BICYCLE CRASHES IN ADULTS 45+ CONVENTIONAL & EAB Bas de Geus, Jelle Van Cauwenberg, Paul Schepers, Mathieu Vanderroost & Jelle Van Hemelryck CYCLING AND SOCIETY, BRISTOL 6-7/09/2018
Introduction
CYCLING Cycling is a form of Active transport Health benefits (Oja, 2011) Economic & environmental advantages (Mueller, 2015; Woodcock, 2008) 07-09-18 3
OLDER ADULTS & CYCLING Bicycles are commonly used as means of transport by older adults (65+) (Van Cauwenberg, 2018) This tendency will continue à electrically assisted bicycles (EAB limited to 250 Watt) 07-09-18 4
OLDER ADULTS & CYCLING FACT CHECK Older adults à most severe injuries and higher risk (Feleke, 2018) Limited number of studies focused on older adults (55+) (Vanparijs, 2015) Even less studies on combination older adults (65+) + EAB 07-09-18 5
EXPOSURE Exposure: frequency, distance and/or time cycled Only few studies measure & include exposure Exposure = crucial for calculation of risks & incidence rates (Vanparijs, 2015) 07-09-18 6
PURPOSE Characteristics conventional vs EAB users (+45 years) Determine factors that increase likelihood of a bicycle crash Include exposure to calculate the risk of having a crash (conventional vs EAB) 07-09-18 7
Methods
STUDY DESIGN Retrospective Cross-sectional Self-reported Online and Paper&pencil Survey 07-09-18 9
INCLUSION & EXCLUSION Participants Dutch speaking male/female Living in Flanders or the Netherlands Aged +45 years 07-09-18 10
INCLUSION & EXCLUSION Bicycle crash? Collision or fall Potentially associated with physical or material damage Crashes during bike races excluded 07-09-18 11
PARTICIPANTS RECRUITMENT Panel of the National Foundation for Elderly (the Netherlands) Online or paper&pencil version of the survey Flemish Senior Council, Fietsersbond and Fietsberaad (Flanders) Online or telephone interview DATA COLLECTION Ø Data collection: 1 June 2017 31 August 2017 07-09-18 12
MEASURES SOCIO-DEMOGRAPHIC CHARACTERISTICS Age Gender (Former) main occupation Educational level Marital status Body Mass Index (BMI) Perceived health 07-09-18 13
MEASURES QUESTIONNAIRE Crash characteristics Experiences while cycling: 9 questions were clustered into: Mental Strength and functionality Limitations during activities of daily living (ADL) Life space area Medication usage 07-09-18 14
MEASURES EXPOSURE Bicycle exposure for conventional bike & EAB: preceding 12 months # trips Never <1 day / month 1-3 days / month 1-2 days / week 3-4 days / week 5-7 days / week Spring Summer Fall Winter 07-09-18 15
STATISTICAL ANALYSIS IBM SPSS 25.0 & Microsoft Excel Socio-demographic - & crash characteristics à Descriptive statistics Socio-demographics (3 groups) Crash characteristics (2 groups) 07-09-18 16
STATISTICAL ANALYSIS Examine crash likelihood à Logistic regression models Conventional & EAB separately Dependent variable: crash / no crash (dichotomous) Independent variable: Characteristics (age, gender, BMI and perceived health) Limitations in ADL Life area displacement Medication usage Experiences while cycling 07-09-18 17
STATISTICAL ANALYSIS Logistic regression analyses Step 1: Logistic regression with 1 independent variable and exposure as covariate Step 2: Logistic regression with all significant independent variables from step 1 and exposure as covariate 07-09-18 18
Results & Discussion
DIFFERENCES IN CHARACTERISTICS BETWEEN EAB & CONVENTIONAL 07-09-18 20
DIFFERENCES IN CHARACTERISTICS BETWEEN EAB & CONVENTIONAL Schepers (2014) It is plausible that EAB users exhibit characteristics and behaviour that influences their crash likelihood. Vlakveld (2015) EAB cyclists might have a poorer physical state than conventional cyclists. è Our findings confirm previous hypotheses 07-09-18 21
