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.

Identifying regions of inhomogeneities in spatial processes via an M-RA and mixture priors.

Soils have been heralded as a hidden resource that can be leveraged to mitigate and address some of the major global environmental challenges. Specifically, the organic carbon stored in soils, called soil organic carbon (SOC), can, through proper soil management, help offset fuel emissions, increase food productivity, and improve water quality. As collecting data on SOC are costly and time-consuming, not much data on SOC are available, although understanding the spatial variability in SOC is of fundamental importance for effective soil management. In this manuscript, we propose a modeling framework that can be used to gain a better understanding of the dependence structure of a spatial process by identifying regions within a spatial domain where the process displays the same spatial correlation range. To achieve this goal, we propose a generalization of the multiresolution approximation (M-RA) modeling framework of Katzfuss originally introduced as a strategy to reduce the computational burden encountered when analyzing massive spatial datasets. To allow for the possibility that the correlation of a spatial process might be characterized by a different range in different subregions of a spatial domain, we provide the M-RA basis functions weights with a two-component mixture prior with one of the mixture components a shrinking prior. We call our approach the mixture M-RA. Application of the mixture M-RA model to both stationary and nonstationary data show that the mixture M-RA model can handle both types of data, can correctly establish the type of spatial dependence structure in the data (e.g., stationary versus not), and can identify regions of local stationarity.

Mandatory Vision Test for Driver License Renewal in Association With Traffic Fatality and Injury Among Older Road Users in Utah.

In 2011, Utah began requiring that drivers aged 65 years and older pass a vision test at each license renewal. This study aims to investigate if the mandatory vision test associated with motor vehicle fatality and injury rates in older road users. We fit controlled interrupted time series analysis models to compare fatality and injury rates for older adults (65+) affected by the law to younger adults (45-64) unaffected by the law. The models yielded estimates of differential level and slope changes in fatality and injury rates, which we used to estimate policy associations. We did not find evidence that implementing an accelerated vision test for older adults in Utah was associated with a reduction in injury or fatality rates among older (65+) drivers and non-drivers relative to those aged 45-64. Other strategies might be considered to prevent fatal motor vehicle crashes (MVCs) in older adults.

A comparison of licensed driver counts from the Federal Highway Administration and driver licensing agencies in 11 states.

Objective: Those who study motor vehicle crashes may rely on counts of licensed drivers to estimate crash, injury, or fatality rates. These counts may be obtained from the U.S. Department of Transportation Federal Highway Administration's (FHWA) annual Highway Statistics Series or directly from state driver licensing agencies. However, previous studies have questioned the accuracy of these counts provided by the FHWA.Methods: To investigate this issue, we compared counts of licensed drivers from the FHWA and state licensing agencies in 11 states, categorized by sex and age group, from 2013 through 2017. We then assessed the impact of any potential differences by fitting two sets of Poisson regression models to estimate age- and sex-based driver fatality rate ratios. One set of models used counts from the FHWA as the offset and the other used counts from state licensing agencies.Results: Our analysis found that the differences between FHWA and state counts varied markedly. Seven states had substantial differences for at least one age group that spanned the entire study period. In several cases, these differences in license counts were large enough to produce directly contradictory driver fatality rate ratio estimates when comparing age groups.Conclusions: These findings highlight the continued concern regarding the accuracy of licensed driver counts from the FHWA and extend previous studies by illustrating the impact of using FHWA counts on statistical inference. We recommend against using these data for traffic safety research or policy evaluation. Nevertheless, we acknowledge the need for a centralized, easily accessible database for licensed driver data.

Reporting of unknown drug test results in the Fatality Analysis Reporting System and associated factors, 2000-2020.

OBJECTIVE: To investigate how the percentage of unknown drug test results among drug-tested drivers in the Fatality Analysis Reporting System (FARS) has trended over the past 2 decades and to evaluate factors that may affect a drug-tested driver having unknown test results in FARS. METHODS: The percentage of unknown test results among fatally injured drivers who were tested for drugs in FARS was assessed from 2000 to 2020. Trends in annual FARS drug testing data were compared with those for alcohol testing. In addition, the percentage of unknown drug test results was regressed on several factors that have been shown to be associated with higher risk of drug-involved crash fatalities. RESULTS: The percentage of unknown drug test results in FARS has decreased drastically over the past 2 decades, and the percentage of unknown drug test data gradually matched that of alcohol data over the study period. Multiple factors such as the fatally injured drivers' age and whether the crash occurred in an urban/rural area were found to be statistically significantly associated with the percentage of unknown drug test results in FARS. CONCLUSIONS: The percentage of unknown test results in FARS drug data is decreasing, and the significant associated factors found in this study may help identify additional strategies for reducing unknown drug test results. Future research should focus on continued improvement of FARS data, given the importance of FARS in understanding fatal crashes and informing strategies for prevention of crash-related injuries and fatalities in the United States.

Short-term impacts of all-driver handheld cellphone bans on high-schoolers' texting while driving: quasi-experimental analyses of Illinois and Georgia.

