A Disaggregate-Level Assessment of Changes to Michigan s Motorcycle Helmet Use Law on Motorcyclist Injury Outcomes by Timothy P. Barrette Department of Civil and Environmental Engineering Wayne State University 00 Anthony Wayne Drive Detroit, MI 0 E-mail: timothy.barrette@wayne.edu Trevor J. Kirsch Department of Civil and Environmental Engineering Wayne State University 00 Anthony Wayne Drive Detroit, MI 0 E-mail: trevorkirsch@wayne.edu Peter T. Savolainen, Ph.D., P.E. Department of Civil and Environmental Engineering Wayne State University 00 Anthony Wayne Drive Detroit, MI 0 E-mail: savolainen@wayne.edu (corresponding author) Brendan J. Russo Department of Civil and Environmental Engineering Wayne State University 00 Anthony Wayne Drive Detroit, MI 0 E-mail: brendan@wayne.edu Timothy J. Gates, Ph.D., P.E., P.T.O.E. Department of Civil and Environmental Engineering Wayne State University 00 Anthony Wayne Drive Detroit, MI 0 E-mail: tjgates@wayne.edu Words excluding Tables =, Figures: x 0 = 0; Tables: x 0 = 0 Total Words =, Date Submitted: November, 0
Barrette, Kirsch, Savolainen, Russo and Gates 0 ABSTRACT On April th, 0, Michigan instituted reforms to its longstanding universal helmet law, becoming the th state with a partial helmet law requiring use by only a subset of the riding population. Given continuing increases in motorcycle fatalities, helmet use remains a divisive policy issue facing state governments. The extant research literature includes several examples of before-and-after studies that have evaluated the effects of changes in motorcycle helmet laws on metrics such as helmet use and statewide motorcycle fatalities. However, there is a gap in terms of a comprehensive assessment of the effects of helmet use laws on the full range of crash injury outcomes. This study adds important evidence to inform the continuing debate as to the efficacy of universal helmet laws. A detailed, disaggregate-level study was conducted to assess the degree of injury severity sustained by crash-involved motorcyclists before and after Michigan s transition from a universal to a partial helmet law. While controlling for a variety of rider, roadway, traffic, and weather characteristics, the results show helmets to reduce the probability of fatalities by more than 0 percent. Beyond helmet use, injuries also tended to be less severe in crashes that involved deer or occurred at lower speeds or under inclement weather conditions. Conversely, injuries were more severe in high-speed collisions or when drugs and alcohol were involved in the crash. Female riders, as well as younger (ages to 0) and older (ages to 0) riders tended to be more susceptible to severe injury.
Barrette, Kirsch, Savolainen, Russo and Gates 0 INTRODUCTION On April th, 0, the State of Michigan amended Section of the Michigan Vehicle Code (PA 00 of ), weakening a universal motorcycle helmet law that had been in place since. The resultant partial use law allows for motorcycle operators over years of age to ride without a helmet if they have had a motorcycle endorsement for at least two years or have passed a motorcycle safety course, in addition to carrying $0,000 of insurance per person on the motorcycle. This legislative change made Michigan one of states with a partial helmet law, requiring use by only a subset of the riding population []. As of August 0, there are only nineteen states with universal helmet laws and three states with no helmet laws []. Figure presents a map, which illustrates helmet law types by state and shows that universal helmet laws are predominantly in effect in states along the east and west coasts. 0 Figure Motorcycle Helmet Laws by State [] Helmet use laws have been an issue of considerable debate among the motorcycle community and the general public, despite the fact that helmets have been shown to be percent effective in preventing motorcycle fatalities and percent effective in preventing brain injuries resulting from motorcycle crashes []. Research has also shown that riders who do not wear helmets are also more likely to require a skilled nursing facility [] and various studies have shown states with universal helmet laws to experience lower fatality rates [,]. The extant research literature includes numerous studies that have examined the effects of motorcycle helmet use and universal helmet laws (UHLs). The National Highway Transportation Safety Administration estimates that, lives were saved by motorcycle helmets from to 00 while an additional, could have been saved by helmet use []. In addition to saving lives, research has demonstrated that helmeted riders have lower hospitalization rates [] and are.
