Ordinal logistic regression modeling of dental caries among preschool children in Bachok district, Kelantan, Malaysia

Abstract

Ordinal logistic regression is a statistical technique used to model a categorical response variable of which the outcome consist of multiple categories having natural order or rank. Modelling in ordinal regression is to calculate cumulative probabilities of the response variable, which considers the probability of a particular category and all others above it in the ordinal ranking. A common approach used in ordinal logistic regression models is to assume that the cumulative probabilities have the same slopes, the assumption of proportional odds. In the proportional odds model, the effect of a predictor variable on the odds of an event occurring in every subsequent category is the same for every category. This study applied ordinal logistic regression to model dental caries status of preschool children in the area of Bachok, Kelantan based on the children's demographic profiles, the families' sociodemographic profiles and parent's awareness on dental care. Early childhood caries is one of the most common chronic disease. It affects the quality of life of young children as it causes anxiety, eating impairment, children's poor concentration in learning and financial burden to their families. The results indicated that high dental caries status is related to mothers' education level and parent's awareness of practice level. The odds of high number of dental caries is higher among children whose mothers of middle education level and parent's low practice on dental care.