Active mobility and health:

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1 Active mobility and health: Insights from the PASTA project Evi Dons, VITO, Belgium Thomas Götschi, UZH, Switzerland on behalf of the PASTA consortium This project has received funding from the European Union s Seventh Framework Programme for research; technological development and demonstration under grant agreement no

2 A Broadband Project on Active Travel and Health HEALTH : Social innovation for health promotion. FP7-HEALTH-2013-INNOVATION-1. EU research should aim to identify, develop and better understand innovative approaches to reduce sedentary behaviour and enhance the level of physical activity in the population. Research should include the evaluation of innovative on-going initiatives that reduce sedentary behaviour, enhance the level of physical activity combined with dietary or other interventions. In this context, research should include the identification of "good practices", as well as the analysis of their economic and social benefits and impact. Correlates will have to be detected (such as cultural, environmental, economic, psychological and others) that inhibit or promote the individuals capacity to increase physical activity, reduce sedentary behaviour and self-regulate their dietary or other relevant behaviour. Research may cover various areas affecting lifestyle (e.g. sports, health, education, transport, urban planning, working environment, leisure) as well as different intervention levels (local, national, European). As a social innovation it should address the role of diverse public and private entities, such as business, including social enterprises, civil society organisations and public authorities, as well as their interaction. The views of potential end-users should be integrated in the design of the project as well as the methodology for assessing impact and outcomes throughout the project. The project should have a strong communication strategy.

Judging from footprints discovered on a former shore in Kenya, it is thought possible that

3 FP7 Call Title: Social Innovation for Health Promotion What could possibly be innovative about walking and biking? Judging from footprints discovered on a former shore in Kenya, it is thought possible that ancestors of modern humans were walking in ways very similar to the present activity as many as 1.5 million years ago. Bicycles were introduced in the 19th century in Europe.

4 Background What s our starting point? Götschi-ICTH

5 Health Associated with Active Travel in the Course of Life

6 Individual vs. Public Health Perspective Individual perspective How healthy or unhealthy (risky) is AT? Public health perspective What is it worth to society?

7 The Role of Public Health in the Promotion of Active Travel 1 Fixed Factors (e.g., topography, weather, 2 demographics) 3 1 Modifiable Factors (e.g., land use, road design, socioeconomics, attit udes) Active travel (surveys, diary, app) Health impacts (benefits and risks) 1 Policies, measures (infrastructure investments, campaigns) 1. Determinants 2. Behaviour 3. Impacts Adapted from Moving Active Transportation to Higher Grounds Conference, Washington DC, April 2015

8 The Role of Individual Health in Active Travel Behavior 1 Fixed Factors (e.g., topography, weather, de 2 mographics) Modifiable Factors (e.g., land use, road design, socioeconomics, attit udes) Policies, measures (infrastructure investments, campaigns) Active Travel (surveys, diary, app) Individual Motivation Health Impacts (benefits and risks) Short term Long term 1. Determinants 2. Behaviour 3. Impacts Adapted from Moving Active Transportation to Higher Grounds Conference, Washington DC, April 2015

10 Literature Review (quasi systematic) Found 26 «new and conceptual» frameworks. Identified common and unique features. Integrated in a single diagram.

11 Götschi, T., de Nazelle, A., Brand, C., Gerike, R., & PASTA Consortium. (2017). Towards a Comprehensive Conceptual Framework of Active Travel Behavior: a Review and Synthesis of Published Frameworks. Current Environmental Health Reports, 1-10.

