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Most of the current literature on transportation network companies (TNCs) or ride-hailing services (e.g., Uber, Lyft) has focused on major metropolitan areas, though TNCs are currently extending their services to smaller cities. This point is particularly salient when examining their impacts on alternative transportation modes, such as public transit which operates very differently in small or medium-sized cities (e.g., less frequent services, shorter routes). This study is the first to use micro-level public transit data to examine the effects of Uber on bus ridership in a medium-sized urban area. Uber entered the neighboring cities of Eugene and Springfield, Oregon on July 23, 2014, but abruptly stopped operating on April 5, 2015 after being sued by the City of Eugene. Consequently, this study leverages a natural experiment since the period during which Uber was active is plausibly exogenous to other factors that affect bus ridership. Results show that when Uber operated in treatment cities, bus ridership reduced by 5.4 percent (p

This article presents the MOBIS dataset and underlying survey methods used in its collection. The MOBIS study was a nation-wide randomised controlled trial (RCT) of transport pricing in Switzerland, utilising a combination of postal recruitment, online surveys, and GPS tracking. 21,571 persons completed the first online survey, and 3680 persons completed 8 weeks of GPS tracking. Many continued tracking for over a year after the study was completed. In the field experiment, participants participated through the use of a GPS tracking app, Catch-my-Day, which logged their daily travel on different transport modes and imputed the trip segments and modes. The experiment lasted 8 weeks, bookended by two online surveys. After the first 4-week control phase, participants were split into two different treatment groups and a continued control group. An analysis of the survey participation shows that the technology is capable of supporting such an experiment on both Android and iOS, the two main mobile platforms. Significant differences in the engagement and attrition were observed between iOS and Android participants over the 8-week period. Finally, the attrition rate did not vary between treatment groups. This paper also reports on the wealth of data that are being made available for further research, which includes over 3 million trip stages and activities, labelled with transport mode and purpose respectively., Transportation, ISSN:0049-4488, ISSN:1572-9435

International comparisons of cycling behaviour have typically been limited to high-income countries and often limited to the prevalence of cycling, with lack of discussions on demographic and trip characteristics. We used a combination of city, regional, and national travel surveys from 17 countries across the six continents, ranging from years 2009 through 2019. We present a descriptive analysis of cycling behaviour including level of cycling, trip purpose and distance, and user demographics, at the city-level for 35 major cities (>1 million population) and in urbanised areas nationwide for 11 countries. The Netherlands, Japan and Germany are among the highest cycling countries and their cities among the highest cycling cities. In cities and countries with high cycling levels, cycling rates tend to be more equal between work and non-work trips, whereas in geographies with low cycling levels, cycling to work is higher than cycling for other trips. In terms of cycling distance, patterns in high- and low-cycling geographies are more similar. We found a strong positive association between the level of cycling and women's representation among cyclists. In almost all geographies with cycling mode share greater than 7% women made as many cycle trips as men, and sometimes even greater. The share of cycling trips by women is much lower in geographies with cycling mode shares less than 7%. Among the geographies with higher levels of cycling, children (60 years) remain underrepresented in all geographies but have relatively better representation where levels of cycling are high. In low-cycling settings, females are underrepresented across all the age groups, and more so when older than 16 years. With increasing level of cycling, representation of females improves across all the age groups, and most significantly among children and older adults. Clustering the cities and countries into homogeneous cycling typologies reveals that high cycling levels always coincide with high representation of females and good representations of all age groups. In low-cycling settings, it is the reverse. We recommend that evaluations of cycling policies include usage by gender and age groups as benchmarks in addition to overall use. To achieve representation across different age and gender groups, making neighbourhoods cycling friendly and developing safer routes to school, should be equally high on the agenda as cycling corridors that often cater to commuting traffic. H2020 European Research Council [817754]; Medical Research CouncilUK Research & Innovation (UKRI)Medical Research Council UK (MRC)European Commission [MR/P02663X/1, MR/P024408/1]; National Institute for Health ResearchNational Institute for Health Research (NIHR) [16/137/64] Published version This work was supported by H2020 European Research Council: [Grant Number 817754]; Medical Research Council: [Grant Number MR/P02663X/1,MR/P024408/1]; National Institute for Health Research: [Grant Number 16/137/64].

Active travel (walking or cycling for transport) is considered the most sustainable form of personal transport. Yet its net effects on mobility-related CO2 emissions are complex and underresearched. Here we collected travel activity data in seven European cities and derived life cycle CO2 emissions across modes and purposes. Daily mobility-related life cycle CO2 emissions were 3.2 kgCO(2) per person, with car travel contributing 70% and cycling 1%. Cyclists had 84% lower life cycle CO2 emissions than non-cyclists. Life cycle CO2 emissions decreased by 14% per additional cycling trip and decreased by 62% for each avoided car trip. An average person who `shifted travel modes' from car to bike decreased life cycle CO2 emissions by 3.2 kgCO(2)/day. Promoting active travel should be a cornerstone of strategies to meet net zero carbon targets, particularly in urban areas, while also improving public health and quality of urban life. This work was supported by the European project Physical Activity through Sustainable Transportation Approaches (PASTA). PASTA (http://www.pastaproject.eu/) was a four-year project funded by the European Union's Seventh Framework Program (EU FP7) under European Commission - Grant Agreement No. 602624. CB is also supported by UK Research and Innovation (UKRI) under the Centre for Research on Energy Demand Solutions (CREDS, Grant agreement number EP/R035288/1). ED is also supported by a postdoctoral scholarship from FWO - Research Foundation Flanders. ML held a joint PASTA/VITO PhD scholarship. SS is supported by the Martin Filko Scholarship from the Ministry of Education in Slovakia. Brand, C (corresponding author), Univ Oxford, Transport Studies Unit, South Parks Rd, Oxford OX, christian.brand@ouce.ox.ac.uk

Active travel (walking or cycling for transport) is considered the most sustainable and low carbon form of getting from A to B. Yet the net effects of changes in active travel on changes in mobility-related CO 2 emissions are complex and under-researched. Here we collected longitudinal data on daily travel behavior, journey purpose, as well as personal and geospatial characteristics in seven European cities and derived mobility-related lifecycle CO 2 emissions over time and space. Statistical modelling of longitudinal panel (n = 1849) data was performed to assess how changes in active travel, the 'main mode' of daily travel, and cycling frequency influenced changes in mobility-related lifecycle CO 2 emissions. We found that changes in active travel have significant lifecycle carbon emissions benefits, even in European urban contexts with already high walking and cycling shares. An increase in cycling or walking consistently and independently decreased mobility-related lifecycle CO 2 emissions, suggesting that active travel substituted for motorized travel-i.e. the increase was not just additional (induced) travel over and above motorized travel. To illustrate this, an average person cycling 1 trip/day more and driving 1 trip/day less for 200 days a year would decrease mobility-related lifecycle CO 2 emissions by about 0.5 tonnes over a year, representing a substantial share of average per capita CO 2 emissions from transport. The largest benefits from shifts from car to active travel were for business purposes, followed by social and recreational trips, and commuting to work or place of education. Changes to commuting emissions were more pronounced for those who were younger, lived closer to work and further to a public transport station. Even if not all car trips could be substituted by active travel the potential for decreasing emissions is considerable and significant. The study gives policy and practice the empirical evidence needed to assess climate change mitigation impacts of urban transport measures and interventions aimed at mode shift to more sustainable modes of transport. Investing in and promoting active travel whilst 'demoting' private car ownership and use should be a cornerstone of strategies to meet 'net zero' carbon targets, particularly in urban areas, while also reducing inequalities and improving public health and quality of urban life in a post-COVID-19 world. This work was supported by the European project Physical Activity through Sustainable Transportation Approaches (PASTA). PASTA (http://www.pastaproject.eu/) was a four-year project funded by the European Union’s Seventh Framework Program (European Commission Grant Agreement No. 602624). CB also gratefully acknowledges support from UK Research and Innovation through the UK Energy Research Centre (grant reference number EP/S029575/1). ED is also supported by a postdoctoral scholarship from FWO – Research Foundation Flanders. ML held a joint PASTA/VITO PhD scholarship. SS is supported by the Martin Filko Scholarship from the Ministry of Education in Slovakia