Barrette, Kirsch, Savolainen, Russo and Gates 0 0 0 0 times less likely to suffer a head injury []. Furthermore, research has shown that upon repeal of the helmet laws, significant increases are experienced in drinking and non-helmeted fatal crashes []. Extensive research has also been conducted to examine how helmet laws affect use rates as universal law states generally show rates above 0 percent, in contrast to rates as low as percent in partial law states []. Collectively, these findings are consistent with those of numerous prior studies, which have shown conclusive benefits of helmet use and UHLs [0-]. In fact, it has been suggested that partial helmet laws are essentially equivalent to a full repeal due to the difficulty of enforcing violations, which are generally based upon age and experience []. However, it should be noted that some studies have drawn conflicting conclusions to the efficacy of universal helmet laws. After Florida repealed their UHL in 000, a subsequent study found no significant difference in the rate of fatal brain injuries months after the repeal []. This study also noted that various prior studies had failed to appropriately consider temporal trends. Other research has shown that the impacts of helmet laws may be understated if appropriate controls, such as temperature and weather, are not accounted for []. Opponents of helmet use legislation frequently cite potential economic benefits that would be generated by increased tourism due to fewer riding restrictions. However, a 0 study estimated that the weakening of Michigan s helmet use law would result in increases of percent in monetary costs and percent in non-monetary costs resulting from motorcycleinvolved crashes []. Initial medical costs for un-helmeted riders were found to be $,000 higher on average than helmeted riders [] and, after the weakening of Florida s motorcycle helmet law, the number of motorcyclists being admitted to hospitals with head, brain, or skull injuries more than doubled from $ million to $ million [].Compounding this rise was a parallel increase in treatments costs for such injuries from $, to roughly $0,000. In spite of these economic benefits, which are well supported [-], debate continues as to the efficacy of helmet use laws in reducing motorcycle fatalities. The principal objective of this study is to determine the impacts of the recent weakening of Michigan s universal helmet use law on motorcyclist crash injury outcomes. This is accomplished through the development of a detailed, disaggregate-level assessment of injury outcomes in motorcycle-involved crashes before and after the weakening of Michigan s helmet use law. A random effects ordered probit model is estimated to ascertain the effects of helmet use while controlling for other important factors. Collectively, the results provide important evidence to guide subsequent policy decisions in Michigan and other states. METHODS In order to assess the effects of helmet use on the degree of injury sustained as a result of motorcycle crashes in the state of Michigan, an ordered probit model is developed. The ordered probit is an appealing analytical framework in that it accounts for the ordinal nature of injury data, which can be ranked in ascending order of severity from property damage only (no injury) to fatal injury. For the ordered probit model, a latent variable, z, is specified as a linear function for each crash observation, such that z = βx + ε, () where X is a vector of variables determining the discrete ordering for each crash observation, β is a vector of estimable parameters, and ε is a disturbance term [,]. With this, observed ordinal-injury data, y, for each observed crash is defined as,
Barrette, Kirsch, Savolainen, Russo and Gates 0 0 0 0 y = if z µ 0 y = if µ 0 <z µ y = if µ <z µ () y =. y = i if z µ i-, where the µ are estimable threshold parameters that define y, which corresponds to integer ordering and i is the highest integer ordered response. The µ are parameters that are estimated jointly with the model parameters β and, without loss of generality, µ 0 can be set to 0. The estimation problem then becomes one of determining the probability of I specific ordered responses for each crash injury, n. If the error term, ε, is assumed to be normally distributed across observations with a mean of zero and variance of one, an ordered probit model results. Setting the lower threshold, µ 0, equal to zero results in the outcome probabilities P y = i = Φ μ! βx Φ μ!!! βx, () where µ i and µ i- represent the upper and lower thresholds for injury severity i. For the purposes of this study, one potential concern in analyzing the injury severity data is that riders on the same motorcycle are likely to share common, unobserved effects. For example, the rider and pillion passenger may be exposed to the same impact forces, may be wearing similar gear, or may share other similarities that cannot be captured by the available data from the crash report form. Failure to account for this correlation can potentially result in inefficient or biased parameter estimates. To address this issue, a motorcycle-specific disturbance term, φ i, is added to account for the random, unobserved effects that are specific to each crash-involved motorcycle: z!" = βx!" + ε!" + φ!. () The random effects ordered probit model can be estimated by standard maximum likelihood methods. DATA SUMMARY Table provides summary statistics for all motorcycle crashes occurring in the state of Michigan over two time periods: from April -December, 0 and from April -December, 0. The April th date coincides with the enactment of the partial helmet law and, as such, this provides a direct comparison of changes in motorcycle crashes before and after the helmet law change. During this time period in 0, there were, motorcycle-involved crashes in the state of Michigan, which resulted in 0 motorcyclist fatalities. During the same period in 0, motorcycle crashes increased by. percent to, while fatalities increased by. percent to. Incapacitating injuries also increased by. percent (from to 0), providing general feedback that crashes have become more severe after the helmet law change. Over the duration of the 0 time period when the UHL was in place, the helmet use rate among all crashinvolved motorcyclists in the state of Michigan was. percent. During the same period in 0 under the PHL, the rate dropped to. percent. The latter rate is very close to the estimated statewide use rate of.0 percent as determined by a recent direct observation survey []. Beyond helmet use and injury severity, the other variables in Table were largely consistent between the two time periods.
