Road Traffic Injuries in Shanghai, China

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This is the published version of a paper published in HealthMed.

Citation for the original published paper (version of record): Wang, S., Dalal, K. (2012)

Road Traffic Injuries in Shanghai, China. HealthMed, 6(1): 74-80

Access to the published version may require subscription. N.B. When citing this work, cite the original published paper.

Permanent link to this version:

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5RDG WUDI¿F LQMXULHV DUH PDMRU SXEOLF KHDOWK social and economic problem. In China road traf- ¿FLQMXULHVDUHLQFUHDVLQJUDSLGO\2EMHFWLYHRIWKH VWXG\ZDVWRDVVHVVWKHULVNIDFWRUVIRUURDGWUDI¿F injuries and the relationship between the individual and environmental factors and the severity of injury in a designated Safe Community in Shanghai, China. Data were retrieved from a Safe Commu- nity surveillance system including hospital, police DQG¿UHEULJDGHUHFRUGV&KLVTXDUHWHVWDQGPXOWL- variate logistic regression were used. Total 568 was injured due to road accidents in 2008 (43% were mild injured and 9% severely injured) .Violation RIWUDI¿FUXOHZDVPDMRUSUREOHPDPRQJGULYHUVRI PRWRUL]HGYHKLFOHV3ROLFHKDVLGHQWL¿HGPDMRU causes of road accidents. Age over 45 years and cloudy/rainy road conditions were major cause of accidents at the individual and environmental level factors. Findings are important for policy makers and Safe Community planning.

.H\ZRUGV5RDGWUDI¿FLQMXULHV5LVNIDFWRUV Safe Community;; China.

Introduction

5RDG WUDI¿F LQMXU\ LV D PDMRU SXEOLF KHDOWK SUREOHP FRQVWLWXWLQJ VLJQL¿FDQW SURSRUWLRQV RI health, social and economic burden. Over 1.2 million people die each year on the world’s roads, and between 20 and 50 million people suffer non- fatal injuries1, 2_{. In most regions of the world the}

HSLGHPLFRIURDGWUDI¿FLQMXULHVLVVWLOOLQFUHDVLQJ :+2SUHGLFWVWKDWURDGWUDI¿FLQMXULHVZLOOULVHWR EHFRPHWKH¿IWKOHDGLQJFDXVHRIGHDWKE\1_.

*OREDOO\URDGWUDI¿FDFFLGHQWGHDWKVDUHSUR- jected to increase from 1.3 million in 2004 to 2.4 million in 2030, primarily due to the increased motor vehicle ownership and use associated with economic growth in low and middle-income co-

untries3_{. Pedestrians, cyclists, and drivers of mo-}

torized two-wheelers and their passengers account IRUDOPRVWKDOIRIJOREDOURDGWUDI¿FGHDWKV1_{. In}

&KLQD IURP WR WKH URDG WUDI¿F LQMXU\ had been increasing at an increasing rate. Since late 1980s this trend was getting worse with more motorized vehicle’s accidents4_{. While higher mo-}

torization in the transportation brought conveni- ence to the people it also brought an increasing WUHQG LQ URDG WUDI¿F DFFLGHQWV5_{7KH WUDI¿F GHDWK}

due to motorized vehicles in China accounted for 8.3% of the total death of the world, and accounted for 1.3% of total death of Chinese residents4_.

According to the report of the Ministry of Public 6HFXULW\VLQFHWKHQXPEHURIWUDI¿FIDWDOLWLHV every year was around 100 000 while the number of injured was around 500 000. However, a hun- GUHGIROGLQFUHDVHLQURDGWUDI¿FPRUWDOLW\GXULQJ previous 55 years6_.

