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Road safety: from public health to psychology
Road traffic crashes are a major public health issue that cause over 1 million deaths per year globally. Vulnerable road users such as pedestrians, cyclists and motorcyclists account for about half of road traffic deaths. Factors that influence the risk of road traffic injuries include human behaviors like speeding, driving under the influence of alcohol, and lack of safety measures like helmet and seatbelt use. Policies and infrastructure changes that enhance road safety, especially for vulnerable users, have been shown to significantly reduce road traffic fatalities.
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Road safety: from public health to psychology
- 1. Improving Road safety: From public health to psychology © WHO, 2007 Aymery Constant, PhD Maître de conférence / Lecturer EHESP / French School of Public Health 1│
- 2. © WHO, 2007 2│ Mobility • Every person has to move during lifetime • Going to school, work, shopping, travel... • Different transportation modes: motorized and non motorized But this is not a safe activity
- 3. © WHO, 2007 Road mortality and injuries: A major public health issue 3│
- 4. © WHO, 2007 Road traffic crashes • 1.2 million deaths a year (road mortality) • 20-50 million injuries/disabilities (road injuries) • 11th leading cause of death • Account for 2.1% of all deaths globally
- 5. Global status reporton road safety 2013 © WHO, 2007
- 6. Drowning 7.3% ©WHO, 2007 6│ Distribution of global injury mortality by cause Suicide 16.9% Violence 10.8% War 3.4% Poisoning 6.7% Falls 7.5% Fires 6.2% Road traffic injuries 22.8% Other intentional injuries 0.2% Other unintentional injuries 18.1% Road traffic injuries account for 23% of all fatal injuries worldwide Source: WHO Global Burden of Disease project, 2002, Version 1
- 7. Indicators of roadtraffic safety © WHO, 2007 7│
- 8. Absolutes Figures •Number of injuries indicating the number of people injured in © WHO, 2007 8│ road traffic crashes Not very useful for making comparisons. A large proportion of slight injuries are not reported • Number of deaths indicating the number of people who die as a result of a road traffic crash Gives a partial estimate of the magnitude of the road traffic injury problem, in terms of death
- 9. • Fatalities per10 000 vehicles © WHO, 2007 9│ showing ratio of fatalities to number of motor vehicles. Shows probability of vehicle involvement in fatal crashes It omits non-motorized transport and declines with motorization Relative figures • Fatalities per 100 000 pop impact of road traffic crashes on human population as a public health problem. Useful for estimating severity of crashes. Might decline in countries with very large populations
- 10. Others indicators •Fatalities per vehicle-kilometre travelled © WHO, 2007 10│ Useful for making international comparisons, decreases with motorization Does not take into account non-motorized travel • Disability-adjusted life years (DALYs) Estimate healthy life years lost to disability and mortality. DALYs combine both mortality and disability but do not include mental health consequences
- 11. Distribution of roadfatalities © WHO, 2007 11│
- 12. ROAD TRAFFIC DEATHRATES PER 100 000 POPULATION (WHO, 2012) © WHO, 2007
- 13. © WHO, 2007 13│
- 14. © WHO, 2007 Evolution of road mortality over time 14│
- 15. © WHO, 2007 15│ Brazil
- 16. © WHO, 2007 16│ India
- 17. © WHO, 2007 17│ Vietnam
- 18. © WHO, 2007 18│
- 19. © WHO, 2007 TRENDS (WHO, 2012)
- 20. © WHO, 2007 20│ Key points Decreasing trends in road traffic deaths in high-income countries, despite high levels of motorization (number of motor vehicle per capita) Increasing or stable trends in most low- and middle-income countries, despite low to average (but increasing) levels of motorization Traffic injuries and deaths represent a serious threat to development in low-income countries, and jeopardise the pursuit of equity in health
- 21. Differences in roadfatalities between low-middle and high © WHO, 2007 income countries 21│
- 22. © WHO, 2007 France
- 23. © WHO, 2007 23│ Brazil
- 24. © WHO, 2007 Thailand
- 25. Proportion of roaddeaths by transportation 0% 20% 40% 60% 80% 100% Australia Delhi, India Kenya Malaysia Netherlands Sri Lanka © WHO, 2007 modes 25│ Pedestrians Motorized 4-wheelers Bicyclists Motorized 2-wheelers USA
- 26. Vulnerable road users Pedestrians, cyclists, motorcyclists and moped riders are considered as vulnerable since they benefit from little or no external protective devices that would absorb energy in a collision. They constitute with almost no exception the weak party in a road traffic crash © WHO, 2007 26│
- 27. Vulnerable road users Half of the road fatalities occurring each year concern vulnerable road users (VRUs). They predominate in low and middle income countries, where levels of motorization are low With children and elderly being overrepresented among victims Safety of VRUs became a health priority for International Agencies such as the WHO and the UN in 2004 (WHO report on road safety, 2004) © WHO, 2007 27│
- 28. Road deaths, 2012 © WHO, 2007
- 29. Impact of policiestoward VRUs © WHO, 2007 29│
- 30. © WHO, 2007 Thailand 30│ Back to Thailand…