Barrette, Kirsch, Savolainen, Russo and Gates TABLE. Summary Statistics for Michigan Crash Severity Analysis Factor Number Observed Percent of Total Factor Number Observed Percent of Total Driver Motorcycle Endorsement Month Endorsed.% April.0% Not Endorsed.% May.% Unknown.% June.% Driver License State July.% Michigan 0.% August.% Other.% September.% Unknown.% October 0.% Driver Helmet Use November.0% Yes 0.% December 0.% No.% Day of Week Unknown.% Weekday 00.% Driver Age Weekend.% Younger than Age 0.% Time of Day Age to.% AM-AM.% Age 0 to 0.% AM-AM.% Age 0 plus.% AM-AM 0.% Unknown.% AM-PM.% Driver Gender PM-PM.% Male.% PM-PM.0% Female.% PM-PM.% Unknown.% PM-AM.% Driver Injury Severity Unknown 0.% Fatal (K) 0.% Weather Incapacitating (A) 000.% Clear 0.% Non-incapacitating (B) 0.% Cloudy.% Possible (C).% Other.% None (O).% Light Unknown.% Daylight.0% Driver Impairment Dark lighted 0.0% Drugs 0.% Dark unlighted.% Alcohol.% Other.% Both 0.% Unknown 0.% Niether.% Road Condition Passenger Helmet Use Dry 0.% Yes.% Wet 00.% No.% Other.% Unknown.% Speed Limit Passenger Gender <0 0.% Male.% 0-0.% Female 0.% >0.% Unknown.% Unknown 0.% Passenger Injury Severity Crash Type Fatal (K).% Single Motor vehicle.% Incapacitating (A).% Head-on.% Non-incapacitating (B).% Angle.% Possible (C).0% Rear-end.% None (O).% Sideswipe.% Unknown.% Unknown.%
Barrette, Kirsch, Savolainen, Russo and Gates RESULTS AND DISCUSSION Table presents the results of the random effects ordered probit model that was estimated as a part of this study. These results show that a variety of motorcyclist, crash, roadway, and temporal factors were found to influence the severity of injuries sustained as a result of motorcycle crashes. Table : Parameter Estimates for Random Effects Ordered Probit Model Parameter Estimate Std. Error T-statistic P-value Constant. 0.0.00 <0.00 Helmet Use -0. 0.0 -.0 <0.00 Age to 0 0. 0.0.0 0.00 Age to 0 0. 0.0.0 0.00 Female 0. 0.0.0 <0.00 Alcohol use 0. 0.0.0 <0.00 Drug use 0. 0..0 0.0 Deer-involved -0.0 0.0 -.0 <0.00 Large truck-involved 0. 0..0 <0.00 Single-vehicle collision -0. 0.00 -.0 <0.00 Rear-end collision -0. 0.00-0.0 <0.00 Same-direction sideswipe collision -0. 0.0 -.0 <0.00 Head-on collision 0. 0..0 0.0 Head-on/left-turn collision 0. 0.0.00 <0.00 Stop-controlled intersection -0. 0.0 -.0 0.00 Signalized intersection -0.0 0.0 -.00 <0.00 Horizontal curve on non-freeway 0.0 0.0.0 0.0 Speed limit 0- mph 0.0 0.0.0 <0.00 Speed limit 0- mph 0. 0.0.0 0.00 Speed limit > mph 0. 0.0.0 <0.00 Rain/Snow -0.0 0. -.0 0.0 November/December -0. 0. -.0 0.0 Weekend 0.0 0.0.0 0.0 Thresholds Mu(0).0 0.0.0 <0.00 Mu(0). 0.0.0 <0.00 Mu(0). 0..00 <0.00 Std. Dev. Of Random Effect Sigma.00 0.00.00 <0.00 Log-likelihood Values: Constant Only -. Ordered Probit -0. Random Effects Ordered Probit -0.0
Barrette, Kirsch, Savolainen, Russo and Gates 0 0 In interpreting the model results from Table, a positive coefficient implies that as that variable is changed from zero to one, the probability of a fatal injury increases while the probability of the motorcyclist sustaining no injury decreases (and vice versa for negative coefficients). Interpretation of changes on interior injury categories is not intuitive, instead requiring the calculation of elasticities. Elasticities, as presented in Table, indicate the percentage change in the probability of each injury outcome as each variable is increased from 0 to. In practical terms, these values represent the percent change in the probability of a specific severity level due to the effects of a specific indicator variable. For example, the results indicate that the probability that a crash results in property damage only (O) increases by. percent when a rider is wearing a helmet (as compared to not wearing a helmet). Similarly, the probability of a possible (C) injury increases by 0. percent when a helmet is used. Conversely, the likelihood of non-incapacitating (B), incapacitating (A), and fatal (K) injuries decrease by.,., and. percent, respectively. Collectively, these findings provide further evidence to demonstrate that helmet use leads to consistent and pronounced reductions in injury severity. Table : Elasticities for Random Effects Ordered Probit Model Percent Change in Probability of Injury Outcome Variable O C B A K Helmet Use.% 0.% -.% -.% -.% Age to 0 -.% -.0%.0%.%.% Age to 0 -.% -.%.%.% 0.% Female -.0% -.%.%.%.% Alcohol use -.% -.%.%.%.% Drug use -.% -.%.%.%.% Deer-involved.%.% -.% -0.% -.% Large truck-involved -0.% -.%.%.% 0.% Single-vehicle collision 0.% 0.% -.% -.0% -.% Rear-end collision.%.% -.% -.0% -.% Same-direction sideswipe collision.%.% -0.0% -.% -.0% Head-on collision -.0% -.0%.%.0% 0.% Head-on/left-turn collision -.% -0.%.%.% 0.% Stop-controlled intersection.%.% -.% -.% -.% Signalized intersection.%.% -0.% -.% -.% Horizontal curve on non-freeway -.0% -.%.%.%.% Speed limit 0- mph -.% -.%.%.%.% Speed limit 0- mph -0.% -.%.%.%.% Speed limit > mph -.% -.%.%.%.% Rain/Snow.%.% -.% -.% -.% November/December.%.% -.% -.% -.0% Weekend -.% -.%.%.%.0% Including helmet use, a total of explanatory variables were found to significantly affect the injury severity outcomes of motorcyclists involved in a crash. Age is shown to have a significant infeluence on the severity of injuries sustained by motorcyclists. The model showed
