Spatial analysis to identify differentials in dental needs by area-based measures

Community Dent Oral Epidemiol. 2002 Apr;30(2):133-42. doi: 10.1034/j.1600-0528.2002.300207.x.

Abstract

Objectives: To examine the association between tooth decay and dental treatment needs in 5-12-year-old schoolchildren in São Paulo with area-level indicators of social development.

Methods: The present study refers to a representative sample of children from the city of São Paulo, Brazil, comprising 2491 girls and boys attending public and private schools in different areas of the city. The assessment of caries and treatment needs followed the international methodological standards prescribed by the World Health Organization. We used spatial data analysis to describe epidemiological measures distributed by small areas, and to explore hypotheses of ecological association between caries indexes and indicators of social development.

Results: Schoolchildren in central districts were less affected by tooth decay and presented fewer dental treatment needs when compared to those in peripheral deprived areas. At the spatial level, average family income, unemployment rate, household overcrowding, and an index of inequality of income distribution were significantly correlated with variables measuring children's caries experience.

Conclusions: The heterogeneous distribution of caries indexes by areas of the city indicates higher levels of dental decay in areas of social deprivation. The delimitation of areas with increased risk of caries and greater dental treatment needs should be helpful to public health services for the formulation of policies and the targeting of resources to address these problems.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brazil / epidemiology
  • Child
  • Child, Preschool
  • Cluster Analysis
  • DMF Index
  • Dental Caries / epidemiology*
  • Female
  • Health Services Needs and Demand / statistics & numerical data*
  • Humans
  • Male
  • Poverty
  • Regression Analysis
  • Risk
  • Small-Area Analysis*
  • Social Class
  • Socioeconomic Factors
  • Statistics, Nonparametric