5LVNIDFWRUVRIURDGWUDI¿FLQMXULHVZHUHH[SOR- red by a worldwide report in different aspects: IDFWRUV LQÀXHQFLQJ H[SRVXUH WR ULVN ULVN IDFWRUV LQÀXHQFLQJ FUDVK LQYROYHPHQW VHYHULW\ DQG VH- verity of post-crash injuries. The general factors contain growing number of motor vehicles, soci- DO GHSULYDWLRQ GHPRJUDSKLF IDFWRUV LQVXI¿FLHQW planning of transport, land use and road network. The risk factors affected crash involvement are divided into two groups: individual factors including young male, excess speed, presence of al- cohol, medicinal o recreational drugs, fatigue, as well as poor road user eyesight, and circumstance factors (travelling in darkness, vehicle factors, de- fect road design, and inadequate visibility due to environmental factors). The factors specially con- WULEXWH WR WKH VHYHULW\ RI URDG WUDI¿F LQMXULHV LQ- clude scarcity of vehicle crash protection, lack of roadside protection, non-use of protective devices in vehicles (for example, seat-belts and air bags), non-use of helmets, inappropriate speed and alco- hol intake 2_.

5RDG7UDI¿F,QMXULHVLQ6KDQJKDL&KLQD

Shu-Mei Wang1_{, Koustuv Dalal}2

1_{6FKRRORI3XEOLF+HDOWK³.H\/DERUDWRU\RI3XEOLF+HDOWK6DIHW\0LQLVWU\RI(GXFDWLRQ´)XGDQ8QLYHUVLW\}

Shanghai, China,

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Community is a setting where people share a common purpose interest or need, express their UHODWLRQVKLSV DQG UHÀHFW GLYHUVLW\ DV ZHOO DV OR- cal characters 7,8_{. The community-based approa-}

ch to injury prevention programs was developed in the 1980s and has since become an essential component of injury prevention 9_{. Community-}

based programs are characterized by collabora- tion among different community sectors and the LQYROYHPHQWRIFRPPXQLW\PHPEHUVWRGH¿QHWKH VDIHW\SUREOHPDQG¿QGVROXWLRQV10, 11_{. Safe Com-}

munity (SC) program aiming to reduce injury and create supportive environment has been operated for the last two decades12_.

The Safe Communities (SC) concept began its formal existence at the First World Conference on Accident and Injury Prevention held in Stoc- kholm, Sweden in September 1989. There are six indicators for International Safe Communities13_.

1. An infrastructure based on partnership and collaborations, governed by a cross- sectional group that is responsible for safety promotion in their community;;

2. Long-term, sustainable programs covering both genders and all ages, environments, and situations;;

3. Programs that target high-risk groups and environments, and programs that promote safety for vulnerable groups;;

4. Programs that document the frequency and causes of injuries;;

5. Evaluation measures to assess their programs, processes and the effects of change;;

6. Ongoing participation in national and international Safe Communities networks.

Safety Community has started in China since early 21 century in Shandong province, named Yo- uth Park Community. So far 35 communities succe- VVIXOO\IXO¿OOHGWKHVL[LQGLFDWRUVDQGEHFDPHWKH member of International Safe Community Network in Mainland China13_{. In China the safe community}

is more likely a kind of top-down model that me- ans the government takes the main responsibility of LQLWLDWLYHSURPRWHFRRUGLQDWHDQGIXQGLQJ7UDI¿F injury has drawn attention of local governments WKDWWKH\ZRXOGOLNHWRUHGXFHWUDI¿FLQMXU\LQWKHLU community through SC movement. The traditional

DSSURDFK RI WUDI¿F LQMXU\ UHSRUWLQJ RQO\ SURYLGHV limited information. So some SC communities try to make use of WHO’s injury surveillance guideli- nes to improve their reporting. This paper is based RQRQHSLRQHHUFRPPXQLW\ZKHUH6&RI¿FHZRUNV FORVHO\ZLWKORFDOSROLFHDXWKRULW\UHJDUGLQJWUDI¿F injury surveillance and prevention.

Objective of the study was to assess the risk IDFWRUVIRUURDGWUDI¿FLQMXULHVDQGWKHUHODWLRQVKLS between the factors and the severity of injury in a designated Safe Community in Shanghai, China.

0DWHULDOVDQGPHWKRGV Data collection

The safe community was situated in Shang- hai, China. Each designated Safe Community has a surveillance system including hospital records, police records and Fire brigade records. In some Safe Communities the stakeholders also perform household surveys. In the current study, data was used from the police records. Data was extracted from the Road Injury Report (RIR) by local police station for a period of one year from 1st January 2008 to 31st December 2008.

