Author:
Masaebi Fatemeh,Ghorbani Zahra,Azizmohammad Looha Mehdi,Deghatipour Marzie,Mohammadzadeh Morteza,Ahsaie Mitra Ghazizadeh,Asadi Fariba,Zayeri Farid
Abstract
IntroductionEarly permanent dental caries can pose a serious threat to oral health in the coming years. This study aimed to investigate the key factors influencing early dental caries in permanent teeth among first-grade Iranian children.MethodsA cross-sectional study involving 778 randomly selected first-grade children from public schools in Tehran, Iran, was conducted between November 2017 and January 2018. The oral health of the children, evaluated by two trained dentists, was recorded based on the DMFT index. Information on maternal education, gender, dmft index, brushing frequency, dental visits, flossing, and sweet consumption was also collected. The Random Forest method was employed to identify factors associated with early permanent dental caries, and its performance was compared with logistic regression using the Area Under the Curve (AUC) index.ResultsLogistic regression, represented by odds ratios (OR), revealed a significant association between early permanent dental caries and dmft index [OR = 1.13, 95% CI (1.07, 1.20), p-value <0.001], maternal education [OR = 2.04, 95% CI (1.15, 3.62), p-value <0.05], and sweet consumption [OR = 0.59, 95% CI (0.36, 0.98), p-value <0.05]. Random Forest analysis indicated that male gender, higher maternal education, and lower sweet consumption were associated with increased likelihood of being caries-free. Notably, Random Forest demonstrated superior performance (AUC = 0.81) compared to logistic regression (AUC = 0.72).ConclusionEarly permanent dental caries can be effectively managed by caring primary teeth and reducing consumption of sweets. Maternal education emerged as a pivotal factor in mitigating the risk of early permanent dental caries. Therefore, prioritizing these factors and preventing permanent teeth caries in childhood can be remarkably influential in reducing future caries. The usage of the Random Forest algorithm is highly recommended for identifying relevant risk factors associated with early permanent teeth.
Reference34 articles.
1. Global burden and inequality of dental caries, 1990 to 2019;Wen;J Dent Res,2022
2. Pathology of dental caries;Fejerskov;Dental Caries: the Disease and its Clinical Management,2003
3. Determinants of dental caries in children in the Middle East and North Africa region: a systematic review based on literature published from 2000 to 2019;Elamin;BMC Oral Health,2021
4. Evaluation of oral health status based on the decayed, missing and filled teeth (DMFT) index;Moradi;Iran J Public Health,2019