Relationships between college settings and student alcohol use before, during and after events: a multi-level study.

INTRODUCTION AND AIMS

We examined how alcohol risk is distributed based on college students' drinking before, during and after they go to certain settings.

DESIGN AND METHODS

Students attending 14 California public universities (N=10,152) completed a web-based or mailed survey in the fall 2003 semester, which included questions about how many drinks they consumed before, during and after the last time they went to six settings/events: fraternity or sorority party, residence hall party, campus event (e.g. football game), off-campus party, bar/restaurant and outdoor setting (referent). Multi-level analyses were conducted in hierarchical linear modeling (HLM) to examine relationships between type of setting and level of alcohol use before, during and after going to the setting, and possible age and gender differences in these relationships. Drinking episodes (N=24,207) were level 1 units, students were level 2 units and colleges were level 3 units.

RESULTS

The highest drinking levels were observed during all settings/events except campus events, with the highest number of drinks being consumed at off-campus parties, followed by residence hall and fraternity/sorority parties. The number of drinks consumed before a fraternity/sorority party was higher than other settings/events. Age group and gender differences in relationships between type of setting/event and 'before,''during' and 'after' drinking levels also were observed. For example, going to a bar/restaurant (relative to an outdoor setting) was positively associated with 'during' drinks among students of legal drinking age while no relationship was observed for underage students.

DISCUSSION AND CONCLUSIONS

Findings of this study indicate differences in the extent to which college settings are associated with student drinking levels before, during and after related events, and may have implications for intervention strategies targeting different types of settings.