Statistical analysis
To calculate participation rates, the denominator was the number of adolescents and the numerator the number of core questionnaires returned with at least one data symptom. For prevalence estimations, positive answers to a specific symptom in the centre was divided by the number of completed questionnaires. There was no data imputation.
All variables included in the GAN environmental questionnaire were used as independent variables in logistic regression analyses (uni and multivariate) in which the three eczema markers (current symptoms, severe symptoms, and current eczema) were the dependent variables. Those analyses were performed within each centre. As the number of cases of severe symptoms was very low, logistic regression analyses were not performed. Factors which showed significant (p<0.05) values of adjusted odds ratios in the multivariate logistic regression analyses in at least one centre were subsequently meta-analysed (random effects) including the results of the six centres. A forest plot was built, including the pooled effect together with the 95%conficence interval and prediction interval. Measures of heterogeneity, such as Q and I2 were also calculated.
To test whether the presence of current wheeze modified the associations between the environmental factors and the eczema markers on the whole sample of adolescents, a multilevel mixed effects logistic regression model was performed, including the same variables as in the within centre logistic regressions; and using the individual as the first level and the centre at the second. As previously and due to the low number of cases, no analysis was made for symptoms of severe eczema.
Most statistical calculations were made using Stata SEĀ® v18 software package (Stata corp., College Station, TX, USA) except meta-analyses that were carried out using Comprehensive Meta-Analysis (CMA) V4.0 software package (Biostat, Englewood, NJ, USA).