- 31. Regulations in Thailand © WHO, 2007 31│
- 32. © WHO, 2007 In Europe Death risk for 100 million person / kilometres travelled: 13.8 for motorised two-wheelers 6.4 for pedestrians 5.4 for bicyclists 0.7 for car users 0.07 for bus and coach passengers. Source: European Transport Safety Council 32│
- 33. © WHO, 2007 Helmet use According to Reviews conducted by Authors from the Cochrane Collaboration: - Helmets are effective in reducing head injuries in motorcyclists who crash by 69% and death by 42% (Liu et al., 2009) - Helmets provide a 63 to 88% reduction in the risk of head, and severe brain injury for all ages (Thompson, Rivara, & Thompson, 2009)
- 34. © WHO, 2007 34│ Road fatalities: Florida Helmet law for motorcyclists was lifted Source: NHTSA (USA)
- 35. Europe standardized rates Source: CARE Database / EC © WHO, 2007 Date 35│ of query: August 2008
- 36. From Islamabad, Pakistan © WHO, 2007 36│
- 37. © WHO, 2007 37│
- 38. © WHO, 2007 38│
- 39. Conclusion Highrates of mortality among VRUS might be due to several interacting factors : Road infrastructure not adapted (bicycle lanes; separation between VRU and motorized traffic; etc.) Few/No policies towards VRU Risk behaviours and/or poor law enforcement Absence of protective behaviour (helmet use..) © WHO, 2007 39│
- 40. Constant & Lagarde © WHO, 2007 40│
- 41. What can bedone?: An example of intervention © WHO, 2007 41│ study towards cyclists Investigating Helmet Promotion for Cyclists: Results from a Randomised Study with Observation of Behaviour, Using a Semi-Automatic Video System
- 42. Helmet use In France, helmet is not mandatory for cyclists The efficacy of lawful mandatory helmet use is in dispute, because: of possible negative side-effects such as risk compensation and possible decline in the number of cyclists (see Robinson, BMJ) We launched a randomized comparative study that measured for the first time the efficacy of non legislative interventions to promote helmet use among cyclists © WHO, 2007 42│
- 43. Methods Participantswere recruited in a borrow-a-bike municipal program. They completed a questionnaire on their attitudes toward road safety and helmet use. They were assigned to one of the four groups: Control group Group #1: They received an information on helmet benefit Group #2: They received a helmet Group #3: They received both An ID coloured code was put on their rear mudguard. © WHO, 2007 43│
- 44. Recruitment center ©WHO, 2007
- 45. Municipality Bicycles ©WHO, 2007
- 46. © WHO, 2007 (Not good looking) helmets were given to groups #2 and #3
- 47. © WHO, 2007 standardized brochures were given to groups #1 and #3
- 48.
- 49. Outcomes Fiveautomatized observation sites were deployed in the urban centre of Bordeaux. Two of them made observations in both directions, leading to a total of seven observation spots A first camera was programmed to detect moving objects, isolate cyclists, and calculate speed A second synchronised high-definition camera automatically took a photo of each detected cyclist from behind at a 45 degree angle. © WHO, 2007 49│
- 50. were connected tothe main our settings via the INSERM © WHO, 2007 50│
- 51.
- 52.
- 53.
- 54. Data collection ©WHO, 2007
- 55. Data collection ©WHO, 2007
- 56.
- 57.
- 58. © WHO, 2007 58│
- 59. © WHO, 2007 59│
- 60. © WHO, 2007 60│
- 61. © WHO, 2007 61│
- 62. © WHO, 2007 62│ An ignored risk: Umbrella and Cycling
- 63. Conclusion Helmetwearing rate ? Efficiency of information to promote helmet use? Duration of effect ? Cues to improve helmet wearing rates ? © WHO, 2007 63│
- 64. © WHO, 2007 Road injuries: Risk Factors 64│
- 65. Male gender ©WHO, 2007 65│
- 66. © WHO, 2007 66│
- 67. Road deaths affectprimarly young © WHO, 2007 people 67│
- 68. © WHO, 2007 68│ Risk factors Behaviours • A study estimate that more than 90% of collisions occur because of human factor (see above) • Some Risky road behaviour increase the likelihood of traffic crashes • Excessive speed • Driving while alcohol-intoxicated • Sleepy driving
- 69. © WHO, 2007 69│ Risk factors • Some behaviours increase the severity of a crash • Seats-belts not used (4-wheel drivers) • Helmet not used, no protective clothes (2-wheel drivers) • Insufficient car protection • Some behaviours increase both • Excessive speed • Driving while alcohol-intoxicated
- 70. © WHO, 2007 70│
- 71. © WHO, 2007 71│ Effect of alcohol in traffic Alcohol directly weakens driver skills: - less attention and visual detection - longer reaction time - problem with keeping course Accident risk increases exponentially depending on Blood Alcohol Content (BAC): - 0,5 g/l: 1,5 times higher than sober - 0,8 g/l: 2 times higher than sober - 1,3 g/l: 15 times higher than sober - 1,8 g/l: 50 times higher than sober 71
- 72. © WHO, 2007 72│ Accident risk of drink drivers at different BAC-levels
- 73. © WHO, 2007 73│ Risk factors Road and environmental factors • Traffic density • Time (day/night; week-end/other; vacations; other) • Reduced visibility (absence / poor street lighting) • Type of road (highway, rural roads..), quality of the road surface • Road engineering and infrastructure • Unforgiving infrastructures • Protection for pedestrians/cyclists (bicycle lanes, traffic island..)
