Youth Motorcycle-Related Brain Injury by StateHelmet Law Type: United States, 2005–2007

WHAT’S KNOWN ON THIS SUBJECT: Youth fatality rates frommotorcycle crashes are higher in states with partial-age helmetlaws, but whether this difference is traumatic braininjury–related has not been determined. This study focused onTBI by using hospital morbidity data from states with differenthelmet laws.

WHAT THIS STUDY ADDS: Study results highlight and quantifythe head-injury risks of different partial-age helmet laws foryoung riders and offers caution for the many states that have orare considering replacement of universal all-age laws with age-specific laws.

abstractBACKGROUND AND OBJECTIVES: Twenty-seven states have youth-specific helmet laws even though such laws have been shown to de-crease helmet use and increase youth mortality compared with all-age(universal) laws. Our goal was to quantify the impact of age-specifichelmet laws on youth under age 20 hospitalized with traumatic braininjury (TBI).

METHODS: Our cross-sectional ecological group analysis comparedTBI proportions among US states with different helmet laws. We exam-ined the following null hypothesis: If age-specific helmet laws are aseffective as universal laws, there will be no difference in the proportionof hospitalized young motorcycle riders with TBI in the respectivestates. The data are derived from the 2005 to 2007 State InpatientDatabases of the Healthcare Cost and Utilization Project. We examineddata for 17 states with universal laws, 6 states with laws for ages�21,and 12 states with laws for children younger than 18 (9287 motorcycleinjury discharges).

RESULTS: In states with a�21 law, serious TBI among youth was 38%higher than in universal-law states. Motorcycle riders aged 12 to 17 in18 helmet-law states had a higher proportion of serious/severe TBI andhigher average Abbreviated Injury Scores for head-region injuries thanriders from universal-law states.

CONCLUSIONS: States with youth-specific laws had an increased riskof TBI that required hospitalization, serious and severe TBI, TBI-relateddisability, and in-hospital death among the youth they are supposed toprotect. The only method known to keep motorcycle-helmet use highamong youth is to adopt or maintain universal helmet laws. Pediatrics2010;126:1149–1155

AUTHORS: Harold Weiss, PhD, MPH, MS,a Yll Agimi,MPH,b,c and Claudia Steiner, MD, MPHd

aCenter for Injury Research and Control and bGraduate Schoolof Public Health, University of Pittsburgh, Pittsburgh,Pennsylvania; cAssociation of Schools of Public Health,Washington, DC; and dCenter for Delivery, Organization andMarkets, Agency for Healthcare Research and Quality, Rockville,Maryland

KEY WORDShospitalizations, hospital discharges, motorcycle, motorcyclehelmets, helmet laws, scooters, traffic accidents, non-trafficaccidents, adolescents, injury, traumatic brain injury, injuryseverity

ABBREVIATIONSTBI—traumatic brain injuryAHRQ—Agency for Healthcare Research and QualityHCUP—Healthcare Cost and Utilization ProjectSID—State Inpatient DatabaseICD-9-CM—International Classification of Diseases, NinthRevision, Clinical ModificationRR—relative riskCI—confidence interval

www.pediatrics.org/cgi/doi/10.1542/peds.2010-0902

doi:10.1542/peds.2010-0902

Accepted for publication Oct 1, 2010

Address correspondence to Harold Weiss, PhD, MPH, MS, PO Box56, Dunedin 9054, New Zealand. E-mail: hw@injurycontrol.com

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2010 by the American Academy of Pediatrics

FINANCIAL DISCLOSURE: The authors have indicated they haveno financial relationships relevant to this article to disclose.