The World Health Organization&rsquo, s Health Economic Assessment Tool (HEAT) for walking and cycling is a user-friendly web-based tool to assess the health impacts of active travel. HEAT, developed over 10 years ago, has been used by researchers, planners and policymakers alike in appraisals of walking and cycling policies at both national and more local scales. HEAT has undergone regular upgrades adopting the latest scientific evidence. This article presents the most recent upgrades of the tool. The health impacts of walking and/or cycling in a specified population are quantified in terms of premature deaths avoided (or caused). In addition to the calculation of benefits derived from physical activity, HEAT was recently expanded to include assessments of the burden associated with air pollution exposure and crash risks while walking or cycling. Further, the impacts on carbon emissions from mode shifts to active travel modes can now be assessed. The monetization of impacts using Value of Statistical Life and Social Costs of Carbon now uses country-specific values. As active travel inherently results in often substantial health benefits as well as not always negligible risks, assessments of active travel behavior or policies are incomplete without considering health implications. The recent developments of HEAT make it easier than ever to obtain ballpark estimates of health impacts and carbon emissions related to walking and cycling.

Active travel (walking or cycling for transport) is considered the most sustainable form of getting from A to B. Yet the net effects of active travel on mobility-related CO2 emissions are complex and under-researched. Here we collected travel activity data in seven European cities and derived lifecycle CO2 emissions from daily travel activity. Daily mobility-related lifecycle CO2 emissions were 3.2 kgCO2 per person, with car travel contributing 70% and cycling 1%. Cyclists had 84% lower lifecycle CO2 emissions from all daily travel than non-cyclists. Lifecycle CO2 emissions decreased by -14% (95%CI -12% to -16%) per additional cycling trip and decreased by -62% (95%CI -61% to -63%) for each avoided car trip. An average person who ‘shifted travel modes’ from car to bike decreased lifecycle CO2 emissions by 3.2 (95%CI 2.0 to 5.2) kgCO2/day, and using a bike as the ‘main method of travel’ gave 7.1 (95%CI 4.8 to 10.4) kgCO2/day lower lifecycle CO2 emissions than mainly using a car or van. Investing in and promoting active travel should be a cornerstone of strategies to meet net zero carbon targets, particularly in urban areas, while also improving public health and quality of urban life.

Increased cycling uptake can improve population health, but barriers include real and perceived risks. Crash risk factors are important to understand in order to improve safety and increase cycling uptake. Many studies of cycling crash risk are based on combining diverse sources of crash and exposure data, such as police databases (crashes) and travel surveys (exposure), based on shared geography and time. When conflating crash and exposure data from different sources, the risk factors that can be quantified are only those variables common to both datasets, which tend to be limited to geography (e.g. countries, provinces, municipalities) and a few general road user characteristics (e.g. gender and age strata). The Physical Activity through Sustainable Transport Approaches (PASTA) project was a prospective cohort study that collected both crash and exposure data from seven European cities (Antwerp, Barcelona, London, Örebro, Rome, Vienna and Zürich). The goal of this research was to use data from the PASTA project to quantify exposure-adjusted crash rates and model adjusted crash risk factors, including detailed sociodemographic characteristics, attitudes about transportation, neighbourhood built environment features and location by city. We used negative binomial regression to model the influence of risk factors independent of exposure. Of the 4,180 cyclists, 10.2 % reported 535 crashes. We found that overall crash rates were 6.7 times higher in London, the city with the highest crash rate, relative to Örebro, the city with the lowest rate. Differences in overall crash rates between cities are driven largely by crashes that did not require medical treatment and that involved motor-vehicles. In a parsimonious crash risk model, we found higher crash risks for less frequent cyclists, men, those who perceive cycling to not be well regarded in their neighbourhood, and those who live in areas of very high building density. Longitudinal collection of crash and exposure data can provide important insights into individual differences in crash risk. Substantial differences in crash risks between cities, neighbourhoods and population groups suggest there is great potential for improvement in cycling safety.

Objectives Ambient particulate matter (PM) is regulated with science-based air quality standards, whereas carcinogens are regulated with a number of “acceptable” cases. Given that PM is also carcinogenic, we identify differences between approaches. Methods We assessed the lung cancer deaths for Switzerland attributable to exposure to PM up to 10 µm (PM10) and to five particle-bound carcinogens. For PM10, we used an epidemiological approach based on relative risks with four exposure scenarios compared to two counterfactual concentrations. For carcinogens, we used a toxicological approach based on unit risks with four exposure scenarios. Results The lung cancer burden using concentrations from 2010 was 10–14 times larger for PM10 than for the five carcinogens. However, the burden depends on the underlying exposure scenarios, counterfactual concentrations and number of carcinogens. All scenarios of the toxicological approach for five carcinogens result in a lower burden than the epidemiological approach for PM10. Conclusions Air quality standards—promoted so far by the WHO Air Quality Guidelines—provide a more appealing framework to guide health risk-oriented clean air policymaking than frameworks based on a number of “acceptable” cases. Electronic supplementary material The online version of this article (10.1007/s00038-019-01324-y) contains supplementary material, which is available to authorized users.

The health economic assessment tool (HEAT) for walking and cycling has been developed as a user-friendly yet robust tool for transport and urban planners allowing the inclusion of physical activity benefits in transport appraisals. The most recent version can now also consider how much road crashes and air pollution affect these results, and what the effects on carbon emissions are. The HEAT process adheres to an agreed set of key principles and a standardized, iterative process for updates. An assessment consists of five steps that are described in this chapter. The HEAT has been used widely, and three practical applications in different settings are presented to illustrate possible uses and ways of disseminating the results.

