The Dental Aesthetic Index and dental health component of the Index of Orthodontic Treatment Need as tools in epidemiological studies

Int J Environ Res Public Health. 2011 Aug;8(8):3277-86. doi: 10.3390/ijerph8083277. Epub 2011 Aug 9.

Abstract

The present study assesses the validity and reproducibility of two occlusal indices for epidemiological studies--the Dental Aesthetic Index (DAI) and the Dental Health Component of the Index of Orthodontic Treatment Need (DHC-IOTN) for the identification of orthodontic treatment needs. The total of 131 study models was examined by an examiner (orthodontic specialist) for the determination of the DAI and DHC-IOTN. Thirty days later, further assessment was performed to determine the reproducibility. The duration of each exam was measured in seconds with a stopwatch. The indices were compared by a panel of three experts in orthodontics to evaluate validity. The intra-examiner reliability evaluation resulted in an intraclass correlation coefficient of 0.89 for the DAI (95% CI = 0.64 to 1.0) and 0.87 for the DHC-IOTN (95% CI = 0.56 to 0.96). The time spent on the evaluation of the DHC-IOTN was less than the time spent on that of the DAI (P < 0.001). The accuracy of the indices, as reflected by the area under the receiver-operating characteristic curve, was 61% for the DAI (95% CI = 51 to 70; p = 0.037) and 67% for the DHC-IOTN (95% CI = 58 to 77; p = 0.001). Both indices presented good reproducibility and validity.

Keywords: epidemiology; indexes; orthodontics.

Publication types

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

MeSH terms

  • Adolescent
  • Brazil
  • Child
  • Epidemiologic Studies
  • Esthetics, Dental / classification*
  • Esthetics, Dental / statistics & numerical data
  • Humans
  • Index of Orthodontic Treatment Need / methods*
  • Index of Orthodontic Treatment Need / statistics & numerical data
  • Observer Variation
  • Oral Health / classification*
  • Orthodontics, Corrective / methods*
  • Reproducibility of Results
  • Statistics, Nonparametric