12 Götschi, T., de Nazelle, A., Brand, C., Gerike, R., & PASTA Consortium. (2017). Towards a Comprehensive Conceptual Framework of Active Travel Behavior: a Review and Synthesis of Published Frameworks. Current Environmental Health Reports, Götschi-Velocity 2017

13 Known Determinants of Active Mobility Rationale factors (mode choice) Distance, duration, purpose Psychological factors Attitudes, TPB, etc. Geographical factors Topography, neighborhood, routes Time factors Weather, time of day, day of week Safety Perceived and objective

14 Description and Classification of Active Mobility Measures Literature review and assessment of state-of-theart of AM WP1 (PASTA - Deliverable D1.1) Policies to increase walking and cycling, Design of urban environment, Residential densities, Mixed land use, Bikeability, Walkability, Infrastructure, street connectivity, facility provision, Slope, Weather, Travel time / distance, Effort, Perceived safety, Safety, (Motorised) traffic speeds, Higher volume vehicles, Traffic calming, Cycle tracks, Large vehicles, Compulsory bicycle helmets, Safety in numbers, Social norm, Normalisation of active mobility, Social support, Socio-economic factors generally, Age, seniors, Age, children, No access to car, Car ownership, Physical ability, Ethnic groups, Lower income, Higher income, Higher socioeconomic position and not owning a motor vehicle, Low socio-economic status areas, Educational level, Area- and individual-level income, Dog ownership, Costs of other modes Authors: The primary authors are: Clark, Anna; Eriksson, Ulf; Witzell, Jacob (Trivector Traffic) With text input from: Brand,Christian (University of Oxford) Götschi, Thomas; Kahlmeier, Sonja (University of Zurich) Dons, Evi; Int Panis, Luc (VITO) Gerike, Regine (TU Dresden) Anaya, Esther; De Nazelle, Audrey (Imperial College London) Rojas Rueda, David; Thomas ColeHunter (CREAL) Uhlmann, Tina; Wegener, Sandra (BOKU) All of the PASTA consortium have been involved in this work Project internal reviewer: Boschetti, Florinda (Polis)

Review of Reviews: Measures to Promote Active Mobility http://activelivingresearch.

Moving Toward Active Transportation: How Policies Can Encourage Walking and

activelivingresearch.org Winters, Meghan, Ralph Buehler, and Thomas Götschi.

15 Review of Reviews: Measures to Promote Active Mobility Buehler, R, Götschi, T, Winters, M. Moving Toward Active Transportation: How Policies Can Encourage Walking and Bicycling. San Diego, CA: Active Living Research; Available at Winters, Meghan, Ralph Buehler, and Thomas Götschi. "Policies to promote active travel: evidence from reviews of the literature." Current environmental health reports (2017): 1-8.

17 Seven Case-study Cities 12% Oerebro 54% 25% 9% Walking Cycling Public Transport Private motorised London / Newham 31% 24% 42% 3% Zurich 20% 41% 23% 16% Antwerp 36% 26% 4% 34% 29% 28% 37% 6% Vienna Barcelona 35% 46% 54% 16% 1% 29% Rome 18% 1%

PASTA Research Objectives What are the determinants of active travel?

What is the interrelation between active travel and physical activity?

Context Individual Impacts Physical environment Transport options Built enviroment Natural

and work loccation Socio-geographical factors Neighborhood perceptions Perception of travel

18 PASTA Research Objectives What are the determinants of active travel? What are effective measures to promote active travel? What is the interrelation between active travel and physical activity? What are the health impacts of active travel? Context Individual Impacts Physical environment Transport options Built enviroment Natural enviroment Social Environment Planning practice Individual characteristics Sociodemographics Home and work loccation Socio-geographical factors Neighborhood perceptions Perception of travel choices Trips Travel choices Socio-psychological factors Extended theory of planned behaviour Physical activity Travel behaviour Safety incidents Health benefits from PA Environmental impacts Health risks from AP Injury risks from travel Net health impacts

19 Study design, methods and tools

20 Online Survey

21 Longitudinal Online Survey Before/after, trend evaluation Active travel and physical activity vary in time Lots of questions to ask Participant burden Baseline Q Socio-d. Commute route Health status GPAQ Mobility scale Travel D Psychology Top measure FU short Mobility scale PA single item Crash-q Crash Q (only in case of crash or near-miss) FU short FU long GPAQ Travel-D Crash-q FU short FU short

