were reviewed. Statistical analyses incorporated a Bayesian approach to compare the timing of dental development for individuals comprising the contemporary Florida sample with the timing of dental development for a contemporary Middle Tennessee population by utilizing the age structure of the Middle Tennessee population as informed prior knowledge, otherwise referred to as an informed prior. Transition distributions for age, given stage of dental development, were also modeled for individuals comprising the contemporary Florida sample. The accurate observation and comparison of probability density distributions for age can serve as a noninvasive method for evaluating the probability of whether or not an unknown individual is a particular age, given the stage of dental development.

Results of this research indicate that there is a consistent underestimation of age for individuals comprising the contemporary Florida population when the age structure of the Middle Tennessee population is utilized as an informed prior. Additionally, the results of this thesis indicate that there is a consistent underestimation of age when utilizing age parameters of Moorrees et al. (1963) for the estimation of age for individuals from a contemporary Florida population. By incorporating a Bayesian approach to compare two contemporary populations of the Southeastern United States, a comprehensive analysis of the relationship between age and stage of dental development can be achieved. Therefore, the results of this thesis support Bayesian analysis as an appropriate method of evaluating perceived differences in the timing of dental development between contemporary populations. Furthermore, the results of this research are beneficial to the field of forensic anthropology as the observation of advanced stages of molar development utilizing panoramic radiographs serves as a noninvasive method in estimating age for unknown juveniles and young adults, and can also assist courts within the United States in determining whether or not an individual is legally considered a minor or an adult.

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