Subjective perception of air pollution is important and can have impacts on health in its own rights, can lead to protective behaviour, or it can be leveraged to engage citizens and stakeholders in support of cleaner air policies. The aim of the current analysis was to examine associations between level of concern over health effects of air pollution and personal and environmental factors. In seven European cities, 7622 adult participants were recruited to complete an online questionnaire on travel and physical activity behaviour, perceptions and attitudes on active mobility and the environment, and sociodemographics. Air pollution at the home address was determined using Europe-wide PM2.5 and NO2 land use regression models. Mixed effects logistic regression was used to model concern over air pollution (worried versus not worried; city as random effect). Fifty-eight percent of participants were worried over health effects of air pollution with large differences across cities (Antwerp 78%, Barcelona 81%, London 64%, Orebro 11%, Rome 72%, Vienna 43%, Zurich 33%). Linking mean modelled air pollution to mean level of concern per city gave a good correlation for NO2 (r(2) = 0.75), and a lower correlation for PM2.5 (r(2) = 0.49). In the regression model, sex, having children in the household, levels of physical activity, and NO2 at the home address were significantly linked to individual concern over health effects of air pollution. We found that NO2 but not PM2.5 at the home address was associated with concern over health effects of air pollution. The authors led the study on behalf of the PASTA consortium funded by the 7th Framework Programme of the European Commission (grant agreement 602624). Evi Dons is supported by a postdoctoral scholarship from FWO-Research Foundation Flanders. Michelle Laeremans holds a joint PASTA/VITO PhD scholarship. List of PASTA investigators is as follows: A. Ambros, E. Anaya, I. AvilaPalencia, F. Benvenuti, F. Boschetti, C. Brand, J. Buekers, L. Carniel, G. Carrasco-Turigas, A. Castro, A. Clark, T. Cole-Hunter, A. de Nazelle, E. Dons, U. Eriksson, H. Franzen, M. Gaupp-Berghausen, R. Gerike, R. Girmenia, T. Gotschi, F. Hartmann, I. Horvath, F. Iacorossi, L. Int Panis, S. Kahlmeier, M. Laeremans, N. Mueller, M. Nieuwenhuijsen, A. Nilsson, F. Nussio, J. P. Orjuela, F. Racioppi, E. Raser, D. Rojas-Rueda, C. Rothballer, J. Sanchez, R. Schuthof, C. Schweizer, A. Standaert, E. Stigell, N. Tabari, T. Uhlmann, S. Wegener, and V. Zeuschner. Additional files: The full questionnaire of the PASTA longitudinal survey is available from: http://pastaproject.eu/fileadmin/editorupload/sitecontent/City_survey/PASTA-questionnaires.pdf.

Exposure to urban air pollution has been associated with adverse effects on cardio-vascular and respiratory health, both short and long term. Consequently, governments have applied policies to reduce air pollution. Quantitative health impact assessments of hypothetic changes in air pollution have been conducted at national and global level, but assessments of observed air pollution changes associated with specific clean air policies at a local or regional scale remain scarce. This study estimates health impacts attributable to a decrease in PM10 and NO2 exposure in the Agglomeration of Lausanne-Morges (ALM), Switzerland, between 2005 and 2015, corresponding to the implementation period of a supra-municipal plan of measures to reduce air pollution in different sectors such as transport, energy, and industry (called Plan OPair 05). The health impact assessment compares health effects attributed to air pollution exposure levels in 2015 (reference case) with those in 2005 (counterfactual scenario), using 2015 as baseline for all other input data. In the ALM, the modeled PM10 exposure reduction of 3.3μg/m3 from 2005 to 2015 prevents 26 premature deaths (equivalent to around 290 years of life lost), 215 hospitalization days due to cardio-vascular and respiratory diseases as well as approximately 47,000 restricted activity days annually. Monetized health impacts of the reduction of PM10 exposure are valued at approximately CHF 36 million annually. Immaterial costs, mainly related to the economic valuation of years of life lost, dominate the monetized health impacts (90% of total value), while savings at the workplace (net loss in production and reoccupation costs) amount to about CHF 1.9 million, and savings in health care costs to about CHF 0.5 million. The assessment is sensitive to the value assigned to immaterial costs and to uncertainties in the relative risk estimates, whereas variations in the baseline year (i.e. using 2005 data instead of 2015 data) affect results to a much lower degree. The alternative calculation based on NO2 exposure, which dropped by 5.6μg/m3, suggests the prevention of 51 premature deaths (equivalent to around 550 years of life lost) overall impacts valued at CHF 49 million. All in all, the reduction in mortality due to the air quality improvements accounts for (depending on the considered pollutant) about 1% to 2% of total all-cause annual mortality in the ALM population or 4-8 times larger than the annual traffic fatalities in the ALM.

Background: Although walking for travel can help in reaching the daily recommended levels of physical activity, we know relatively little about the correlates of walking for travel in the European context. Objective: Within the framework of the European Physical Activity through Sustainable Transport Approaches (PASTA) project, we aimed to explore the correlates of walking for travel in European cities. Methods: The same protocol was applied in seven European cities. Using a web-based questionnaire, we collected information on total minutes of walking per week, individual characteristics, mobility behavior, and attitude (N = 7,875). Characteristics of the built environment (the home and the work/study addresses) were determined with geographic information system (GIS)-based techniques. We conducted negative binomial regression analyses, including city as a random effect. Factor and principal component analyses were also conducted to define profiles of the different variables of interest. Results: Living in high-density residential areas with richness of facilities and density of public transport stations was associated with increased walking for travel, whereas the same characteristics at the work/study area were less strongly associated with the outcome when the residential and work/study environments were entered in the model jointly. A walk-friendly social environment was associated with walking for travel. All three factors describing different opinions about walking (ranging from good to bad) were associated with increased minutes of walking per week, although the importance given to certain criteria to choose a mode of transport provided different results according to the criteria. Discussion: The present study supports findings from previous research regarding the role of the built environment in the promotion of walking for travel and provides new findings to help in achieving sustainable, healthy, livable, and walkable cities. https://doi.org/10.1289/EHP4603. PASTA (Physical Activity through Sustainable Transport Approaches; http://www.pastaproject.eu/) is a 4-y project funded by the European Union’s Seventh Framework Program under EC-GA No. 602624-2 (FP7-HEALTH-2013-INNOVATION-1).

Background: Sufficient sample size and minimal sample bias are core requirements for empirical data analyses. Combining opportunistic recruitment with a Web-based survey and data-collection platform yields new benefits over traditional recruitment approaches. Objective: This paper aims to report the success of different recruitment methods and obtain data on participants’ characteristics, participation behavior, recruitment rates, and representativeness of the sample. Methods: A longitudinal, Web-based survey was implemented as part of the European PASTA (Physical Activity through Sustainable Transport Approaches) project, between November 2014 and December 2016. During this period, participants were recruited from 7 European cities on a rolling basis. A standardized guide on recruitment strategy was developed for all cities, to reach a sufficient number of adult participants. To make use of the strengths and minimize weakness, a combination of different opportunistic recruitment methods was applied. In addition, the random sampling approach was applied in the city of Örebro. To reduce the attrition rate and improve real-time monitoring, the Web-based platform featured a participant’s and a researchers’ user interface and dashboard. Results: Overall, 10,691 participants were recruited; most people found out about the survey through their workplace or employer (2300/10691, 21.51%), outreach promotion (2219/10691, 20.76%), and social media (1859/10691, 17.39%). The average number of questionnaires filled in per participant varied significantly between the cities (P

Munich, Berlin, Hamburg, Vienna, and Zurich – the largest cities in Germany, Austria, and Switzerland – have significantly reduced the car share of trips over the past 25 years in spite of high motorisation rates. The key to their success has been a coordinated package of mutually reinforcing transport and land-use policies that have made car use slower, less convenient, and more costly, while increasing the safety, convenience, and feasibility of walking, cycling, and public transport. The mix of policies implemented in each city has been somewhat different. The German cities have done far more to promote cycling, while Zurich and Vienna offer more public transport service per capita at lower fares. All five of the cities have implemented roughly the same policies to promote walking, foster compact mixed-use development, and discourage car use. Of the car-restrictive policies, parking management has been by far the most important. The five case study cities demonstrate that it is possible to redu...

