Utilising surface-level data to explore surface, tooth, individual and family influence on the aetiology of hypomineralised second primary molars

Abstract

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.