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The Application of the Cameriere’s Methodologies for Dental Age Estimation in a Select KwaZulu-Natal Population of South Africa

Dent J (Basel). 2022 Jul 8;10(7):130. doi: 10.3390/dj10070130.

ABSTRACT

BACKGROUND: The estimation of an individual’s age is a fundamental component of forensic odontology. Literary reports found that the efficiency of Cameriere methodology for age estimation varied among many population groups. Therefore, this study aimed to determine the applicability of the Cameriere methods to a select South African population of the KwaZulu-Natal (KZN) province.

MATERIALS AND METHODS: This cross-sectional retrospective study was conducted on 840 digital panoramic radiographs that met the inclusion criteria. Dental maturity was determined through the morphometric analysis of the seven left permanent mandibular and maxillary teeth in accordance with Cameriere et al. (2006). Moreover, the dental age was also calculated using the South African Black Bayesian formulae of the Cameriere method by Angelakopoulos et al. (2019). The paired sample t-test or Wilcoxon’s signed rank test assessed the significant difference between the chronological age and estimated dental age for the various formulae. A p-value < 0.05 was considered to be statistically significant.

RESULTS: The Cameriere et al. (2006) Italian formula and the South African Black Bayesian formulae of the Cameriere method by Angelakopoulos et al. (2019) underestimated and overestimated age in the South African Black and Indian population groups of the KZN province, respectively. Therefore, the authors generated a novel population-specific regression formulae (including and excluding third molars) using “step-wise regression analysis” and a “best-fit model” for the South African Black and Indian population groups of KZN.

CONCLUSION: This study recommends that the population-specific formulae generated in this study be utilized in the KZN population to improve the accuracy of dental age estimation within this region.

PMID:35877404 | DOI:10.3390/dj10070130

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