Analysis of periodontal health related factors by using data mining method

데이터 마이닝 기법을 이용한 치주건강 관련요인 분석연구

Objectives: The purpose of this study was to evaluate self-reported symptoms of periodontal diseases. We performed a comprehensive analysis of periodontal health related factors. Methods: 581 volunteers representing a broad range of age from 20 to 65 were recruited from Seoul and Gyeonggi provinces. They participated in a self-administered survey of which the results were analyzed through the decision tree analysis using the data mining program. Results: 67% of the participants reported 'bad breath,' whereas 13.9% of participants reported 'toothache'. The decision analysis revealed that age was the most determining factor of adult periodontal health. Participants in 20s with a profound understanding of their periodontal health status exhibited a low vulnerability to periodontal diseases, whereas those lacking the awareness were more susceptible to the diseases. However, other participants in 30s and older showed a higher vulnerability to periodontal illness than those in 20s, whether or not they had suffered from chronic diseases. Conclusions: In order to effectively prevent periodontal diseases, an age-appropriate clinical approach will be necessary. For the younger age group it will be crucial to enhance the self-awareness of their current oral health status. On the other hand, those in 30s and older will need to pay a close attention to the prevention of chronic periodontal disease.