:KHQWUDI¿FDFFLGHQWKDSSHQHGWKHUHDUHGLIIH- rent ways to report to local police station including report by people in person, by 110 police hotline, interphone and petrol car et al. Then the police- man will rushed to the event site as soon as possible to take care of the situation. It is required by the municipal police authority that for every road WUDI¿FHYHQWDIRUPVKRXOGEH¿OOHGEXWLWLVYHU\ simple with only limited information about injury. Since this community is carrying out SC experts were invited to develop Road Injury Report (RIR) which guided by the ICECI and ICD10 and com- bine with the original form.

Dependent variables: Severity of injury was the main variable of interest. According to the severity of injured the subjects were divided into three JURXSVZLWKFRGLQJQRLQMXU\ PLQRULQMXU\ DQGVHYHUHLQMXU\GHDWK

Independent variables: Two main factors, in- dividual factors and environmental factors were analyzed as independent variables in order to explore the relationship between the factors and the severity of injury. Environmental factors con-

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tain seven variables: place of accident, whether condition, visibility, road surface, time of a day, region of road and partition. Individual factors include four variables: gender, age, migrated population and transportation mode. Codes for independent variables are shown in table 1.

$OVR YLRODWLRQ RI WUDI¿F UXOH \HVQR DQG causes of road injuries according to police records were considered in the study.

6WDWLVWLFDODQDO\VLV

Pearson Chi-square test was used to determine UHODWLRQEHWZHHQYLRODWLRQRIWUDI¿FUXOHDQGURDG users (driver of motorized/non-motorized vehicle, pedestrian and vehicle occupant). Multivariate logistic regression was used to explore the relationship between severe injuries and all independent environmental and individual variables. Due to a very few numbers of detah register in the system we did not consider death in the regression anal- \VLV$VLJQL¿FDQFHOHYHORIZDVHPSOR\HG

(WKLFDOFRQVLGHUDWLRQ

The study has used secondary data without assessing the identity of the victims. Furthermore,

only the researchers concerned with the study had accessed the data. So anonymity was maintained. For such studies with secondary data, the concerned university had waived for ethical permissions.

5HVXOWV

,QWKHUHZHUHWUDI¿FDFFLGHQWVLQWRWDO in the community in relation to 641 motor vehicles and 1205 individuals. Among which 504 events were reported to police by 110 phone calls which accounted for 88.7%. Five people died on the spot, SHRSOHGLHGDIWHU¿UVWDLGZDVFRQGXFWHGDQG 563 people were injured.

Figure 1 shows the percentage of severity of URDG WUDI¿F LQMXULHV$V WKH VHYHULW\ ZDV GH¿QHG into three groups (no injury, minor injury and severe injury/death), 48% of the cases were without injured, following by mild injured, 43%. Only 9% RIWKHWUDI¿FDFFLGHQWVDFFRXQWHGDVVHYHUHLQMXUL- es and dead.

Among 1205 individuals, involved in the acci- GHQWV YLRODWHG WKH WUDI¿F UXOHV ZKLFK DFFR- unted for 52.45% in total (table 2). The most common violation was drivers of motor vehicle not allowing vehicles or passengers going strai- JKWWRJR¿UVWZKHQLWZDVWXUQLQJDWURDGFRUQHUV Table 1. Independent variables

9DULDEOHV &RGHVIRUYDULDEOHV

(QYLURQPHQWDOIDFWRUV

Place of accidents URDGIRUQRQPRWRUL]HGYHKLFOH

URDGIRUPRWRUL]HGYHKLFOH

Whether condition VXQVKLQH FORXG\UDLQ\

Visibility !P P P

Road surface GU\ ZHWLF\VQRZ\VHHSHU

Time of a day GD\WLPH QLJKW

Region of road VWUDLJKWURDG FURVVLQJURDG

Partition QR SDUWLWLRQEHWZHHQPRWRUL]HGYHKLFOHURDGDQGQRQPRWRUL]HGYHKLFOH

URDG RWKHUV

,QGLYLGXDOIDFWRUV

Gender PDOH IHPDOH

Age !