Aim To assess the main and interaction effects of black carbon and physical activity on arterial blood pressure in a healthy adult population from three European cities using objective personal measurements over short-term (hours and days) and long-term exposure. Methods A panel study of 122 healthy adults was performed in three European cities (Antwerp, Barcelona, and London). In 3 seasons between March 2015 and March 2016, each participant wore sensors for one week to objectively measure their exposure to black carbon and monitor their physical activity continuously. Blood pressure was assessed three times during the week: at the beginning (day 0), in the middle (day 4), and at the end (day 7). Associations of black carbon and physical activity with blood pressure and their interactions were investigated with linear regression models and multiplicative interaction terms, adjusting for all the potential confounders. Results In multiple exposure models, we did not see any effects of black carbon on blood pressure but did see effects on systolic blood pressure of moderate-to-vigorous physical activity effect that were statistically significant from 1 h to 8 h after exposure and for long-term exposure. For a 1METhour increase of moderate-to-vigorous physical activity, the difference in the expected mean systolic blood pressure varied from −1.46 mmHg (95%CI -2.11, −0.80) for 1 h mean exposure, to −0.29 mmHg (95%CI -0.55, −0.03) for 8 h mean exposure, and −0.05 mmHg (95%CI -0.09, −0.00) for long-term exposure. There were little to no interaction effects. Conclusions Results from this study provide evidence that short-term and long-term exposure to moderate-to-vigorous physical activity is associated with a decrease in systolic blood pressure levels. We did not find evidence for a consistent main effect of black carbon on blood pressure, nor any interaction between black carbon and physical activity levels.

This paper presents fatality rates for walking and cycling in European Countries used in the World Health Organization’s Health Economic Assessment Tool (HEAT). It evaluates and ranks the quality of data sources and gives fatality rates adjusted by exposure (i.e. distance travelled). It also discusses the different methodologies applied for national exposure data, as well as the proposed solutions to make these figures comparable across countries.

Active mobility is related to various positive effects and is promoted in urban planning, transport planning, and in public health. The goals of these three disciplines differ in many respects but have a strong overlap in the ambition to foster active mobility. Until now, efforts for strengthening active mobility have typically not been combined, but rather promoted separately within each discipline. This paper presents a review of research on determinants and impacts of active mobility and of policy measures for supporting active mobility, including the three disciplines of transport planning, urban planning, and public health. The paper further shows the different perspectives and ambitions of the three disciplines and, simultaneously, the substantial synergies that can be gained from an interdisciplinary collaboration in research and practice.

Background: Transport mode choice has been associated with different health risks and benefits depending on which transport mode is used. We aimed to evaluate the association between different transport modes use and several health and social contact measures. Methods: We based our analyses on the Physical Activity through Sustainable Transport Approaches (PASTA) longitudinal study, conducted over a period of two years in seven European cities. 8802 participants finished the baseline questionnaire, and 3567 answered the final questionnaire. Participants were 18 years of age or older (16 years of age or older in Zurich) and lived, worked and/or studied in one of the case-study cities. Associations between transport mode use and health/social contact measures were estimated using mixed-effects logistic regression models, linear regression models, and logistic regression models according to the data available. All the associations were assessed with single and multiple transport mode models. All models were adjusted for potential confounders. Results: In multiple transport mode models, bicycle use was associated with good self-perceived health [OR (CI 95%) = 1.07 (1.05, 1.08)], all the mental health measures [perceived stress: coef (CI 95%) = −0.016 (−0.028, −0.004); mental health: coef (CI 95%) = 0.11 (0.05, 0.18); vitality: coef (CI 95%) = 0.14 (0.07, 0.22)], and with fewer feelings of loneliness [coef (CI 95%) = −0.03 (−0.05, −0.01)]. Walking was associated with good self-perceived health [OR (CI 95%) = 1.02 (1.00, 1.03)], higher vitality [coef (CI 95%) = 0.14 (0.05, 0.23)], and more frequent contact with friends/family [OR (CI 95%) = 1.03 (1.00, 1.05)]. Car use was associated with fewer feelings of loneliness [coef (CI 95%) = −0.04 (−0.06, −0.02)]. The results for e-bike and public transport use were non-significant, and the results for motorbike use were inconclusive. Conclusions: Similarity of findings across cities suggested that active transport, especially bicycle use, should be encouraged to improve population health and social outcomes. This work was supported by the European project PASTA, which had partners in London, Rome, Antwerp, Örebro, Vienna, Zurich, and Barcelona. PASTA (http://www.pastaproject.eu/) was a 4-year project funded by the European Union's Seventh Framework Program under EC-GA No. 602624-2 (FP7-HEALTH-2013-INNOVATION-1). ED was supported by a postdoctoral scholarship from FWO – Research Foundation Flanders. JPO was financed by the Colombian Government, Colciencias Scholarship for PhD's abroad number 646. The funding sources had no involvement in the study. MJN had full access to all the data in the study and had final responsibility for the decision to submit for publication.

BACKGROUND: In the fight against rising overweight and obesity levels, and unhealthy urban environments, the renaissance of active mobility (cycling and walking as a transport mode) is encouraging. Transport mode has been shown to be associated to body mass index (BMI), yet there is limited longitudinal evidence demonstrating causality. We aimed to associate transport mode and BMI cross-sectionally, but also prospectively in the first ever European-wide longitudinal study on transport and health. METHODS: Data were from the PASTA project that recruited adults in seven European cities (Antwerp, Barcelona, London, Oerebro, Rome, Vienna, Zurich) to complete a series of questionnaires on travel behavior, physical activity levels, and BMI. To assess the association between transport mode and BMI as well as change in BMI we performed crude and adjusted linear mixed-effects modeling for cross-sectional (n = 7380) and longitudinal (n = 2316) data, respectively. RESULTS: Cross-sectionally, BMI was 0.027 kg/m2 (95%CI 0.015 to 0.040) higher per additional day of car use per month. Inversely, BMI was -0.010 kg/m2 (95%CI -0.020 to -0.0002) lower per additional day of cycling per month. Changes in BMI were smaller in the longitudinal within-person assessment, however still statistically significant. BMI decreased in occasional (less than once per week) and non-cyclists who increased cycling (-0.303 kg/m2, 95%CI -0.530 to -0.077), while frequent (at least once per week) cyclists who stopped cycling increased their BMI (0.417 kg/m2, 95%CI 0.033 to 0.802). CONCLUSIONS: Our analyses showed that people lower their BMI when starting or increasing cycling, demonstrating the health benefits of active mobility. ispartof: ENVIRONMENT INTERNATIONAL vol:119 pages:109-116 ispartof: location:Netherlands status: published

Background/aim Transport behaviours have been associated with several positive and negative health effects. The current study evaluates the association between different modes of transport and subjective general health in an adult population in seven European cities, and explores whether mental health, vitality, perceived stress, social contacts, and physical activity are mediators of this association. Methods A longitudinal study was performed in seven European cities (Antwerp, Barcelona, London, Orebro, Rome, Vienna, and Zurich). Participants responded to two comprehensive questionnaires (Baseline and Final) concerning their transport behaviour and health, using an on-line platform. The transport mode usage was assessed using a frequency scale (days/month) of five different transport modes: car, motorbike, public transport, e-bike, bicycle, and walking. Participants were categorised as with ‘good or more’ or ‘less than good’ subjective general health. Multilevel regression models will be used to evaluate the association between transport mode and subjective general health, adjusting for potential confounders. We will follow Vander Weele’s framework to establish the mediation roles. Results (ongoing analyses): The sample had more than 7000 adults, fairly distributed in the seven cities (16% Antwerp, 16% Barcelona, 14% London, 10% Orebro, 14% Rome, 16% Vienna, 14% Zurich). In initial analyses we find positive associations between active transport modes (e-bike, bicycle, walking) and subjective general health and negative associations between motorised transport modes (car, motorbike, public transport) and subjective general health. We also expect to find indications for mediation of these associations by mental health, vitality, perceived stress, social contacts, and physical activity. Conclusion We hypothesise that mental health, social contacts, perceived stress, and levels of physical activity may be important consequences of transport behaviours which could lead to different levels of subjective general health.