- 74. © WHO, 2007 74│ Risk factors Vehicle characteristics • Roadworthiness • Lighting • Braking • Handling • Speed management • Etc.
- 75. The psychology ofroad traffic © WHO, 2007 Crashes 75│
- 76. The Haddon Matrix Conceptual model that applies basic principles of public health to the problem of traffic safety. extremely useful and effective tool for revealing where and when to best conduct traffic safety interventions • Highlight injuries in terms of causal and contributing factors, as well as in terms of a time sequence consisting of pre-event, event, and post-event phases. © WHO, 2007 76│
- 77. The Haddon Matrix Consists of four (or three) columns representing the causal agents in the crash: the driver, the vehicle, and the physical and socio-economic environment Three rows representing time phases: pre-crash (before a potential vehicle collision), crash (the actual event), and post-crash (the immediate aftermath). © WHO, 2007 77│
- 78. Haddon Matrix ©WHO, 2007 78│ Factors Vehicles and equipment Environment Phase Human Pre-crash Crash prevention Information Attitudes Impairment Police enforcement Roadworthiness Lighting Braking Handling Speed management Road design and road layout Speed limits Pedestrian facilities
- 79. Haddon Matrix ©WHO, 2007 79│ Factors Vehicles and equipment Environment Phase Human Pre-crash Crash prevention Information Attitudes behaviourt Police enforcement Roadworthiness Lighting Braking Handling Speed management Road design and road layout Speed limits Pedestrian facilities Crash Injury prevention during the crash Use of restraints Impairment Occupant restraints Other safety devices Crash protective design Crash-protective roadside objects Forgiving infrastructure
- 80. Haddon Matrix ©WHO, 2007 80│ Factors Vehicles and equipment Environment Phase Human Pre-crash Crash prevention Information Attitudes behaviour Police enforcement Roadworthiness Lighting Braking Handling Speed management Road design and road layout Speed limits Pedestrian facilities Crash Injury prevention during the crash Use of restraints Impairment Occupant restraints Other safety devices Crash protective design Crash-protective roadside objects Forgiving infrastructure Post-crash Life sustaining First-aid skill Access to medics Ease of access Fire risk Rescue facilities Congestion
- 81. Haddon Matrix ©WHO, 2007 81│ Factors Vehicles and equipment Environment Phase Human Pre-crash Crash prevention Information Attitudes behaviour Police enforcement Roadworthiness Lighting Braking Handling Speed management Road design and road layout Speed limits Pedestrian facilities Crash Injury prevention during the crash Use of restraints Impairment Occupant restraints Other safety devices Crash protective design Crash-protective roadside objects Post-crash Life sustaining First-aid skill Access to medics Ease of access Fire risk Rescue facilities Congestion
- 82. Psychological andsociological models are of interest in studying human factors influencing the likelihhod of a crash before its occurrence (pre-crash) © WHO, 2007 82│ Information Attitudes Norms Police enforcement Behaviours
- 83. Theory of plannedbehaviour (TPB) Azjen (1991) suggested various factors combine to form an intention to act a certain way. © WHO, 2007 83│ Attitudes toward behaviour Subjective norms Perceived behavioural control Intention to behave in a certain way Behaviour
- 84. Application of theTPB to road safety © WHO, 2007 84│
- 85. Application of theTPB to road safety © WHO, 2007 85│
- 86. Application of theTPB to road safety © WHO, 2007 86│
- 87. Application of theTPB to road safety © WHO, 2007 87│
- 88. © WHO, 2007 88│ Predict intention Predict self reported behaviour Do not predict actual behaviour
- 89. © WHO, 2007 89│
- 90. © WHO, 2007 90│
- 91. © WHO, 2007 Develop and evaluate intervention 91│
- 92. © WHO, 2007 92│ How to reduce road fatalities ? Evidence-based interventions • Usually, preventive interventions are assessed through longitudinal studies • The statistical unit is a target population • An outcome of interest is assessed before and after a preventive intervention (number of fatalities or head injuries when testing helmet law) • Ecological or “before-after” studies
- 93. Recent changes inFrench road safety 14 000 12 000 10 000 8 000 6 000 4 000 2 000 © WHO, 2007 93│ 0 number of fatalities Number of road fatalities
