Associations between Adolescent Marijuana Use, Driving after Marijuana Use and Recreational Retail Sale in Colorado, USA.

OBJECTIVE: We investigated associations between the retail distribution of recreational marijuana in Colorado and (i) past 30-day marijuana use and (ii) driving after marijuana use (DAMU) among a representative sample of public high school students using four waves of data from a state surveillance system. METHODS: Past 30-day marijuana use was assessed among all sampled students (n = 85,336). DAMU was assessed among students 15 years or older who indicated driving (n = 47,518). Modified Poisson regression with robust variance estimates was used to estimate prevalence ratios (PR) comparing the pre-distribution (2013) and post-distribution (2015, 2017, 2019) periods for marijuana-related behaviors. Frequency of behavioral engagement was assessed using a multinomial approach. RESULTS: An estimated 20.3% of students engaged in past 30-day marijuana use and 10.5% of student drivers engaged in DAMU. Retail distribution of recreational marijuana was not significantly associated with the prevalence of any marijuana use or DAMU. However, it was associated with 1.16 (95% CI: 1.04-1.29) times the prevalence of using marijuana one or two times in the last 30 days, 1.27 (1.03, 1.55) times the prevalence of DAMU one time, and 0.82 (0.69, 0.98) times the prevalence of DAMU six or more times. No significant associations were observed for the remaining frequency categories. CONCLUSIONS: Approximately 1 in 10 students who drive reported DAMU. Varying prevalence in the frequency of past 30-day marijuana use and DAMU was observed following the retail distribution of recreational marijuana in Colorado. Care should be taken to properly educate adolescent drivers regarding the dangers of DAMU.

Racial and ethnic disparities in motor vehicle crash-related outcomes in North Carolina surrounding the COVID-19 pandemic.

Long-term impacts of the COVID-19 pandemic on racial and ethnic disparities in motor vehicle crash (MVC) injuries and death are poorly understood. This study aimed to characterize trends and investigate the heterogeneity of MVC-related disparities in North Carolina across several data sources. Crash reports, emergency department visit records, and death certificates from 2018 to 2021 were used to calculate monthly population-rates of MVC-related public health outcomes. We estimated trendlines using joinpoint regression and compared outcomes across racial and ethnic classifications. MVC and MVC-related injury rates declined in conjunction with NC's stay-at-home order, while rates of severe outcomes remained unimpacted. By December 2021 rates of MVC-related outcomes met or exceeded pre-pandemic levels, with the highest rates observed among non-Hispanic Black individuals. Racial and ethnic disparities in MVC-related outcomes remained prevalent throughout the COVID-19 pandemic. These results highlight the importance of a holistic approach to traffic injury surveillance when assessing the impact of MVCs.

Feasibility of linking violent death decedents to prior-month emergency department visits in North Carolina, 2019-2020.

OBJECTIVE: Linking data between violent death decedents and other sources can provide valuable insight, highlighting opportunities for prevention of violent injury. This study investigated the feasibility of linking North Carolina Violent Death Reporting System (NC-VDRS) records with North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) emergency department (ED) visit data to identify prior-month ED visits among this population. METHODS: NC-VDRS death records from 2019 through 2020 were linked to NC DETECT ED visit data from December 2018 through 2020 using a probabilistic linkage approach. Linkage variables included date of birth, age, sex, zip code and county of residence, date of event (death/ED visit) and mechanism of injury. Potential linkable ED visits were filtered to those occurring in the month prior to death and manually reviewed for validity. Linked records were compared with the NC-VDRS study population to assess linkage performance and generalisability. RESULTS: Among the 4768 violent deaths identified, we linked 1340 NC-VDRS records to at least one ED visit in the month prior to death. A higher proportion of decedents dying in medical facilities (ED/outpatient, hospital inpatient, hospice or nursing/long-term care facility) linked to a prior-month visit (80%) relative to those dying in other locations (12%). When stratified by place of death, linked decedents demographically resembled the overall NC-VDRS study population. CONCLUSIONS: Though resource intensive, an NC-VDRS-to-NC DETECT linkage was successful in identifying prior-month ED visits among violent death decedents. This linkage should be leveraged to further analyse ED utilisation prior to violent death, expanding the knowledge base surrounding prevention opportunities for violent injuries.

Trends in Passenger Seat Belt Use Among High School Students-United States, 1991-2019.

