Department of Child Dental Health and Orthodontics, Faculty of Dental Surgery, University of Malta, Msida, Malta.
Department of Oral Rehabilitation and Community Care, Faculty of Dental Surgery, University of Malta, Msida, Malta.
BMC Oral Health. 2022 Jul 28;22(1):312. doi: 10.1186/s12903-022-02334-8.
Despite increasing prevalence, age-specific risk predictive models for erosive tooth wear in preschool-age children have not been developed. Identification of at-risk groups and the timely introduction of behavioural change or treatment will stop the progression of erosive wear in the permanent dentition. This study aimed to identify age-specific risk factors for erosive wear. Distinct risk prediction models for 3-year-old and 5-year-old children were developed.
A prospective cohort study included school-based clinical examinations and parent administered questionnaires for consented 3 and 5-year-old healthy children. Calibrated examiners measured the following health parameters under standardised conditions: erosion, using the Basic Erosive Wear Examination Index (BEWE), caries using the International Caries Detection and Assessment System (ICDAS), plaque and calculus according to the British Association for the Study of Community Dentistry (BASCD) scores, dental traumatic injuries and soft tissue lesions, salivary testing and BMI. Other health conditions were collected via a parent-administered questionnaire that explored oral- and general-health. Non parametric tests were utilised to explore the temporal relation of erosion with, demographic factors, oral hygiene habits, general health and dietary habits. Variables showing significance with a difference in BEWE cumulative score over time were utilised to develop two risk prediction models. The models were evaluated by Receiver Operating Characteristics analysis.
Risk factors for the 3-year-old cohort (N = 336) included erosive wear (χ(1, 92) = 12.829, p < 0.001), district (χ(5, 92) = 17.032, p = 0.004) and family size (χ(1, 92) = 4.547, p = 0.033). Risk factors for the 5-year-old cohort (N = 441) also included erosive wear (χ(1, 144) = 4.768, p = 0.029), gender (χ(1, 144) = 19.399, p < 0.001), consumption of iced tea (χ(1, 144) = 8.872, p = 0.003) and dry mouth (χ(1, 144) = 9.598, p = 0.002).
Predictive risk factors for 3-year-old children are based on demographic factors and are distinct from those for 5-year-old children based on biological and behavioural factors. Erosive wear is a risk factor for further wear in both age cohorts.
尽管患病率不断上升，但针对学龄前儿童的侵蚀性牙齿磨损的特定年龄风险预测模型尚未建立。识别高危人群并及时引入行为改变或治疗将阻止恒磨牙中侵蚀性磨损的进展。本研究旨在确定侵蚀性磨损的特定年龄相关风险因素。为 3 岁和 5 岁儿童开发了不同的风险预测模型。
一项前瞻性队列研究纳入了基于学校的临床检查和同意的 3 岁和 5 岁健康儿童的家长管理问卷调查。经过校准的检查者在标准化条件下测量了以下健康参数：使用基本侵蚀性磨损检查指数 (BEWE) 测量侵蚀情况、使用国际龋病检测和评估系统 (ICDAS) 测量龋齿、根据英国社区牙科研究协会 (BASCD) 评分测量牙菌斑和牙石、根据牙齿创伤损伤和软组织病变、唾液测试和 BMI。通过家长管理的问卷收集其他健康状况，该问卷探讨了口腔和一般健康状况。非参数检验用于探讨侵蚀性与人口统计学因素、口腔卫生习惯、一般健康和饮食习惯之间的时间关系。显示出随着时间推移而在 BEWE 累积评分上存在差异的变量被用于开发两个风险预测模型。通过接收者操作特征分析评估模型。
3 岁队列（N=336）的风险因素包括侵蚀性磨损（χ(1, 92)=12.829，p<0.001）、区（χ(5, 92)=17.032，p=0.004）和家庭规模（χ(1, 92)=4.547，p=0.033）。5 岁队列（N=441）的风险因素还包括侵蚀性磨损（χ(1, 144)=4.768，p=0.029）、性别（χ(1, 144)=19.399，p<0.001）、冰茶消费（χ(1, 144)=8.872，p=0.003）和口干（χ(1, 144)=9.598，p=0.002）。
3 岁儿童的预测风险因素基于人口统计学因素，而 5 岁儿童的预测风险因素则基于生物学和行为因素。侵蚀性磨损是两个年龄组中进一步磨损的风险因素。
