Occupational light vehicle (OLV) use The Drive To Policy Rwth Stuckey PhD Candidate OHS Adviser Transport Accident Commission Victoria, Australia Supervisors:

Occupational light vehicle (OLV) use The Drive To Policy

Rwth StuckeyPhD CandidateOHS Adviser Transport Accident CommissionVictoria, Australia

Supervisors:A/P Anthony D. LaMontagne A/P Malcolm SimDr. Deborah GlassStatistical Assistance: Pam Simpson

Rationale

• Road crashes are the most common cause of traumatic work-related death, injury and absence from work.

• Work driving research has related largely to heavy vehicles.

• There are no comprehensive descriptions of the light vehicles work group.

• Confusion between OH&S and road safety policy application.

• Complex mix of vehicle-control arrangements with varied work patterns of drivers and passengers.

• Occupational light vehicle (OLV) use is large and under-recognised issue lacking a clear policy framework

NOHSC all Vehicle related claims - 1994-2000

0

200

400

600

800

1000

1200

1400

1600

1800

1994-1995 1995-1996 1996-1997 1997-1998 1998-1999 1999-2000

Year

Trucks, semi-trailers,lorriesBuses & minibuses

Cars, stationwagons,vans, utesMotorcycles

Pushbikes

Other road transport

All Compensated Road Related Fatal Occupational Vehicle Claims By Vehicle Type Group, Australia, 1994-2000

0

5

10

15

20

25

30

35

40

45

50

1995 1996 1997 1998 1999 2000

Year (Fiscal:June-July)

Collated from National Workers’ Compensation Statistics Database

Nu

mb

er o

f F

atal

Cla

ims

Co

mp

ensa

ted

Trucks, semi-trailers, lorries

Buses & minibuses

Cars and Light Trucks

Motorcycles

Pushbikes

Other road transport

Data Source: National Occupational Health and Safety Commission

Occupational Light Vehicle Claims as a Percentage of all Road Vehicle Compensation Claims by Occupation, Australia, 1994-2000

Data Source: National Occupational Health and Safety Commission On-line Statistical database URL:http://NOHSC.info.au.comp/

Collated from Data source: ABS Australian Social Trends 2000 Work - Paid Work: Employment arrangements in the late 1990’s, Citing - Unpublished data, Forms of Employment Survey, August, 1998.

Occupation (Based on ASCO Categories)25% or more in non-traditional patterns & category 4&5, lowest skilled rank workers

Employment Arrangements 1998 by Occupation, Australia.

0

20

40

60

80

100

120

Man

ager

s & A

dmin

istra

tors

Profe

ssio

nals

Para-

profe

ssio

nals

Trades

perso

ns & re

late

d work

ers

Advance

d cle

rical

& s

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orker

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Inte

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cle

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Inte

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ansp

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Elem

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ales

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ervi

ce w

orker

s

Laboure

rs &

rela

ted w

orker

s

Perc

en

t

Other Employment Arrangements

Traditional Jobs

Work Arrangements Vehicle Ownerships

Corporate Vehicles

Private Vehicles

Permanent Work Arrangements

Permanent full time employees

Permanent part-time employees

Precarious or Contingent Work Arrangements

Casuals -

Restricted tenure/Contractors

-

Labour hire -

Self Employed or Own Account Workers

--

Indicates the one sub-group who have been the focus of previous research.

The Varied Organisation Of Vehicles And Work Arrangements Across OLV Users.

Annual Work-Related Business And Private Use Of Road Vehicles In Australia Of Total Kilometres Travelled

Year

Journey to Work/Commuting Use

Business And Private Use Of Road Vehicles In Australia By Total Kilometres Travelled

0

50000

100000

150000

200000

250000

1998 1999 2000 2002

Kilometres Travelled (Millions)

Private Vehicle Use

Other Work Vehicle Use

Occupational Light Vehicle Use

Data Sources: *Australian Bureau of Statistics Survey of Motor Vehicle Use. Catalogue No.: 9208.0 ABS;and +Year Book Australia 2003 Transport; General transport activity - Road transport activity•(*1998, 1999 & 2002 data; +2000 data; no data was available for 2001.)

There are increasing numbers of OLV users due to work arrangement

changes in many occupations and industries including:

• permanent workers employed as drivers

• permanent workers using employer owned vehicles or driving private

vehicles while working incidentally to their primary occupation

• contingent workers using vehicles between workplaces.

• contingent workers using work specific vehicles such as tradesmen using

vans as a work base

• OLV-user is not a job title, and frequently the road-based work activity is

irregular and incidental to a designated occupation.

The Impact Of Burden Shifting

• Across all jurisdictions burden shifting leads to subsidisation for many injured OLV users by the driving public through registration levies.

• Employers’ levies should be bearing such costs.

