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How teeth can be used to estimate sexual dimorphism? A scoping review
Tatiana M Herrera-Escudero1, David Arboleda Toro1, Monica T Parada-Sanchez1
1Grupo Estudios Biosociales del Cuerpo, EBSC, Faculty of Dentistry, University of Antioquia, Medellín, Colombia.
Introduction:
Teeth are biological structures with a high degree of hardness, density, calcification, and capacity to adapt to extrinsic factors at physical, biological, and physiological levels. Subsequently, they resist for a longer period in deteriorating environmental conditions. With dental analysis, it is possible to acquire biographical data about a person. The aim of this scoping review was to identify publications using human teeth tissues to estimate sexual dimorphism.
Methods:
The scoping review was carried out in the following databases: Jstor, Scielo, Science Direct, PubMed, and Scopus, using ten search strategies in English and guaranteeing completeness and reproducibility of the phases stipulated in the PRISMA guide.
Results:
143 studies on sexual dimorphism based on dental tissue traits were included, of which 40.6% (n = 58) were done in Asia and 27.2% (n = 39) in America. 80% of the studies (equivalent to 114 articles) focused their observations and measurements on the dental crown; 4.2% in enamel, dentin, and pulp together; 3.5% in dental pulp; 2.1% in the entire tooth; 2.8% in enamel, root, and the enamel-cementum junction, and only 0.7% in dentin and pulp. In addition, 92.3% of the studies used metric methods, while only 4.9% and 2.8% used biochemical and non-metric method respectively.
Conclusion:
For sexual dimorphism establishment, enamel has been the most analyzed dental tissue in permanent canines and molars mainly. Likewise, the most widely and accurately used methods for this purpose are the metrics, with the odontometry as the most implemented (intraoral or by using dental plaster models, digital scanning or software) with prediction percentages ranging from 51% to 95.9%. In contrast to biochemical methods, that can achieve the highest precision (up to 100%), the non-metric methods, to a less extent, reported prediction percentages of 58%.
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