Teen drivers are more likely than their older counterparts to engage in distracted driving. Many states prohibit cellphone use for teen drivers, but only prohibit texting for all drivers. Evidence that these laws have been effective is mixed. We hypothesize that recent policy changes in Georgia and Illinois from teen cellphone bans with all-driver texting bans to all-driver handheld phone bans yielded short-term reductions in teen texting while driving. We analyzed Youth Risk Behavior Surveys in Georgia, Illinois, and control states North Carolina and Michigan. We estimated the reduction in texting while driving associated with policy changes via difference-in-differences models. In Illinois, 45.4 % of high school drivers texted while driving in 2013. After a 2014 policy change to an all-driver handheld ban, the percentage decreased in 2015 to 41.8 %, and decreased further in 2017 to 37.7 %. The adjusted DID estimate comparing Illinois to Michigan from 2013 to 2017 was -8.3 % (95 % CI: -15.5 % 1.1 %; p-value = 0.025). In Georgia, the percentage decreased from 37.5 % before the law to 30.8 % after, and the adjusted DID estimate comparing Georgia to North Carolina was -10.8 % (95 % CI: -19.0 %, -2.5 %; p-value = 0.011) than in North Carolina. Results support all-driver handheld phone bans to improve traffic safety for high school drivers.

The impact of Illinois' comprehensive handheld phone ban on talking on handheld and handsfree cellphones while driving.

INTRODUCTION: Distracted driving has been linked to multiple driving decrements and is responsible for thousands of motor-vehicle fatalities annually. Most U.S. states have enacted restrictions on cellphone use while driving, the strictest of which prohibit any manual operation of a cellphone while driving. Illinois enacted such a law in 2014. To better understand how this law affected cellphone behaviors while driving, associations between Illinois' handheld phone ban and self-reported talking on handheld, handsfree, and any cellphone (handheld or handsfree) while driving were estimated. METHODS: Data from annual administrations of the Traffic Safety Culture Index from 2012-2017 in Illinois and a set of control states were leveraged. The data were cast into a difference-in-differences (DID) modeling framework, which compared Illinois to control states in terms of pre- to post-intervention changes in the proportion of drivers who self-reported the three outcomes. Separate models for each outcome were fit, and additional models were fit to the subset of drivers who talk on cellphones while driving. RESULTS: In Illinois, the pre- to post-intervention decrease in the drivers' probability of self-reporting talking on a handheld phone was significantly more extreme than that of drivers in control states (DID estimate -0.22; 95% CI -0.31, -0.13). Among drivers who talk on cellphones while driving, those in Illinois exhibited a more extreme increase in the probability of talking on a handsfree phone while driving than those control states (DID estimate 0.13; 95% CI 0.03, 0.23). CONCLUSIONS: These results suggest that Illinois' handheld phone ban reduced talking on handheld phones while driving among study participants. They also corroborate the hypothesis that the ban promoted substitution from handheld to handsfree phones among drivers who talk on the phone while driving. PRACTICAL APPLICATIONS: These findings should encourage other states to enact comprehensive handheld phone bans to improve traffic safety.

Talking on hands-free and handheld cellphones while driving in association with handheld phone bans.

INTRODUCTION: Concurrent use of a cellphone while driving impairs driving abilities, and studies of policy effectiveness in reducing distracted driving have yielded mixed results. Furthermore, few studies have considered how hands-free phone use associates with handheld phone bans. It is not clear whether hand-held phone bans dissuade some drivers from using the phone while driving completely, or whether it simply promotes a shift to hands-free use. The present study estimates the association between handheld phone policies and self-reported talking on hands-free and handheld cellphones while driving. METHODS: Our data consisted of 16,067 respondents to annual administrations of the Traffic Safety Culture Index from 2012-2017. Our primary exposure variable was handheld phone policy, and our primary outcome variables were self-reported talking on any phone, self-reported talking on a handheld phone, and self-reported talking on a hands-free phone while driving. We estimated adjusted prevalence ratios of the outcomes associated with handheld phone bans via modified Poisson regression. RESULTS: Drivers in states with handheld bans were 13% less likely to self-report talking on any type of cellphone (handheld or hands-free) while driving. When broken down by cellphone type, drivers in states with handheld bans were 38% less likely to self-report talking on a handheld phone and 10% more likely to self-report talking on a hands-free phone while driving. CONCLUSIONS: Handheld phone bans were associated with more self-reported talking on hands-free phones and less talking on handheld phones, consistent with a substitution hypothesis. Handheld bans were also associated with less talking on any phone while driving, supporting a net safety benefit. PRACTICAL APPLICATIONS: In the absence of a national ban on handheld phone use while driving, our study supports state handheld phone bans to deter distracted driving and improve traffic safety.

Age-based variability in the association between restraint use and injury type and severity in multi-occupant crashes.

