Sustainable Transport Approaches Research Articles

Air pollution, greenspace and active travel infrastructure impacts on stress while walking, cycling, or in motorized transport

BACKGROUND AND AIM Recent studies have shown that active travel is generally associated with lower levels of both perceived and measured stress. Specific microenvironmental conditions encountered during daily journeys, however, may lead to varying degrees of stress experienced at that moment. Our aim is to evaluate how travel mode-specific stress, as measured by Galvanic Skin Response (GSR), varies given different levels of Black Carbon (BC) and greenspace exposure, and by road type. METHODS BC and GSR were collected alongside confounders and travel information from 122 participants across 3 European cities for 3 weeks as part of the Physical Activity through Sustainable Transport Approaches (PASTA) study. Greenspace and road type were identified from the geo-locations recorded by a GPS device also worn by participants. A Bayesian Doubly Robust (BDR) estimation method via bootstrapping (which allows us to incorporate randomness originating from the random nature of the unobserved observations of GSR and to simulate the posterior distribution of GSR given the measured covariates) was employed to estimate the effect of BC, green space and road type on cycling-/walking-/motoring-specific GSR, while accounting for confounders such as physical activity, gender, and age. RESULTS BC significantly increases GSR when people are cycling or walking, but has no statistically significant effect on people in motorized transport. In reverse, greenspace and traveling on roads with active travel infrastructures (i.e. cycleways and/or pedestrian paths) both lead to lower GSR while walking and cycling, with again no effect on people in motorised transport. CONCLUSIONS Decreasing air pollution, improving active travel infrastructure and increasing greenspace along travel routes can reduce stress experienced during active travel. Reducing traffic and improving active travel microenvironments may thus further enhance benefits of walking and cycling in reducing stress in urban populations. KEYWORDS Built environment, urban planning, stress, air pollution, active travel, causal inference.

Day-to-day intrapersonal variability in mobility patterns and association with perceived stress: A cross-sectional study using GPS from 122 individuals in three European cities

Many aspects of our life are related to our mobility patterns and individuals can exhibit strong tendencies towards routine in their daily lives. Intrapersonal day-to-day variability in mobility patterns has been associated with mental health outcomes. The study aims were: (a) calculate intrapersonal day-to-day variability in mobility metrics for three cities; (b) explore interpersonal variability in mobility metrics by sex, season and city, and (c) describe intrapersonal variability in mobility and their association with perceived stress.Data came from the Physical Activity through Sustainable Transport Approaches (PASTA) project, 122 eligible adults wore location measurement devices over 7-consecutive days, on three occasions during 2015 (Antwerp: 41, Barcelona: 41, London: 40). Participants completed the Short Form Perceived Stress Scale (PSS-4). Day-to-day variability in mobility was explored via six mobility metrics using distance of GPS point from home (meters:m), distance travelled between consecutive GPS points (m) and energy expenditure (metabolic equivalents:METs) of each GPS point collected (n = 3,372,919). A Kruskal-Wallis H test determined whether the median daily mobility metrics differed by city, sex and season. Variance in correlation quantified day-to-day intrapersonal variability in mobility. Levene's tests or Kruskal-Wallis tests were applied to assess intrapersonal variability in mobility and perceived stress.There were differences in daily distance travelled, maximum distance from home and METS between individuals by sex, season and, for proportion of time at home also, by city. Intrapersonal variability across all mobility metrics were highly correlated; individuals had daily routines and largely stuck to them. We did not observe any association between stress and mobility.Individuals are habitual in their daily mobility patterns. This is useful for estimating environmental exposures and in fuelling simulation studies.

The effects of traveling in different transport modes on galvanic skin response (GSR) as a measure of stress: An observational study.