- 94. Recent changes inFrench road safety 14 000 12 000 10 000 8 000 6 000 4 000 2 000 © WHO, 2007 94│ 0 number of fatalities 40,00% 35,00% 30,00% 25,00% 20,00% 15,00% 10,00% 5,00% 0,00% speed excesses % fatalities up to 2001 fatalities from 2001
- 95. The case ofFrance • France is a high income country • Good infrastructure (highway, rural roads) and vehicles • High level of motorization • Numerous information campaigns against risky road behaviours since the 70’s • Road fatalities in 1976: 16 000 • Decrease in road fatalities: 1975 -2001: - 2% on average © WHO, 2007 95│ • 2002 - 2009: -44.4%
- 96. Automatic Speed camerasIn France © WHO, 2007 96│
- 97. © WHO, 2007 97│
- 98. Influence on attitudestowards road safety and road behaviours How attitudes toward traffic safety have changed between 2001 and 2004? How road behaviours have changed between 2001 and 2007 What are the determinants of these changes? Relevance: Providing useful insights into what occurred in this remarkable period and help assessment of whether observed behavioural changes are stable. © WHO, 2007 98│
- 99. Methods: a prospectivestudy in the GAZEL cohort Participants: Current employees or recent retirees of the French national electricity and gas company, who volunteered to participate in a research cohort, known as the GAZEL cohort. The same questionnaire was used to assess behaviours and attitudes toward road safety in 2001, 2004 and 2007 Data was also available from the cohort database (gender, age, occupational category, alcohol consumption, etc.) © WHO, 2007 99│
- 100. Study on attitudesand road behaviors and in the GAZEL cohort © WHO, 2007 100│ 2001 2002 2004 First Assessment 2003 2005 2006 2007
- 101. Study on attitudesand road behaviors and in the GAZEL cohort French government © WHO, 2007 101│ 2001 2002 2004 First Assessment 2003 2005 2006 2007 enact a zero tolerance policy
- 102. Study on attitudesand road behaviors and in the GAZEL cohort French government © WHO, 2007 102│ 2001 2002 2004 First Assessment 2003 2005 2006 2007 enact a zero tolerance policy Increased law enforcement: -Automatic speed cameras - Alcohol controls Phoning and driving forbidden End of indulgences (ticket fixing) Legal sanctions harshened Dramatic decreases in road fatalities and in road injuries
- 103. Study on attitudesand road behaviors and in the GAZEL cohort © WHO, 2007 103│ 2001 2002 2004 First Assessment 2003 2005 2006 2007 Second Assessment Third Assessment French government enact a zero tolerance policy
- 104. Influence of increasedenforcement on attitudes © WHO, 2007 104│
- 105. Influence of increasedenforcement on attitudes © WHO, 2007 105│
- 106. Conclusion 1 Increasedtraffic law enforcement measures led to increasing support for current restrictions between 2001 and 2004. Even if support for additional traffic law enforcement began to wane slightly in 2004 (-4%), a large part of participants remained in favour of strengthening law enforcement related to speeding (61%) and drink driving (80%). © WHO, 2007 106│
- 107. Influence of increasedenforcement on excessive speed (reported speed at least 20 km/hour above the limit) © WHO, 2007 107│
- 108. Influence of increasedenforcement DWI © WHO, 2007 108│
- 109. Conclusion 2 Between2001 and 2007, the proportion of participants who reported having driven at speeds at least 20 km/hour above the limit decreased in built-up areas, on rural roads and on highways But the recent crackdown on road violations by the French government has failed to deter DWI, despite declines in overall alcohol consuption over the same period © WHO, 2007 109│
- 110. Unlike speeding, detectionof DWI offenders cannot be achieved through automated devices, thus limiting the probability of being arrested for DWI. DWI remained unchanged although attitudes and norms rejecting such behaviour are very high in the population And despite the fact that DWI is identifed by 92% of drivers as a major cause of fatal crash (SARTRE Study) © WHO, 2007 110│ Conclusions
- 111. Safety is mainlyabout…. 1) behaviour 2) behaviour change 3) and (in the case of road safety) law enforcement © WHO, 2007 111│ Conclusions
- 112. First, change behaviours(hardest part of the job, really) Then, health issues, and all related costs, will (hopefully) decrease, And finally, attitudes and norms will follow … © WHO, 2007 112│ Implications for health actions and prevention initiatives