Exploring substance use and impaired driving among adults aged 21 years and older in the United States, 2015

Risk factors associated with driving after marijuana use among West Virginia college students during the COVID-19 pandemic

OBJECTIVES

The purpose of this study was to assess sociodemographic and behavioral risk factors associated with driving after marijuana use (DAMU) among West Virginia college students.

METHODS

Participants were recruited from West Virginia University between September and November 2022. The study sample was restricted to students who were ≥18 years of age; reported recently driving; possessed a current, valid driver's license from any US state; and were enrolled for at least one credit hour in the Fall 2022 semester.

RESULTS

Among respondents (N = 772), 28.9% reported DAMU. Students who had a GPA of B (adjusted odds ratio [AOR]: 2.17, 95% confidence interval [CI]: 1.06-4.42), smoked or ingested marijuana in the past year (AOR: 26.51, 95% CI: 10.27-68.39), drove after drinking (AOR: 2.38, 95% CI: 1.18-4.79), and used both marijuana and alcohol concurrently and then drove (AOR: 10.39, 95% CI: 2.32-46.54) associated with DAMU. Individuals who felt the behavior was somewhat dangerous or not dangerous or thought their peers approved of DAMU showed significant associations with DAMU.

CONCLUSIONS

As DAMU was prevalent, future interventions that raise awareness of the danger and potential consequences of DAMU may be needed to reduce this risky behavior on college campuses.

Risk Factors Associated With Driving After Marijuana Use Among US College Students During the COVID-19 Pandemic

PURPOSE

To assess the sociodemographic and behavioral risk factors associated with driving after marijuana use among US college students.

METHODS

A secondary analysis used the fall 2020 and spring 2021 American College Health Association- National College Health Assessment III and the dataset was restricted to college students ≥18 years of age who reported recent driving and marijuana use. Associations between risk factors and driving after marijuana use were estimated using multivariable logistic regression.

RESULTS

A total of 29.9% (n = 4,947) of the respondents reported driving after marijuana use. Males (adjusted odds ratio [AOR]: 1.64, 95% confidence interval [CI]: 1.48-1.82), non-Hispanic Black (AOR: 1.32, 95% CI: 1.02-1.71), sexual minorities (AOR: 1.19, 95% CI: 1.07-1.31), individuals with an alcohol or substance use disorder (AOR: 1.44, 95% CI: 1.08-1.91), anxiety (AOR: 1.20, 95% CI: 1.06-1.36), higher suicidality (AOR: 1.18, 95% CI: 1.07-1.31), and those who also drank and drove (AOR: 3.18, 95% CI: 2.84-3.57) had a higher risk of driving after marijuana use.

DISCUSSION

Future research should focus on increasing awareness of driving after marijuana use and prevention programs and/or strategies on college campuses regarding driving after marijuana use for these groups to reduce this risky behavior.

Assessment of delta-9-tetrahydrocannabinol (THC) in saliva and blood after oral administration of medical cannabis with respect to its effect on driving abilities

Medical cannabis has recently been legalized in many countries, and it is currently prescribed with increasing frequency, particularly for treatment of chronic pain resistant to conventional therapy. The psychoactive substance delta-9-tetrahydro-cannabinol (THC) contained in cannabis may affect driving abilities. Therefore, the aims of this study (open-label, monocentric, nonrandomized) were to evaluate blood and saliva concentrations of THC after oral administration of medical cannabis and to assess the time needed for THC levels to decline below a value ensuring legal driving. The study involved 20 patients with documented chronic pain using long-term medical cannabis therapy. They were divided into two groups and treated with two different doses of cannabis in the form of gelatin capsules (62.5 mg or 125 mg). In all patients, the amount of THC was assessed in saliva and in blood at pre-defined time intervals before and after administration. THC levels in saliva were detected at zero in all subjects following administration of both doses at all-time intervals after administration. Assessment of THC levels in blood, however, showed positive findings in one subject 9 h after administration of the lower dose and in one patient who had been given a higher dose 7 h after administration. Our finding suggested that for an unaffected ability to drive, at least 9-10 h should elapse from the last cannabis use.

Driving after marijuana use among U.S. adolescents: Prevalence profiles and related behaviors

OBJECTIVES

The interplay between marijuana legislation, perceptions of risks associated with marijuana use, and marijuana-related risk behaviors is an ever changing and complex issue. Marijuana impaired driving is of concern as legalization continues to expand in the United States. While driving after using marijuana has been shown to be prevalent among adults, little research has examined the behavior in adolescents. The aim of the present study was to examine the prevalence of driving after using marijuana among U.S. adolescents, with an examination of the relationship to age of marijuana initiation and marijuana usage patterns.

METHODS

We analyzed data from the 2017 Youth Risk Behavior Survey, a nationally representative sample of high schools students in the U.S. The sample was current marijuana users, defined as past 30 day use. Driving after using marijuana was the main outcome variable, with analyses examining the association between the outcome and age of initiation and patterns of use. Prevalence ratios were obtained by modeling Poisson regression to examine factors associated with driving under the influence of marijuana.

RESULTS

Nearly half of all marijuana users reported driving after use during the past 30 days, and did not differ between males and females. Prevalence of driving after using marijuana was significantly higher among heavy users (PR = 2.8; 95% CI 2.1-3.6). A higher prevalence of driving after drinking alcohol (PR = 1.7; 95% CI 1.5-1.9) was also found among those who had driven after using marijuana.