Stress is one of many ailments associated with urban living, with daily travel a potential major source. Active travel, nevertheless, has been associated with lower levels of stress compared to other modes. Earlier work has relied on self-reported measures of stress, and on study designs that limit our ability to establish causation. To evaluate effects of daily travel in different modes on an objective proxy measure of stress, the galvanic skin response (GSR). We collected data from 122 participants across 3 European cities as part of the Physical Activity through Sustainable Transport Approaches (PASTA) study, including: GSR measured every minute alongside confounders (physical activity, near-body temperature) during three separate weeks covering 3 seasons; sociodemographic and travel information through questionnaires. Causal relationships between travel in different modes (the "treatment") and stress were established by using a propensity score matching (PSM) approach to adjust for potential confounding and estimating linear mixed models (LMM) with individuals as random effects to account for repeated measurements. In three separate analyses, we compared GSR while cycling to not cycling, then walking to not walking then motorized (public or private) travel to any activity other than motorized travel. Depending on LMM formulations used, cycling reduces 1-minute GSR by 5.7% [95% CI: 2.0-16.9%] to 11.1% [95% CI: 5.0-24.4%] compared to any other activity. Repeating the analysis for other modes we find that: walking is also beneficial, reducing GSR by 3.9% [95% CI: 1.4-10.7%] to 5.7% [95% CI: 2.6-12.3%] compared to any other activity; motorized mode (private or public) in reverse increases GSR by up to 1.1% [95% CI: 0.5-2.9%]. Active travel offers a welcome way to reduce stress in urban dwellers' daily lives. Stress can be added to the growing number of evidence-based reasons for promoting active travel in cities.

Stress in different travel modes: an observational study of Galvanic Skin Response measurements (GSR)

BACKGROUND AND AIM: Stress is often associated with urban living, although active travel may reduce stress compared to other modes. Earlier work, however, has relied on self-reported measures of stress, and on study designs that limit our ability to establish causation. METHODS: Galvanic Skin Response (GSR), a proxy for stress, was collected alongside confounders and travel information from 122 participants across 3 European cities during 3 weeks as part of the Physical Activity through Sustainable Transport Approaches (PASTA) study. Causal effects of daily travel in different modes on GSR were evaluated through propensity score matching (PSM) and linear mixed models (LMMs). Separately, cycling, then walking then motorized (public or private) travel were compared to “any other activity”. RESULTS:Cycling reduces 1-minute GSR by 7.6% [95% CI: 2.6-22%] to 10.5% [95% CI: 4.9-22.7%] compared to any other activity. Walking is also beneficial, reducing GSR by 4.3% [95% CI: 1.6-11.9%] to 6.2% [95% CI: 2.9-13.3%] compared to any other activity; motorized mode (private or public) in reverse increases GSR by up to 1.4% [95% CI: 0.6-3.2%]. CONCLUSIONS:Active travel offers a welcome way to reduce stress in urban dwellers’ daily lives. Stress can be added to the growing number of evidence based reasons for promoting active travel in cities. KEYWORDS: Built environment, walkability, causal inference

Smartphone Mobile Sensing and Geospatial Physical Activity Space Analytics in the PASTA-LA study

Physical activity is intimately linked to the built environment and health. Major on-going efforts are being made to increase physical activity rates in urban settings. One such effort, quickly becoming prevalent across many global cities, is the implementation of bike sharing programs. In October 2017, UCLA launched the Bruin Bike Share program. It provided a unique opportunity to conduct a before-and-after natural intervention study, the Physical Activity through Sustainable Transport Approaches in Los Angeles (PASTA-LA) study, to assess the health-related outcomes of bike-sharing programs. During the 2016-2018 study period, the PASTA-LA study enrolled 440 physically-capable participants from the UCLA-Westwood area. Participants were administered online questionnaires and a smartphone app (MOVES) was deployed on their phones for location and activity tracking. A nested sample of 140 participants were also outfitted with research grade GPS and accelerometers for comparison. Across all participants, over 30 million observations of location and activity were recorded. Using these ‘big data’, we can address our specific research questions: (1) can smartphones be used instead of expensive research-grade devices without sacrificing measurement validity, and (2) can these ‘big data’ be used to model Physical Activity Spaces (PASs) to better quantify environmental context. We have addressed these research questions using advanced geospatial and geostatistical approaches. To evaluate context variable allocation for individuals, we have used location and activity levels (steps) to demonstrate the predictive accuracy of four approaches to defining physical activity space: (1) circular home buffers, (2) directional ellipses, (3) machine learning route allocation models, and (4) kernel density ranking. These models can be used to quantify variables such as exposure to green space, dose of air pollution, and other neighborhood-based statistics that are instrumental for spatial models of association (e.g. such as the impact of heat exposure on physical activity rates, as moderated by green space access.)

Cyclist crash rates and risk factors in a prospective cohort in seven European cities

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.

Impacts of study design on sample size, participation bias, and outcome measurement: A case study from bicycling research

IntroductionMeasuring 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. MethodsWe 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. ResultsRelative 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. ConclusionsIn 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.

Correlates of Walking for Travel in Seven European Cities: The PASTA Project.

