Road safety issues in China: Understanding key risk factors to improve public health and safety

Dr Judy Fleiter Postdoctoral Research Fellow

Australia China Centre for Public Health, SYSU visit, May 11, 2015

Overview

• Global road safety

• Road safety in China

• Behavioural research conducted by CARRS-Q in

China

• Future research priorities

Acknowledgements

• Partner Institutions:– Institute of Psychology, Chinese Academy of Science, Beijing (5 months)– Zhejiang Police College, Hangzhou, China (2 years) – Guangdong Institute of Public Health, Guangdong Province Centre for Disease

Control and Prevention (4 months)– Yinchuan City Centre for Disease Control and Prevention (4 months)

• Colleagues:– Dr Barry Watson, Dr Mark King, Emeritus Professor Mary Sheehan, Dr George

Jia, Dr Alexia Lennon - CARRS-Q (QUT)– Professor Shi Kan, - Chinese Academy of Sciences– Professor Guan Manquan, Ding Jingyan, Xu Cheng – Zhejiang Police College– Professor Ma Wenjun – Guangdong Institute of Public Health– Dr Jing Lei - Yinchuan City Centre for Disease Control and Prevention

Acknowledgements

Funding

• Australia’s National Health & Medical Research Council– Postdoctoral Research Fellowship (Australia-China Exchange)– Promote Australia-China road safety research & capacity building (2011-2015)

• Endeavour Australia Awards– Cheung Kong Postgraduate Award – 2008 (Fleiter)– Prime Minister’s Australia Asia Postgraduate Award – 2012 (Jia)

United Nations Decade of Action for Road Safety

(2011-2020)

• Every year, globally, road crashes:– kill 1.3 million people– injure 20 – 50 million people

• Aim to reduce road-related trauma– save 5 million lives in 10 years– by sharing experiences, and introducing effective legislation,

enforcement and education

World Health Organization, 2009; 2013

United Nations Decade of Action for Road Safety

(2011-2020)

Globally,• Road traffic injuries 8th leading cause of death

• Leading cause of death of young people 15-29

• 90% of road deaths & injuries occur in low- & middle-income countries

• 46% of global road deaths are ‘vulnerable road users’– pedestrians, cyclists, motorcyclists

World Health Organization, 2013

In China

• Scale of road trauma problem difficult to determine:– Unlinked reporting systems (police, hospital datasets)– Reporting mechanisms vary (e.g., death within 7 days of crash in police records,

doesn’t follow ICD10 classification)– Under-reporting likely

• Police records indicate ~70,000 fatalities/year with sharp decrease since 2002

– Examination of 210 military hospitals shows slow increase since 2002– Analysis of city level data indicates 3 times as many fatalities and up to 5 times

as many injuries as reported in official data (Qui et al., 2015)– These data similar to WHO estimates

Alcorn, 2011; Hu et al, 2012; Qiu et al, 2015; WHO, 2103; Zhang et al., 2008

In China

• Road fatalities = leading cause of injury deaths – ahead of all natural disasters (including fire, earthquake, and flood) (Ma, et al;, 2012).

– 25% of total productive years lost from all injuries (Zhou et al., 2003)

• Road fatalities– Males = 76%– Majority of road traffic injuries (RTI) occur among young males– RTI = one of the top 3 causes of death in people aged 60+ (Zhou et al., 2014)

– Vulnerable road users = 70 %

Vulnerable Road Users, China

Driver

s 4-w

heel

light

Passe

nger

s 4-w

heel

light

Riders

-mot

orise

d 2

& 3 w

hl

Cyclis

ts

Pedes

trian

s

Truck

Driv

ers/p

sgr

Other

6%

17%

35%

10%

25%

5%2%

% of Fatalities

Source: 2010 PRC Road Traffic Accident Annual Statistic Report, Traffic Management Bureau of Ministry of Public Security, cited in WHO, 2103 Global Road Safety Status Report.