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Motorcycling is risky. Motorcyclistsare 35 times more likely thanpassenger-car occupants to die in amotor vehicle traffic crash and 8 timesmore likely to be injured per vehicle-mile.1 They are 58 times more likely tobe killed than passenger-vehicle occu-pants on a per-trip basis.2

The numbers ofmotorcycle deaths andinjuries are rising because of in-creased use of motorcycles for recre-ation, more powerful motorcycles,more older riders, and the desire forfuel-efficient travel. An additional fac-tor is the repeal of universal (all-age)helmet laws.3

The contemporary increase in motor-cycle injuries is also observed amongyoung riders aged 12 to 20 years.Their motorcyclist death rate was 0.52per 100 000 population in 1999 andincreased to 0.98 in 2006 (88% in-crease).4 Their nonfatal emergencydepartment visit motorcycle traffic–related injury rate (per 100 000persons) also increased from 63.9 in2001 to 78.1 in 2007 (22% increase).4 Ina recent review of trends in traumaticbrain injury (TBI) that require hospital-ization, a significant increase in teen-aged male TBI hospitalization ratesfrom 1998 to 2005 was reported for

motorcycle crashes, one of but a fewTBI causes that showed increases.5

Youth are especially at risk for injuryfrom motorcycles because of in-creased risk-taking behavior and alack of experience.6,7

Fundamental to reducing motorcyclehead injury among motorcycle ridersis the use of a proper safety helmet. Ina recent Cochrane meta-analysis of 61different observational studies, Liu etal8 concluded that motorcycle helmetsreduce death from head injury by 42%and head injury by 69%. Despite dem-onstrated efficacy, 30 states aban-doned universal helmet laws afterwithdrawal of federal sanctions. In1975, after 8 years of sanctions, all but3 states had universal helmet laws.9

However, in 1976, congressional actioneliminated the withholding of highway-safety appropriations from states thatdid not require helmets among motor-cyclists over the age of 17. Federalhelmet-law incentives were reintro-duced in the early 1990s, only to be re-versed again in 1995. Currently, 20states and the District of Columbia(51% of the US population) have uni-versal helmet laws.9 Three states (6%of the population) have no helmet

laws*; 27 remaining states (43% of thepopulation) have retained age-specificlaws (Table 1).

There is evidence that partial age-specific youth helmet laws do not workwell. In North Dakota (1977–1980), a“substantial decline” in helmet use bychildren younger than 18 years wasnoted after passage of a partial-agelaw.10 In Texas (1991), only 29% of in-jured riders younger than 18 werefound to be helmeted under theirpartial-age helmet law.11 In Florida(2000), downgrading to an age-specificlaw was associated with a 26% declinein helmet usage among young riderskilled and a twofold increase in young-rider fatalities.12

In a 2006 study, the Insurance Institutefor Highway Safety reported that instates with weak laws, helmets wereworn by fewer than 40% of fatally in-jured minors.9 In a national study from1975 to 2004, Houston13 reported thatuniversal helmet laws were correlatedwith a substantial reduction in motor-cyclist fatalities and that partial-coverage laws did not result in a re-duction of youth fatality rates

*Colorado introduced a helmet law on July 1, 2007,to cover riders under the age of 18, which resultedin 3 states having no helmet laws.

TABLE 1 Helmet-Law Types and Percentage of Population in the AHRQ HCUP SIDs: United States, 2007

Helmet-Law Type in 2007a No. of States(IncludingWashington,DC) 2007

Percentage of2007 USPopulation

Percentage of2007 YouthPopulation(Ages 12–20 y)

HCUP SIDs2005, No.of States

HCUP SIDs2006, No.of Statesb

HCUP SIDs2007, No.of States

Universal law (all ages) (CA, DC, GA, LA, MD, MA, MI,MS, MO, NE, NV, NJ, NY, NC, OR, TN, VT, VA, WA,WV)

21 51.2 50.5 16 17 15

�21 law (AR, FL, PA, RI, SC, TX, KY) 7 22.3 21.6 5 6 4�19 law (DE) 1 0.3 0.3 0 0 0�18 law (CO, CT, HI, ID, IN, KS, MN, MT, NM, ND, OH,OK, SD, UT, WI, WY, AK, AZ)