Barrette, Kirsch, Savolainen, Russo and Gates 0 0 0 0 motorcycle riders between the ages of -0 and -0 had similar injury outcome characteristics and were more likely to experience severe crash related injuries. Motorcycle riders between the ages of -0 may be inherently riskier drivers and engage in reckless behavior while riding and the finding that they are at greater risk for injury is consistent with past studies. [0]. Older drivers may be at greater risk for injury or fatality due to the effects of aging such as reduced reaction times or frailty, and this result is also consistent with past findings. []. In addition to age, gender was found to have an effect on injury outcomes as females were found to be at greater risk for severe or fatal injury. Both alcohol use and drug use were found to significantly increase the likelihood of a motorcyclist sustaining a fatal injury (by.% and % for alcohol and drug use, respectively). These results are not surprising as alcohol and drug use can affect cognitive abilities in a multitude of ways such as slowed reaction time, poor judgment, and false sense of confidence. These findings are consistent with previous studies [0] and strengthen the argument for continuing education and enforcement campaigns aimed at reducing impaired riding. Those riders involved in collisions with a deer were found to be less likely to experience fatal injuries and more likely to experience no injury, a finding most likely related to the smaller mass of a deer as compared to a collision with another motor vehicle. Motorcyclists involved in collisions with large trucks were 0.% more likely to experience a fatal injury. This result is not surprising simply due to the sheer size and mass differential between a motorcycle and a large truck. Crash type was also found to significantly affect injury severity levels of crash involved motorcyclists. Those riders involved in single-vehicle, rear-end, or same direction sideswipe crashes were less likely to experience severe injuries, while those riders involved in head-on or left-turn head-on collisions were more likely to experience severe injuries. These results are consistent with past studies [] and are simply related to the speed differential and crash-force characteristics associated with each crash type. Riders who crashed at an intersection (either stop controlled or signalized) were less likely to experience sever injuries. This finding may be related to the speed at which a cyclist is moving when the crash occurred. Motorcyclists stopped or moving slowly at or near intersections may be less likely to be injured than riders travelling at full speed, especially on a freeway. Crashes occurring at horizontal curves on non-freeway roads tended to result in increased injury severities. This finding is consistent with past studies [0]. and is most likely due to restricted sight distances associated with curved road segments. Higher speed limits were also associated with more severe injury outcomes for motorcyclists. Crashes occurring on roads with speeds greater than mph (freeways) resulted in a.% increase in likelihood of a fatal injury, a finding that was not surprising. Interestingly, crashes occurring in the rain or snow tented to result in less severe injuries. This finding is consistent with past studies [].and is most likely due to slower travel speeds and more cautious riding in poor weather conditions. Similarly, crashes occurring in the months of November or December tended to result in less severe injuries. This finding is most likely due to the winter weather conditions Michigan experiences during these months that would result in slower travel speeds and more cautious riding. Finally, crashes occurring on a weekend tended to result in slightly more severe injury outcomes as compared with crashes occurring on a weekday. This may be due to riskier driving behavior exhibit during weekend riding as compared with daily commuting travel during the standard Monday to Friday work week.
