Association of genetic and environmental factors with dental caries among adolescents in south China: A cross-sectional study

Oral health and caries/gingivitis-associated factors of adolescents aged 12-15 in Shandong province, China: a cross-sectional Oral Health Survey

Background

We aimed to analyse the oral health status of adolescents in Shandong province, including dental caries and gingivitis, and their associated factors.

Methods

Adolescents aged 12–15-years in Shandong province were recruited. Caries and gingival status were assessed following the World Health Organisation diagnostic criteria. Information including the sociodemographic, oral hygiene knowledge, attitudes and practices were collected through the questionnaire. Chi-square test and multivariate logistic regression analysis were used to investigate the oral diseases associated factors.

Results

In total, 3868 students (50.2% males) were enrolled. Of these, 39.9% of the participants experienced caries, and 81.7% and 31.3% had calculus and bleeding gingival, respectively. Multivariate logistic regression analysis revealed that there was an association between dental caries and toothaches, dental visits and sleeping troubles caused by oral problems (P < 0.024). A low-frequency of brushing, high sugar consumption and no flossing were more associated with calculus formation and gingival bleeding (P < 0.008).

Conclusion

Compared to caries, worse gingival condition was more prevalent among adolescents in Shandong province. Brushing behaviour is associated with gingivitis, while dental visits and toothaches are associated with caries. Hence, prevention-oriented dental visits and oral hygiene training are strongly recommended to improve oral health status.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-021-01640-x.

Factors Affecting Future Caries Occurrence Among Preschoolers in Northern Guangdong: A Longitudinal Study

Purpose

This study aimed to investigate the new development of caries among preschoolers in northern Guangdong and to assess caries-related factors to distinguish groups with different caries risk levels.

Methods

Baseline data were recorded for participants from September to November 2019, and participants were reexamined from September to November 2020. A longitudinal observation of 11,973 preschoolers was conducted. The simplified debris index (DI-S) and decayed-missing-filled tooth (dmft) index values were obtained for each participant.

Results

Factors associated with whether caries would occur in the future and one-year increase in dmft (Δdmft) included baseline dmft, baseline DI-S, and baseline age. The risk ratio (RR) of caries occurrence and the number of teeth with new-onset caries were 4.482 (95% confidence interval, 4.056-4.957) and 2.945 (2.742-3.165) in the participants with baseline dmft ≥3, which were higher than those with baseline dmft =1 or 2. In the baseline caries-free group, whether caries would occur in the future was related to the baseline DI-S (95% confidence interval, 0.022-0.062). The caries incidence of maxillary central incisors (27.9%) was the highest among teeth of preschoolers without caries at baseline, whereas the caries incidence of mandibular first deciduous molars (42.7%) was the highest among teeth of preschoolers with caries at baseline.

Conclusion

Baseline dmft is a good predictor of future caries. Children with baseline caries-free status, baseline dmft >0, and baseline dmft ≥3 should be treated with preventive interventions of different intensities and frequencies. The occurrence of future caries in baseline caries-free participants is related to oral hygiene status. Measures to prevent caries on smooth surfaces, such as topical fluoridation, should be applied to all preschoolers. Preschoolers with caries at baseline may be given priority for pit and fissure sealing.

A New Model for Caries Risk Prediction in Teenagers Using a Machine Learning Algorithm Based on Environmental and Genetic Factors

Dental caries is a multifactorial disease that can be caused by interactions between genetic and environmental risk factors. Despite the availability of caries risk assessment tools, caries risk prediction models incorporating new factors, such as human genetic markers, have not yet been reported. The aim of this study was to construct a new model for caries risk prediction in teenagers, based on environmental and genetic factors, using a machine learning algorithm. We performed a prospective longitudinal study of 1,055 teenagers (710 teenagers for cohort 1 and 345 teenagers for cohort 2) aged 13 years, of whom 953 (633 teenagers for cohort 1 and 320 teenagers for cohort 2) were followed for 21 months. All participants completed an oral health questionnaire, an oral examination, biological (salivary and cariostate) tests, and single nucleotide polymorphism sequencing analysis. We constructed a caries risk prediction model based on these data using a random forest with an AUC of 0.78 in cohort 1 (training cohort). We further verified the discrimination and calibration abilities of this caries risk prediction model using cohort 2. The AUC of the caries risk prediction model in cohort 2 (testing cohort) was 0.73, indicating high discrimination ability. Risk stratification revealed that our caries risk prediction model could accurately identify individuals at high and very high caries risk but underestimated risks for individuals at low and very low caries risk. Thus, our caries risk prediction model has the potential for use as a powerful community-level tool to identify individuals at high caries risk.