Data analysis
SPSS Statistics 21.0 software was used for statistical analysis. Chi
square test was used to compare the count data. The significant
variables in univariate analysis were used as independent variables, and
multiple linear regression was performed. By using Delta method, the
excel table compiled by Andersson et al. [35] was introduced to
calculate the related indexes of interaction, and the β1, β2, (β1+β2+β3)
and the variance and covariance between factors in logistic regression
analysis were input into it. The OR value obtained by logistic
regression model in the interaction calculation process was used as the
estimation value of relative risk (RR). Interaction index: (1) the
relative excess risk due to interact (RERI) was used to evaluate the
difference between the combined effect of factor A and factor B and the
sum of factors A and B alone; (2) the attributable proportion due to
interaction (AP) was used to evaluate the proportion of interaction
between two factors when two factors A and B exist at the same time; (3)
the synergy index (S): when the interaction does not exist, the
confidence interval of RERI and AP should contain 0, and the confidence
interval of S should include [36-38]. Correlations among variables
were examined by Pearson’s correlation. Hierarchical regression analysis
was used to prove the relationship of variables and to examine the
moderating effect. Finally, the simple slope analysis was conducted to
visualize the interaction term [39]. Significance level was α=0.05,
and a two-tailed P<0.05 was considered to have statistical
significance.