Applying Bayesian Model to Predict Socio-demographic and Occlusal Determinants of Early Childhood Caries (ECC)

Abstract

Objective: To use the Bayesian statistical Model approach to predict the most important socio-demographic and occlusal factors pertinent to high prevalence of ECC. Material and Methods: A questionnaire and an oral examination was conducted on children who attended a pediatric dental clinic in Nairobi during the period of study. The parents provided information on socio-demographic and oral habits of the children. The oral examination for presence of dental caries was recorded for each child. Descriptive statistics were obtained for dental caries, oral hygiene, using plaque score, and malocclusion. The results of the questionnaire and presence of dental caries were analyzed and the results subjected to Bayesian statistical analysis to determine any predictive factors for ECC. Results: 55% of the children had plaque accumulating on more than one third but less than two thirds of tooth surfaces. The highest plaque scores were reported among children whose fathers (48.2%) and mothers (42.0%) had completed secondary, and whose fathers were in non-formal employment 73.2%. The overall prevalence of dental caries in the study group was 95.5% with a mean dmft of 8.53 (+ 5.52 SD), with the male children having higher dmft 8.65 (SD+5.54) than the female children 8.37 (SD+ 5.50). The prevalence of malocclusion among children in the study was 55%. The majority had mesial step, 51.5% (n=140) and flush terminal plane 28.3% (n=77). Conclusion: The Bayesian Model, with a correct assumption, can be used to determine the important factors involved in high prevalence of ECC.