Post on 02-Apr-2018
transcript
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
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
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
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