Statistical Analysis
The primary outcome was total difficulties score for SDQ in each domain: hyperactivity, emotional symptoms, conduct problems, and peer problems. Each score can be interpreted as “normal,” “borderline,” and “clinical,” on a scale from the lowest to highest score. Matsuishi proposed the total difficulties score classification as “normal,” “borderline,” and “clinical,” corresponding to 0-12, 13-15, and 16-40 points, respectively. Matsuishi sets the ranges for the domains of emotional problems, conduct problems, and peer problems as 0-3 for “normal,” 4 for “borderline,” and 5-10 for “clinical”. The ranges for the hyperactivity domain were defined as 0-5 for “normal,” 6 for “borderline,” and 7-10 for “clinical”. In cases where the outcomes were divided into binary results corresponding to non-occurrence or occurrence, it is generally recommended that “borderline” results are included in occurrence when high sensitivity is desired(normal vs. borderline and clinical) , and excluded when high specificity is desired(normal and borderline vs. clinical). 20 We have used the recommended borderline and clinical cutoff scores as criteria for dichotomizing primary outcome variables.
Exposure variables used in this study were history of allergic symptoms such as wheezing, eczema, and nose symptoms since birth. The potential confounding variables were age and sex (demographic characteristics), PSI-SF scores (parents’ psychological aspect), doctor’s diagnosis, and family history of allergic diseases such as atopic dermatitis, food allergy, asthma, rhinoconjunctivitis, and hay fever, as well as other items of the ISAAC.
We performed logistic regression analyses to estimate crude and adjusted odds ratios (OR), accounting for propensity scores yielded by all confounding variables. The items used to determine propensity scores are shown in Supplementary Table 1. When integrating all confounders into one variable as a propensity score and determining the propensity score variables for each exposure, the variables relevant to the simultaneous factors inducing collinearity, such as a history of diseases or period prevalence, were excluded. The analyses applied a complete case analysis. As the online survey prevented responders from submitting their forms with missing values, the dataset involved no missing values. All statistical analyses were performed using SPSS version 22.0.