Migrated population QR \HV

Transportation mode GULYHURIPRWRUL]HGYHKLFOH

GULYHURIQRQPRWRUL]HGYHKLFOH SHGHVWULDQ

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(28.01%). The second one was drivers of motor vehicle had disturbed other moving vehicles (13.92%). The third one was non-motorized vehicles drove on restored road (9.18%). Drivers of motor vehicle had highest percentage in terms of YLRODWLQJWKHWUDI¿FUXOHV3

Figure 1. Distribution of severity of injured 7DEOHUHÀHFWVWKHFDXVHVRILQMXULHVLGHQWL¿- ed by police authority. The leading three causes constituted over 50% of the accidents. ‘When motorized vehicles tuning corners without allowing other vehicles or passengers going straight to go ¿UVW¶ZDVDFFRXQWHGRIDOODFFLGHQWV7RS two cause of injuries was ‘Behavior of drivers of motor vehicles in ways of disturbing other vehicles driving’ (12.67%), followed by ‘Non-motorized vehicles drove in restored road’ (8.62%). ‘Overtaking vehicles when possible to meet the vehicles in other side’ associated lowest number of accidents, sharing 1.23%.

7DEOH&DXVHVRILQMXULHVLGHQWL¿HGE\SROLFHDX- thority

&DXVHV _DFFLGHQWVNo. of 3HUFHQWDJH

When motorized vehicles tuning corners not allow vehicles or passengers going straight to JR¿UVW

171 30.11

Behave of drivers of motor vehicle in ways of disturbing other vehicles driving

72 12.67

Non-motorized vehicles drove

in retrorse road 49 8.62

Drivers of motor vehicle not

IROORZWKHWUDI¿FOLJKW 34 5.99

The short distance between

two vehicles 33 5.81

Others 28 4.93

When turning round disturbing

other vehicles and pedestrians 20 3.52

When changing lanes distur-

bing other vehicles 15 2.64

When non-motorized vehicles tuning corners not allow vehicles or passengers going straight WRJR¿UVW

15 2.64

Inappropriate control of acce-

lerograph 15 2.64

When non-motorized vehicles overtaking other vehicles disturbing other vehicles moving

13 2.29

Drivers of non-motorized ve- KLFOHVQRWIROORZLQJWKHWUDI¿F light

11 1.94

Motorized vehicles moving in

retrorse road 10 1.76

Motorized vehicles moving in

non-motorized vehicles road 8 1.41

Overtaking vehicles when possible to meet the vehicles in other side

7 1.23

7DEOH&RPSDULVRQRIGLIIHUHQWWUDQVSRUWDWLRQUHJDUGLQJYLRODWLQJRIWUDI¿FUXOHV

7UDI¿FUXOHV 'ULYHURI09 'ULYHURI109 3HGHVWULDQ 9HKLFOHRFFXSDQW

1XPEHU 1XPEHU 1XPEHU 1XPEHU

No violation 186(32.46) 303(52.88) 24(4.19) 60(10.47)

Violation 470(74.37) 145(22.94) 17(2.69) 0(0.00)

Total 656(54.44) 448(37.18) 41(3.40) 60(4.98)

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Table 4 shows the association between factors DQG VHYHULW\ RI LQMXU\ 7KHUH DUH QR VLJQL¿FDQW differences within environmental factors, except road for motorized vehicle and weather condition (p < 0.05). In the individual level factors, gender KDV QR VLJQL¿FDQW UROH RQ URDG WUDI¿F LQMXULHV LQ the study. Contrarily, age over forty, migrated po- SXODWLRQDQGWUDQVSRUWDWLRQPRGHVUHÀHFWVLJQL¿- cant relation with severe road injuries. At the environment level factors, road for motorized vehicles DQG UDLQ\FORXG\ ZHDWKHU KDYH VLJQL¿FDQW HIIHFW on road accidents.

