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Published on: August 15, 2018
Age estimation using extracted teeth in coastal Karnataka population
S Kavya1, Sudeendra Prabhu1, Soniya Adyanthya1
1Centre for Forensic Odontology, Department of Oral Pathology and Microbiology, Yenepoya Dental College, Yenepoya (Deemed to be) University, Mangalore, Karnataka, India.
Introduction:
Age estimation using regressive alterations such as root dentin translucency, PDL attachment, and attrition are easy and reliable way of predicting the age. However, extensive and population-specific formula has not been generated. This attempt was to assess the correlation of these alterations with age and to generate a Linear regressive formula, specific to this population.
Methods And Material:
Three alterations were assessed such as dental attrition, root dentin translucency, and periodontal attachment level from the extracted teeth. Dental attrition was measured using Johanson's and Li and Ji criteria. PDL attachment level and root dentin translucency was measured using the Johanson method and the Lamendin method.
Statistical Analysis:
SPSS software (Version 27), Pearson correlation test, and Linear regressive analysis were used.
Results:
Our results showed all three factors/parameters such as attrition, periodontal ligament, and translucency having a very good correlation with age and correlation coefficient r value ranging from 0.6 to 0.8. All the parameters were having statistically significant correlation with P value <0.005. Among them, root dentin translucency with Johanson G method showed excellent correlation with r = 0.83 followed by PDL attachment by Johanson G method with r = 0.702.
Conclusions:
Regressive changes such as Dentin translucency, PDL attachment and attrition on Coastal Karnataka showed a very good correlation with age. Among them, Dentin translucency by Johanson G method had the best correlation with the a standard error of estimate (SEE). Results of our study indicates that all these parameters [Translucency, PDL attachment, and attrition] can be utilized in age estimation.
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