70%

Large population, unprecedented economic growth, rapid motorisation, large number of novice drivers

Mixed traffic fleet: pedestrians, non-motorised vehicles, increase in e-bikes (banned in some places), heavy vehicles

Large rural > urban migration = unfamiliarity with traffic and traffic rules

In Transition

– Road safety legislation relatively new (2004) and still in formative stage

– Traffic police not well respected & responsible for public education with limited resources

– Varying levels of traffic law enforcement

– Traffic laws not well understood by general community

– Road safety awareness relatively low

– Non-compliance with traffic laws evident

Fleiter et al., 2009; 2011; 2013a,b,c; Jia et al., 2013; Senserrick et al., 2011

Enforcement & Education

Behavioural factors

• Illegal/risky on-road behaviours common & appear normalised– Non-use of helmets & seat belts– Phone use while driving/riding– Over-crowded & overloaded vehicles– Drink driving– Speeding (main reported cause of crashes in China - estimates of

between 50-90% of all crashes

Du et al., 2013; Fleiter et al., 2009; Fleiter et al., 2013a,b,c; Jia et al., 2013a,b; Routley et al., 2008

Behavioural factors

• Illegal/risky on-road behaviours common & appear normalised– Non-use of helmets & seat belts– Phone use while driving/riding– Over-crowded & overloaded vehicles– Drink driving– Speeding

• 2 risk factors identified by Bloomberg-funded Global Road Safety Program (2010-2014)– Dalian & Suzhou

• Bloomberg Initiative for Global Road Safety (BIGRS) 2015-2019 – Shanghai, legislative focus

Du et al., 2013; Fleiter et al., 2009; Fleiter et al., 2013a,b,c; Jia et al., 2013a,b; Routley et al., 2008

CARRS-Q Behavioural Research

Speeding

CRICOS No. 00213J

Beijing & Hangzhou

Speeding• Qualitative & quantitative research with car drivers:

– Speeding viewed as common, normal, necessary, safe

– Self-reported ‘usual’ speeds up to 50% above posted speed limits (link to

enforcement tolerance in legislation)

– ‘Safe speeds’ reported as up to 20 km/h above posted speed limits

– ‘Preferred speeds’ significantly faster than ‘safe speeds’

– Penalties not certain and can be avoided (use of ‘guanxi’/networks; arguing with

police, convincing police not to issue infringement)

– Experiences of avoiding detection & punishment encourage future offending

Fleiter et al., 2009; Fleiter et al., 2013a,b,c; Fleiter & Watson, 2015

CARRS-Q Behavioural Research

Speeding

Drivers attending re-training program after losing licence– Significantly more crashes among newly licensed drivers– Mean of 4.6 infringements in previous year (range 2-18, SD=3.8)

– 62% drink driving offence; 48% speeding offence– Identification of ‘most dangerous’ on-road behaviours by drivers

• Speeding• Drink driving• ...• Phone use while driving, fatigue, non-use of seat belts nominated by very few• Reflects enforcement practices by police?

Fleiter & Watson, 2015

CARRS-Q Behavioural Research

Drink Driving

Guangzhou & Yinchuan

Drink Driving

• Legislative change in May 2011, Drunk driving criminalised• 2 legal blood alcohol concentration limits

– Drink driving = 20mg-80mg/100 ml – Drunk driving = >80mg/100ml

• Qualitative & quantitative research – General drivers– Convicted drunk driving offenders in detention– Traffic police

Jia, 2015; Jia et al., 2013a,b, c

CARRS-Q Behavioural Research

Drink Driving

• High awareness in both cities that Drunk driving now a criminal offence

• Low awareness of legal BAC levels in all samples – Only 16 – 40% reported correct knowledge of legal BACs

• Knowledge of how to keep BAC below legal limit was extremely low for all, including traffic police

Jia, 2015; Jia et al., 2013a,b, c

CARRS-Q Behavioural Research

Drink Driving

• Evidence of limited police roadside testing and lack of adequate police resourcing

• Drivers use many strategies to avoid detection, some endangering police safety

• AUDIT scores used to assess problematic drinking– Higher level of alcohol misuse among convicted drunk driving offenders (both

cities). Higher among Yinchuan than Guangzhou offenders– 1st time vs Repeat offenders: significant difference in AUDIT scores in both cities.

1st time offenders had a significant lower AUDIT scores than recidivists. – Indicates problematic alcohol use levels among repeat drink drivers

Jia, 2015; Jia et al., 2013a,b, c

Future Research

• Legislation in formative stage– penalties not necessarily a deterrent

– low levels of awareness (e.g. BAC levels)

– low levels of perceived risk associated with high risk behaviours (e.g. speeding, phone use while driving)

• Evidence needed to reduce harm– Enhance data quality

– Inform policy development

– Inform public education campaigns

– Raise awareness about high risk behaviours

– Consider culturally-specific issues when introducing countermeasures

Thank you for your attention today.

j.fleiter@qut.edu.au

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