Dental caries or tooth decay is the most common oral health problem. Although it is quite preventable, it still remains the most common chronic disease of children aged 5 to 17 years, and has been linked with poor academic performance, low self confidence and poor peer interactions.

Despite the many epidemiologic studies conducted to assess the intra-oral pattern of dental caries, there are still some unanswered questions. There are four quadrants in the mouth believed to be inter-correlated and it is widely believed that dental caries develop symmetrically within the mouth but much statistical results are still needed. Most of the previous studies have relied on the usage of the decayed, missing, and filled (DMF) index developed in the 1930s, to analyze dental caries outcomes. It has its limitations in explaining the development of caries and is unable to measure tooth-specific problems such as caries patterns. It is speculated that a more effective manner to study the spatial distribution of dental caries may be to analyze using adequate statistical models such as generalizing estimated equations (GEE), and Alternating Logistic Regression (ALR). Such models can be used to determine tooth surface susceptibility to caries formation and to answer questions regarding dental caries spatial distribution that may exist in the mouth. These findings should enable dentists/hygienists to detect dental caries at earlier stages and provide more subject specific treatment plans.