Identifying high-risk children for dental caries in school settings: A simple predictive model.

Abstract

Untreated caries in permanent teeth is the most prevalent condition worldwide. Use of a simple, validated caries risk prediction tool will offer a low-cost mechanism to identify high-risk children for targeted preventive programmes. To develop and validate a caries risk prediction model for 5-6-year-old Sri Lankan children. Methods Two case-control studies were done for model development and validation. Cases and controls were defined as 8-9-year-olds with and without permanent tooth caries respectively. Based on dental records and confirmation by clinical examination, 120 cases and 360 controls for model development, and 100 cases and 100 controls for model validation were selected. Data was collected using dental records and a pretested parental self-administered questionnaire. Risk predictors were identified by logistic regression analysis. Cut-off point was determined by plotting a ROC curve. Four risk predictors were identified: 'having 5 or more posterior decayed teeth' (OR= 2.1, 95% CI: 1.0 - 4.4), 'brushing frequency of once or less' (OR= 3.5, 95% CI: 2.1 - 6.0), 'not using fluoridated toothpaste' (OR= 3.2, 95% CI: 1.8 - 5.6) and 'consuming more than two snacks containing fermentable carbohydrates in between meals' (OR= 1.6, 95% CI: 0.9 - 2.9). A 10-point score was developed. Following external validation, a sensitivity of 31% (95% CI: 22.1% - 41.0 %) and a specificity of 87% (95% CI: 78.8% - 92.9 %) was obtained for a cut-off value of 2.5. The model could be used to identify high-risk children, especially in areas with higher disease burdens.