PURPOSE: Previous studies have shown older adults receive relatively less protection from seat belts against fatal injuries, however it is unknown how seat belt protection against severe and torso injury changes with age. We estimated age-based variability in seat belt protection against fatal injuries, injuries with maximum abbreviated injury scale greater than two (MAIS 3+), and torso injuries. METHODS: We leveraged the Crash Outcome Data Evaluation System to analyze binary indicators of fatal, MAIS 3+, and torso injuries. Using a matched cohort design and conditional Poisson regression, we estimated age-based relative risks (RR) of the outcomes associated with seat belt use. RESULTS: Our results suggested that seat belts were highly protective against fatal injuries for all ages. For ages 16-30, seat belt use was associated with 66% lower risk of MAIS3+ injury (RR 0.34, 95% CI 0.30, 0.38) for occupants of the same vehicle, whereas for ages 75 and older, seat belt use was associated with 38% lower risk of MAIS3+ injury (RR 0.62; 95% CI 0.45, 0.86) for occupants in the same vehicle. The association between restraint use and torso injury also attenuated with age. CONCLUSIONS: In multi-occupant crashes, seat belts were highly protective against fatal and MAIS3+ injury, however seat belt protection against MAIS3+ and torso injury attenuated with age.

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.

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.

Comparing distance and time as driving exposure measures to evaluate fatal crash risk ratios.

BACKGROUND: The use of an appropriate driving exposure measure is essential to calculate traffic crash rates and risks. Commonly used exposure measures include driving distance and the number of licensed drivers. These measures have some limitations, including the unavailability of disaggregated estimates for consecutive years, low data quality, and the failure to represent the driving population when the crash occurred. However, the length of driving time, available annually from the American Time Use Survey (ATUS), can be disaggregated by age, gender, time-of-day, and day-of week, and addresses the temporal discontinuity limitation of driving distance on the United States (U.S.) national scale. OBJECTIVES: The objective of this study is to determine if the length of driving time as a driving exposure measure is comparable to driving distance by comparing distance-based and time-based fatal crash risk ratios by driver age category, gender, time-of-day, and day-of-week. METHODS: The 2016-2017 National Household Travel Survey (NHTS) provided driving distance, and 2016-2017 Fatality Analysis Reporting System provided the number of drivers in fatal crashes. The distributions of driving distance and length of driving time by driver age category (16-24, 25-44, 45-64, and 65 years or older), gender, time-of-day, day-of-week were compared. Two negative binomial regression models were used to compute the distance-based and time-based fatal crash risk ratios. RESULTS: The distributions of driving-distance were not different from the length-of-driving-time distributions by driver age category, gender, time-of-day, and day-of-week. Driving distance and the length of driving time provide similar fatal crash risk ratio estimates. CONCLUSIONS: The length of driving time can be an alternative to driving distance as a measure of driving exposure. The primary advantage of driving time over driving distance is that, starting from 2003, the disaggregated estimates of the length of driving time are available from ATUS over consecutive years, curtailing the discontinuity limitation of driving distance. Furthermore, the length of driving time is related to drivers' perceived risks about their driving conditions and as a result, may be a better exposure measure than driving distance in comparing crash risks between drivers whose likelihood of traveling in hazardous driving conditions (e.g., nighttime) varies substantially.

Sedation and Analgesia Influence Electroencephalography Monitoring in Pediatric Neurocritical Care.

OBJECTIVES: We assessed neuroactive medication use in critically ill children who require neurological consultation and evaluated the associations between administration of these medications and continuous electroencephalography (cEEG) utilization and seizure frequency. METHODS: We evaluated exposure to sedatives, analgesics, anesthetics, and paralytics in consecutive patients (0 days to 18 years) for whom neurological consultation was requested in three intensive care units (ICUs) [neonatal (NICU), pediatric (PICU), and cardiothoracic (PCTU)]) at one children's hospital. We assessed cEEG usage and seizure incidence in relation to drug exposure. RESULTS: From November 2015 to November 2016, 300 consecutive patients were evaluated (93 NICU, 139 PICU, and 68 PCTU). Ninety-seven (32%) were receiving ≥1 sedative infusion at the time of consultation [NICU 7 (8%), PICU 50(36%), PCTU 40 (58%%]; 91 (30%) received ≥1 paralytic agent within the preceding 24 hours. Continuous electroencephalography was performed more often for patients treated with sedative infusions (81 of 97 versus 133 of 203, P = 0.001) and paralytic medications (80 of 91 versus 134 of 209, P < 0.001) within 24 hours preceding consultation than those who were not. Sixty-eight of 214 (32%) had electrographic seizures (65 of 68 within initial 24 hours of monitoring); seizures were less common among patients who had received sedative infusions (18 of 81 versus 51 of 133, P = 0.014). In multivariable analysis of seizure likelihood, only younger age was associated with increased risk (P = 0.037). CONCLUSIONS: Critically ill infants and children are frequently treated with sedatives, anesthetics, analgesics, and paralytics. Neuroactive medications limit bedside neurological assessments and, in this cohort, were associated with increased cEEG usage. Our data underscore the need to study the effect of these medications on clinical care and long-term outcomes.