CONCLUSIONS

Among adolescent marijuana users, the prevalence of driving after using marijuana was high. Enhanced surveillance, prevention, and control measures are necessary to mitigate the negative impacts of marijuana consumption and related behaviors.

The prevalence of alcohol and other drugs in fatal road crashes in Victoria, Australia

BACKGROUND

Driving under the influence of drugs, including alcohol, is a globally recognised risk factor for road traffic crashes. While the prevalence of alcohol and other drugs in fatal road crashes has been examined in other countries, recent data investigating drug driving in fatal Australian crashes are limited. This study aimed to examine how the presence of alcohol and other drugs in fatal road trauma in Victoria has changed over time in different road users.

METHODS

A population-based review of road trauma deaths was performed over the period of 01 July 2006 to 30 June 2016 in Victoria, Australia, using data from the National Coronial Information System (NCIS) and the Victorian State Trauma Registry (VSTR). Drugs were grouped according to type and analysed accordingly. Poisson regression models were used to determine change in incidence rates over the study period.

RESULTS

There were 2287 road traffic fatalities with complete toxicology data (97% of all road traffic fatalities). Alcohol (blood alcohol concentration, BAC) was the most commonly detected drug (>0.001 g/100 mL: 21.1%; >0.05 g/100 mL: 18.4%), followed by opioids (17.3%), THC (13.1%), antidepressants (9.7%), benzodiazepines (8.8%), amphetamine-type stimulants (7.1%), ketamine (3.4%), antipsychotics (0.9%) and cocaine (0.2%). Trends demonstrated changing use over time with specific drugs. Alcohol positive road fatalities declined 9% per year in passenger car/4WD drivers (IRR = 0.91, 95% CI: 0.88-0.95). The incidence of strong opioids (oxycodone, fentanyl, morphine, and methadone) increased 6% per year (IRR = 1.06; 95% CI: 1.02-1.10). Methylamphetamine was detected in 6.6% of cases and showed a yearly increase of 7% (IRR = 1.07; 95% CI: 1.01-1.13). The incidence of THC remained unchanged over the period, observed in 13.1% of cases. Stronger opioids were more commonly detected among pedal cyclists (19.0%) and pedestrians (20.9%) while THC was more commonly detected among motorcyclists (19.8%) and other light vehicle drivers (17.6%).

CONCLUSIONS

A decline in the prevalence of alcohol in fatalities suggests that law enforcement and public health strategies in Australia to address road fatalities and drink-driving may have had a positive effect. However, increases were observed in the incidence of other potentially impairing drugs including opioids and amphetamines, specifically methylamphetamine, indicating a concerning trend in road safety in Victoria that warrants further monitoring.

Differential effects of stimulant versus opiate drugs on driving performance

BACKGROUND AND AIMS

Pharmacological differences among different drug classes influence human cognition, visual, and motor behavior in different ways. These differences impact driving safety, and therefore individuals who use stimulant and opioid drugs might experience different patterns in driving safety and impairment in driving performance. This study examined the effect of long-term use of stimulant drugs and of opiate drugs on driving performance, hazard perception, visual search skills and psychomotor skills related to driving.

METHODS

A total of 75 individuals, including 28 predominantly stimulant users, 22 predominantly opiate users and 25 healthy non-drug users, participated. Driving performance and psychomotor skills were assessed via a 15-minute drive in a simulator; hazard perception was assessed via a computerized task; and visual search skill was assessed by eye tracking.

RESULTS

ANOVA analyses indicate both stimulant and opiate users drove at higher speeds and experienced more crashes than the healthy non-drug users. Stimulant but not opiate users violated red light regulations more often than the healthy non-drug users. In the hazard perception task, stimulant drug users performed more poorly than both opioid drug users and healthy non-drug users. Specifically, they had lower saccade movement scores and higher average fixation times.

CONCLUSIONS

Results confirm that both stimulant drug users and opiate drug users show impaired driving performance compared to healthy non-drug users. Stimulant drug users possessed poorer hazard perception skills compared to the opiate users and the control group, perhaps as a result of cognitive deficits created by the drug use.

Drugged driving among US adults: Results from the 2016-2018 national survey on drug use and health

INTRODUCTION

Drugged driving, the act of driving while under the influence of one or more illicit substances, remains a critical problem needing to be addressed. The present study sought to analyze risk factors associated with past-year driving under the influence of alcohol and marijuana among a national sample of U.S. adults.

METHOD

Pooled data from the 2016-2018 National Survey on Drug Use and Health were analyzed among 124,466 adults ages 18 years or older.

RESULTS

Weighted logistic regression analyses revealed that 8.52% of adults drove under the influence of alcohol in the past year and 4.49% of adults drove under the influence of marijuana in the past year. Of concern, compared to heterosexuals, greater than 1 in 10 sexual minorities drove under the influence of alcohol in the past year. Moreover, a sizeable percentage of adults used other drugs while under the influence of alcohol including inhalants (70.3%), cocaine (68.9%), and hallucinogens (63.7%). Moreover, a great percentage of adults (53.4%) reported using methamphetamine while also under the influence of marijuana. Practical Applications: We believe our findings can inform harm reduction efforts and prevention messaging surrounding the dangers of drugged driving.