Statistical analysis

Autistic children's characteristics in the study were presented. Counts and percentages were shown for categorical variables, the mean and standard deviation (SD) were presented for continuous variables with a normal distribution, and the median and interquartile range (IQR) were presented for continuous variables without a normal distribution. The multivariate linear regression model was used to examine the association of diagnostic age and first-concern age with autistic clinical characteristics such as severity, cognition, language, and regression. A series of interaction terms between autistic clinical phenotypes and sex, as well as autistic clinical phenotypes and maternal education and autistic clinical phenotypes, and family monthly income, were performed to determine if the relationship between diagnostic age and autistic clinical phenotypes differed by sex, maternal education, and family monthly income. Only there were significant interactions, stratified analyses were further conducted. The covariates to control for potential confounders included in the multiple regression model above were child sex, parity, maternal age at birth, maternal education, and family income. The linear regression model was also used to examine the association between the first concern age of the autistic children and the diagnostic age of autistic children. All analyses were performed using SAS statistical software version 9.3 (SAS Institute Inc., Cary, NC, USA). A two-tailed P < 0.05 was considered statistically significant.