Regional and gender differences in population-based oral health insurance data

Clin Oral Investig. 2020 Jul;24(7):2331-2339. doi: 10.1007/s00784-019-03090-w. Epub 2019 Oct 29.

Abstract

Objective: Early dental monitoring contributes substantially to good oral health in children. However, little is known on whether children from different geographical regions and gender are equally reached with current preventive and curative oral health strategies. The aim of our study therefore was to explore regional and gender differences in a population-based oral health dataset of Austrian children up to the age of 14.

Materials and methods: We extracted the first electronically available health insurance data of children aged up to 14 years on dental services within a 4-year observation period in Austria and performed a separate analysis in up to 6-year-old children. In addition, we used a smaller randomly selected sample dataset of 3000 children as the large numbers would result in significant, but very small effects.

Results: In a total of 130,895 children, of whom 77,173 children (59%) were up to the age of six, we detected an east-west gradient: The eastern regions of Austria showed an older age at first contact and a higher number of dental services. A child aged up to 6 years who needed more than four dental services had a likelihood of 40% to be from Vienna, Austria's capital city located in the east. The smaller random sample did not show significant gender differences.

Conclusions: Even in regions with a high density of dentists, such as Vienna, we obviously did not reach young children in the same extent as in other regions.

Clinical relevance: Stratified interventions could be developed to overcome regional inequalities.

Keywords: Health services research; Machine learning; Oral health–related quality of life; Pediatric dentistry; Population-based data.

MeSH terms

  • Adolescent
  • Austria / epidemiology
  • Child
  • Child, Preschool
  • Dental Caries* / epidemiology
  • Dental Caries* / prevention & control
  • Humans
  • Insurance Coverage
  • Insurance, Dental* / statistics & numerical data
  • Oral Health*
  • Sex Factors
  • Socioeconomic Factors