1. Analysis of Census of Fatal Occupational Injuries/Fatality Analysis Reporting System matched data: New insights on work-related
motor vehicle crashes.
Rosa L Rodríguez-Acosta, Christen Byler, Stephanie G Pratt, Scott Richardson
National Institute for Occupational Safety and Health, Morgantown, WV
Bureau of Labor Statistics, Washington, DC
2017 Traffic Records Forum
New Orleans, Louisiana

2. Background Why study work-related motor vehicle crashes (MVCs)
Leading cause of U.S. work-related deaths.
Approximately 1,700 deaths per year from
1st or 2nd leading cause of death in every major industry group

3. Background Why match MVC data? Individual sources lack:
data on potential risk factors leading to fatal crashes
work-relatedness confirmation
employment characteristics
Matched data = more details:
more information on risk factors leading to crashes and circumstances of each event
occupational characteristics
opportunity to conduct detailed analysis
improved prevention and policy recommendations

4. Methods: Data Sources Census of Fatal Occupational Injuries (CFOI)
Federal/State cooperative program conducted by the Bureau of Labor Statistics.
Produces comprehensive, accurate, and timely annual counts of all fatal work injuries in the U.S.
Cases confirmed using multiple source documents including:
Death certificates
Reports from:
Occupational Safety and Health (OSHA) Administration
Coroner/Medical examiner
Police
Workers’ compensation
Media

5. Methods: Data Sources Collects data on:
Employment: industry, occupation, and, ownership
Demographic characteristics
Injury case characteristics
Analyzed the subset of motor vehicle occupant fatalities resulting from roadway incidents involving a motorized land vehicle
“those occurring on that part of public highway, street, or road normally used for travel … where at least one vehicle was in regular operation…”

6. Methods: Data Sources Fatality Analysis Reporting System (FARS)
Census of police-reported traffic crashes involving a motor vehicle travelling on traffic way open to the public, and, resulting in the
death of a motorist or non-motorist within 30 days of crash
Hierarchical data system: crash-, vehicle-, and person-level data.
At-work determination based on “injury-at-work” item in death certificate.

7. Methods: CFOI/FARS Matched Dataset
Methods Manuscript

8. Methods: CFOI/FARS Matched dataset, 2011-2014
Source files
Matched cases
Data set
CFOI Highway
All Fatal FARS
All Matches N
4,512
98,464
4,060
Description
All CFOI records for which event = roadway incident involving motorized land vehicle
All FARS person-level records for fatally-injured persons*
CFOI Highway merged with All Fatal FARS
* Excludes pedestrians.
90% of CFOI roadway cases were also in All Fatal FARS (4,060/4,512)
Only 60% of matched cases were identified as at work in FARS (2,442/4,060)
Data were generated with restricted access to the CFOI Research file.

9. Methods: Data Analysis
Generated descriptive analysis
Crash-level (FARS)
Harmful event
Manner of collision
Speeding and alcohol
Vehicle-level (FARS)
Vehicle type

10. Methods: Data Analysis
Person-level (all fatalities and drivers only)
Demographic characteristics (CFOI)
Age
Race
Gender
Occupational characteristics (CFOI)
Industry
Occupation
Drivers’ risk factors/behaviors (FARS)

11. Results: CFOI/FARS matched dataset
Fatal Work-related Motor Vehicle Incidents,
CFOI/FARS Matched Data
Crashes
Vehicles
Fatalities
Drivers
3,822
3,879
4,060
3,581
Data were generated with restricted access to the CFOI Research file.

12. Results: Crash-level 3,822 work-related fatal crashes
3,156 (83%) collisions
Type of collision n (%)
Motor vehicle in transport 1,769 (56%)
Fixed object 1,276 (40%)
Non-fixed object/person ( 4%)
Manner of Collision n %
Angle
606 34
Front-to-Rear
563 32
Front-to-Front
387 22
Sideswipe - Same Direction 94 5
Sideswipe - Opposite Direction 96
Rear-to-Side
Not reported, Unknown 18 1
Data were generated with restricted access to the CFOI Research file.

13. Results: Vehicle-level
Vehicles Involved in Fatal Crashes (N=3,879)
Vehicle Classification n %
Heavy trucks
1,761 45
Pick-up trucks
555 14
Passenger cars
478 12
Medium trucks
317 8
Vans
308
Utility vehicles
155 4
Farming/Construction equipment
104 3
Other/unknown/missing
201 5
Data were generated with restricted access to the CFOI Research file.

