Equation for tooth size prediction from mixed dentition analysis for taiwanese population: A pilot study

See Yen Chong, Lwin Moe Aung, Yu Hwa Pan, Wei Jen Chang, Chi Yang Tsai

Research output: Contribution to journalArticlepeer-review

Abstract

Background: In mixed dentition analysis, estimation of the mesiodistal width of unerupted permanent canines and premolars is essential for successful diagnosis and treatment planning. The present study aimed to develop a simple linear equation to predict permanent tooth sizes from mixed dentition analysis for Taiwanese people. Methods: The sample comprised 200 dental casts, derived from Taiwanese patients (100 males and 100 females; age, 12–35 years). Mesial distal tooth widths were measured in dental casts with a digital caliper. A student’s t-test was conducted to detect tooth size correlations with gender-specific differences, as well as intra-arch counterparts. Standard linear regression was conducted to develop a simple equation representing predictions of canine-premolar relationships. Results: All teeth were not significantly different between the left and right sides, regardless of gender and upper or lower arches. In terms of types of teeth, males had larger tooth dimensions in both arches than females. New regression equations for estimating the dimensions of the unerupted canines and premolars in the Taiwanese population were developed. Conclusions: Using a sample of Taiwanese people, new models derived for females and males separately were developed, which should provide highly accurate predictions for unerupted canines and premolars in the Taiwanese population.

Original languageEnglish
Article number6356
JournalInternational journal of environmental research and public health
Volume18
Issue number12
DOIs
Publication statusPublished - Jun 2 2021

Keywords

  • Mixed dentition analysis
  • Moyers’ probability tables
  • Regression equation
  • Taiwanese
  • Tanaka–Johnston
  • Tooth size prediction

ASJC Scopus subject areas

  • Pollution
  • Public Health, Environmental and Occupational Health
  • Health, Toxicology and Mutagenesis

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