18 20.1 20.1 11 11 12

�15 law (ME) 1 0.4 0.4 0 1 1No law (CO, IA, IL, NH) 3 5.7 7.1 4 4 3Total 51 100.0 — 36 39 35

Helmet-law source: Insurance Institute for Highway Safety (www.iihs.org/laws/HelmetUseCurrent.aspx).a In 2007, Colorado changed from a no-helmet-law state to a�18-law state. It was the only state whose helmet-law status changed during the study period. Maine changed to a�18-law froma�15-law state in mid-2009. The Missouri governor vetoed a bill in July 2009 that would have changed it to a�21-law state.b States included in the SIDs are Arizona, Arkansas, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Illinois, Indiana, Iowa, Kansas, Kentucky, Maine, Maryland, Massachusetts,Michigan, Minnesota, Missouri, Nebraska, Nevada, New Hampshire, New Jersey, New York, North Carolina, Ohio, Oklahoma, Oregon, Rhode Island, South Carolina, South Dakota, Tennessee,Texas, Utah, Virginia, Vermont, Washington, West Virginia, Wisconsin, and Wyoming.

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compared with universal-law states.Another multistate study that ad-dressed this issue was conducted byCoben et al3 with 2001 Agency forHealthcare Research and Quality(AHRQ) Healthcare Cost and UtilizationProject (HCUP) hospital dischargedata from 33 states. It was the firststudy to cover hospital dischargesfrom multiple states, and the authorsreported that “partial requirementlaws may not be protective of youngriders.” However, this study had thebroader aim of addressing all-agemorbidity effects of helmet require-ments and did not focus on youth.

The goals of our study were to fill thesegaps by using additional states, cover-ing a larger population, and more re-cent (2005–2007) AHRQ HCUP data. Weexamined the null hypothesis that ifage-specific helmet laws are as effec-tive as universal laws, there should beno difference in the proportion ofmotorcycle-related TBI versus othermotorcycle injury in states with age-specific laws versus those with univer-sal helmet laws.

METHODS

Retrospective data were obtainedfrom the 2005–2007 State Inpatient Da-tabases (SIDs),14 which were devel-oped as part of the HCUP. There were36, 39, and 35 states available throughthe SIDs in 2005–2007, respectively,which include data on almost 90% ofall US community hospital discharg-es.† The SIDs contain both patient (de-mographic and clinical data) andhospital-level data. Details on how SIDdata are collected can be found else-where.14 The University of Pittsburghinstitutional review board categorizedthis study as exempt. Analyses wereperformed by using Stata 10.0 (Stata

Corp, College Station, TX) and SAS 9.1(SAS Institute Inc, Cary, NC).

Cases were selected from 99.3 milliondischarges across the 3 years. In con-trast to customary 5-year age groups,we used a 9-year range, because manystate motorcycle-helmet laws requireyouth aged 20 years or younger towear a helmet even when personsaged 21 years and older are exempt.The lower age bound was chosen be-cause of the sharp decrease in expo-sure and incidence among childrenyounger than 12. Three equal agegroups were used (12–14, 15–17, and18–20 years). Injuries caused by mo-torcycles were selected on the basis ofInternational Classification of Dis-eases, Ninth Revision, Clinical Modifi-cation (ICD-9-CM) external cause-of-injury codes (E-codes) (E810–E819,traffic) with a fourth digit of .2 (motor-cyclist) or .3 (passenger) in any of the4 E-code fields. Analyses were con-ducted on the combined group of rid-ers and passengers (passengersmade up�7%).

Although predominantly made up ofstreet-registered motorcycles, se-lected E-codes may include motorizedbicycles (mopeds), scooters, andminibikes. “Traffic” crashes are thosethat occurred on a public highway.Non–traffic cases, which make up ap-proximately one-third of the hospitaldischarges related to injury caused bymotorcycles, were excluded becausehelmet laws often differ according towhether vehicles are used on- or off-road.15 Thirteen cases with ambiguoustraffic status codes were set to “miss-ing traffic status.”

