Review and recommendations for zero-inflated count regression modeling of dental caries indices in epidemiological studies.
Over the past 5-10 years, zero-inflated (ZI) count regression models have been increasingly applied to the analysis of dental caries indices (e.g. DMFT, dfms). The main reason for that is linked to the broad decline in children's caries experience, such that dmf and DMF indices more frequently generate low or even zero counts. This article specifically reviews the application of ZI Poisson and ZI negative binomial regression models to dental caries, with emphasis on the description of the models and the interpretation of fitted model results given the study goals. The review finds that interpretations provided in the published caries research are often imprecise or inadvertently misleading, particularly with respect to failing to discriminate between inference for the class of susceptible persons defined by such models and inference for the sampled population in terms of overall exposure effects. Recommendations are provided to enhance the use as well as the interpretation and reporting of results of count regression models when applied to epidemiological studies of dental caries.
Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA. jpreisse@bios.unc.edu
J S
JS
Preisser
J W
JW
Stamm
D L
DL
Long
M E
ME
Kincade
D016010:Binomial Distribution; D004245:DMF Index; D003731:Dental Caries / Q000453:epidemiology*; D016021:Epidemiologic Studies; D006801:Humans; D015994:Incidence; D016012:Poisson Distribution; D015995:Prevalence; D012044:Regression Analysis