Background/aim People living in urban areas in Europe are exposed to elevated concentrations of air pollution. The lower the air pollution levels, the better for your health; so people exposed to higher concentrations should be worried more about air pollution. The aim of this analysis was to examine associations between concern over health effects of air pollution and personal and environmental factors. Methods In 7 European cities, >12 000 participants over 18 years were recruited to complete an online questionnaire on travel and physical activity behaviour, perceptions and attitudes, and sociodemographics. The following question was assessed on a 5-point scale: ‘Are you worried that air pollution in the neighbourhood of either your home or work can lead to health problems?’ Mixed effects logistic regression was used to model concern over health effects of air pollution (worried (level 4–5) versus not-worried (level 1–3); city as random effect). Air pollution at the home address was determined using the West-European PM2.5 and NO2 land use regression models from de Hoogh et al. (2016). Potential confounding variables were chosen based on previous studies, and most variables were self-reported. Results 57% of participants were worried over health effects of air pollution with large differences across cities (Antwerp 77%; Barcelona 81%; London 64%; Oerebro 12%; Rome 72%; Vienna 43%; Zurich 34%). Linking mean modelled air pollution to mean level of concern per city, gave a good correlation for NO2 (r²=0.75) and a lower correlation for PM2.5 (r²=0.49). In bivariate analyses, city, sex, education level, self-reported health, having children in the household, distance to the nearest major road, physical activity level, and NO2 and PM2.5 at home were significantly linked to concern over health effects of air pollution. In the mixed effects logistic regression model sex, self-reported health, having children in the household, physical activity level, and NO2 at home remained significant. Conclusion Being male, having a worse self-reported health, having children in the household, being more physically active, and higher NO2 at the home address were associated with higher concern over health effects of air pollution.

Background/aim The increased inhalation rate during physical activity in urban environments may result in increased inhaled dose of traffic-related air pollutants. Short-term exposure to traffic-related air pollutants has been associated with increasing blood pressure. The current study assesses the main effects and interaction effects of traffic-related air pollution and physical activity on blood pressure. Methods A panel study was performed in three European cities (Antwerp, Barcelona, and London) with 122 healthy adults (approx. 40 participants/city) who completed 7 day measurement periods in winter, summer, and mid-season, between February 2015 and March 2016. The participants wore sensors to measure exposure to black carbon (marker of traffic-related air pollution) and physical activity levels. Blood pressure was measured three times during each measurement period. Participants also completed a questionnaire about their personal characteristics and lifestyle behaviours. Multilevel regression models will be used to assess associations and interaction effects. All models will be adjusted by potential confounders. Results (ongoing analyses): Participants had a median (IQR) moderate-to-vigorous physical activity of 71 (49–111) min/day measured by an accelerometer. Mean black carbon exposure over all sample in coinciding time periods was 1636±673 ng/m³. The mean black carbon exposure increased with higher levels of physical activity. In initial analyses we find associations between the two exposures (black carbon and physical activity) and blood pressure. We also expect to find that physical activity levels moderates the negative effects of black carbon exposure on blood pressure. Conclusion We hypothesise that the cardiovascular effects from traffic-related air pollution exposure could be attenuated by physical activity levels.

Cycling infrastructure has been implemented worldwide to promote bicycle use and to minimize injury risk. A comprehensive evaluation of such infrastructure is required to assess its success. In terms of safety, assessments ideally focus on both objective and subjective parameters. This study explores the application of a combined objective-subjective safety assessment approach in a pre-post analysis of a left-turning bicycle box in Zurich, Switzerland. A computer-based video technology was used to objectively measure passing distance between bicycles turning left and continuing motor vehicles passing on the right. In an in-situ survey perceived safety while crossing the intersection and a photo-based assessment of the intersection were collected as indicators of subjective safety. Median passing distance between bicycles and motor vehicles did not significantly change after the implementation of the bicycle box, but the shortest distances were increased. Perceived safety while crossing the intersection was significantly higher after marking the bicycle box, which is consistent with safety expectations expressed based on photos with and without left-turning box. Gender and general perception of traffic safety within the city are significant determinants of expected and perceived intersection safety. Women expect greater safety gains from the left-turning box (photo based), but its effect on perceived safety when actually crossing the intersection does not differ between genders. While the applied video technology is not yet practice-ready, it shows great potential to complement cycling safety evaluations, in combination with self-reported perceived safety indicators.

Background Active transport (i.e. walking and cycling for transport) can provide substantial health benefits by increasing levels of physical activity (PA) and help reduce transport-associated emissions. Our aim was to conduct a health impact assessment (HIA) of cycling networks expansions in seven diverse European cities (Antwerp, Barcelona, London, Orebro, Rome, Vienna, Zurich) that form part of the Physical Activity through Sustainable Transport Approaches (PASTA) project. We modeled the association between cycling network distance (km) and cycling mode share (%) and estimated health impacts of the expansion of cycling networks. Methods Cycling network distances were computed for 168 European cities using OpenStreetMap data for designated cycling ways. Cycling mode share was available through the European Platform on Mobility Management. We performed a non-linear least square regression to assess the relationship between cycling network and cycling mode share. We performed a quantitative HIA for five different scenarios (S) (10% (S1); 50% (S2); 100% (S3), Go-Orebro (S4) and All-streets (S5)) assessing how an expansion of the cycling network would lead to an increase in cycling mode share and estimated associated mortality impacts thereof. We quantified mortality impacts in terms of changes to PA levels, exposure to air pollution and traffic incidents for the cyclist. Results Our results suggest that the cycling network may contribute to a cycling mode share of up to 25% in European cities. A cycling network as that of Orebro (S4; 255 km/100,000 persons) produced greatest health benefits through increases in cycling for London with 646 (95% CI: 397;1012) annual deaths avoided, followed by Rome (224; 95% CI: 133;359), Barcelona (162; 95% CI: 103;248), Vienna (82; 95% CI: 47;133), Zurich (27; 95% CI: 16;42) and Antwerp (3; 95% CI: 2;6). If all 168 European cities achieved a cycling mode share of 25% over 16,000 deaths (95% CI: 9,861;25,763) could be avoided each year. The largest cost-benefit ratios were found for the 10% increase in cycling network (S1) suggesting it to be most cost-effective (Rome € 40:1; Barcelona € 20:1; Zurich € 16:1; Vienna € 11:1, London € 3:1). Conclusions Especially in cities with a currently low cycling mode share, expansion of cycling networks may promote increases in cycling mode share. Increases in cycling mode share were estimated to provide considerable health benefits in European cities.