TBI was defined on the basis of a TBI-related diagnoses in any of the first 10diagnosis fields in accordancewith ICDcodes specified by the Centers for Dis-ease Control and Prevention (CDC) TBIsurveillance case definition.16 This def-inition includes ICD-9-CM diagnosiscodes 800.0–801.9, 803.0–804.9, and

850.0–854.1. The code 959.01 (head in-jury unspecified) was also included.TBI codes that included late effects andcomplications (905.0 and 907.0) wereexcluded. TBI cases that met the CDCcase definition were grouped into 3 dif-ferent types according to the Barellbody-region by nature-of-injury diag-nosis matrix and injury severity.17 In-tracranial injury was defined by usingthe AHRQ Clinical Classification Soft-ware.18 To avoid duplicate counts be-cause of hospital transfers, 265 pa-tients who were discharged to anothershort-term care facility were ex-cluded, consistent with the approachof other population-based hospital-ization studies.5

Estimates for TBI-related long-termdisability were computed from regres-sion coefficients provided by Selassieet al.19 Injury severity was calculatedby using the algorithms of the ICDPrograms for Injury Categorization(ICDPIC), which translates ICD diagno-sis codes into Abbreviated InjuryScores and Injury Severity Scores.20

Under the assumption that the propor-tion of motorcycle-related head inju-ries is inversely related to helmet useby motorcyclists, we compared theproportion of young motorcyclistswith head injuries in states with differ-ent helmet laws. This assumption isreasonable, because helmet use hasbeen shown to reduce head injuries.8

Non–head injury serves as a proxymeasure of exposure to head-injuryrisk. When focused on severe injury(which requires hospitalization), thisproxy has been shown to be a reason-able alternative measure of exposure;other exposure indices, such as hoursof riding or miles traveled, were notavailable.21 This approach has beenused in evaluating the effectiveness ofsimilar bicycle- andmotorcycle-helmetlaws.21–25

Most comparisons were limited to the3 major helmet-law types: (1) for all

†This percentage dropped in 2007 because datafrom Connecticut, Texas, Massachusetts, and NewHampshire were not available at the time of thestudy.

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ages (universal); (2) for youth youngerthan 21 years (�21); and (3) for chil-dren younger than 18 years (�18).Only 1 small state used the�15 partialhelmet law, which made it unsuitablefor separate analysis, so it was ex-cluded from our analyses. Anotherstate with a �19 partial helmet lawwas not part of the HCUP data set. Rel-ative risks (RRs) and 95% confidenceintervals (CIs) for proportional differ-ences were calculated.

RESULTS

There were 9287 motorcycle traffic-related hospital discharges among 12-to 20-year-olds (representing 2.8% ofall injuries in this age group) over the3-year period. The age distribution was1134 12- to 14-year-olds (12%), 2400 15-to 17-year-olds (26%), and 5753 18- to20-year-olds (62%). The number of dis-charges observed within each of thelaw types was 4602 (50%) universal,1916 (21%)�21 years, and 2313 (25%)�18 years. Analyses excluded thecases from �15 helmet-law states(n � 32 [0.3%]) and no-helmet-lawstates (n � 424 [4.6%]). Mean agesand the percentage of boys were simi-lar across all 3 major law types (Table2). Mean length of stay was greater fordischarges in the �21 group but nodifferent in the �18 group comparedwith those in the universal-law states.

