Int. J. Environ. Res. Public Health 2010, 7 8 Factor 3 (previous interest in the subject matter and general understanding—2 items); and, Factor 4 (lecture time and module importance—2 items). We developed scores for each Factor by adding its item values and dividing it by number of items. Cronbach‘s alphas for the subscales of the student satisfaction questionnaire were 0.89 (Factor 1), 0.73 (Factor 2), 0.56 (Factor 3), and 0.27 (Factor 4). Bivariate linear regression analysis: was used to screen all health/wellbeing-related items and socio-demographic variables of the health questionnaire and all four Factors‘ scores of the students‘ satisfaction questionnaire for statistically significant associations with module mark (grade) as the educational outcome. Only those items that were significantly associated with module marks (p-value < 0.05) were further analysed for their association with educational achievement in the multivariate models (described below). These six items included age, income sufficiency, general health, health awareness, sleep disorder/insomnia, and frequency of binge drinking. Only Factor 1 score of the students‘ satisfaction factors described above displayed a significant association with module mark (grade), explaining 1.3% of the variance in module marks, while the other three Factors each explained less than 1% of the variance. Therefore only Factor 1 was maintained for subsequent analysis. The response categories to the six items remaining in the further analyses are depicted in Table 1. Chi-square statistics (χ2) and t-test statistics: were used for categorical and continuous variables respectively as we compared all the variables in Table 1 for gender differences in order to decide whether stratification for gender would be relevant in subsequent analysis. Multivariate linear regression analyses: with enter mode examined the associations between importance (of good grades), performance (relative to other students), and module marks (actual achieved module grade) as the three dependent variables of educational achievement on the one hand and the selected health, demographic and educational satisfaction variables as independent variables on the other hand. As the dependent variables did not differ between males and females (Table 1), we did not stratify the analyses for gender. As described above, the selection of variables to be included in the regression models was based on significance in bivariate analysis performed with all health and demographic variables from the health questionnaire and the four Factors that emerged from the principal component analysis of the students‘ satisfaction questionnaire. The independent variables included in the final models comprised students‘ educational satisfaction (Factor 1), age, sleep disorder/insomnia during the last 12 months, had five or more drinks in a row last month, income sufficiency, general health, and extent of keeping an eye on one‘s health. In addition, each of the three models contained the two dependent variables in the other two models as independent variables. Collinearity statistics for all three models displayed tolerance levels <1.0 and VIF values <1.3 indicating no substantial problems with collinearity between the independent variables [62]. Autocorrelation of residuals was in acceptable ranges indicated by Durbin−Watson statistics showing values of 1.86, 1.92 and 2.06 in the three models respectively. 3. Results The sample comprised of 380 questionnaires (195 male and 185 female students) (Table 1). Educational satisfaction: females were marginally more satisfied with their educational experience, although both genders did not significantly differ on their extent of satisfaction as measured by Factor