• The costs of work related incidents are subsumed into Motor Accident and Social Security systems, and cannot be teased back out.

• With no evidence-base to guide policy and practice for intervention, problems are not characterised and the OHS system fails.

Legislative Position:

•Australian occupational health and safety statutes define a workplace as a place where an employee works.

• Vehicles of employees driving for work or while working are considered a workplace. • Duty of care of employers to employees applies regardless of the nature of the workplace.

• Requirement for provision of a safe workplace includes training, instruction, protection of people other than employees.

• Applies to an employee even occasionally driving for work.

Policy Environment: External Influences: Relevant Local, National & International Public Policy

Organisational Environment: Work Arrangements

External Physical Work Environment - Road Environment

Immediate Physical Work Environment - Vehicle

Locus of Injuries & Fatalities:

Drivers & Passengers

Figure Legend:

OLV Users

The OLV Use Systems ModelRef: Stuckey, R. LaMontagne A.D. Sim, M. “Working in light vehicles - a review and conceptual model for Occupational

Health & Safety” in press: Accident Analysis and Prevention.

Vehicles with seating capacity of 13 or more n= 4,276

Vehicles registered for substantively social, pleasure or domestic use purposes or not likely to be used on public roadsroads n= 2,878,205

RTA NSW June 2003 Light Vehicle Registrationsn= 3,529,761 vehicles

Selected OLV Cohort: Vehicles formally declared as substantially used for business purposes by registrants n= 646,201

Study 1 OLV Population Description – Selection Process

Vehicles with inconsistent vehicle age, make or model data n= 1,052

Vehicles 4.5 tonne GVM or more; & mobile homes; buses; heavy plant ; cycles; trailers, etc. N=27

Vehicles registered for Private use N=2,440,269

Vehicles registered for other non-OLV uses N=437,936

Users (OLV Population c.f. Private registrants)

• OLV registrant is more likely male than private (OR=3.4, <0.000; CI 3.35-3.43).

• 6% of OLV users under 30 years age compared to 17% private

• 2.3% of OLV registrations to the NSW government

• OLV registrants more likely to register light trucks than private registrants,

•(OR=7.6, P<0.000, CI 7.52-7.62).

• OLV fleet more than half load shapes.

• Vehicles less than 5 years old more likely to be OLV than privately registered,

(OR=3.5, P<0.000 CI 3.4-3.5).

• 50% of load-shaped OLV vehicles were more than five years old.

Vehicles

• Nearly 80% of primary-producer & 44% of general business OLV light trucks.

• OLV cars & 4-wheel-drives newer, while 50% of light trucks >5 years old.

• Light trucks more likely to be heavier (OR=58, P<0.000, CI 54-63) but less powerful than cars, with engines of four or less cylinder size, (OR=4.12, P<0.000, CI 4.1-4.2).

• 4-wheel-drives heavier & more powerful than all other vehicle types.

• half OLV fleet colored white, but private fleet less than third white vehicles

• nearly 80% of OLV load vehicles & 30% of cars and 4-wheel-drives white

• OLV made up of 149 makes and 1,015 models, Toyotas the largest market share of which 23% car shapes.

Environment

• Sydney city metropolitan region the registered location for

the majority of all light vehicles in New South Wales

• OLV were slightly more likely to be registered in the

Sydney area than privately registered vehicles, (OR=1.1, P<0.000, CI 1.60-

1.64).

• Rural or regional NSW registered OLV included around

95% of primary producers and half the load vehicles.

• More than 80% of taxis, 70% of general business and 65%

of government registrations were in the Sydney metropolitan

region.

Work Organization

• OLV registered for work-use either by an organization or a private-person/s – sole traders, unincorporated-organizations

• up to 38% of OLV were registered by a sole-trader not an organization.

• organizations more likely than sole-traders to register car shapes five or less years old in the Sydney area for general business use.

• around half regional vehicles registered by sole-traders for primary production.

•vehicles registered for farming or taxi use much more likely to belong to a sole trader than an organization. (OR=6.25, P<0.000, CI=6.1-6.4; OR=6.7, P<0.000, CI=6.3-7.1 respectively)

• Sole traders more likely to register light trucks (OR=1.9, P<0.000, CI=1.8-1.9), & have vehicles >5 years old than organizations, (OR=2.2, P<0.000, CI. 0.45-0.46).

• Most OLV & nearly all private vehicles were registered in small fleets - 99% of all sole-trader OLV in fleets of ten or fewer registrations.

• Light trucks more likely to be registered in small fleets (five or fewer vehicles) than larger fleets, (OR=1.6, P<0.000, CI=1.60-1.64).

• Only 2 OLV fleets had more than 5,000 registrations

• Majority of single-vehicles leases light trucks such as those used by couriers, maintenance or trades workers eg. plumbers or electricians.

