Abstract
One of the principal conditions that affects oral health worldwide is dental caries, occurring in about 90% of the global population. This pathology has been considered a challenge because of its high prevalence, besides being a chronic but preventable disease which can be caused by a series of different demographic, dietary, among others. Based on this problem, in this research a demographic and dietary features analysis is performed for the classification of subjects according to their oral health status based on caries, according to the age group where the population belongs, using as feature selector a technique based on fast backward selection (FBS) approach for the development of three predictive models, one for each age range (group 1: 10–19; group 2: 20–59; group 3: 60 or more years old). As validation, a net reclassification improvement (NRI), AUC, ROC, and OR values are used to evaluate their classification accuracy. We analyzed 189 demographic and dietary features from National Health and Nutrition Examination Survey (NHANES) 2013–2014. Each model obtained statistically significant results for most features and narrow OR confidence intervals. Age group 2 obtained a mean NRI = −0.080 and AUC = 0.933; age group 3 obtained a mean NRI = −0.024 and AUC = 0.787; and age group 4 obtained a mean NRI = −0.129 and AUC = 0.735. Based on these results, it is concluded that these specific demographic and dietary features are significant determinants for estimating the oral health status in patients based on their likelihood of developing caries, and the age group could imply different risk factors for subjects.
Highlights
Health is a condition that presents difficulties in its description due to its different definitions.According to the World Health Organization (WHO), health can be defined as a physical, mental, and social healthy status and as the absence of diseases
According to the contributions mentioned above, the hypothesis of this work makes reference to the possibility of developing a multivariate model through statistical analysis—based on demographic and dietary features that were provided from National Health and Nutrition Examination Survey (NHANES) 2013–2014—that is able to automatically classify between patients with the presence and absence of caries, in order to find a tool that provides information about the risk factors that make subjects vulnerable to dental caries, according to their age range
Results obtained from the feature extraction using a fast backward selection (FBS) approach for each dataset and the validation of each multivariate model using net reclassification improvement (NRI), OR, receiver operating characteristic (ROC), and area under the curve (AUC) are presented
Summary
Health is a condition that presents difficulties in its description due to its different definitions. Other statistical parameters that are commonly used in clinical research include the receiver operating characteristic (ROC) curve, the area under the curve (AUC), the benefit function, and the Brier score, among others [10] Based on this general oral health problem description, the main contribution of this paper is to analyze the relationship between demographic and dietary features and the dental caries status, in order to develop a multivariate model (based on CADx) for three different age groups for the classification of subjects according to their dental caries status (presence/absence), in addition to looking for the different features that affect the age groups. According to the contributions mentioned above, the hypothesis of this work makes reference to the possibility of developing a multivariate model through statistical analysis—based on demographic and dietary features that were provided from National Health and Nutrition Examination Survey (NHANES) 2013–2014—that is able to automatically classify between patients with the presence and absence of caries, in order to find a tool that provides information about the risk factors that make subjects vulnerable to dental caries, according to their age range
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