There were no significant interactions between any of the risk variables and sex in predicting new HCV infection.
The association between risk variables and SGA were tested using Chi-square test with Yates correction.
The relationship between childhood risk variables and adult MetS (Table 2) was examined by age- and sex-adjusted logistic regression.
Logistic regression analysis examined the association between EI and risk variables, adjusted for by baseline characteristics (gestational age < 28 weeks, multiple birth and male gender).
Consequently, resilience implies an interaction between risk variables, protective factors, and the intervention that is offered to the adolescent, which must be based on a correct assessment of his or her resources [ 21].
Univariable associations assessed with multinomial logistic regression analysis between certain risk variables and ARMD are presented in Table 4.
Differences between groups and associations between CV risk variables and tertiles of serum uric acid were tested with ANOVA (for continuous CV risk factors) or Chi squared statistics (for nominal CV risk factors), adjusted for differences by age and sex.
The relationships between the risk-dependent variable and each of the categorical explanatory variables are shown in Table 1.
The association between survival and ordinal risk variables (RAI scales) was analysed by non-parametric correlation analyses (Spearman's rho).
As above, the likelihood-based estimator expresses the causal increase in the outcome per unit change in the risk factor assuming a linear association between the risk factor and outcome variables.