OLV Crash Study

AimAim to research OLV crash/injury/fatality outcomes to assess the relative contributions of co-variates at different systems levels.

Ecological study Using the NSW RTA crash data set for 2004Linked to the NSW RTA 2004 registration data set& OLV population characterisation derived from NSW RTA 2003 registration dataset - descriptive tabulations - OR and 95%CI of covariates at each model level

Vehicles less than 4.5 tonne tare, and all light vehicle types

Vehicles 4.5 tonne Tare or more; mobile homes; buses; heavy plant ; cycles; trailers, etc. Vehicles with

seating capacity of 13 or more

Vehicles with seating capacity less than 13Vehicles with usage

categories not/unlikely to relate to OLV activity on public roads

Vehicles with non-OLV related usage categories but of the same vehicle types as the OLV group Selected OLV 2004 Crash Cohort:

Events involving Vehicles with OLV related usage categoriesN= 13,491

RTA NSW June 2004 Linked Registration Data

Selection of the Study population

RTA NSW crash data33,003 crash events

424 fatality; 14,396 injury; 18,183 tow-away events

OLV involved in:- 34 Fatal events (36 OLV killed)- 2,480 Injury events (4,466 injured)- 10,988 non-casualty tow-away events

Other motor vehiclesand pedestrians involved in OLV crashes

Data Source - NSW RTA Traffic Accident Database

Traffic Accident Database System (TADS) data is entered “for all accidents in which a person was

killed or injured or at least one motor vehicle was towed away.”

Road Vehicle Accident – any apparently unpremeditated event reported to the police resulting in

death, injury, property damage, attributable to the movement of the vehicle on the road.”

Vehicle of interest – the ‘key’ vehicle, the vehicle considered to have played the major role in the crash

For the study:

Fatal OLV crash – crash in which at least one OLV user was killed

Injury OLV crash – crash in which at least one OLV user was injured as a result of the accident but

no OLV user killed

Non-Casualty OLV crash – crash in which at least one OLV was involved and was damaged and

towed from the scene and no OLV user casualties resulted

(Ref: Traffic Accident Database Systems Data Manual, version 1.6, RTA, NSW, June 2002.)

• Females 1.8 times more likely to be casualty if in crash (P<0.000, CI 1.67-2.03)

• Males 2.5 times more likely to die if in casualty crash than females

(2.03; P<0.057, CI 0.15-1.02)

• Key vehicle user 16.4 times more likely to die if in casualty crash (P<0.000, CI 3.9-68.4)

• 13% of OLV population female registrants / 18% of fatalities & 37% injuries female OLV users

• 84% of OLV population male registrants / 82% of fatalities & 61% injuries male OLV users

• OLV user casualty mean age around 10 years younger than registrants

Users

(Users continued)

• Tired driver 3 times more likely to be casualty if in crash; and

• 9.1 times more likely to die if casualty in crash (P<0.000, CI 2.44-3.65; P0.000, CI 4.48-18.5)

• Tired farmer 6.1 times more likely to be casualty if in crash (P<0.000, CI 2.9-13.1)

• Tired sole-trader 3.8 times more likely to be casualty if in crash (P<0.000, CI 2.65-

5.448)

• Speeding drivers 2.4 times more likely to be a casualty if in crash, and

• 3.1 more likely to die if casualty (P<0.000, CI 1.5-3.9; P<0.086, CI 0.9-11.4)

• Non-seat belt user 1.6 times more likely to be casualty if crash; (P<0.000, CI 1.25-

1.97)

• if non-seat belt farmer 11.6 times more likely to be casualty; (P<0.002, CI 2.5-53.9)

Work Environment – Vehicles

• car shapes 1.25 more likely to have a casualty if in a crash than light truck (LT) (P<0.000,

0.74-0.88)

• LT shapes 3.6 more likely to have a death if in a casualty crash (P<0.001, 1.67-7.75)

• if in a casualty crash vehicle 15 or more years old, 3.5 times more likely to die than if in vehicle less than 5 years old (P<0.004, CI 1.47-8.17)

• If in crash 3.5 times more likely to have a casualty if a single vehicle crash, & if in a single vehicle casualty crash 5.7 times more likely to die than be injured.

(P<0.000, CI 3.10-3.88; P<0.000, CI2.78-11.5)

Fatal events:

• 50% ‘fatal’ vehicles 1-4 yrs old

• Two third of car shapes & half the commercial shape ‘fatals’ were in vehicles 5 or more years old.