Significant increases in the proportionof discharges in which the patient wastransferred to another facility and in-hospital deaths for all youth aged 12 to20 were found between each of the 2major partial-law states comparedwith universal-law states (Table 2). Theproportion of cases with the first listeddiagnosis (principal diagnosis) of in-tracranial injury also varied signifi-cantly according to partial-law type. Instates with universal helmet laws,16.2% of discharges had a principal di-agnosis of intracranial injury com-pared with 18.0% and 20.0% for �21

and �18 partial-law states, respec-tively (�2, P � .05 for both categoriescompared with universal-law states).Table 3 lists the RR of TBI severity (cat-egorized according to the Barell ma-

trix) comparing partial-law states touniversal-law states. Significant in-creased risks were demonstratedfor serious/severe TBI in both types ofpartial-law-helmet states compared

TABLE 2 Characteristics of Youth Hospital Discharges Resulting From Motorcycle Injury Accordingto State Law Type: USAHRQ, HCUP, SIDs, 2005–2007

Universal Helmet-LawStates (n� 16)(Ages 12–20 y)

�18 Helmet-LawStates (n� 16)(Ages 12–20 y)

�21 Helmet-LawStates (n� 4)(Ages 12–20 y)

No. of cases in group 4602 2313 1916TBI, % 30.9 37.8 32.1Principal diagnosis ofintracranial injury,%a

16.2 20.2 18.0

Age, mean, y 17.6 17.6 17.7Age, %12 y 2.3 3.0 3.113 y 4.2 4.5 3.614 y 5.3 5.7 6.015 y 7.5 7.3 6.416 y 9.0 8.4 7.617 y 11.6 9.3 8.618 y 15.0 17.6 15.919 y 20.4 21.7 23.020 y 24.7 22.7 25.9Males, %a 89.5 87.3 88.2Length of stay, dMean 5.1 5.1 6.3Median 3.0 3.0 3.0Disposition, %b

Routine 83.9 82.4 80.1Transfer to other facility 6.4 8.2a 8.6Home health care 7.3 6.5 8.2Left against advice 0.7 �0.5 0.8Died 1.6 2.6 2.4Payer, %b

Medicaid 20.4 16.5 16.7Private 61.2 63.0 55.8Self-pay 11.6 12.9 17.2No charge 0.3 0.5 4.0Other 6.5 7.0 6.2

a �2, p�.05.b �2, p�.0001.

TABLE 3 RRs of Youth TBI Injury, Using Barell Matrix, Comparing Partial-Law and Universal-LawStates: USAHRQ, HCUP, SIDs, 2005–2007

Law Type Type 1(Serious/Severe)

Types 2 and 3(Moderate/Mild)

Universal law (referent), n (%) 476 (10.3) 326 (7.1)All partial law for ages 12–20, n (%) 600 (14.2) 281 (6.6)RR (95% CI) 1.37 (1.23–1.54)a 0.94 (0.80–1.10)

�18 law for ages 12–20, n (%) 382 (13.7) 176 (6.3)RR (95% CI) 1.32 (1.16–1.50)a 1.08 (0.91–1.30)

�21 law for ages 12–20, n (%) 273 (14.3) 103 (5.4)RR (95% CI) 1.38 (1.20–1.58)a 0.76 (0.61–0.94)

�18 law for only ages 12–17, n (%) 109 (12.4) 73 (8.3)RR (95% CI) 1.20 (0.98–1.45)b 1.17 (0.92–1.49)

a P� .001.b P� .072.

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with universal-law states. The RR wassmaller and of borderline statisticalsignificance for �18-law states whenrestricted to ages 12 to 17 (P� .072).The probability of long-term disabilityamong caseswith TBI was 25% (95%CI:23–26) in universal-law states, 30%(95% CI: 27–33) in�21-law states and27% (95% CI: 25–30) in�18-law states(data not shown). Therewere no signif-icant differences observed for cervicalor thoracic spinal cord injury betweenthe states with 1 of the 2 major partial-law types and universal-law states.