Barrette, Kirsch, Savolainen, Russo and Gates 0 0 0 0 0 CONCLUSIONS This study adds further evidence to inform the continuing debate as to the efficacy of universal helmet laws (UHLs). On April th, 0, the State of Michigan repealed its UHL in lieu of a partial helmet law (PHL), which requires use only for inexperienced or uninsured riders. Following enactment of the PHL, helmet use rates have fallen from over percent to approximately percent []. To understand the broader impacts of this helmet use policy, a detailed, disaggregatelevel study was conducted that assessed the degree of injury severity sustained by crash-involved motorcyclists before and after Michigan s transition from a UHL to a PHL. While controlling for a variety of rider, roadway, traffic, and weather characteristics, the results show helmets to reduce the probability of fatalities by more than 0 percent. Beyond helmet use, injuries also tended to be less severe in crashes that occurred at intersections, at low speeds, and under inclement weather conditions. Conversely, injuries were more severe in high-speed collisions or when drugs and alcohol were involved in the crash. Female riders, as well as younger (age to 0) and older (age to 0) riders tended to be more susceptible to injury. Ultimately, the study results provide further support for universal helmet laws. Detractors of UHLs often posit that riders should be free to choose whether to wear a helmet and that safety advocates should instead focus on furthering education to encourage helmet use without mandating it by law. Despite the evidence to support the use of a UHL, a survey conducted in Florida in 0 found that the vast majority of riders were in favor of the state s mandatory training law but were less supportive of a mandatory helmet law []. However, sound arguments have been presented that argue UHLs are necessary to protect individuals against their own poor choices []. A recent analysis found that while other measures could produce positive results in helmet use rates and injury reductions, UHLs are the most effective at promoting safety and mitigating the economic impacts of injuries and fatalities []. These findings are echoed by a 00 study that suggests legislation may be a more effective and efficient means to increase helmet use than educational programs [0]. Helmet use rates in states with UHLs are around percent while compliance rates in states without UHLs are around 0 percent []. This fact, coupled with the overwhelming body of evidence from the research literature [-], as well as the compelling evidence on the effectiveness of helmets as shown in this study, show that it i imperative that states carefully consider moving further toward universal helmet laws. REFERENCES. Insurance Institute For Highway Safety. Motorcycle and bicycle helmet use laws. http://www.iihs.org/laws/helmetusecurrent.aspx. Accessed June, 0.. Johnson, S., J. Walker, and D. Utter. Crash Outcome Data Evaluation System (CODES) Project Safety Belt and Helmet Analyses. USDOT NHTSA Research Note, February,.. Hooten, K. G. and G. J. A. Murad. Helmeted vs Nonhelmeted: A Retrospective Review of Outcomes From -Wheeled Vehicle Accidents at a Level Trauma Center. Clinical Neurosurgery, Vol., 0, pp. -0.. Houston, D. J., and L. E. Richardson. Motorcyclist fatality rates and mandatory helmet-use laws. Accident Analysis and Prevention, Vol. 0, 00, pp. 00-0.. Morris, C. C. Generalized linear regression analysis of association of universal helmet laws with motorcyclist fatality rates. Accident Analysis and Prevention, Vol., 00, pp. -.
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