A risk algorithm that predicts alcohol use disorders among college students

Abstract

The first year of college may carry especially high risk for onset of alcohol use disorders. We assessed the one-year incidence of alcohol use disorders (AUD) among incoming first-year students, predictors of AUD-incidence, prediction accuracy and population impact. A prospective cohort study of first-year college students (baseline: N = 5843; response rate = 51.8%; 1-year follow-up: n = 1959; conditional response rate = 41.6%) at a large university in Belgium was conducted. AUD were evaluated with the AUDIT and baseline predictors with the Composite International Diagnostic Interview Screening Scales (CIDI-SC). The one-year incidence of AUD was 3.9% (SE = 0.4). The most important individual-level baseline predictors of AUD incidence were being male (OR = 1.53; 95% CI = 1.12-2.10), a break-up with a romantic partner (OR = 1.67; 95% CI = 1.08-2.59), hazardous drinking (OR = 3.36; 95% CI = 1.31-8.63), and alcohol use characteristics at baseline (ORs between 1.29 and 1.38). Multivariate cross-validated prediction (cross-validated AUC = 0.887) shows that 55.5% of incident AUD cases occurred among the 10% of students at highest predicted risk (20.1% predicted incidence in this highest-risk subgroup). Four out of five students with incident AUD would hypothetically be preventable if baseline hazardous drinking was to be eliminated along with a reduction of one standard deviation in alcohol use characteristics scores, and another 15.0% would potentially be preventable if all 12-month stressful events were eliminated. Screening at college entrance is a promising strategy to identify students at risk of transitioning to more problematic drinking and AUD, thus improving the development and deployment of targeted preventive interventions.

Keywords: Alcohol use disorder; Hazardous drinking; Incidence; Risk algorithm; University students.