The age-group–specific pattern for 3measures of TBI are compared forstates with universal helmet laws to allstates with partial helmet laws in Figs1 and 2. Although each of the partial-law states demonstrated higher risksof TBI across the combined age groups(Table 3), when the age groups wereanalyzed separately, significant differ-ences were observed in the (larger)18- to 20-year age group alone. Asshown in Fig 2, a significantly higherpercentage of severe TBIs occurred inpartial-law states compared withuniversal-law states in the 18- to 20-year age group. This increase was notobserved in the 12- to 17-year agegroup. Similarly, mean Abbreviated In-jury Scores for the head region weresignificantly higher in the states withpartial helmet laws in the 18- to 20-year age group. Finally, the percentageof severe/serious TBIs were signifi-cantly higher in the partial-law statescompared with universal-law states inthe18- to20-yearagegroup. There is lessdifference between the discharges instates with universal helmet laws com-pared with states with partial helmetlaws in the�18 population.

DISCUSSION

Our results revealed a 37% increasedrisk of serious/severe TBI that re-quired hospitalization for youthmotor-cycle riders in states with limited-age

helmet laws compared with youth instates with universal helmet laws. Thelargest effects were observed for themost severe type of head injury in thelargest group of injured young motor-cycle riders: ages 18 to 20. There wasalso a significantly increased probabil-ity of long-term TBI-related disabilityand in-hospital death after a motorcy-cle crash for youth in states withlimited-age helmet laws. Helmet-usagerates for youth decrease substantiallywhen universal helmet laws are re-pealed, even in states in which youthriders are theoretically covered bypartial age-specific laws.3,13,26 This de-crease has been shown to affect youthmotorcycle fatality rates and overallmorbidity. Our results extend estab-

lished findings to hospitalized patientsspecifically with TBI, precisely whereeffects would be expected to be seen.

The lower helmet use in states withlimited-age laws is likely related to thedifficulty law enforcement officers ex-perience in gauging the rider’s ageduring a potential traffic stop and en-forcing a helmet law on a relativelysmall segment of the motorcycle-riding population. Less rigorous en-forcement may also result from per-ceived lack of priority once older agegroups have been exempted fromhelmet-use compliance. From a behav-ioral perspective, these findings areconsistent with “deterrent” theory,which assumes that in states with the

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FIGURE 1Percentage of TBIs according to age group and helmet-law type for motorcycle-related hospitaldischarges: HCUP SID, 2005–2007. a Cases of youth aged 18 to 20 were excluded from�18 helmet-lawstates.

02468

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FIGURE 2Percentage of serious/severe TBIs according to age and helmet-law type for motorcycle-relatedhospital discharges: HCUP SID, 2005–2007. a Cases of youth aged 18 to 20 were excluded from �18helmet-law states.

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narrowest coverage of motorcycle hel-met law, enforcement is the weakest.Youth are less likely to use a helmet ifthey perceive a low likelihood of en-forcement in a state with limited-agelaws than in states in which enforce-ment is high and punishment is likely.27

This was an ecological study. No dataon patient helmet use were availablefrom hospital discharge data, norwere age-specific observational dataavailable. Exposure-based risk com-parisons (eg, ownership levels, regis-tration rates, licensing, number oftrips, or miles traveled) were not con-sidered. This study was also limitedbecause it did not include data fromchildren who died before their hospi-talization or were not admitted to thehospitals and thus, may have underes-timated the impact of helmet use ifout-of-hospital deaths were higher inpartial-helmet-law states.

As in all observational studies, therewas a risk for confounding that couldhave influenced the frequency of ob-served TBIs beyond helmet-law differ-ences.28 Confounding was minimized,though, in several ways. First, by study-ing a population-based intervention(helmet laws) and by selecting manylarge groups (states) for analysis andusing all the states available for study,confounding was reduced. Second, be-cause the selection of cases is a cen-sus from states that includes most ofthe population (90%) of the UnitedStates, the results are nationally rep-resentative. Third, the nature of the di-agnosis and treatment of severe headinjury indicate that almost all childrenin these cases would have been hospi-talized in the states under study; thus,their data were captured with littlestate-by-state bias. Although differentstates may have different out-of-hospital TBI survival rates because ofvariation in emergency medical ser-vices and trauma systemdevelopment,bias could have been introduced as to

