Statistical power of multilevel modelling in dental caries clinical trials: a simulation study

Dental caries in children and adolescents with juvenile idiopathic arthritis and controls: a multilevel analysis

Background

Optimal utilization of dental caries data is crucial in epidemiological research of individuals with juvenile idiopathic arthritis (JIA). The aims were to: explore whether caries is more prevalent among children and adolescents with JIA compared to controls; examine presence of caries according to JIA group, socio-behavioral and intraoral characteristics, and the extent to which surface-specific caries varies between and within individuals; assess whether surface-specific caries varies according to JIA group and dentition; and investigate whether disease-specific clinical features of JIA are associated with presence of caries.

Methods

In this comparative cross-sectional study, calibrated dentists examined index teeth (primary 2. molars, 1. permanent molars) of 4–16-year-olds with JIA (n = 219) and matched controls (n = 224), using a detailed caries diagnosis system (including enamel caries). JIA-specific characteristics were assessed by pediatric rheumatologists and socio-behavioral information collected by questionnaires. Multilevel mixed-effect logistic regressions reporting odds ratios (OR) with 95% confidence interval (CI) were applied (caries at surface level as outcome variable). Potential confounders were adjusted for, and the effect of dependency of surface-specific caries data was estimated by calculating intra-class correlation coefficients (ICC).

Results

At individual level, no significant difference in caries prevalence was found between individuals with JIA and controls, regardless of inclusion of enamel caries. Proportion of enamel lesions exceeded dentine lesions. JIA was not associated with presence of caries, but in both groups, low maternal educational level was associated with presence of caries (OR: 2.07, 95% CI: 1.24–3.46). Occlusal and mesial surfaces, compared to buccal surfaces, had generally higher OR according to presence of caries than distal and lingual surfaces (ICC = 0.56). Surface-specific caries in the permanent dentition differed significantly according to group affiliation. Some JIA disease-specific variables were suggested to associate with presence of caries.

Conclusions

No overall difference in caries prevalence between individuals with JIA and controls was observed, but for both groups, low maternal educational level and tooth surface associated with presence of caries. Associations between JIA disease-specific variables and presence of caries cannot be excluded. Due to predominance of enamel lesions, the potential of preventative dental strategies is considerable.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-021-01758-y.

Risk factors of chronic periodontitis on healing response: a multilevel modelling analysis

Background

Chronic periodontitis is a multifactorial polygenetic disease with an increasing number of associated factors that have been identified over recent decades. Longitudinal epidemiologic studies have demonstrated that the risk factors were related to the progression of the disease. A traditional multivariate regression model was used to find risk factors associated with chronic periodontitis. However, the approach requirement of standard statistical procedures demands individual independence. Multilevel modelling (MLM) data analysis has widely been used in recent years, regarding thorough hierarchical structuring of the data, decomposing the error terms into different levels, and providing a new analytic method and framework for solving this problem. The purpose of our study is to investigate the relationship of clinical periodontal index and the risk factors in chronic periodontitis through MLM analysis and to identify high-risk individuals in the clinical setting.

Methods

Fifty-four patients with moderate to severe periodontitis were included. They were treated by means of non-surgical periodontal therapy, and then made follow-up visits regularly at 3, 6, and 12 months after therapy. Each patient answered a questionnaire survey and underwent measurement of clinical periodontal parameters.

Results

Compared with baseline, probing depth (PD) and clinical attachment loss (CAL) improved significantly after non-surgical periodontal therapy with regular follow-up visits at 3, 6, and 12 months after therapy. The null model and variance component models with no independent variables included were initially obtained to investigate the variance of the PD and CAL reductions across all three levels, and they showed a statistically significant difference (P < 0.001), thus establishing that MLM data analysis was necessary. Site-level had effects on PD and CAL reduction; those variables could explain 77–78% of PD reduction and 70–80% of CAL reduction at 3, 6, and 12 months. Other levels only explain 20–30% of PD and CAL reductions. Site-level had the greatest effect on PD and CAL reduction.

Conclusions

Non-surgical periodontal therapy with regular follow-up visits had a remarkable curative effect. All three levels had a substantial influence on the reduction of PD and CAL. Site-level had the largest effect on PD and CAL reductions.

Electronic supplementary material

The online version of this article (10.1186/s12911-017-0533-2) contains supplementary material, which is available to authorized users.

The clustering effects of surfaces within the tooth and teeth within individuals

The objectives of this study were 1) to provide an estimate of the value of the intraclass correlation coefficient (ICC) for dental caries data at tooth and surface level, 2) to provide an estimate of the design effect (DE) to be used in the determination of sample size estimates for future dental surveys, and 3) to explore the usefulness of multilevel modeling of cross-sectional survey data by comparing the model estimates derived from multilevel and single-level models. Using data from the United Kingdom Adult Dental Health Survey 2009, the ICC and DE were calculated for surfaces within a tooth, teeth within the individual, and surfaces within the individual. Simple and multilevel logistic regression analysis was performed with the outcome variables carious tooth or surface. ICC estimated that 10% of the variance in surface caries is attributable to the individual level and 30% of the variance in surfaces caries is attributable to variation between teeth within individuals. When comparing multilevel with simple logistic models, β values were 4 to 5 times lower and the standard error 2 to 3 times lower in multilevel models. All the fit indices showed multilevel models were a better fit than simple models. The DE was 1.4 for the clustering of carious surfaces within teeth, 6.0 for carious teeth within an individual, and 38.0 for carious surfaces within the individual. The ICC for dental caries data was 0.21 (95% confidence interval [CI], 0.204-0.220) at the tooth level and 0.30 (95% CI, 0.284-0.305) at the surface level. The DE used for sample size calculation for future dental surveys will vary on the level of clustering, which is important in the analysis-the DE is greatest when exploring the clustering of surfaces within individuals. Failure to consider the effect of clustering on the design and analysis of epidemiological trials leads to an overestimation of the impact of interventions and the importance of risk factors in predicting caries outcome.