DIFFERENCES IN CHARACTERISTICS BETWEEN EAB & CONVENTIONAL CRASH CHARACTERISTICS Crash cause EAB Conventional 5% 3% 4% During cycling During cycling 31% 40% Collisions other bicycles or pedestrians Falls during mounting/dismounting Collisions motorized vehicle Other 27% 44% Collisions other bicycles or pedestrians Falls during mounting/dismounting Collisions motorized vehicle 21% 13% 12% Other 07-09-18 22
DIFFERENCES IN CHARACTERISTICS BETWEEN EAB & CONVENTIONAL CRASH CHARACTERISTICS Falls when (dis)mounting more than two times more frequent in EAB group à Corresponds with Schepers (2014) Why? EAB +/- 10 kilo heavier (Vlakveld, 2015) EAB cyclist: older and poorer physical condition (Vlakveld, 2015) Falls while (dis)mounting à typical crash type for older adults (75+) (BoeleVos, 2016) 07-09-18 23
DIFFERENCES IN CHARACTERISTICS BETWEEN EAB & CONVENTIONAL EXPOSURE No significant difference in #trips between EAB and conventional group (p=0.166) No significant difference in #trips between men and women in EAB group (p=0.316) No significant difference in #trips between men and women in conventional group (p=0.539) è Significant differences might be present in distance and time. 07-09-18 24
INCIDENCE RATES EAB: 291 participants 102 crashes (40.1% of all crashes) Conventional: 952 participants 150 crashes (58.5% of all crashes) Combination: 317 participants Type Incidence rate (95% CI) (per 1000 trips) Overall 0.937 (95% CI 0.824 1.051) Conventional - MEN 0.856 (95% CI 0.673 1.038) Conventional - WOMEN 0.701 (95% CI 0.534 0.868) EAB - MEN 0.883 (95% CI 0.582 1.185) EAB - WOMEN 1.489 (95% CI 1.145 1.833) 07-09-18 25
CRASH LIKELIHOOD PREDICTION FINAL BINARY LOGISTIC REGRESSION Poor strength & functionality beliefs and experiences à main argument for cyclists to choose for an EAB (Vlakveld, 2015; Scheiman, 2010) Our questionnaire à Screening tool? 07-09-18 26
Limitations
DISCUSSION STUDY LIMITATIONS Overrepresentation of well-educated participants Recall bias à retrospective design Selection bias à organizations and snowball sampling No amount of kilometres or time spent cycling 07-09-18 28
Conclusion
CONCLUSION Different characteristics between EAB & conventional bike users EAB à older and less physical fitness Main cause of crash: For both types: during cycling EAB: falls during mounting & dismounting Conventional bicycle: collision with motorised vehicle Incidence rate is highest for women on EAB Mental and Strength&Functionality increase the likelihood of crashes 07-09-18 30
Thank you for your attention de Geus B.1,2, Van Cauwenberg J.3, Schepers P.4, Vanderroost M., Van Hemelryck J. 1 Human Physiology Research Group, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium ² Mobility, Logistics and Automotive Technology Research Centre (MOBI), Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium 3 Department of Public Health, Ghent University, Belgium 4 Department of Human Geography and Spatial Planning, Faculty of Geosciences, Utrecht University, The Netherlands Corresponding author: prof dr Bas de Geus [E] bas.de.geus@vub.be 07-09-18 31 [W] www.blits.org
APPENDIX B FLOW CHART 07-09-18 32
APPENDIX A INTRACLASS CORRELATION Clustering à Mental, Strength & Functionality, Limitations during activities of daily living Two way ICC > 0.70 p < 0.05 07-09-18 33
APPENDIX C COLLINEARITY ANALYSIS Collinearity analysis (Field, 2009) Tolerance < 0.1 and/or VIF > 10.0 à Multicollinearity 07-09-18 34
LOGISTIC REGRESSION STEP 1 - EAB
LOGISTIC REGRESSION STEP 1 - CONVENTIONAL
EXPOSURE VRAGENLIJST 07-09-18 37
EXPERIENCES WHILE CYCLING Q19
SCHOLING Q3BIS 07-09-18 39