who survived to be admitted and cap-tured by the database; however, fatalcases were a small part of our analy-ses and such variation should havehad little to do with the status of thestate law and, thus, should have beenfairly randomly distributed across thestates and groups under study. Fourth,we avoided differences in temporalconfounding by using the same periodof analysis for all groups. Fifth, allstates but 1 had instituted theirhelmet-law type under study severalyears before data were collected,which ensured proper classification ofboth the social and legal climates.Sixth, different age-related demo-graphic characteristics were mini-mized by selecting a narrow age rangefor study. Finally, although demo-graphic variables such as income, gen-der, and ethnicity and environmentalvariables such as speed, weather, anddaylight hours may have been factorsin riding frequency and crash risk,they are not known to affect the distri-bution of serious injury types after acrash. In other words, the biomechani-cal forces that influence the likelihoodof a TBI, relative to other injuries, arenot likely to be affected by such differ-ences among serious (requiring hospi-talization) injuries. Nevertheless, theproportional morbidity approach un-derlying our study, although appropri-ate for examining state-level policy in-terventions, has its limitations. Aregression model with a variety ofstate-specific panel data that takesinto account individual state differ-ences (ie, registration and crash rates,drinking age, speed limits, climate, al-cohol consumption, quality of medicalcare, and income, among others)would complement this study.

CONCLUSIONS ANDRECOMMENDATIONS

This study quantifies for serious/se-vere TBI what the National Transporta-tion Safety Board has declared from

fatality data, namely, that “the mostvulnerable and least risk-averse seg-ments of the motorcyclist populationare more likely to be unprotected inthe absence of universal laws.”29 Instates with a �21 law, serious TBIamong youth was 38% higher than inuniversal-law states. Motorcycle rid-ers aged 12 to 17 years in �18-lawstates had a higher proportion of seri-ous/severe TBI and higher average Ab-breviated Injury Scores for head-region injuries than riders fromuniversal-law states.

Effective prevention efforts to re-duce the risk of both crashes and in-jury among youth, as in adult riders,are needed. TBIs are of particularconcern because of their long-termeffects and high mortality risk. Al-though the youth helmet mandateswere purportedly passed to maintainhead protection for young riders(and also for political expediency tofacilitate passage of this always con-troversial legislation), age-specifichelmet laws increase the risk ofdeath and serious head injury com-pared with universal laws. The onlymethod shown to keep helmet usehigh among youth is to adopt ormaintain universal laws.

Unfortunately, it seems that the num-ber of states with partial age-basedlaws may continue to rise. State leg-islative tracking in 2008 showed thatbills were introduced in 10 state leg-islatures to repeal universal cover-age, and most of them were aimed atmandating helmet use for thoseyounger than 21.30 Advocates for re-pealing universal helmet laws oftenassert that this retains their desirefor choice while protecting youngadults. This assertion is dubious;with consistent evidence of in-creased death and serious injury toyoung adults and minors who aresupposed to be protected.

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ACKNOWLEDGMENTSThis work was performed under a co-operative agreement with the NationalHighway Traffic Safety Administration(DTNH22-04-H-05087).

We acknowledge assistance from DrEduard Zaloshnja (Pacific Institute forResearch and Evaluation) and Dr Anbe-saw Selassie (Medical University of

South Carolina) for calculating long-term TBI disability. We also thank DrDavid Clark for developing and sharingthe ICD Programs for Injury Categori-zation software used for assigning in-jury severity. We also thank Dr Cobenand his colleagues for demonstratingin their earlier work the usefulness ofthe approach of using the SID to com-

pare TBI and non-TBI diagnoses ac-cording to the type and coverage ofmotorcycle-helmet legislation. We alsoacknowledge the key role of the statedata organizations, the HCUP partici-pation of which made this study possi-ble. These state data organizations arelisted in a companion article in this is-sue of Pediatrics.31

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