A Case⁻Control Study of Socio-Economic and Nutritional Characteristics as Determinants of Dental Caries in Different Age Groups, Considered as Public Health Problem: Data from NHANES 2013⁻2014

Influence of digital media in the oral health education of mother-child pairs: study protocol of a parallel double-blind randomized clinical trial

BACKGROUND

Dental caries is the most common non transmissible chronic disease in childhood and the control of dental biofilm in children is one of the greatest challenges in oral disease prevention. Digital media applications can help patients in improving their oral hygiene performance and reducing the number of appointments due to pain and discomfort reasons. This study aims to investigate the use of an smartphone application (WhatsApp) to deliver oral health education to mother-child pairs, with the ultimate goal of controlling dental biofilm and caries through digital activities focused on oral hygiene.

METHODS

This study was designed as a randomized, double-blind, parallel clinical trial involving 100 pairs of mothers and children (6-12 years old). The mothers and children will be randomly allocated to the control group (n = 50 pairs), who will receive a single visit conventional oral health education, or to the experimental group (n = 50 pairs), who will receive both a single visit conventional oral health education and educational videos through WhatsApp Messenger, twice a week. Before randomization of the groups and after the intervention, pairs will be evaluated regarding to plaque index (VPI), gingival bleeding index (GBI), and number of decayed, missing and filled permanent or primary teeth (DMF-T) modified by the inclusion of active non-cavitated carious lesions (Nyvad criteria). Socioeconomic data, dental history, and oral health literacy will obtained using questionnaires (Oral Health Literacy Assessment Task for Paediatric Dentistry; BOHLAT-P). Chi-square, Student's t-test, paired Student's t-test, Mann-Whitney, and Friedman tests will be used with a 5% significance level.

DISCUSSION

This intervention proposal is designed to motivate behavioral change in mother-child pairs. We hypothesize that adding digital media to traditional oral health programs will provoke improvements in oral hygiene behavior and health outcomes. To our knowledge, this is the first study evaluating the effect of educational videos communicated by digital media (WhatsApp) on the oral health of mother-child pairs evaluated by long-term dental examinations. In addition, we will assess the maternal level of comprehension of the provided information via a literacy assessment tool. The clinical trial is registered at the Brazilian Registry of Clinical Trials (No. RBR-7s8bw6m).

Factors Associated with E-Cigarette Use in U.S. Young Adult Never Smokers of Conventional Cigarettes: A Machine Learning Approach

E-cigarette use is increasing among young adult never smokers of conventional cigarettes, but the awareness of the factors associated with e-cigarette use in this population is limited. The goal of this work was to use machine learning (ML) algorithms to determine the factors associated with current e-cigarette use among US young adult never cigarette smokers. Young adult (18-34 years) never cigarette smokers from the 2016 and 2017 Behavioral Risk Factor Surveillance System (BRFSS) who reported current or never e-cigarette use were used for the analysis (n = 79,539). Variables associated with current e-cigarette use were selected by two ML algorithms (Boruta and Least absolute shrinkage and selection operator (LASSO)). Odds ratios were calculated to determine the association between e-cigarette use and the variables selected by the ML algorithms, after adjusting for age, gender and race/ethnicity and incorporating the BRFSS complex design. The prevalence of e-cigarette use varied across states. Factors previously reported in the literature, such as age, race/ethnicity, alcohol use, depression, as well as novel factors associated with e-cigarette use, such as disabilities, obesity, history of diabetes and history of arthritis were identified. These results can be used to generate further hypotheses for research, increase public awareness and help provide targeted e-cigarette education.

Deep Artificial Neural Networks for the Diagnostic of Caries Using Socioeconomic and Nutritional Features as Determinants: Data from NHANES 2013⁻2014

Oral health represents an essential component in the quality of life of people, being a determinant factor in general health since it may affect the risk of suffering other conditions, such as chronic diseases. Oral diseases have become one of the main public health problems, where dental caries is the condition that most affects oral health worldwide, occurring in about 90% of the global population. This condition has been considered a challenge because of its high prevalence, besides being a chronic but preventable disease which can be caused depending on the consumption of certain nutritional elements interacting simultaneously with different factors, such as socioeconomic factors. Based on this problem, an analysis of a set of 189 dietary and demographic determinants is performed in this work, in order to find the relationship between these factors and the oral situation of a set of subjects. The oral situation refers to the presence and absence/restorations of caries. The methodology is performed constructing a dense artificial neural network (ANN), as a computer-aided diagnosis tool, looking for a generalized model that allows for classifying subjects. As validation, the classification model was evaluated through a statistical analysis based on a cross validation, calculating the accuracy, loss function, receiving operating characteristic (ROC) curve and area under the curve (AUC) parameters. The results obtained were statistically significant, obtaining an accuracy ≃ 0.69 and AUC values of 0.69 and 0.75. Based on these results, it is possible to conclude that the classification model developed through the deep ANN is able to classify subjects with absence of caries from subjects with presence or restorations with high accuracy, according to their demographic and dietary factors.