In order to examine representativeness, a comparison was made of basic demographic variables between the study sample group and the independent set of women remaining in the eligible cohort.
A positive and significant gradient of FAI with stroke prevalence remained after the adjustment of the basic demographic variables (age, gender and area) and a group of defined conventional risk factors.
Bivariate comparisons were complemented with multivariate logistic regression models, controlling for the effects of basic demographic variables.
As before, the significance of basic demographic variables and additional clinical characteristics were examined in different blocks.
To describe the distribution of basic demographic variables, t-tests were used for the continuous variables and Χ tests were used for categorical variables.
Two-sample t tests or chi-square tests, as appropriate, were used to compare the distributions of basic demographic variables between participants with and without chronic diseases.
Two-sample t-tests, Wilcoxon-Mann-Whitney tests, chi-square tests, or Fisher's exact tests, as appropriate, were used to compare the distributions of basic demographic variables between participants with and without chronic diseases.
We calculated the mean and standard deviation of the basic demographic variables.
In the distributed lag models, basic demographic variables were included as the first step of covariable adjustment.
Basic demographic variables, i.e. birth date, sex, marital status, number of children, origin of parents, highest level of education, profession, number of working hours will be assessed.