22 Rolling recruitment, hibernation for participants affected by top measures

23 Health and Air Pollution Add-on Real-life study design 40 healthy adults / city (Antwerp, London, Barcelona) 1 week, 3 seasons Personal exposure to black carbon, GPS, Sensewear, ExpoApp, Zephyr bioharness Health parameters: HRV, blood pressure, fundus photography, eno, spirometry Zephyr Bioharness Blood pressure Retinal pictures Concentrations eno Lung inflammation Spirometry Lung function

24 Tracking Add-on: PASTA on the Move 546 participants were followed for up to 6 months using the commercial smartphone application Moves ( track journeys and automatically detect travel modes 29 April January

25 Tracking add-on: PASTA on the Move Participants per city 16% 13% 10% 19% 24% 12% 6% Antwerpen Barcelona London Örebro Roma Wien Zürich City n % Antwerp Barcelona London Oerebro Rome Vienna Zurich TOTAL

26 Sample Description Who are the PASTA participants?

27 Recruitment Progress over Time 12,825 registrations

28 How did participants find out about the survey? 18% 8% 22% 22% 13% 12% Work Word of mouth Other organisations Outreach activities News Social media Public notice Random sampling

29 Sample description 54% 46% 12% 14% 16% Participants by city 17% 12% 15% 14% Antwerp Barcelona London Oerebro Rome Vienna Zurich

30 Distribution across Cities Number of registrations Number of people who started baseline questionnaire Number of people who finalized baseline questionnaire Registrations n = 12,825 People started baseline n = 10,691 People finalized baseline n = 8, Antwerp Barcelona London Örebro Rome Vienna Zurich

31 Participants, Questionnaires

32 How Representative is the PASTA Sample? (age) Antwerp City Census PASTA Barcelona City Census Barcelona PASTA Barcelona Delta London City Census London PASTA London Delta Oerebro City Census Oerebro PASTA Oerebro Delta Rome City Census Rome PASTA Rome Delta Vienna City Census Vienna PASTA Vienna Delta Zurich City Census Zurich PASTA Zurich Delta

33 Travel Data Understanding travel patterns and their determinants

34 Oversampling of Cyclists 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% PAST A official PAST A official PAST A official PAST A official Antwerp Barcelona London Oerebro Rome Vienna Zurich Walking 11% 20% 38% 46% 29% 24% 13% 12% 16% 16% 24% 28% 22% 27% Cycling 54% 23% 17% 1% 24% 3% 36% 25% 22% 1% 27% 6% 24% 4% Car 28% 41% 17% 35% 12% 31% 46% 54% 32% 54% 14% 27% 13% 30% PT 7% 16% 28% 18% 34% 42% 5% 9% 29% 29% 34% 39% 40% 39% PAST A official PAST A official PAST A official

35 number of participants Gender Split in Cycling Contrasts in active transport behaviour across four countries: How do they translate into public health benefits? Götschi et al non cycl - ist cycl ist non cycl - ist cycl ist non cycl - ist cycl ist non cycl - ist cycl ist Antwerp Barcelona London Oerebro Rome Vienna Zurich 50, 49, 49, 59, 46, 63, 58, 59, 22, 39, 39, 56, 47, 58, 49, 50, 50, 40, 54, 36, 41, 40, 77, 60, 60, 43, 52, 41, cycl ist non - cycl ist cycl ist non - cycl ist cycl ist non - cycl ist Cyclist: 54.5% 45.5% Non-cyclist: 45.4% 54.6% N = 5,650

36 Cycling as a Mode of Transport 77% think that it saves time 57% find it comfortable 23% consider it safe with regards to the risk of traffic

37 Health Attitude: Does it matter? Cycling for travel offers personal health benefits : 92% agree Very much agree bike 4 minutes more than very much disagree Health is a criterion when choosing mode of transport Very much agree bike 20 minutes (+ 30%) more than very much disagree (72 min vs. 55 min/day) Götschi-ICTH