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 (). 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

Evaluation of Different Recruitment Methods: Longitudinal, Web-Based, Pan-European Physical Activity Through Sustainable Transport Approaches (PASTA) Project.

BackgroundSufficient 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.ObjectiveThis 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.MethodsA 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.ResultsOverall, 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<.001), with the highest number in Zurich (11.0, SE 0.33) and the lowest in Örebro (4.8, SE 0.17). Collaboration with local organizations, the use of Facebook and mailing lists, and direct street recruitment were the most effective approaches in reaching a high share of participants (P<.001). Considering the invested working hours, Facebook was one of the most time-efficient methods. Compared with the cities’ census data, the composition of study participants was broadly representative in terms of gender distribution; however, the study included younger and better-educated participants.ConclusionsWe observed that offering a mixed recruitment approach was highly effective in achieving a high participation rate. The highest attrition rate and the lowest average number of questionnaires filled in per participant were observed in Örebro, which also recruited participants through random sampling. These findings suggest that people who are more interested in the topic are more willing to participate and stay in a survey than those who are selected randomly and may not have a strong connection to the research topic. Although direct face-to-face contacts were very effective with respect to the number of recruited participants, recruiting people through social media was not only effective but also very time efficient. The collected data are based on one of the largest recruited longitudinal samples with a common recruitment strategy in different European cities.

The effects of transport mode use on self-perceived health, mental health, and social contact measures: A cross-sectional and longitudinal study

BackgroundTransport 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. MethodsWe 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. ResultsIn 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. ConclusionsSimilarity of findings across cities suggested that active transport, especially bicycle use, should be encouraged to improve population health and social outcomes.

European cyclists' travel behavior: Differences and similarities between seven European (PASTA) cities

Background The number of trips of the average urban inhabitant per year has grown steadily in recent years – but we are actually moving (our bodies) less. Every day, millions of trips are made by car (where 50% of these are less than 5 km) or other motorised private vehicles as well as with public transport, while only a small percentage of trips are made by active modes, such as cycling and walking. This lack of physical activity causes major health problems for individuals and great economic costs for society as a whole. To reverse these negative impacts the World Health Organisation (WHO) recommends a minimum of 150 minutes of moderate physical activity per week (e.g. 30 minutes 5 times per week). Replacing short motorized trips can feasibly increase physical activity in everyday life. Methods PASTA “Physical Activity trough sustainable transport approaches” collected data in a longitudinal web-based survey with a cohort design to study the effects of active mobility on overall physical activity and health. The target population for the survey was the entire adult population in 7 European Cities. In total, more than 12.000 people participated in the survey with half of them filling in valid travel diaries on actual trips on a regular basis. Results Differences in sociodemographics and travel behaviour of cyclists in the seven cities will be shown in the paper. Preliminary results reveal that more than 2.000 participants from the total sample can be identified as regular cyclists (reported in their trip diaries) with an average age of 40 years. Most of them are highly educated and full time employed. In comparison to non-regular cyclists, the share of female is lower; however the share of people who have a driving licence and who have at least sometimes access to a car is higher within the group of cyclists. About 85% of regular cyclists reach at least 30 cycling-minutes per reported day. This indicates that a high share of regular cyclists can reach the WHO´s recommended level only by routine cycling trips. Further the threshold of reaching the minimum recommendation by cycling will be analysed between the cities. Conclusions In this study, we compare cyclists and their travel behaviour in seven European cities. Our first results indicate, that cycling as a mean of transport can help reach the WHO’s physical activity recommendations and including physical activity into daily life without much of extra effort.

Respiratory Health Effects of Black Carbon and Physical Activity Depend on Baseline Exposure Levels

Background/Aim: The Physical Activity through Sustainable Transport Approaches PASTA) study aims to increase physical activity (PA) levels by promoting active mobility. Performing PA in traffic, ho...

A Comparison between Literature Findings and Stakeholder Perspectives on Active Travel Promotion

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.