PURPOSE: Despite having the highest risk per miles driven for motor vehicle crash involvement, only 57% of US high school students reported always using a seat belt when riding in a car with another driver in 2019. METHODS: Data from the national Youth Risk Behavior Surveys conducted biennially from 1991 to 2019 were used to assess trends in seat belt use. Modified Poisson regression with robust variance estimates and linear splines was used to examine seat belt use trend changes overall and by gender, race/ethnicity, and grade. RESULTS: From 1991 to 2015, seat belt use was about 3.3% higher each survey cycle compared with the previous survey cycle, adjusting for gender, race/ethnicity, and age. After 2015, seat belt use was about 1.8% lower each survey cycle than the previous survey cycle, adjusting for the same covariates. DISCUSSION: New and effective strategies should be considered for promoting consistent seat belt use among US high school students.

Motor vehicle-related electric scooter injuries in the US: A descriptive analysis of NEISS data.

INTRODUCTION: The introduction of scooter-share programs across the United States has led to an increased incidence of electronic scooter (e-scooter) injuries presenting to emergency departments (EDs). As legislation begins to push scooters from the sidewalk to the street, injuries resulting from collisions between e-scooters and motor vehicles are an important, but poorly characterized consideration. This study leverages data from a national injury surveillance system to characterize e-scooter versus motor vehicle collisions resulting in ED presentation. METHODS: This study utilizes data from the National Electronic Injury Surveillance System (NEISS). NEISS was queried for e-scooter-related injuries from January 1st, 2015 through December 31st, 2019. Injuries were characterized as motor vehicle-related (MV-involved) or non-motor-vehicle-related (MV-uninvolved) based on a manual review by the study investigators. Weighted tabular analyses were used to characterize both types of e-scooter injuries across demographic, diagnostic, and event-related factors. RESULTS: Over the study period an estimated 60,554 (95% CI: 37,525-84,594) injuries were treated in US EDs. Approximately 19% of these injuries involved motor vehicles. Those sustaining MV-involved injuries were significantly younger (p = 0.01), with a higher proportion of males injured (p = 0.01). Additionally, when compared to MV-uninvolved injuries, a significantly higher proportion of those with MV-involved injuries were admitted to the hospital for treatment (8.8% vs. 14.6%, p < 0.01). MV-involved injuries occurred primarily in the street (96.3%), while MV-uninvolved injuries were split across streets (44.0%), at one's home (~20%), and on public property (~20%) (p < 0.01). CONCLUSIONS: Electric scooter injuries involving a motor vehicle differed from those that did not across several key categories. As e-scooters and motor vehicles start to share the road more frequently, greater consideration should be made regarding how these two modes of transportation interact with each other. The promotion of thoughtful e-scooter legislation and infrastructure changes could help promote safer travel.

The Relationship of School Start Times, Sleep Duration and Mental Health among a Representative Sample of High School Students in Colorado, 2019.

This cross-sectional study utilized responses from 46,537 students enrolled in grades 9 through 12 in 166 high schools across the state of Colorado via the 2019 Healthy Kids Colorado Survey to: (1) quantify the association between high school start times and student sleep duration and (2) investigate the associations between school start times and student mental health. Descriptive and bivariate analyses were used to investigate associations between school start times and self-reported demographic, sleep, and mental health factors. Survey-weighted multivariate regression modeling was used to investigate associations between school start times, sleep duration, and mental health. Schools with late start times (≥8:30 a.m.) saw 32.2% (95% Confidence Interval: 29.5-35.0) of students sleeping 8 h or more relative to 23.2% (22.0-24.4) in schools with very early start times (<8:00 a.m.). For every 15 min later school start time, students' sleep duration was 4.6 (3.4-5.9) min longer. Students attending schools with very early start times had 1.10 (0.95-1.27) times the odds of attempting suicide compared to those attending schools with later start times, while students at schools with early starts (8:00-8:29 a.m.) were associated with 1.11 (0.98-1.27) times the odds. Schools with later school start times had a statistically significantly higher proportion of students sleeping 8+ hours. Schools with start times before 8:30 a.m. had 10-11% higher odds of students attempting suicide compared to schools with late start times, though these differences were not statistically significant. Student mental health should continue to be investigated when assessing the potential impacts of delayed school start times.

Demographic and policy-based differences in behaviors and attitudes towards driving after marijuana use: an analysis of the 2013-2017 Traffic Safety Culture Index.