Exposure to urban air pollution has been associated with adverse effects on cardio-vascular and respiratory health, both short and long term. Consequently, governments have applied policies to reduce air pollution. Quantitative health impact assessments of hypothetic changes in air pollution have been conducted at national and global level, but assessments of observed air pollution changes associated with specific clean air policies at a local or regional scale remain scarce. This study estimates health impacts attributable to a decrease in PM

Only 21% of American adults achieve recommended levels of physical activity. Urban trails are popular venues both to engage in recreational physical activities and for active commuting. The Rails-to-Trails Conservancy's Trail Modeling and Assessment Platform (T-MAP) is a multi-year research project to develop data-driven trail planning and management tools. We surveyed over 3000 trail users on 14 US urban trails. The survey was developed specifically to inform health impact calculation, including items on trail use and other physical activity. We calculate health impacts in terms of six chronic diseases and mortality, and use treatment costs and Value of Statistical Life (VSL) for monetization, respectively. Regular trail use prevents 36 hospitalizations due to chronic diseases and 182 premature deaths per 100,000 trail users and year, worth $2,1 million in avoided treatment costs and $1,7 billion based on VSL, respectively. Compared to VSL, avoided treatment costs provide more tangible estimates of health impacts, but challenges with data availability and comparability call for cautious interpretations. Our estimates for chronic disease cases are limited to hospitalization discharges and treatment costs, resulting in considerably lower figures than those for reduction in mortality risk. Trail users are a highly active population. 40% achieve physical activity recommendations even without trail use, and with trail use, 87% do. Health benefits would be more than double if inactive subjects would take up the same amount of trail use as observed in our sample.

Physical activity and ventilation rates have an effect on an individual’s dose and may be important to consider in exposure−response relationships; however, these factors are often ignored in environmental epidemiology studies. The aim of this study was to evaluate methods of estimating the inhaled dose of air pollution and understand variability in the absence of a true gold standard metric. Five types of methods were identified: (1) methods using (physical) activity types, (2) methods based on energy expenditure, METs (metabolic equivalents of task), and oxygen consumption, (3) methods based on heart rate or (4) breathing rate, and (5) methods that combine heart and breathing rate. Methods were compared using a real-life data set of 122 adults who wore devices to track movement, black carbon air pollution, and physiological health markers for 3 weeks in three European cities. Different methods for estimating minute ventilation performed well in relative terms with high correlations among different methods, but in absolute terms, ignoring increased ventilation during day-to-day activities could lead to an underestimation of the daily dose by a factor of 0.08−1.78. There is no single best method, and a multitude of methods are currently being used to approximate the dose. The choice of a suitable method for determining the dose in future studies will depend on both the size and the objectives of the study. This work was supported by the European project Physical Activity through Sustainable Transportation Approaches (PASTA). PASTA (http://www.pastaproject.eu/) is a four-year project funded by the European Union's Seventh Framework Program (EU FP7) under European Commission Grant Agreement 602624. E.D. is supported by a postdoctoral scholarship from FWO-Research Foundation Flanders. M.L. holds a joint PASTA/VITO Ph.D. scholarship.

While many levels of government recognize that walking and cycling (active travel) are critical to healthy cities, a continued challenge is to identify and prioritize strategies that will increase walking and cycling for transportation. We review evidence on policies that can increase active travel. The reviews included here conclude that policies related to active travel may operate at various levels of the socio-ecological framework, including society, cities, routes or individuals. The provision of convenient, safe and connected walking and cycling infrastructure is at the core of promoting active travel, but policies may work best when implemented in comprehensive packages. There is strong evidence that active travel can result in substantial health benefits. However, there remains considerable uncertainty about the exact effects of specific policies on walking or cycling rates or safety. Further research is needed to quantify the impact of specific policies or packages of policies, especially across different settings or for different population segments.

Introduction Measuring bicycling behaviour is critical to bicycling research. A common study design question is whether to measure bicycling behaviour once (cross-sectional) or multiple times (longitudinal). The Physical Activity through Sustainable Transport Approaches (PASTA) project is a longitudinal cohort study of over 10,000 participants from seven European cities over two years. We used PASTA data as a case study to investigate how measuring once or multiple times impacted three factors: a) sample size b) participation bias and c) accuracy of bicycling behaviour estimates. Methods We compared two scenarios: i) as if only the baseline data were collected (cross-sectional approach) and ii) as if the baseline plus repeat follow-ups were collected (longitudinal approach). We compared each approach in terms of differences in sample size, distribution of sociodemographic characteristics, and bicycling behaviour. In the cross-sectional approach, we measured participants long-term bicycling behaviour by asking for recall of typical weekly habits, while in the longitudinal approach we measured by taking the average of bicycling reported for each 7-day period. Results Relative to longitudinal, the cross-sectional approach provided a larger sample size and slightly better representation of certain sociodemographic groups, with worse estimates of long-term bicycling behaviour. The longitudinal approach suffered from participation bias, especially the drop-out of more frequent bicyclists. The cross-sectional approach under-estimated the proportion of the population that bicycled, as it captured ‘typical’ behaviour rather than 7-day recall. The magnitude and directionality of the difference between typical weekly (cross-sectional approach) and the average 7-day recall (longitudinal approach) varied depending on how much bicycling was initially reported. Conclusions In our case study we found that measuring bicycling once, resulted in a larger sample with better representation of sociodemographic groups, but different estimates of long-term bicycling behaviour. Passive detection of bicycling through mobile apps could be a solution to the identified issues.

Introduction: In times of contemporary sedentarism and the convenience of motor transport, active mobility (AM; walking and cycling for transport) can provide substantial health benefits by increas...

Introduction Cities are increasingly turning to active travel policies to address great public health challenges, in particular physical inactivity. However, what will actually work to promote walk...

While cost-benefit analysis has been employed in highway planning processes for decades, such analytical approaches are less frequently used in trail planning due to the limited availability of data and methodologies for quantifying trail benefits. As a result, even projects that provide critical access to safe, high-quality open space with real mobility and health benefits are often considered “amenities,” rather than “needs.” Individual agencies and trail project sponsors have measured trail use and benefits along local greenways, but there currently are no generalizable methods for predicting demand or conducting impact assessment on trails. To address this gap, the Rails-to-Trails Conservancy (RTC) is developing the Trail Modeling and Assessment Platform (T-MAP), a set of trail planning data collection and analysis tools, including a trail user survey. The T-MAP survey tool was developed to allow implementing agencies to learn more about trail use and users, especially users’ physical activity. This paper describes the development of a survey instrument and sampling protocol that yielded a response rate of 55% in field testing. The survey includes questions from the Global Physical Activity Questionnaire, an internationally validated instrument developed by the World Health Organization. We report the results of testing the effect of alternative survey distribution methods (in-person interview and online post-survey) and incentives on overall response rates and sample bias across multiple population variables, including gender, age, trail use mode, overall health status, and physical activity frequency. The highest response rates (64%) were achieved through a combination of personal intercept interview with incentive, followed by online participation after receiving a card from a surveyor on the trail. When designing a survey data collection and sampling plan, decisions such as whether to use field workers, to offer incentives, and the survey administration format all impact the response rate and the representativeness of the sample, and thus the cost and quality of the data collected. These findings can help trail managers, local planners, or advocates to estimate survey administration costs and maximize returns through efficient and valid data collection to conduct trail benefit assessments based on high-quality data.

