Statistical Methods
Normally-distributed continuous data (age, age at diagnosis, lung
function measures) were expressed as mean and standard deviation, and
not-normally distributed continuous data (eosinophil counts and total
IgE values) as median and interquartile ranges (IQR). Group comparisons
carried out using student´s t-test, Mann–Whitney U-test, ANOVA or
Kruskal Wallis test as appropriate for the continuous, and the
chi-square test or Fisher test for categorical variables.
Latent class analysis (LCA) was performed to identify patterns of
clinical clusters using 17 variables (allergic conjunctivitis, eczema,
asthma, family history of asthma, family history of allergic rhinitis,
skin sensitization to 8 common allergens, tonsillectomy, adenoidectomy).
Starting with a latent model including 2 classes, we compared models
with increasing numbers of classes using the Bayesian information
criterion (BIC). The expectation maximization algorithm was used to
estimate relevant parameters, with 100 000 iterations and 500
replications. The optimal number of classes was selected based on the
lowest BIC, and interpretability.
Association of LCA-driven classes with clinical outcomes was examined
using regression models adjusted for potential confounders, including
gender and maternal history of allergic rhinitis. The odds ratio (OR)
and 95% confidence interval (CI) were reported. Analyses were performed
using SPSS Statistics v21.0 (IBM, Chicago, IL, USA), Stata 16
(StataCorp, College Station, TX), MPlus 8, and R
(http://www.r−project.org/).