38 Electric-assist Bikes (E-bikes/Pedelecs) E-bikers tend to be heavier than conventional cyclists E-bikers travel longer distances E-bikers achieve similar levels of physical activity as conventional cyclists Distance covered by e-bikes vs. non-electric bikes E-biking is a valuable source of physical activity, in particular for older people who benefit even more from physical activity. Distance per day (km) Distance per trip (km) Non-electric bike E-bike 5.1

39 Infrastructure Evaluation What is the effectiveness of specific infrastructures?

40 London Case Study: Spatial analysis of cycling infrastructures Exposure = affected population within buffers Dose response analysis = multiple exposures (quantity) and quality of interventions.

41 Behaviour Change Model (Stages of Change Diagnosis) Do not cycle regularly Do not intend to Do not cycle reg. Intend to Have no access Precontemplation Contemplation Cycle regularly Has increased lately Have access Do not cycle reg. Intend to Have access Preparation Cycle regularly Has not increased lately Do it automatically Action Maintenance Baseline Questionnaire Stage diagnosis general sample Trans-theoretical Model of the five stages of change. Based on Prochaska and Diclemente (1986)

42 Cycling Networks are Associated with Cycling Mode Shares Mode share 25% Mueller N. Et al. forthcoming

Antwerp Cycling Highway Cost-benefit ratios indicate that the benefits of the cycling highway Antwerp-Mechelen (Belgium) are 2 to 14 times higher than the initial investment.

43 Antwerp Cycling Highway Cost-benefit ratios indicate that the benefits of the cycling highway Antwerp-Mechelen (Belgium) are 2 to 14 times higher than the initial investment. Impact factor euro Physical activity (reduced mortality) Physical activity (reduced morbidity) Reduced air pollution society (mortality) Air pollution active mobility Crash risk Total Infrastructure construction costs Benefit:cost ratio 2.0

44 Active Mobility and Physical Activity Is active mobility a net gain, or does it substitute for other forms of physical activity (e.g. going to the gym)?

45 AM PA relationship Does an increase in walking and cycling translate into more physical activity? YES: active mobility helps to increase physical activity levels

46 Is self-reported PA reliable? Vigorous-intensity PA: YES Moderate-intensity PA: underestimated Sedentary time: inaccurate SenseWear vs. GPAQ

47 Safety Exposure adjusted crash risks

48 Exposure Adjusted Crash Rates Crashes Exposure Valid comparisons Identification of safety factors

49 Exposure Adjusted Bicycle Crash Rates Per «hours cycled» Per «km cycled» Travel Diary Sub-Sample (participants = 2,101 ; crashes = 496 )

50 Crash Risk Factors (Preliminary Results) Effects Hazard Ratio (95% CI) Sex - Female 0.80 (0.63, 1.01). Age (0.61, 1.00). Age (0.66, 1.21) City - Barcelona 1.18 (0.79, 1.77) City - London 1.47 (1.04, 2.09)* City - Oerebro 0.22 (0.09, 0.49)*** City - Roma 1.27 (0.89, 1.79) City - Wien 1.44 (1.08, 1.91)* City - Zurich 1.53 (1.10, 2.11)* Signif. codes: 0 *** ** 0.01 * (based on km)

51 Concerns about Air Pollution Are they justified?

52 Concern over health effects of air pollution NO 2 PM % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 29% 48% 13% 8% 16% 15% 65% 14% 49% 21% 11% 11% 32% 29% 27% 21% 51% 19% 7% 7% 5% 36% 26% 25% 7% 29% 23% 30% 13% Antwerp Barcelona London Oerebro Rome Vienna Zurich Not worried at all Not worried Neither worried nor not worried Worried Extremely worried

Concern over health effects of TRAP Concern over health effects of air pollution NO 2 4.0 y 1.4 0.057 x, r 2 = 0.752 Rome Antwerp Barcelona 3.5 London 3.0 Vienna Zurich PM 2.5 2.