Context Physical activity has various health benefits. Active transport can contribute to total physical activity and thus affect body weight because of increased energy expenditure. This review summarizes published evidence on associations of active transport, general physical activity, and body weight in adults. Evidence acquisition A systematic review of the literature was conducted in October 2010 using eight databases. A total of 14,216 references were screened; full texts were retrieved for 95 articles. Forty-six articles (36 unique studies) were included: 20 (17) from Europe; 18 (13) from North America, Australia, and New Zealand; and eight (six) from other countries. Analyses of the retrieved papers were carried out between November 2010 and March 2011. Evidence synthesis Of 15 studies assessing active transport and physical activity, five found associations in the expected direction (more active transport associated with more physical activity) for all or most variables studied, nine found some associations, and one reported no associations. Of 30 studies assessing active transport and body weight, 13 reported associations in the expected direction (more active transport associated with lower body weight) for all or most variables studied, 12 found some associations, two presented some associations in the expected and some in the opposite direction, and three reported no associations. Conclusions There is limited evidence that active transport is associated with more physical activity as well as lower body weight in adults. However, study heterogeneity, predominantly cross-sectional designs, and crude measures for active transport and physical activity impede quantitative conclusions.

Background Cities are increasingly turning towards active travel policies to help address some the world’s greatest public health challenges, in particular physical inactivity. However, what will actually work to promote walking and cycling remains uncertain, and findings from the scientific literature may differ from what stakeholders and decision makers believe. Comparing these perspectives can help better align science and policy making. Methods Drawing on research conducted as part of the PASTA (Physical Activity through Sustainable Transport Approaches) project, this study compares the perspectives of stakeholders on active transport with academic evidence, with regard to 1) barriers to active travel behaviour, and 2) policy measures effective in promoting active transport. In 7 case-study cities across Europe, stakeholder perspectives were investigated by means of semi-structured interviews and workshops involving a total of 59 stakeholders representing health, environment, transport and planning sectors. These perspectives are compared to findings from a review of reviews in the literature. Results There is a good degree of alignment on the relevance of infrastructure measures such as cycle lanes, bike sharing, and creating attractive routes; social environment measures such as awareness campaigns and travel to school campaigns; and regulatory measures such as pedestrian friendly zones and car parking restrictions. The literature seems to put more emphasis on the use of cycle subsidies and training, traffic calming and temporary road closures, while stakeholders lay more hope on increasing cycle parking than the literature warrants. The literature highlights the effectiveness of approaches such as showers at work, signage, individual marketing, and car free zones which are not mentioned in general by stakeholders. In reverse the quality of infrastructure, cycling maps, low emissions zones, highway codes and 30km/h zones are only highlighted by stakeholders. Conclusions The study identifies areas which could benefit from better research translation, or in reverse, where research gaps may exist. There are challenges in interpreting such comparisons, such as issues with language or terminology used in different sectors, with framework and implementation conditions which may affect stakeholders’ perception on feasibility, and with the difficulty of evaluating complex measures. The study proposes a novel approach to help better align research and policy research which should be further explored in the future with more targeted stakeholder interview protocols.

Reduction of sedentary time and an increase in physical activity offer potential to improve public health. However, quantifying physical activity behaviour under real world conditions is a major challenge and no standard of good practice is available. Our aim was to compare the results of physical activity and sedentary behaviour obtained with a self-reported instrument (Global Physical Activity Questionnaire (GPAQ)) and a wearable sensor (SenseWear) in a repeated measures study design. Healthy adults (41 in Antwerp, 41 in Barcelona and 40 in London) wore the SenseWear armband for seven consecutive days and completed the GPAQ on the final day. This was repeated three times. We used the Wilcoxon signed rank sum test, Spearman correlation coefficients, mixed effects regression models and Bland-Altman plots to study agreement between both methods. Mixed models were used to assess the effect of personal characteristics on the absolute and relative difference between estimates obtained with the GPAQ and SenseWear. Moderate to vigorous energy expenditure and duration derived from the GPAQ were significantly lower (p0.59). Results for sedentary behaviour did not differ, yet were poorly correlated (r

Background In order to increase the levels of physical activity in urban population, it is essential to evaluate how real-life policy interventions affect the population cycling attitudes and behaviour. There is evidence to support that policies of different nature have the potential to influence cycling behaviour, but few studies have done longitudinal and multiple interventions assessments. Methods As part of the PASTA European project (Physical Activity through Sustainable Travel Approaches), a longitudinal survey in 7 European cities provides data for the analysis. The questionnaires in the survey feature socio-demographic, psycho-social and city-specific policy-related questions. For each of the 7 cities, a selection of the highest impact policy measures implemented during the survey (November 2014 – January 2017) has been made. The effect of the policy interventions is studied as a natural experiment, with exposed and non-exposed population based on the distance to the infrastructure. The study includes unique a dose-response function which considers the exposure to multiple interventions, the technical quality of these interventions and an adapted bikeability index associated to each participant in each time stamp. Results Our sample includes 10,557 participants across the seven cities. Results will be shown for the complete dataset. Preliminary results from the initial questionnaire (baseline) are already available. A substantial part of the participants are initially either non-cyclists (24%) or cycling less than once a month (23%), which means that 47% of the sample could potentially start cycling or increase their frequency. Furthermore, 52% of the participants intend to increase their cycling rates in the future. All the cities have selected “top measures” and details are being collected. Measures range from bike to work campaigns, to cycle superhighways or other built environment interventions. For example, we have an estimate of a 36% of the participants in London being exposed to any kind of cycling policies. Once the evaluation model will be applied, results will show which profiles of participants are influenced by which types and dose of policies in their attitudes and decisions around cycling for transport. Conclusions The PASTA project explores the bridges between science and policymaking. This study develops and tests an innovative evaluation model which seeks to account for the impact in cycling behaviour of multiple interventions and for the quality of the build environment and interventions themselves. The relation between cycling policies and cycling behavioural aspects will help to determine the most promising policy avenues to promote cycling.

Background In order to increase the levels of physical activity in urban population, it is essential to know how a behavioural change towards cycling as active mobility can be produced and what factors influence people in their choice to cycle. But few studies have done longitudinal analysis of behavioural changes in cycling in relation to their policy context. Methods As part of the PASTA European project (Physical Activity through Sustainable Travel Approaches), a longitudinal survey in 7 European cities will provide the core data for the analysis. This survey was closed the 13th January 2017, after 2 years of data collection. The PASTA survey features specific questions designed to determine the attitudinal and behavioural profile of the participants. The conceptual framework used for the behavioural change assessment features an adaptation of the Transtheoretical Model of Behaviour Change and further developments, which describes five stages of change: Precontemplation, Contemplation, Preparation, Action and Maintenance. The sub-set of questions to determine the stage of change diagnosis are included in the initial (baseline) and final questionnaires, so that a “before” and “after” analysis can be undertaken. Other relevant psycho-social variables featured in the questionnaires will also be explored. The survey data is being complemented with background information including cycling policy and GIS data. Results Our sample is 10,557 participants across the seven cities (subject to further data cleaning). For this sample, a cross-city analysis of behavioural questions will be explored and compared for the initial (baseline) and final questionnaires. The baseline questionnaire has been already analysed and is showing a share of 23% of the sub-sampled participants (n=7,580) in the Precontemplation stage, 7% in Contemplation, 18% in Preparation, 41% in Action and 11% in Maintenance. In this presentation, results will be shown from the complete dataset (that is including all questionnaires) detailed for each of the seven cities, which is being analysed at the moment. The results of the stage diagnosis will be crossed with several socio-demographic variables, such as income, age, education level and sex. As an example, mean age is 40.08 (13.04) years and 54% of the participants are female. Conclusions Understanding the relative importance of the factors influencing mobility behaviour will help to determine the most promising policy avenues for the change towards cycling. This study puts together a unique mix of theories and methods in order to explore the bridges between behavioural change science and policy making.