'LVFXVVLRQ

This study researched the risk factors of road WUDI¿FLQMXULHVDQGWKHUHODWLRQVKLSZLWKWKHVHYH- rity of injury in a designated Safety Community in Shanghai, China. Age over 45 years, migrated population, transportation mode, road condition DQGZHDWKHUFRQGLWLRQZHUHUHYHDOHGDVVLJQL¿FDQW ULVNIDFWRUIRUVHYHUHURDGWUDI¿FLQMXULHV

Over 50% of people involved into road accidents suffered from injuries suggest that road accidents are highly related with injuries which is higher than the rate in general2_{. The drivers had}

KLJKSHUFHQWDJHRIYLRODWLQJWKHWUDI¿FODZ)URP WKH WRS FDXVHV LGHQWL¿HG E\ SROLFH DXWKRULW\ there were 12 items related to behaviors of the drivers of motorized vehicles, accounting for about 80.31% of total. This indicates that it is necessary WRSURPRWHURDGVDIHW\DQGWUDI¿FUXOHVWRWKHSX- blic. Furthermore, drivers of motorized vehicles should be the key target population. A research investigated 1340 drivers about their unsafe driving behaviors for the last one month showed that the frequency of unsafe driving behaviors in rural areas was much higher than in urban areas and the number in male was much higher than female. Driving without seatbelt, drink diving, fatigue driving and driving without licenses were the main causes of injuries 14_{. Through SC program, data}

Table 4. Multivariate logistic regression analysis 2GGV5DWLRV &, Personal factors Gender Male (968) 1.0 Female (237) 0.928(0.667 - 1.290) $JH < 25 (148) 1.0 25-45 (828) 0.968(0.656 1.427) > 45 (229) 1.613(1.003 - 2.595)* )ORDWLQJSRSXODWLRQ No (704) 1.0 Yes (501) 1.897(1.349 - 2.666)*** 7UDQVSRUWDWLRQPRGH

Driver of motorized vehicle

(656) 1.0

Driver of non-motorized vehicle (448) 14.318 (9.696 - 21.143)*** Pedestrian (41) _{(25.538 - 110.675)***}53.164 Vehicle occupant (60) _{(22.642 - 79.332)***}42.382 Environmental factors 3ODFHRIDFFLGHQWV

Road for non-motorized

vehicle (348) 1.0

Road for motorized vehicle (857) 3.021 (2.139 - 4.267)*** :HDWKHUFRQGLWLRQ Sunshine (859) 1.0 Cloudy/rainy (346) 1.445(1.009 - 2.071)* 9LVLELOLW\ > 200m (272) 1.0 100-200m (548) 1.065(0.766 - 1.481) <100m (385) 0.753(0.496 - 1.144) 5RDGVXUIDFH Dry (996) 1.0 Wet/icy/snowy/sleeper (209) 0.762(0.498 - 1.164)

Time of a day

Day time (873) 1.0 Night (332) 1.093(0.773-1.546) 5HJLRQRIURDG Straight road (690) 1.0 Crossing road (515) 1.186(0.893 - 1.576) 3DUWLWLRQ No (336) 1.0

Partition between motorized vehicle road and non- motorized vehicle road (32)

1.097(0.499 - 2.413)

Others (837) 0.972(0.718 - 1.314)

The contrast category was denoted by OR =1.0. *p<0.001, **p<0.005, *** p<0.010

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would be shown to them to demonstrate that how WUDI¿FLQMXU\KDSSHQHGZKDWWKH\FDQGRWRSUH- vent it. Also, let them imagine if they can change their behavior how many lives will be saved and how many people will not suffer from injury any more. Additionally, law enforcement can be en- hanced strongly by the governmental administra- tion. Punishment would be a good way to lead the GULYHUVWRREH\WKHWUDI¿FVDIHW\ODZ