Developing a Score to Assess the Policy Environment for Cycling and Walking Promotion in Cities – Results of a Feasibility Study

Background The suitability of transport environments for active mobility (i.e. cycling, walking) depends on its recognition in policy and transport planning processes. While a range of quantitative scores exist to assess cycling and walking environments, to date hardly any scores focus on the qualitative aspects of the policy and social environment. Methods As part of the PASTA (Physical Activity through Sustainable Transport Approaches) study, information on the social, policy and planning contexts was collected in seven cities through standardized workshops and semi-structured interviews with key stakeholders in health and transport sectors. Information was collected on main policies and projects in place, challenges in supporting active mobility and a qualitative rating of local pedestrians’ and cyclists’ environments. A purposive literature search in literature databases (ScienceDirect, PubMed, JSTOR) did not return any qualitative score to assess the policy/social environment for active mobility. Grey literature searches and expert input revealed the Copenhagenize Index as most suitable guidance. Results A subset of the Copenhagenize Index categories’ was adapted and used to analyse the qualitative information from the workshops and stakeholder interviews on the social (bicycle/walking culture, social acceptance) and the policy environment (advocacy, politics, urban planning), respectively. Perception of safety was assessed using respondent’s data from the PASTA survey. Feasibility to derive scores was tested using data from two cities (Zurich, London). Sequential text interpretation was used to derive a scoring for walking/cycling, i.e. two experts independently derived a score from 0-4 for each of the categories, one from the local PASTA team and one rating each of the cities. Sections to be used from the coded interview and workshop reports were pre-determined. Explanations on why a particular score was given were recorded. Disagreements were resolved through discussion and arguments for the agreed score were documented. Conclusions The approach was found to be feasible to derive initial scores to capture the policy and social context for walking/cycling, respectively, which can be included into quantitative analysis of active transport data. Further work will be done to test and refine the approach with the data from the other five PASTA cities. Validation will be explored using indices of bikeability, walkability and traffic calming that will be created using quantitative data from each of the PASTA cities as well as information from the PASTA survey on social acceptance of cycling and walking, respectively, in each of the cities.

Health Impact Assessment of Cycling Network Expansions in European Cities

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.

Does an Increase in Walking and Cycling Translate into a Higher Overall Physical Activity Level?

Background Physical inactivity is the fourth leading cause of global mortality. Hence, the Physical Activity through Sustainable Transport Approaches (PASTA) study aims to promote active mobility (i.e. walking and cycling) as an innovative measure to increase physical activity levels. Studying the health benefits of an increase in active mobility is challenging as we lack understanding of its relation with overall physical activity. Therefore, we studied the association between changes in overall physical activity level and changes in the amount of active mobility and leisure-time physical activity. Methods A set of online questionnaires was deployed in seven European cities to collect data on travel and physical activity behaviour. After completing a baseline questionnaire, follow-up questionnaires were sent every thirteen days, alternating a short and a longer version (every third follow-up). The amount of total and domain-specific (i.e. transport and leisure-time) physical activity was reported in the Global Physical Activity Questionnaire (GPAQ) (separating cycling and walking for transport). The GPAQ was incorporated in the baseline questionnaire and the longer version of the follow-up. To analyse the association between a change in overall physical activity and a change in active mobility and leisure-time physical activity, a mixed effect model was used. This model included sex, age and season as covariates and all interaction terms for active mobility and leisure-time physical activity. We used random participant effects nested in city effects to account for repeated measures. Results 3083 participants completed at least two GPAQs. The maximum number of GPAQs collected per participant was 14 and the median amount of time between two questionnaires was 51 days (IQR:44-86 days). A one-minute increase in daily active mobility or leisure-time physical activity was associated with an increase of 1.14 (p 0.05), so participants who increased their active mobility did not decrease their leisure-time physical activity accordingly. Changes in overall physical activity were not affected by sex, age and season (p>0.05). However, the increase in total physical activity per unit increase in active mobility depended on sex (p Conclusions Our findings provide evidence that an increase in active mobility translated into an increase in overall physical activity, while the amount of leisure-time physical activity was not modified.

Health impact assessment of cycling networks of seven, diverse European cities: Application of the PASTA model

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 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 of 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 were interested in assessing whether the length of the cycling network (km) predicts the cycling mode share (%) and what the associated health impacts and co-benefits might be. Methods: We developed and applied the PASTA HIA model to a comparable AM measure (i.e. km of cycling network) across the seven PASTA cities. City characteristics of demographics, cycling network, mode share, PA levels, air quality, traffic safety and health status were collected from city, transport and health statistics. Across different scenarios, we estimated how increases in km of cycling network would lead to increases in cycling mode share. We quantified health impacts of increases in cycling mode share in terms of changes to PA levels, exposure to air pollution and traffic hazards. Exposure response functions were obtained from the literature based on best available evidence. Results: Our results show that the extension of cycling networks can explain up to 80% of variability in cycling mode share in the seven PASTA cities. Health benefits resulting from increases in cycling mode share are predominantly due to increases in PA levels that outweigh associated detriments of air pollution exposure and traffic incidents. Environmental co-benefits were estimated. Conclusions: Expansion of cycling networks in European cities can promote increases in cycling mode share. Increases in cycling mode share provide considerable health and other co-benefits.