• 92% of the commercial shapes were not fitted with air-bags & in 40% seat belt not worn/fitted

Work Environment – Vehicles

OLV Users in Fatal events:

• 28% fatalities not wearing seat belt

• 6% ill or asleep at time of crash

• 42% assessed with error factors

• 39% assessed as ‘fatigued”

• 30% fatal crashes occurred after 10.00pm & before 5.00am

• 65% fatalities alone in vehicle

OLV Crash Outcome by Vehicle Shape

0

10

20

30

40

50

60

70

80

Fatality Injury Non-Casualty

%

Commercial Shapes

Car Shapes

Likelihood of death as an outcome if in a Hilux, Rodeo or Triton light truck compared to all other vehicle models = 7.12 P<0.000, CI 3.62-14.26

Road Environment

Crash Outcome by Road Type

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freew

ay/m

otor

way

stat

e hi

ghway

othe

r clas

sified

road

uncla

ssifie

d road

%

killed

injured

all crashes

• 1.2 times more likely to have casualty if crash in dark, dawn or dusk compared to daylight, (P<0.000, CI 1.08-1.31)

• 3.1 times more likely to have a casualty if crash on unsealed road compared with sealed road (P<0.000, CI 2.45-3.95)

OLV movement before crash by crash outcome

05

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turn

right

into

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fatality

injury

non-casualty

Road Environment

Likelihood of casualty outcome rather than non-casualty outcome if crashed in higher speed-zones compared to those less than 60kph (35mph):

3.3 if in 100kph (60 mph) or more (P<0.000, CI 2.86-3.84)

1.5 if in 60-99kph (35-59mph) (P< 0.000 CI 4.44-18.4)

If casualty crash in speed-zone 100kph (60 mph) or more 9.0 times more likely to have death outcome than if in <60kph (35mph) zone.

Work Arrangements

Work Arrangement

Fatalities Injuries Non-casualty (tow-away)

OLV population

Self Employed 38% 27% 27% 28%

Organisation 62% 73% 73% 72%

Total 100% 100% 100% 100%

OLV Population Work Arrangement & Crash Outcome

0

10

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30

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60

70

80

killed injured OLV Population

% o

f w

ork

arr

ang

emen

t

Sole Traders

Organisations

Business General Primary Producers Taxis Others Total

85%

12%

1%

2%

24

10

--

34

71%

29%

--

100%

2,064

143

202

632472

83%

6%

8%

3%100%

9,464

336

981

20410,985

86%

3%

9%

2%100%

11,552

489

1183

26713,491

85.6%

3.6%

8.8%

2.0%100%

Usage All OLV

Killed Injured Non-casualty All crashes

Work Arrangements

If crashed:

• Farmers 2.1 times more likely to have a casualty outcome than general business (P<0.000, CI 1.60-2.69)

• Farmers 3.9 times more likely to have a death outcome if

casualty crash than general business users (P<0.014, CI 1.30-11.4)

Crash Outcome by Fleet Size

05

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1 ve

hicle

2-5

vehic

les

6-10

veh

icles

11-1

00 v

ehicl

es

100

- 499

vehi

cles

500-

4999

vehi

cles

5000

+

No of Vehicles in Fleet

%

Fatality

Injury

Tow-away

• 69% of all OLV are in fleets of 2 or less vehicles

• Taxis travel up to 189,000km annually• 57% of casualty taxi events involved self employed registrations • 68% of self-employed registered OLV taxi casualties wore seatbelts compared to 48% of organisation registered taxis

Study Strengths & Limitations

Limitations:

• Data reliant on police reporting

• No accurate exposure data available

• No drug or alcohol or other potentially criminally related data available

• Conservative estimates

Strengths

• Census rather than a sample

• Lot of new OLV-use related information

• Strengthened by use of OLV population data to give access to work arrangement information

Data Source &Time Period Data cover Fatalities Reported

Fatality Incidence

OLV Population &OLV Crash data2004

Light vehicle types – NSW only – used substantively for work purposes

34 5.3/100,000 OLV registrations

NSW CSB -July 03-June 04.

All vehicle types – NSW only – road traffic injury - worker on duty claims

25 Not known

ASCC-NOSI 2-NDSJuly 03-June 04.

Light vehicle types – Australia wide all claims except commuting

28 0.3/100,000 workers

ASCC -NDS-July 03-June 04.

Australia wide all claims except commuting

74 Not known

NDS: July 03-June 04. Australia wide all claims except commuting

49 Not known

NF: July 03-June 04. Australia wide all claims except commuting

7 Not known

NCIS: July 03-June 04. Australia wide all claims except commuting

51 Not known

To underpin OLV related policy and further improve our understanding of OLV users, their injury burden and their risk factors we require identification of:

• the at-risk OLV-user population;

• OLV crashes distinct from those of other road vehicle users;

• OLV road-use activity as work-related at the time of the MVC; and

• the OLV crash risk factors.

This could be assisted by:

• the use of vehicle registration data as a proxy for the OLV-user population

• the addition of vehicle usage purpose categories to light vehicle registration

• the addition of questions by investigators of OLV crashes about vehicle type,

usage purpose and users-work arrangements