Most of environmental factors were not the PDLQUHDVRQIRUWKHURDGWUDI¿FLQMXULHVDVUHÀHF- ted by the logistic regression analysis with no si- JQL¿FDQWLQÀXHQFH+RZHYHUURDGIRUPRWRUL]HG vehicle was the risk place. Cloudy and rainy weather condition would affect the severity of injury GLVWLQFWO\6RLQJHQHUDOWKHURDGWUDI¿FLQMXULHVDUH PDLQO\ LQÀXHQFHG E\ LQGLYLGXDO IDFWRUV 7KH UH- sults of logistic regression analysis represents that WKHULVN\SRSXODWLRQVIRUURDGWUDI¿FLQMXULHVDUH migrated people who come to Shanghai from rural areas. Drivers of non-motorized vehicles, pedestrians and vehicle occupants are also in the risk of road injuries. On the other hand, some previous researches reported that most of the injured people were male, aged between 21 - 45 years, with an increasing proportion of people aged over 60. The majority of the victims were passengers, mo- torcyclists and pedestrians. Road accidents mainly occurred at night between 19- 20 pm being peak hours, and most deaths occurred at 3- 5am. Road WUDI¿FLQMXULHVZHUHFDXVHGPRVWO\E\PRWRUYH- hicles, mainly passenger cars, motorcycles and vans. Electric bicycles were the main type of non- PRWRU WUDI¿F YHKLFOHV WKDW FDXVHG FUDVKHV 7KH crashes and casualties showed an upward trend every year. RTIs crashes caused by motor vehicle GULYLQJZHUHGXHWRODZYLRODWLRQV7KH¿YHOHD- ding causes of RTI crashes were: over speed, not giving way as required, driving without license, retrograde driving and alcoholic driving15-18_{. Safe}

Community can promote road safety education to the high risk population. Work places, scho- ols, residential committees can be targeted by the Safe Community programs to improve the risky people’s knowledge and to correct their attitudes and road using behaviors. Construction compani- es where most of the migrated population works should also be targeted to improve their awareness of road safety and to improve their road safety

behavior. In addition, organizations which are responsible for management of car parking at resi- GHQWLDODUHDVVKRXOGEHWDUJHWHGWR¿JXUHRXWPRUH effective way to promote road safety.

Limitation of this study: The study has consi- dered only FDXVHVRIWUDI¿FLQMXULHVGH¿QHGE\ police authority. They can help to explore the risk IDFWRUVRIWUDI¿FLQMXULHVKRZHYHUZLWKDQRSHQHQG questionnaire study can provide us many more risk factors of road injuries. The study is a secondary GDWDDQDO\VLV$¿UVWKDQGLQYHVWLJDWLRQFDQSURYLGH XVPRUHDFFXUDWHUHVHDUFKEDVH7UDI¿FUXOHYLRODWL- on should be more wide studied in absence of such information for the researchers and policy makers. It should be investigated to better understand the DFWXDOFDXVHRIVXFKWUDI¿FUXOHYLRODWLRQ

&RQFOXVLRQ

During renovation of community road the local government should consider the results and sugge- stions from this kind of study. The roads should be prepared for and/or awareness should be provided to the drivers that cloudy or rainy weather conditions are dangerous for the road occupants. Drivers of motorized vehicles are mostly the violator of the WUDI¿F UXOHV 7KHUHIRUH 6DIH &RPPXQLW\ VKRXOG VSHFL¿FDOO\ HPSKDVL]H VWUDWHJLHV IRU WKH PLJUDWHG people, drivers of motorized vehicles, pedestrians and vehicle occupant. Also the study suggests that ORFDODUHDEDVHGVWXGLHVDUHLPSRUWDQWWRVSHFL¿FDOO\ VHWWLQJWKHWUDI¿FLQMXU\SUHYHQWLRQDFWLYLWLHV,QMXU\ surveillance at the local level is very important to decide the priority interventions 19.

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World Health organization, 2008.

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Corresponding author Shu-Mei Wang,

School of Public Health,

“Key Laboratory of Public Health Safety, Ministry of Education”,

Fudan University, Shanghai,

China,

Road Traffic Injuries in Shanghai, China

5RDG7UDI¿F,QMXULHVLQ6KDQJKDL&KLQD

5RDG7UDI¿F,QMXULHVLQ6KDQJKDL&KLQD