1. Victoria Pyta ARRB Group
Disadvantage and Road Safety
Victoria Pyta
ARRB Group

2. Contents About this project Overview of literature review
Preliminary findings
Next steps

3. Background
Objectives
Definition of disadvantage
Project Overview

4. Background Austroads project SS1761 (2012 – 2015) Project Team:
Literature review
Data analysis and modelling
Consultation
Project Team:
Project Technical Leader: Victoria Pyta (ARRB)
Project Manager: Anita Baruah (VicRoads)
Quality Manager: Dr Peter Cairney (ARRB)

5. Project Objectives
1. Determine how the incidence, severity, nature and location of crash involvement varies between persons from more versus less disadvantaged areas.
2. Gain an understanding of how road environment, vehicle and behavioural factors are related to crash likelihood and severity outcomes among persons from disadvantaged areas.
3. Recommend evidence-based strategies for addressing the issues that are identified through this process.

6. What is disadvantage? What is disadvantage?
Low income relative to others and/or expenditure on necessities
Barriers to education, social opportunities or work
A ‘relative’ and ‘multi-dimensional’ concept
How is disadvantage related to road safety?
Socio-economic disadvantage is associated with higher injury rates due to transport-related injuries.

7. Literature review Effects of disadvantage on road trauma
Factors that are associated with both disadvantage and road trauma
Interventions
Literature review

8. Victoria, Australia Victorian Injury Surveillance Unit
Transport injuries represent 14% of all injuries in the hospital admissions data
Persons with greatest risk come from the 2nd and 3rd quintiles
Victorian hospital data (2005 to 2007)
Persons assigned to LGA of residence
LGA ranked by Index of Relative Social Disadvantage (IRSD)

9. New South Wales, Australia
Remoteness and low SES associated with increased risk of death among young drivers
Rural fatalities
Low SES fatalities
Higher posted speed limits
Fatigue
Drink-driving
Seatbelt non-use
Higher posted speed limits
Fatigue
Driving an older vehicle

10. Indigenous populations of Australia and New Zealand
Among most severely disadvantaged
High road fatality rate compared to non-indigenous populations
Cultural and language differences
Australia
New Zealand
Drink driving
Unlicensed driving
Remoteness amplifies problems and accounts for much of the disparity
Over-representation is particularly strong among year olds
Disparities persist after accounting for differences in SES

11. International Many studies (UK, Europe, Israel, USA)
Disadvantage associated with higher risk, particularly for child pedestrians
Concomitant factors:
Environmental, e.g. location (especially remoteness), exposure
Behavioural factors, e.g. unlicensed driving, drug and alcohol use
Socio-cultural factors, i.e. peer group and culture
Personal factors, e.g. health, self-efficacy

12. Existing interventions
Low income earners (registration discounts and discounts on drink drive programs)
Indigenous communities (wide range)
CALD communities (translation, education and awareness raising, licensing assistance)
Young drivers (supervised practice, first car safety)
Children (proper restraint use and early childhood road safety education)
Engineering treatments
Enforcement and diversionary programs
Partnerships and community engagement

13. Data Analysis Data sources
Results so far (exploratory descriptive analysis)
Next steps, methods and data sources
Data Analysis

14. Data sources (Australia)
Crash data with postcode of crash involved persons
Vic, NSW, SA
NZ (needs to be geocoded)
SES data
ABS Index of Relative Social Disadvantage (IRSD)
Remoteness data
ABS remoteness index
Potential for inclusion of travel survey data
e.g. ABS Survey of Motor Vehicle Use (SMVU)

15. Index of Relative Social Disadvantage (Australia)
Takes into account:
Income
Household occupancy
Vehicle ownership
Illness and disability
% of residents speaking LOTE
% of residents of indigenous origin
Etc.

16. Preliminary results (drivers and riders, Victoria)

17. Preliminary results (drivers and riders, NSW)

18. Preliminary results (drivers and riders, SA)

19. South Australia (All road users, 10 years)
IRSD Quintile
Population (2006)
Number of persons
Rate per 100,000 population
Killed
Seriously Injured
Total Q1
713
4 684
5 397
22.2
145.8
168.0 Q2
520
4 064
4 584
17.4
135.6
153.0 Q3
496
3 492
3 988
18.4
129.7
148.1 Q4
429
3 595
4 024
14.4
120.4
134.7 Q5
378
3 395
3 773
11.8
105.9
117.7
TOTAL
2 536
19 230
21 766
16.8
127.4
144.2

20. Looking forward
Years 2 and 3

21. Remainder of 2013 – Modelling
Develop model for crash risk associated with SES that takes into account:
Demographic profile of area
Remoteness
Environmental factors (e.g. speed limits)
Individual demographic factors (age, gender etc.)
Behavioural factors (e.g. restraint use)
Other explanatory factors (e.g. vehicle age)

22. 2014/15
detailed consultation regarding the operation of programs for disadvantaged groups or locations
develop recommendations for actions to address these issues

23. Acknowledgements Data providers in road agencies SS1761 Project Team:
Dr Peter Cairney, Principal Behavioural Scientist (ARRB)
Anita Baruah, Senior Policy Analyst, Road Safety and Network Access (VicRoads)
Project steering committee
Supervisor
Dr Lyndon Walker, Swinburne University