Background There is increasing evidence that active mobility contributes to overall physical activity, and is negatively associated with obesity. However, the associations between active mobility, physical activity and body weight are complex. In the current analysis, a number of research gaps are tackled (e.g. including leisure-time physical activity, ensuring a balanced and large enough sample size for different transport modes, a multicentre study in European cities). Methods The PASTA project recruited over 10,000 adults in 7 European cities (Antwerp, Barcelona, London, Oerebro, Rome, Vienna, Zurich) to complete a questionnaire on how they move around the city, their levels of physical activity, and sociodemographics. Self-reported use of different transport modes (“How often do you currently use each of the following methods of travel to get to and from places?”) was operationalized in eight categories: car, bike, e-bike, walk, bike and walk, motorcycle/moped, public transport, mixed. BMI was the dependent variable in multivariate linear regression models; models were sex-stratified; and city was included as random effect. Dominant transport mode was the primary exposure variable; daily car drivers were selected as the reference category. A number of important confounders were included in the analysis: age, days per week of moderate leisure physical activity, education level, household income, alcohol use, smoking, and self-rated health. Results The final sample size for the cross-sectional analysis was 10,562 (54% female, age 40 ± 13). In the models linking transport mode and BMI, we observed stronger relationships in men. A male daily cyclist versus a male daily car driver has a BMI that is on average 1.26 (95%CI 0.64-1.89) points lower, equivalent to 4 kg in our sample. For women, the difference was smaller and not statistically significant: 0.54 BMI points (95%CI -0.14-1.22) or 1.5 kg. In the full sample, we observed the largest difference in BMI for active modes (walking, cycling, and a combination) compared to daily car drivers, and a smaller difference for public transport (-0.58 BMI points; 95%CI -1.01-(-0.16)). People that combine active modes with motorized modes still have a lower BMI compared to only car drivers (-0.33 BMI points; 95%CI -0.79-0.13). Conclusions Men who drive cars as their main form of transport are on average 4kg heavier than those who cycle. In the future, we plan to investigate causality in a longitudinal study design by including results from a follow-up questionnaire reassessing BMI 1-2 years later in the same sample.

Few studies have investigated new onset of asthma in adults in relation to air pollution. The aim of this study is to investigate the association between modeled background levels of traffic-related air pollution at the subjects' home addresses and self-reported asthma incidence in a European adult population.Adults from the European Respiratory Health Survey were included (n = 4185 from 17 cities). Subjects' home addresses were geocoded and linked to outdoor nitrogen dioxide (NO2) estimates, as a marker of local traffic-related pollution. We obtained this information from the 1-km background NO2 surface modeled in APMoSPHERE (Air Pollution Modelling for Support to Policy on Health and Environmental Risk in Europe). Asthma incidence was defined as reporting asthma in the follow-up (1999 to 2001) but not in the baseline (1991 to 1993).A positive association was found between NO2 and asthma incidence (odds ratio 1.43; 95% confidence interval = 1.02 to 2.01) per 10 microg/m. Results were homogeneous among centers (P value for heterogeneity = 0.59).We found an association between a marker of traffic-related air pollution and asthma incidence in European adults.

Epidemiological studies have shown weak or inconsistent associations between ambient air pollutants and allergic sensitization. The aim of this study was to evaluate whether regional urban air pollution may partly explain the large variation in the prevalence of allergic sensitization across cities of the European Community Respiratory Health Survey (ECRHS) II.ECRHS is a cross-sectional survey initiated in 29 countries across Europe in the 1990s (ECRHS I) with a follow-up conducted 10 years later (ECRHS II). Subject characteristics were measured by questionnaires and blood tests conducted for the measurement of specific immunoglobulin E. Fine particle mass (PM(2.5),2.5 microm) and sulphur on PM(2.5) were measured in 21 centres and annual averages of urban regional background air pollution were calculated. Results were scaled by an interquartile range increase in ambient PM(2.5) (6.03 microg/m(3)) and sulphur (1336 ng/m(3)). Generalized estimating equations were applied to compute population average effect estimates with adjustment for age, gender, smoking habit, education and number of siblings.A notable variation in pollution level and prevalence of allergic sensitization was observed. Moreover, exposure to urban regional background air pollution was not associated with allergic sensitization; adjusted odds ratios and 95% confidence interval were 1.02 (0.95-1.09) for PM(2.5) and 1.08 (0.86-1.31) for sulphur. These statistically non-significant associations were sensitive to model specification.The study suggests that regional air pollution measured at fixed sites is not associated with allergic sensitization among adults in ECRHS II.

Background Annoyance due to air pollution is a subjective score of air quality, which has been incorporated into the National Environmental monitoring of some countries. The objectives of this study are to describe the variations in annoyance due to air pollution in Europe and its individual and environmental determinants. Methods This study took place in the context of the European Community Respiratory Health Survey II (ECRHS II) that was conducted during 1999-2001. It included 25 centres in 12 countries and 7867 randomly selected adults from the general population. Annoyance due to air pollution was self-reported on an 11-point scale. Annual mean mass concentration of fine particles (PM2.5) and its sulphur (S) content were measured in 21 centres as a surrogate of urban air pollution. Results Forty-three per cent of participants reported moderate annoyance (1-5 on the scale) and 14% high annoyance (≥6) with large differences across centres (2-40% of high annoyance). Participants in the Northern European countries reported less annoyance. Female gender, nocturnal dyspnoea, phlegm and rhinitis, self-reported car and heavy vehicle traffic in front of the home, high education, non-smoking and exposure to environmental tobacco smoke were associated with higher annoyance levels. At the centre level, adjusted means of annoyance scores were moderately associated with sulphur urban levels (slope 1.43 μg m−3, standard error 0.40, r = 0.61). Conclusions Annoyance due to air pollution is frequent in Europe. Individuals' annoyance may be a useful measure of perceived ambient quality and could be considered a complementary tool for health surveillance

Fine particulate matter (PM2.5) was sampled at 5 Spanish locations during the European Community Respiratory Health Survey II (ECRHS II). In an attempt to identify and quantify PM2.5 sources, sourc ...

Objective Walking and cycling for transportation (i.e. active transportation, AT), provide substantial health benefits from increased physical activity (PA). However, risks of injury from exposure to motorized traffic and their emissions (i.e. air pollution) exist. The objective was to systematically review studies conducting health impact assessment (HIA) of a mode shift to AT on grounds of associated health benefits and risks. Methods Systematic database searches of MEDLINE, Web of Science and Transportation Research International Documentation were performed by two independent researchers, augmented by bibliographic review, internet searches and expert consultation to identify peer-reviewed studies from inception to December 2014. Results Thirty studies were included, originating predominantly from Europe, but also the United States, Australia and New Zealand. They compromised of mostly HIA approaches of comparative risk assessment and cost–benefit analysis. Estimated health benefit–risk or benefit–cost ratios of a mode shift to AT ranged between −2 and 360 (median=9). Effects of increased PA contributed the most to estimated health benefits, which strongly outweighed detrimental effects of traffic incidents and air pollution exposure on health. Conclusion Despite different HIA methodologies being applied with distinctive assumptions on key parameters, AT can provide substantial net health benefits, irrespective of geographical context.