14. Demographic Characteristics All at-work fatalities (N=4,060)
Results: Person Level
Demographic Characteristics
All at-work fatalities (N=4,060)
n %
Age
≤17 12
18-24
325 8
25-54
2,424 60
55-64
866 21
65+
433 11
Sex
Male
3,752 92
Female
308
Race/ethnicity
White
2,916 72
Black
481
Hispanic
530 13
Other
133 4
Data were generated with restricted access to the CFOI Research file.

15. Results: Occupational Characteristics
Leading Industries
Rank
Industry
At-work fatalities n % 1
Transportation and Warehousing
1,545 38 2
Construction
435 11 3
Wholesale Trade
257 6 4
Agriculture, Forestry, Fishing and Hunting
235 5
Administrative support, waste management and remediation services
226
Data were generated with restricted access to the CFOI Research file.

16. Results: Occupational Characteristics
Leading Occupations
Rank
Occupation
At-work fatalities N % 1
Transportation and Material Moving
2,330 57 2
Construction and Extraction
396 10 3
Management
228 6 4
Installation, maintenance and repair
195 5
Protective Occupations
188
Data were generated with restricted access to the CFOI Research file.

17. Results: Driver-related Factors
Driver related factors* n (%)
Improper lane usage (11%)
Overcorrecting ( 9%)
Careless driving ( 4%)
Failure to yield right-of-way 139 ( 4%)
*Leading factors.
Data were generated with restricted access to the CFOI Research file.

18. Results: Driver-related Factors
Seat belt use
Yes 1,615 (45%)
No 1,279 (36%)
Drivers Blood Alcohol level*
0.00 g/dl 2,303 (84%)
g/dl ( 3%)
≥0.08 g/dl ( 5%)
Drivers with BAC ≥ 0.08 g/dl by Vehicle Type
Vehicle Type n %
Pick-up trucks 33 27
Heavy trucks 26 21
Passenger cars 20 16
Medium trucks 15 12
Vans 9 7
Farm/Construction equipment
* 2,727 drivers tested
FARS data allowed us to examine SB use. We found that only 45% of deceased drivers were wearing their seat belt at the time of crash.
We were also able to examine BAC among deceased drivers. A total of 2,727 drivers were tested for alcohol, out of those: 5% had BAC ≥0.08 g/dl (n=124)
Pick-up trucks 33 (27%)
Heavy trucks 26 (21%)
Passenger cars 20 (16%)
Medium trucks 15 (12%)
Vans 9 (7%)
Farm/construction equipment 9 (7%)
Data were generated with restricted access to the CFOI Research file.

19. Results: Driver-related Factors
Driver speeding
Yes (21%)
No 2,719 (76%)
Driver Distracted
Yes ( 9%)
No 2,411 (67%)
Unknown (23%)
Distraction n %
Unknown source
226 65
Cell phone use 48 14
Inattention/carelessness 44 13
Using/reaching object or device 9 3
Data were generated with restricted access to the CFOI Research file.

20. Conclusions
Vehicles in fatal work-related motor vehicle crashes include a wide range of types beyond heavy and medium trucks.
Although the transportation and warehousing industry has the highest number of deceased workers, fatally-injured workers are found across a range of industries.

21. Conclusions
At-work driver fatalities compared to all driver fatalities in FARS:
Similar seat belt use.
Lower % BAC ≥0.08 g/dl.
Lower % speeding.
Very low % of speeding drivers who also had BAC ≥0.08 g/dl.
Risk Factors
CFOI/FARS
Matched Dataset
FARS
National
Data¥
Seat belts
45%
46%*; 43%^
BAC ≥0.08 g/dl 5%
21%
Speeding
~ 30%
Speeding, with BAC≥0.08 g/dl 4%
42%
¥ Data from Traffic Safety Facts Reports
*Passenger vehicles and light trucks
^Large trucks and buses.
~ FARS provides data for all occupants.

22. Strengths
Analysis shows the value of matching CFOI/FARS data to advance knowledge and understanding of work-related motor vehicle crashes.
Additional analysis of driver’s characteristics and risk factors linked to occupational characteristics will lead to more focused prevention recommendations.

23. Limitations
Definitional differences in CFOI and FARS make complete matches impossible.
Cannot address full impact of work-related fatal crashes.

24. Next Steps Match two additional years of data (2015-2016).
Conduct further analysis on seat belt use.
Conduct industry-specific analyses.
Examine the full impact of work-related fatal crashes by adding data from other road users (not at-work) involved in those.

25. Questions? Rosa L Rodriguez-Acosta, Ph.D.
National Institute for Occupational Safety and Health
The findings and conclusions in this presentation are those of the author and do not necessarily represent the views of the National Institute for Occupational Safety and Health.
This research was conducted with restricted access to Bureau of Labor Statistics (BLS) data. The views expressed are those of the authors and do not reflect the views of the BLS.