Table 2.
Adjusted multinomial logistic regression model using intoxication ratings to predict the number of days an individual drove under the influence of cannabis (DUIC) in the past 30 daysa
| Dependent variable: Number of days drove under the influence of cannabis (DUIC) within the past 30 days | ||||||
|---|---|---|---|---|---|---|
| Comparison 1 | Comparison 2 | Comparison 3 | ||||
| DUIC 1–9 days vs. DUIC 0 days (Ref) | DUIC 10–19 days vs. DUIC 0 days (Ref) | DUIC 20–30 days vs. DUIC 0 days (Ref) | ||||
| MOR | (95% CI) | MOR | (95% CI) | MOR | (95% CI) | |
| Model 1: Typical intoxication rating | 1.05 | (0.97, 1.13) | 1.01 | (0.93, 1.09) | 1.12 | (1.03, 1.23) |
| Model 2: DUIC intoxication rating | 1.18 | (1.13, 1.23) | 1.40 | (1.30, 1.50) | 1.68 | (1.57, 1.80) |
a
Both models adjusted for number of days used cannabis in past 30 days, lifetime number of days used cannabis, years living in current U.S. state, age, gender, race, education, employment, sampling strategy and number of methods of administration used in ones lifetime. Models estimated using cluster-robust standard errors to account for intrastate correlation. Both models limited to respondents who had used cannabis once or more the past 30 days and had driven under the influence of cannabis at least once in their life.
MOR = multinomial logistic odds ratio.