A Comparison of Motorcycle Crash Outcomes Between Universal and

Partial Helmet Law States

Larry Cook, Andrea Thomas,

Cody Olsen, Lenora Olson

University of Utah School of Medicine,Intermountain Injury Control Research Center

Background

• Motor vehicle crash injuries have declined over the past decade– Similar declines have not been observed in

motorcycle injuries

• It is estimated that close to 50% of motorcyclists in crashes are injured or killed

Motorcycle Crash Injuries

• Motorcycle crashes can have serious consequences such as head and brain injuries– Lead to a lifetime of disability and rehab

• Wearing a motorcycle helmet is an effective means of reducing the risk of these injuries

Motorcycle Helmet Laws

• Legislative approaches– Universal – all motorcyclists must wear helmets at all

times

– Partial – Only some motorcyclists are covered (usually based on age)

– None

• Helmet laws are difficult to retain once enacted– Florida – 2000

– Pennsylvania – 2003

– Nebraska and Missouri – 2010

Helmet Law Debate

• Public health vs. individual choice

• An analysis comparing states, rather than focusing on individual motorcyclist choices, shifts the focus from individual choice to statewide impact

• Compare crash outcomes for motorcyclists in states with a universal helmet law to those in states with either a partial or no helmet law

Methods

Data

• Collected data on motorcycle crashes from 18 states in the Crash Outcome Data Evaluation System (CODES) Data Network

– 7 universal law states

– 11 partial/no law states

Crash Outcome Data Evaluation System

• The CODES Data Network is a collection of states which work together on traffic safety issues

• Probabilistically link statewide

– Crash

– Emergency Medical Services (EMS)

– Emergency Department (ED)

– Hospital discharge

Data Processing

• Standardized data model

– Crash years 2003 – 2005

• Multiple imputation was used to estimate missing values

– State specific imputation models

• Data were combined into a single data set for analysis

Crash Data Elements*

• Crash month

• Crash time

• Crash type

• Urban/rural

• Intersection related

• Posted Speed

• Body type

• Alcohol/Drugs

• License type

• Speed related

• Motorcyclist type

• Age

• Gender

• Helmet use

• Injury severity

• VIN

*Collected from state crash reports completed by the investigating officer

Linked Data Elements

• Highest level of care

– None, ED, Inpatient

• Total hospital charges

• AIS body regions*

• Traumatic brain injury (TBI)*

– Barrel Matrix

*Generated from ICD-9-CM codes

Data Analysis

• One- and two-way tables

• Descriptive statistics

• Logistic regression

Results

Demographics

• 104,472 motorcyclists

– 48,184 (46.1%) universal law state

– 53,527 (51.2%) partial law state

– 2,761 (2.6%) no helmet law state

• Largest state 15,910 (15%)

• Smallest state 737 (0.7%)

Crash Characteristics by Law Type

Partial/No Law Universal Law

Helmet Worn 39% 78%

Speed Related 13% 19%

Single Vehicle Crash 53% 43%

Alcohol Related 9% 6%

Nighttime Crash 18% 17%

Male 83% 86%

Average Age (years) 37 37

Total 56,288 (54%) 48,184 (46%)

Age by Law Type

0%

10%

20%

Pe

rce

nt

of

Mo

torc

yclis

ts in

Law

Typ

e

Age in Years

Partial/No Universal

n = 104,472

Percent of Unhelmeted Motorcyclistsby Age Group and Law Type

0%

35%

70%

% o

f M

oto

rcyc

lists

in A

ge G

rou

p

Age in Years

Partial/No Universal

n = 104,472

Hospitalizations

Partial/No Law States

• 33,285 (59%) No hospital treatment

Universal Law States

• 27,266 (58%) No hospital treatment

• 16,485 (29%) ED treated– $1,242 median charges

– 95% CI ($1,213, $1,271)

• 11,400 (24%) ED treated– $1,083 median charges

– 95% CI ($1,056, $1,109)

• 6,510 (12%) admitted– 4 days median LOS

– $23,580 median charges

– 95% CI ($22,961, $24,200)

• 8,839 (18%) admitted– 4 days median LOS

– $19,297 median charges

– 95% CI ($18,766, $19,827)

AIS Body Area Injured forHospital Treated Motorcyclists

0%

25%

50%

Pe

rce

nt

of

Mo

torc

yclis

ts in

Law

Typ

e

AIS Body Region

Partial/No Universal

n = 43,234

Logistic Regression Models

• Estimate the effect of helmet law on injury outcomes while controlling for other covariates

• Outcomes– Head

– Face

– TBI

• Generalized estimating equations (GEE) to control for clustering within states

Covariates

• Motorcyclist is Male• Age (continuous)• Speed related• Speed limit• Intersection related• Motorcyclist type

– Rider (operator)– Passenger

• Alcohol/drug related• Single vehicle crash

• Helmet Law type– Universal

– Partial/no law

• Nighttime crash– 9:00 pm – 5:59 am

• Urban location

• Interaction– Law type*single vehicle

– Law type*nighttime

– Law type*alcohol use

Odds Ratio and 95% CI for Universal Helmet Laws

0.4 0.5 0.6 0.7 0.8 0.9 1 1.1

Head

Face

TBI

Adjusted Odds Ratio for Universal Law States

Ou

tco

me

Other Important Crash Factors

• Alcohol

• Speed

• Single vehicle

Limitations

• Reported crashes

– Minor single vehicle crashes may be underrepresented

• Do not have access to death certificate data

– Underestimate number of head, face, and brain injuries

• Results may not generalize to all states

Strengths

• Probabilistically linked crash and hospital data

• Able to conduct a comparison of legislation between states using crash and hospital data from one-third of US

Conclusions/Implications

• Universal helmet laws are associated with

– Higher helmet usage

– Lower hospital and ED charges

– Reduction in the odds of

• Head, face, and brain injuries

• Results may be useful in efforts to support/ defend helmet legislation

Acknowledgements

• Analysts from the 18 CODES states

• NHTSA

– State Data System Office

– Motorcycle Safety Program Office

Questions?

Larry Cook

larry.cook@hsc.utah.edu

801 – 585 – 9760

295 Chipeta Way

PO Box 581289

Salt Lake City, UT 84158-0289