In the bivariate analysis, female gender, migration background, variables of overweight and obesity, single parenthood, lower household income, parental overweight and obesity, parental smoking, one or more soft drinks per week, and screen media use exceeding 1 hour per day had higher odds for skipping breakfast. On the other hand, tertiary family education level, parental health awareness, playing outside more than 60 min per day, and physical activity of more than 60 minutes on 4 days and more per week showed lower odds for skipping breakfast. The ICCLogit of skipping breakfast was 0.045, indicating that 4.5% of the total variance is due to clustering of data in schools. This would lead to differences in the ORs between a logistic regression model and a generalized linear mixed model. Therefore, the model presented here is the generalized linear mixed model for binary outcomes, which accounts for the clustering of data in schools. Table 3 shows both the results of the full model and of sub-models for groups and behaviors for targeted preventive measures.Table 3Generalized linear mixed models for skipping breakfast, full and sub-models for target groups and behaviorsFull modelSub-model target groupsSub-model target behaviors(n = 1,441)(n = 1,515)(n = 1,612)OR95% CIOR95% CIOR95% CIMigration background2.39***(1.68; 3.40)2.81***(2.02; 3.91)Tertiary family education level0.55**(0.35; 0.85)0.42***(0.28; 0.64)Single parent2.17**(1.33; 3,54)2.13**(1.34; 3.40)Female gender1.53*(1.07; 2.18)1.43*(1.03; 1.99)≥95th percentile for %body fat1.51† (0.99; 2.24)1.47† (1.00; 2.17)Soft drinks > 1/week2.41***(1.70; 3.44)2.49***(1.81; 3.43)Physically active ≥ 4 days/week ≥ 60 min/day0.71(0.47; 1.07)0.64*(0.44; 0.93)Screen media > 1 h/day1.91***(1.31; 2.79)2.48***(1.77; 3.46) NOTE. OR odds ratio, CI confidence interval†p < .10; *p < .05; **p<. 010; ***p < .001