Dental age assessment in a northern Chinese population

J Forensic Leg Med. 2016 Feb:38:43-9. doi: 10.1016/j.jflm.2015.11.011. Epub 2015 Nov 25.

Abstract

Introduction: Age estimation is imperative in the fields of paediatric dentistry, orthodontics and forensic science. Studies have shown that dental age estimation by the radiological method is reliable and non-destructive. Although Demirjian's method was the most widely used estimation method, in recent studies, the Willems' method has been found to be more accurate. The aim of this study was to compare the accuracy of dental age estimation methods and to modify the Demirjian method to make it more applicable for a northern Chinese population.

Materials and methods: An assessment was made of 1004 digital orthopantomographs of a northern Chinese population (392 boys and 612 girls) ranging in age from 11 to 18 years old. Dental ages were calculated using both the Demirjian method and the Willems method. Discrepancies between chronological ages and dental ages were statistically analysed by the paired t-test and the Wilcoxon signed rank test. A nonlinear fitting method was applied to construct a mathematical model to modify the Demirjian method.

Results: The Demirjian method underestimated age by 0.47 y in boys and 0.63 y in girls, while the Willems method underestimated age by 0.54 y and 1.01 y in boys and girls, respectively. The mean absolute error was 1.08 y for the Demirjian method and 1.22 y for the Willems method.

Conclusion: The Demirjian method was more accurate for estimating dental age compared with the Willems method. However, the Demirjian method may not be suitable for the northern Chinese population; therefore, it should be modified so that it can be used for this population.

Keywords: Demirjian method; Dental age estimation; Modified Demirjian method; Northern Chinese population; Willems method.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Age Determination by Teeth / methods*
  • Asian People*
  • Child
  • China
  • Female
  • Humans
  • Male
  • Models, Statistical
  • Radiography, Dental, Digital*
  • Radiography, Panoramic*