Utilising surface-level data to explore surface, tooth, individual and family influence on the aetiology of hypomineralised second primary molars.
Utilising surface-level data to explore surface, tooth, individual and family influence on the aetiology of hypomineralised second primary molars.
复制标题
利用表面数据探索表面、牙齿、个人和家庭对第二乳磨牙矿化不足病因的影响。
DOI：
10.1016/j.jdent.2021.103797
复制
发表时间：
2021
影响因子：
4.4
通讯作者：
Scurrah,KJ
中科院分区：
文献类型：
--
作者：
Silva,MJ;Zheng,Y;Zaloumis,S;Burgner,DP;Craig,JM;Manton,DJ;Kilpatrick,NM;Scurrah,KJ
目的低矿化第二初级磨牙是常见的发育性牙釉质缺损。本研究的目的是利用表面水平的数据来探讨HSPM在四个水平（家庭、儿童、牙齿、表面）的聚类。方法本研究采用围产期/产后表观遗传双胞胎研究中的172对双胞胎。6岁时采用标准化口腔检查测量HSPM。拟合多水平logistic回归模型，评估地表水位数据与HSPM变化的相关结构。采用最佳拟合相关结构的多水平logistic回归模型探讨地表危险因素与HSPM之间的关系。结果儿童HSPM患病率为68例（19.8%），共有141颗（10.3%）牙和264个牙面（6.3%）受到影响。多层模型显示，在家庭、儿童和牙齿水平上考虑相关性的层次结构最能解释HSPM的变化。最佳拟合模型（模型3）在家庭水平上的估计方差最大（12.27,95% CI 6.68, 22.51），而在儿童水平上的估计方差为5.23，在牙齿水平上的估计方差为1.93。除了先前确定的HSPM的家族性和个人危险因素外，应用该三水平相关结构的回归分析确定了牙齿/表面水平因素。结论HSPM的病因除受家族性（环境和遗传）及儿童特有因素影响外，还可能受局部牙水平因素的影响。
ObjectivesHypomineralised second primary molars (HSPM) are common developmental enamel defects. The aims of this study were to use surface-level data to explore the clustering of HSPM at four levels (family, child, tooth, surface).MethodsThis study of 172 twin pairs was nested within the Peri/postnatal Epigenetic Twin Study. HSPM was measured by standardised oral examinations at age 6 years. Multilevel logistic regression models were fitted to assess the correlation structure of surface level data and variation in HSPM. The associations between surface level risk factors and HSPM were then explored using the multilevel logistic regression model using the best fitting correlation structure.ResultsThe prevalence of HSPM was 68 (19.8%) children, with a total of 141 (10.3%) teeth and 264 tooth surfaces (6.3%) affected. Multilevel models revealed that a hierarchical structure accounting for correlation at the family, child and tooth level best accounted for the variation in HSPM. The estimated variances from the best fitting model (Model 3) were largest at the family level (12.27, 95% CI 6.68, 22.51) compared with 5.23 at the child level and 1.93 at the tooth level. Application of regression analysis utilising this three-level correlation structure identified tooth/surface level factors in addition to the previously identified familial and individual risk factors for HSPM.ConclusionIn addition to familial (environmental and genetic) and unique child-level factors, the aetiology of HSPM is likely to be influenced by local tooth-level factors.