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Dimensional and discrete dental trait asymmetry relationships
American Journal of Physical Anthropology
|March 1, 1986
Summary
This study examined dental asymmetry in Inuit populations, finding no significant differences between upper and lower teeth. While some patterns align with tooth field models, random dental asymmetry remains difficult to test.
Area of Science:
- Anthropology
- Paleodontology
- Human Biology
Background:
- Dental asymmetry, both dimensional and morphological, offers insights into developmental processes.
- Previous research suggests varying patterns of asymmetry across different populations and tooth types.
Purpose of the Study:
- To quantify dimensional and morphological dental asymmetry in Inuit (Eskimos) from the Foxe Basin.
- To investigate conformity to tooth field models and Dahlberg's Field Concept.
- To explore associations between dental asymmetry and tooth size.
Main Methods:
- Analysis of dental casts or direct examination of dentitions from the study population.
- Measurement of tooth dimensions to assess dimensional asymmetry.
- Assessment of morphological traits to evaluate morphological asymmetry.
Main Results:
- No significant difference in dimensional asymmetry was observed between maxillary and mandibular teeth.
- Both dimensional and morphological asymmetry showed partial conformity to tooth field models, increasing distally.
- Mandibular incisors presented an exception in morphological asymmetry, aligning with Dahlberg's Field Concept.
- No detectable patterns were found in rank-order correlations between dimensional and morphological asymmetry.
- No association was found between the presence of morphological asymmetry and tooth size.
Conclusions:
- Dental asymmetry in this Inuit population exhibits specific patterns related to tooth position and developmental fields.
- The lack of association between morphological asymmetry and tooth size may relate to differential developmental timing, requiring further investigation.
- Testing hypotheses on random dental asymmetry is challenging due to inherent variability and data limitations.