53 Concern over health effects of TRAP Concern over health effects of air pollution NO y x, r 2 = Rome Antwerp Barcelona 3.5 London 3.0 Vienna Zurich PM Oerebro NO2 Being male, having children in the household, being more physically active, and higher NO 2 at the home address higher concern over health effects of air pollution

54 BMI What happens when you start cycling?

55 BMI analysis Baseline questionnaire (t 0 ) - height - weight - transport mode - etc. N=8,579 << 476 days >> Final questionnaire (t 1 ) - height - weight - transport mode - etc. N=3,292 Key gaps addressed: Cross-sectional analysis vs. longitudinal analysis Taking into account important covariates like leisure-time PA Many participants using many different modes Multicentre study

56 BMI difference (kg/m²) per additional day per month Bike Walk Public transport Motorcycle E-bike Car BMI difference (kg/m²) Non-cyclist Occasional cyclist Frequent cyclist BMI analysis Results from the cross-sectional analysis 0, ,03-0,05 0,025-0,1 0,02-0,15 0,015 0,01 0, ,005-0,01-0,015-0,2-0,25-0,3-0,35-0,4-0,45-0,5

57 BMI analysis Translate BMI in kilograms. Reverse causality.

58 Conclusions Achievements and outlook

59 Conclusions - Contributions in terms of innovative research - Successful implementation of a cutting-edge online survey - Recruitment, online platform, - Innovative longitudinal study design - Unique data set in terms of size and contents - Some unique findings - Crash rates - Effects of active mobility on BMI, (and other health endpoints) - E-bikes -...and many more to come!

60 Recap and Outlook Ample gaps in (quantitative) understanding of active travel remain! PASTA research progress timeline 2014: can we measure it? 2015: can we find particpants? 2016: can we clean all that data? 2017: can we analyze all this? 2018: can we find funds to continue analyzing? (Research) progress is a slow vehicle! - keep pushing!

61 Thanks to our Collaborators B. Alasya, E. Anaya, I. AvilaPalencia, D. Banister, I. Bartana, F. Benvenuti, F. Boschetti, C. Brand, M. Brannion- Calles, J. Buekers, L. Carniel, G. Carrasco Turigas, A. Castro, M. Cianfano, A. Clark, T. Cole-Hunter, V. Copley, P. De Boever, A. de Nazelle, C. Dimajo, E. Dons, M. Duran, U. Eriksson, H. Franzen, M. Gaupp- Berghausen, R.Gerike, R.Girmenia, T.Götschi, F.Hartmann, F. Iacorossi, L. Int Panis, S. Kahlmeier, H. Khreis, M. Laeremans, T. Martinez, M. Meschik, P. Michelle, P. Muehlmann, N. Mueller, M. Nieuwenhuijsen, A. Nilsson, F. Nussio, J.P. Orjuela Mendoza, S. Pisanti, J. Porcel, F. Racioppi, E. Raser, S. Riegler, H. Robrecht, D. Rojas Rueda, C. Rothballer, J. Sanchez, A. Schaller, R. Schuthof, C. Schweizer, A. Sillero, L. Smidfeltrosqvist, G. Spezzano, A. Standaert, E. Stigell, M. Surace, T. Uhlmann, K. Vancluysen, S. Wegener, H. Wennberg, G. Willis, J. Witzell, and V. Zeuschner. Advisory Board: K. Dziekan, A. Ahrens, M. Jerrett, A. Davis Footer 67

Thomas Götschi University of Zurich, Switzerland thomas.goetschi@uzh.ch Evi Dons VITO, Belgium evi.dons@vito.

62 Thomas Götschi University of Zurich, Switzerland Evi Dons VITO, Belgium This project has received funding from the European Union s Seventh Framework Programme for research; technological development and demonstration under grant agreement no

Active mobility and health: Insights from the PASTA Project

Active mobility and health: Insights from the PASTA Project According to the PASTA survey, over 40% of car and public transport trips are less than 5km. Shifting such short trips to active mobility, such