V. Martínez Ruiz, E. Jiménez Mejías, C. Amezcua Prieto, J.D. Luna del Castillo, P. Lardelli Claret, J.J. Jiménez Moleón

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1 V. Martínez Ruiz, E. Jiménez Mejías, C. Amezcua Prieto, J.D. Luna del Castillo, P. Lardelli Claret, J.J. Jiménez Moleón Department of Preventive Medicine and Public Health University of Granada No conflict of interest exist in this work

2 BACKGROUND AND OBJECTIVES Cyclists: vulnerable users of road Promotion of bicycle use as urban mobility solution (by State, regions, cities ) 1. Economic crisis: rising cost of fossil fuel 2. Reducing traffic congestion in the urban centre 3. Physical activity promotion in populations increasingly sedentary 4. Growing environmental consciousness. (Barómetro anual de la bicicleta, DGT) 2

3 BACKGROUND AND OBJECTIVES % fatalities by mode in the EU 7.37% Tractor Bus/Coach Private car + Taxi Truck >3500 kg Truck <3500 kg Moped Motorcycle Bicycle Pedestrian % fatalities by mode in the EU, urban area 10.74% (CARE, 2012) % fatalities corresponding to cyclists in different countries vs. % modal bicycle share 35% 30% 25% 20% 15% 10% 5% 0% (OMS, 2013) 3

4 BACKGROUND AND OBJECTIVES SINGLE CRASH MULTIPLE ACCIDENT Risk factors depending on the type of accident (single vs. multiple) Risk factors associated with the driver of the other vehicle Risk factors adjusting on exposure 4

5 BACKGROUND AND OBJECTIVES EXPOSURE: Why is important to take it into account? Example: He usually rides 2 hours every day She rides 30 minutes over weekend He is more likely to have an accident, just because he rides more Exposure = number of km, time traveled 5

6 BACKGROUND AND OBJECTIVES Identifying and quantifying RISK FACTORS: relatives to the cyclist and his bicycle associated with a single-bicycle crash. relatives to the cyclist and his bicycle associated with the risk of provoking a collision with a motorized vehicle. relatives to a driver of a motorized vehicle associated with provoking a collision with a cyclist. 6

7 METHODS POPULATION STUDIED cyclists involved in road crashes in Spain ( ) Spanish Register of Traffic Accidents with Victims (Traffic General Directorate) = Police data Biased: most serious crashes, mostly collisions Only accident data available No exposure data (distance or time traveled) problem Possible solution QUASI-INDUCED EXPOSURE METHOD 7

8 METHODS QUASI-INDUCED EXPOSURE METHOD Conceived for 4-wheel motorized vehicles Thorpe, Traffic Safety Res Rev Indirect method not real data of exposure, based on: -assessment of responsibility -comparison of responsible vs non-responsible drivers ASSUMPTION: non-responsible drivers characteristics would resemble those of all drivers on the road representative sample The probability of being at the scene of the crash is not related to the crash, but only with the probability of being there by chance. 8

9 METHODS QUASI-INDUCED EXPOSURE METHOD Police register Recorded information about infractions Cyclist Motorized driver Responsible cyclists infractor cyclists Responsible drivers infractor drivers 9

10 METHODS Types of crashes cyclists Other types of traffic accidents drivers of motorized vehicles - Assessment of infraction (by cyclists and by other drivers) - Exclusion of accidents without information 2 datasets were created 10

11 METHODS Dataset-1 (studying collisions): collisions bicycle-vehicle; only one of them committed an infraction (clean collisions) -Non-infractor cyclists involved in clean collisions (9713) = ref. group -Infractor cyclists involved in clean collisions (9294) Dataset-2 (studying single crashes): cyclists in 3 groups - Non-infractor cyclists involved in clean collisions (9713) = ref. group - Non-infractor cyclists involved in single crashes (1322) - Infractor cyclists involved in single crashes (2505) QUASI-INDUCED EXPOSURE METHOD Non-infractor cyclists involved in a collision Representative sample of the road cyclist population and its level of exposure. 11

