Missing data
The total number of missing data values for the analytical sample including 1098 participants was 419 out of 15372 (2.5%). The percentage of missing values varied from 0 to 16% between the variables. The data was missing due to the invalid and missing measurements as well as unclear or incomplete questionnaire response. Thus, missing data were assumed to occur at random. Multiple imputation was used to create and analyze 50 multiply imputed data sets, and the model parameters were estimated separately for each data set. The used number of iterations for chained equations21 was 50. Multiple imputation and pooling of the model estimates were carried out in R22 using the standard settings of the “mice” package.21 For comparison, we also performed complete case analysis, but the results were not notably different.