Predicting population dental disease experience at a small area level using Census and health service data

Background: Information on the dental disease patterns of child populations is required at a small area level. At present, this can be provided only by expensive whole population surveys. The aim of this study was to evaluate the ability of Census data combined with health service information to provide estimates of population dental disease experience at the small area level. Method: Clinical dental data were collected from a large cross-sectional survey of 5-year-old children. A preliminary series of bivariate linear regression analyses were undertaken at ward level with the mean number of decayed, missing or filled teeth per child (dmft) as the dependent variable, and the Census and health service and lifestyle variables suspected of having a strong relationship with dmft as independent variables. This was followed by fitting a multiple linear regression model using a stepwise procedure to include independent variables that explain most of the variability in the dependent variable dmft. Results: All deprivation indicators derived from the Census showed a highly significant (p