Dental caries experience and related risk indicators of 12-year-old students in Jilin, China

Prediction model of dental caries in 12-year-old children in Sichuan Province based on machine learning

OBJECTIVES

The machine learning algorithm was used to construct a prediction model of children's dental caries to determine the risk factors of dental caries in children and put forward targeted measures and policy suggestions to improve children's oral health.

METHODS

Stratified cluster random sampling was adopted in this study. In accordance with different policies and measures in Sichuan Province, 12-year-old students from 3-4 middle schools in eight cities of Sichuan Province were randomly selected for questionnaire survey, oral examination, and physical examination. Multivariate logistic regression analysis of risk factors for dental caries in 12-year-old children was conducted. The dataset was randomly divided into training set and validation set at a ratio of 7∶3. Four machine learning algorithms, including random forest, decision tree, extreme gradient boosting (XGBoost), and Logistic regression, were constructed using R version 4.1.1, and the prediction effects of the four prediction models were evaluated using the area under receiver operating characteristic curve (AUC).

RESULTS

A total of 4 439 children aged 12 years were included in this study. The incidence of permanent teeth caries was 50.93%. The results of multivariate logistic regression analysis showed that body mass index, highest educational background of the father, highest educational background of the mother, whether to brush teeth, how many times a day, use of toothpaste when brushing teeth, duration of brushing teeth, mouthwash after meals, eating before going to bed after brushing teeth, sweet drinks, snacks, going to dental clinic to examine teeth, and age of brushing teeth were the factors influencing children's dental caries (P<0.05). The AUC values predicted by random forest, decision tree, Logistic regression, and XGBoost were 0.840, 0.755, 0.799, and 0.794, respectively. In the random forest model, the variable with the highest contribution was eating before bed after brushing.

CONCLUSIONS

A prediction model of dental caries in children was established on the basis of random forest, showing good prediction effect. Taking preventive measures for the main factors affecting the occurrence of dental caries in children is beneficial.

Streptococcus sobrinus as a Predominant Oral Bacteria Related to the Occurrence of Dental Caries in Polish Children at 12 Years Old

Dental caries is listed by the WHO as one of the major non-communicable diseases that need to be prevented and treated. The aim of the study was to evaluate the prevalence and severity of caries expressed as the Decayed, Missing and Filled Permanent Teeth (DMFT) index in 12-year-old Polish children and to verify bacterial species related to the occurrence of dental caries. Quantitative real-time PCR analysis of DNA isolated from saliva samples was performed to detect 8 cariogenic and periopathogenic bacterial strains. A total of 118 Polish children were enrolled in the study. They had low mean DMFT scores of 1.58 ± 1.98. The prevalence of dental caries in the children tested was low (53.4%), with a tendency to decrease compared to previous oral surveys. Bacterial abundance of other species in the dental caries and caries-free groups did not differ; however, periopathogenic Prevotella pallens, Fusobacterium nucleatum along with cariogenic Streptococcus mutans and Lactobacillus fermentum were significantly strongly correlated in the caries-active subjects. The prevalence of S. sobrinus was significantly higher in children with dental caries (p = 0.023) and correlated with higher DMFT. It may temporarily play an important role in the initiation of the cariogenic process or in its enhancement due to an ecological imbalance in dental microbiota.

Regional variations in caries experience, predictors, and follow-up among children and adolescents in Western Norway

OBJECTIVE

To identify regional differences in, and determinants of dental caries among children in western Norway.

MATERIAL AND METHODS

We studied dental caries in 705 children aged 12 years and 18 years living in the southern region (n = 403) and other parts of Hordaland County (n = 302) in Norway. Information on oral hygiene, fluoride intake, and sugar consumption was collected using questionnaires. We also collected information from the Public Dental Service (PDS) on the history of decayed, missing, or filled teeth; professional fluoride application; recall and regular check-up intervals and treatment visits. Residence (southern region versus the rest of Hordaland, the reference) was the independent variable. We analysed regional differences in (i) caries prevalence and severity, (ii) potential contributors to caries, and (iii) procedures and routines in PDS.

RESULTS

Caries prevalence and severity were higher in the southern region (67% and 24%, respectively). Self-reported brushing habits, fluoride use, and sugar consumption patterns were similar between regions. We observed more frequent application of professional fluoride (incidence rate ratio [IRR] = 3.05, 95% CI: 1.99-4.66], fewer check-ups [IRR = 0.88, 95% CI: 0.81-0.95], and fewer treatment visits [IRR = 0.77, 95% CI: 0.60-0.98] among participants in the southern region, compared to the rest of Hordaland. The recall intervals in the southern region were 10% longer among 12-year-olds and 10% shorter among 18-year-olds, compared to their respective counterparts in Hordaland.

CONCLUSIONS

The observed regional gradients in caries experience mirrored regional differences in dental routines and procedures. Caries-related risk behaviours did not explain the observed differences in caries experience.

A predictive nomogram: a cross-sectional study on a simple-to-use model for screening 12-year-old children for severe caries in middle schools

BACKGROUND

A nomogram is a tool that transforms complex regression equations into simple and visual graphs and enables clinicians and patients to conveniently compute output probabilities without needing medical knowledge and complex formulas. The aim of this study was to develop and validate a predictive nomogram to screen for severe caries among 12-year-old children based on risk factors in Sichuan Province, China.

METHODS

A cross-sectional study of 4573 12-year-olds was conducted up to May 2016 in middle schools from three districts and three counties in Sichuan Province, China. All the children underwent oral examinations and completed questionnaires to assess general information, oral impacts on daily performance, dietary habits, subjective health conditions, history of dental trauma, frequency of toothache, dental visits, and knowledge, attitudes, and behaviours toward oral hygiene. Univariate analysis and multivariate logistic regression analysis were used to determine which variables were significantly associated with severe caries (operationalized as DMFT ≥ 3). A nomogram was developed and validated by using the 'rms' package and two cross-validation methods.

RESULTS

Severe caries was found in 537 of the 4573 children (11.74%). Multivariate logistic regression analysis revealed that the following variables predicted a higher risk of severe caries: 'female' [odds ratio (OR) = 1.985, 95% confidence interval (95% CI): 1.63-2.411], 'urban' (OR = 2.389, 95% CI: 1.96-2.91), 'non-only child' (OR = 1.317, 95% CI: 1.07-1.625), 'very poor self-assessment of oral health status' (OR = 2.157, 95% CI: 1.34-3.467) and 'visited a dentist less than 6 months' (OR = 1.861, 95% CI: 1.38-2.505). Multivariate logistic regression analysis also indicated that the following variables predicted a lower risk of severe caries: 'middle level of urbanization' (OR = 0.395, 95% CI: 0.32-0.495) and 'high level of urbanization' (OR = 0.466, 95% CI: 0.37-0.596). Both the fivefold and leave-one-out cross-validation methods indicated that the nomogram model built by these 6 variables displayed good disease recognition ability.

CONCLUSIONS

The nomogram was a simple-to-use model to screen children for severe caries. This model was found to facilitate non-dental professionals in assessing risk values without oral examinations and making referrals to dental professionals.