OBJECTIVE: Marijuana policies in the United States have become more permissive, motivating research on demographic and policy-based differences in behaviors and attitudes towards driving after marijuana use. The Traffic Safety Culture Index is an annual survey with national scope and multiple measures relevant to driving after marijuana use. We tabulated responses to questions about driving after marijuana use from the Traffic Safety Culture Index based on demographic factors, recreational and medical marijuana policies, and per-se marijuana laws. RESULTS: Male, younger, lower-income, and lower-education respondents self-reported driving after marijuana use more than their demographic counterparts, more often reported such behavior to be personally acceptable, and exhibited lower support per-se laws. Drivers in states that legalized medical marijuana self-reported driving after marijuana use slightly more than drivers in states where both medical and recreational were illegal. Support for per-se laws was higher among those in states that legalized recreational marijuana and in states with per-se laws. Demographic differences in our outcomes were consistent and cohesive. On the other hand, we found no predominant pattern suggesting that those in states with liberal marijuana policies were more tolerant of driving after marijuana use.

Driving contradictions: behaviors and attitudes regarding handheld and hands-free cellphone use while driving among young drivers.

BACKGROUND: Cellphone use while driving (CUWD) is a frequent source of distraction for young drivers. These distractions commonly lead to motor vehicle crashes and, in some cases, death. Crash risk differs depending on if the driver is engaging in handheld or hands-free CUWD. This pilot study sought to investigate the differences between handheld versus hands-free CUWD behaviors in younger drivers and the attitudes and social norms that inform them. METHODS: Young drivers (mean age: 19.6 years, standard deviation: 0.8 years) were recruited from a large Midwestern city in the United States as part of a pilot study. The 62 enrolled drivers (51 females, 43 non-Hispanic white) completed an online survey measuring behavioral frequencies, attitudes, and social norms regarding talking on the phone, sending messages, and reading messages. These cross-sectional data were then categorized and used for a descriptive analysis. RESULTS: The majority of young drivers reported participating in some form of handheld CUWD, with reading messages being the most popular (95%). Only 43% of participants used hands-free technology for sending messages and 30% for reading messages, while half reported not using the technology at all. Whereas handheld messaging behaviors were viewed negatively by the participants, they were unsure of the impact on their driving ability and the legality surrounding hands-free messaging behaviors. CONCLUSIONS: Handheld CUWD behaviors were more popular among young drivers compared to hands-free CUWD. Further, even though young drivers understood handheld cellphone use while driving is unsafe, they engaged in it anyway. The findings of this pilot study highlight the importance of better educational initiatives and optimizing hands-free interventions for young driver use cases.

Self-reported driving after marijuana use in association with medical and recreational marijuana policies.

BACKGROUND: A common concern surrounding increasingly permissive marijuana policies in the US is that they will lead to more dangerous behavior, including driving after marijuana use. Although there is considerable research on the effects of marijuana policies on behaviours, few studies have examined self-reported driving after marijuana use. In this study, we use data from the Traffic Safety Culture Index (TSCI) to model self-reported past-year driving after marijuana use in association with medical and recreational marijuana policies. METHODS: We analysed individual responses to annual administrations of TSCI from years 2013-2017 using a multiple logistic regression model. Our outcome variable was self-reported past-year driving after marijuana use (at least once vs. never), and our primary explanatory variable was the respondents' state medical marijuana (MM) and recreational marijuana (RM) policy. Additional explanatory variables include policies that specify thresholds for marijuana-intoxicated driving, year, and demographic factors. RESULTS: Drivers in states that legalized MM but not RM had marginally higher odds of self-reporting driving after marijuana use compared to drivers in states where both RM and MM were illegal (adjusted OR 1.29; 95% CI 0.98, 1.70; p = 0.075). However, we found little evidence that drivers in states that legalized both RM and MM had higher odds of driving after marijuana use compared to drivers in states where both RM and MM were illegal (adjusted OR 1.06; 95% CI 0.71, 1.56; p = 0.784). Per-se or THC threshold laws were associated with lower self-reported driving after marijuana use (adjusted OR 0.74; 95% CI 0.57, 0.95; p = 0.018). CONCLUSION: Although we found some evidence of an association between MM legalization and self-reported driving after marijuana use, our results provide only mixed support for the hypothesis that permissive marijuana policies are associated with higher odds of self-reported driving after marijuana use.