Physical Activity through Sustainable Transport Approaches (PASTA): a study protocol for a multicentre project

IntroductionOnly one-third of the European population meets the minimum recommended levels of physical activity (PA). Physical inactivity is a major risk factor for non-communicable diseases. Walking and cycling for transport...

Physical Activity through Sustainable Transport Approaches (PASTA): protocol for a multi-centre, longitudinal study.

BackgroundPhysical inactivity is one of the leading risk factors for non-communicable diseases, yet many are not sufficiently active. The Physical Activity through Sustainable Transport Approaches (PASTA) study aims to better understand active mobility (walking and cycling for transport solely or in combination with public transport) as an innovative approach to integrate physical activity into individuals’ everyday lives. The PASTA study will collect data of multiple cities in a longitudinal cohort design to study correlates of active mobility, its effect on overall physical activity, crash risk and exposure to traffic-related air pollution.Methods/DesignA set of online questionnaires incorporating gold standard approaches from the physical activity and transport fields have been developed, piloted and are now being deployed in a longitudinal study in seven European cities (Antwerp, Barcelona, London, Oerebro, Rome, Vienna, Zurich). In total, 14000 adults are being recruited (2000 in each city). A first questionnaire collects baseline information; follow-up questionnaires sent every 13 days collect prospective data on travel behaviour, levels of physical activity and traffic safety incidents. Self-reported data will be validated with objective data in subsamples using conventional and novel methods. Accelerometers, GPS and tracking apps record routes and activity. Air pollution and physical activity are measured to study their combined effects on health biomarkers. Exposure-adjusted crash risks will be calculated for active modes, and crash location audits are performed to study the role of the built environment. Ethics committees in all seven cities have given independent approval for the study.DiscussionThe PASTA study collects a wealth of subjective and objective data on active mobility and physical activity. This will allow the investigation of numerous correlates of active mobility and physical activity using a data set that advances previous efforts in its richness, geographical coverage and comprehensiveness. Results will inform new health impact assessment models and support efforts to promote and facilitate active mobility in cities.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-2453-3) contains supplementary material, which is available to authorized users.

A13 Comprehensive Health Impact Assessment for Active Travel: A "PASTA" project approach

Abstract Background Health impact assessment (HIA) is a combination of methods by which a policy or intervention may be assessed and judged for its potential effects on the health of the population. The HIA is classified in four levels of depth: desk-based, rapid, intermediate and comprehensive. These different levels vary in resources, capacity, duration and level of health impacts. Comprehensive HIA is the more complex, collecting and analyzing data from different sources. It also offers more accurate estimates of the health impacts related with multiple pathways and health determinants. PASTA (Physical Activity through Sustainable Transport Approaches) is a European project with detailed case studies in seven cities (Antwerp, Barcelona, London, Orebro, Rome, Vienna and Zurich) that focuses on promoting and assessing active travel and developing a new comprehensive health impact assessment (HIA) model for active transport. Methods Identifying stakeholders and experts in each city. conduct workshops (one in each city) with stakeholders and experts. Perform individual interviews (12 in each city) with experts and stakeholders. Conduct a systematic review on active travel HIA, risk assessments and cost benefits analysis published in peer review journals. Conduct systematic reviews to identify the most robust epidemiological evidence between health exposures and outcomes. Build a HIA model quantifying the health risk and benefits related with active travel interventions and measure the uncertainties. Report and communicate the results to stakeholders, experts and citizens. Results The workshops and interviews showed their importance to identify 1) main interventions or policies on active travel in the local context; 2) the requirements, priorities and expectations of HIA in the decision making process; 3) local and regional data sources; and 4) key stakeholder networks for participation and dissemination. The systematic review of HIA showed that there is further improvement needed in 1) the identification and quantification of health determinants (e.g. physical activity, traffic hazards, air pollution, noise, etc.); 2) selection of robust dose-response functions based on the weight of evidence; 3) the harmonization of methods, definitions and assumptions used; and 4) the close collaboration between urban planners, transport practitioners and health experts. Conclusions The novel approach of integrating stakeholder and expert workshops, interviews, systematic reviews and evidence based approaches in the HIA process is a necessary advancement for comprehensive HIA for active travel.