12 METHODS STUDY VARIABLES Outcome variable (Y) Dataset-1: studying collisions Dataset-2: studying single crashes Y= infractor driver 1: the cyclist 0: the other driver (the cyclists is non-infractor = ref. group) Y= considered subgroup of cyclists 0: non-infractor cyclists involved in clean collisions (ref.group) 1: non-infractor cyclists involved in single crashes 2: infractor cyclists involved in single crashes Dataset-1 Explicative variables (X) Dataset-2 1. Variables referring to the cyclist / the driver of the other vehicle 2. Variables referring to the bicycle / the other vehicle 1. Variables referring to the cyclist 2. Variables referring to the bicycle 3. Environmental variables 3. Environmental variables 12

13 METHODS ANALYSIS QUASI-INDUCED EXPOSURE METHOD 2.1. Multiple imputation Missing information: 66.7% records Dataset % records Dataset-2 Chained equations method 2.2. Analysis of Dataset-1 Logistic regression analysis (Y = 0, 1) Risk factors for being responsible for the collision 2.3. Analysis of Dataset-2 Multinomial regression (Y = 0, 1, 2) Risk factors for single crashes 13

14 RESULTS AND DISCUSSION Multivariate analysis - Adjusted on other variables: age, sex, urban or rural area, hour, type of day, month, year, visibility conditions, surface, weather, light conditions. OR = odds ratio - OR < 1 protective effect - OR > 1 risk factor 14

15 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH SINGLE CRASHES BEING A WOMAN Reference: Male Tin Tin, 2010 Johnson, 2011 Infractor cyclist Non-infractor cyclist 15

16 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH SINGLE CRASHES AGE Reference: years old Infractor cyclist Non-infractor cyclist Maring,

17 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH SINGLE CRASHES PSYCHOPHYSICAL CIRCUMSTANCES Referencia: None Andersson, Infractor cyclist Non-infractor cyclist 17

18 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH SINGLE CRASHES NON-HELMET USE Reference: Wearing helmet Crocker, Infractor cyclist Non-infractor cyclist 18

19 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH SINGLE CRASHES HOURS CYCLING WITHOUT RESTING Reference: <1 hour Infractor cyclist Non-infractor cyclist 19

20 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH SINGLE CRASHES BICYCLE DEFECTS Reference: None Infractor cyclist Non-infractor cyclist 20

21 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH SINGLE CRASHES TWO OCCUPANTS RIDING Reference: One occupant Infractor cyclist Non-infractor cyclist 21

22 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH COLLISIONS AGE RESPONSIBILITY IN THE ACCIDENT Reference: years old Reference: years old Infractor cyclist Infractor driver 22

23 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH COLLISIONS BEING A WOMAN ALCOHOL/ DRUGS CONSUMPTION NON-HELMET USE 10 Reference: Male Reference: No Reference:Wearing helmet 4.45 Infractor cyclist

24 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH COLLISIONS BICYCLE DEFECTS Reference: None TWO OCCUPANTS RIDING Reference: One occupant Infractor cyclist

25 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH COLLISIONS TYPE OF MANEUVER Reference: Travelling with the direction of traffic Infractor cyclist

26 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH COLLISIONS ALCOHOL/DRUGS CONSUMPTION NON-USE OF SAFETY DEVICES BEING A PROFESSIONAL DRIVER Reference: No Reference: Yes Reference: Nonprofessional Infractor driver

27 RESULTS AND DISCUSSION FACTORS ASSOCIATED WITH COLLISIONS TYPE OF VEHICLE Reference: Private car 10 Infractor driver

28 CONCLUSIONS FACTORS ASSOCIATED TO SINGLE CRASH Responsibility in a single crash was higher for: male cyclists riding under alcohol/drugs brake deffects extra occupant For non-infractor cyclists: sudden illness For infractor cyclists: non-helmet use year-old. 28

29 CONCLUSIONS RISK OF CAUSING A COLLISION 1. For cyclists male sex age <20 years old alcohol/drugs consumption non-helmet use brake or light defects on their bicycle. 2. For drivers of the other vehicle age >60 years old alcohol/drugs not using safety devices driving a moped 29

30 RESULTS AND DISCUSSION LIMITATIONS REFERRING TO THE METHOD Infractor = Responsible Non infractor cyclists = Representative sample of the entire cyclist population REFERRING TO THE DATABASE High underreporting Severity of the accident Information recorded is incomplete multiple imputation 30

31 THANKS FOR YOUR ATTENTION Accid Anal Prev 2013; 51: Department of Preventive Medicine and Public Health, University of Granada, Spain 31

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