The Health Economic Assessment Tool (HEAT) for walking and cycling - experiences from 10 years of application of a health impact assessment tool in policy and practice.

Introduction: In recent years, walking and cycling have moved into the focus as promising approaches to achieve public health, sustainable transport, climate goals and better urban resilience. However, they are only realistic transport and activity options for a large proportion of the population when they are safe, inclusive and convenient. One way to increase their recognition in transport policy is the inclusion of health impacts of walking and cycling into transport economic appraisals. Methods: The Health Economic Assessment Tool (HEAT) for walking and cycling calculates: if x people walk or cycle a distance of y on most days, what is the economic value of impacts on premature mortality, taking into account effects of physical activity, air pollution and road fatalities, as well as effects on carbon emissions. Different data sources were collated to examine how the HEAT in more than 10 years of existence, and to identify lessons learned and challenges. Results: Since its launch in 2009, the HEAT has gained wide recognition as a user friendly, yet robust, evidence-based tool usable by academics, policymakers, and practitioners. Originally designed for use in Europe, it has since been expanded for global use. Discussion: Challenges for a wider uptake of health-impact assessment (HIA) tools including active transport such as HEAT are the promotion and dissemination to local practitioners and policy makers also outside European and English-speaking regions and in low- and middle-income contexts, further increasing usability, and more generally the advancement of systematic data collection and impact quantification related to walking and cycling.

The impact of black carbon (BC) on mode-specific galvanic skin response (GSR) as a measure of stress in urban environments.

Previous research has shown that walking and cycling could help alleviate stress in cities, however there is poor knowledge on how specific microenvironmental conditions encountered during daily journeys may lead to varying degrees of stress experienced at that moment. We use objectively measured data and a robust causal inference framework to address this gap. Using a Bayesian Doubly Robust (BDR) approach, we find that black carbon exposure statistically significantly increases stress, as measured by Galvanic Skin Response (GSR), while cycling and while walking. Augmented Outcome Regression (AOR) models indicate that greenspace exposure and the presence of walking or cycling infrastructure could reduce stress. None of these effects are statistically significant for people in motorized transport. These findings add to a growing evidence-base on health benefits of policies aimed at decreasing air pollution, improving active travel infrastructure and increasing greenspace in cities.

The MOBIS dataset: a large GPS dataset of mobility behaviour in Switzerland.

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. Supplementary Information: The online version contains supplementary material available at 10.1007/s11116-022-10299-4.

Integrated Impact Assessment of Active Travel: Expanding the Scope of the Health Economic Assessment Tool (HEAT) for Walking and Cycling.

The World Health Organization'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.

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.

Comparing the lung cancer burden of ambient particulate matter using scenarios of air quality standards versus acceptable risk levels.

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.

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 (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.

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

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<.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. CONCLUSIONS: We 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.

Effects of physical activity and air pollution on blood pressure.

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.

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

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.

Transport mode choice and body mass index: Cross-sectional and longitudinal evidence from a European-wide study.

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.

Health impact assessment of cycling network expansions in European cities.

We conducted a health impact assessment (HIA) of cycling network expansions in seven European cities. We modeled the association between cycling network length and cycling mode share and estimated health impacts of the expansion of cycling networks. First, we performed a non-linear least square regression to assess the relationship between cycling network length and cycling mode share for 167 European cities. Second, we conducted a quantitative HIA for the seven cities of different scenarios (S) assessing how an expansion of the cycling network [i.e. 10% (S1); 50% (S2); 100% (S3), and all-streets (S4)] would lead to an increase in cycling mode share and estimated mortality impacts thereof. We quantified mortality impacts for changes in physical activity, air pollution and traffic incidents. Third, we conducted a cost-benefit analysis. The cycling network length was associated with a cycling mode share of up to 24.7% in European cities. The all-streets scenario (S4) produced greatest benefits through increases in cycling for London with 1,210 premature deaths (95% CI: 447-1,972) avoidable annually, followed by Rome (433; 95% CI: 170-695), Barcelona (248; 95% CI: 86-410), Vienna (146; 95% CI: 40-252), Zurich (58; 95% CI: 16-100) and Antwerp (7; 95% CI: 3-11). The largest cost-benefit ratios were found for the 10% increase in cycling networks (S1). If all 167 European cities achieved a cycling mode share of 24.7% over 10,000 premature deaths could be avoided annually. In European cities, expansions of cycling networks were associated with increases in cycling and estimated to provide health and economic benefits.

Policies to Promote Active Travel: Evidence from Reviews of the Literature.

PURPOSE OF REVIEW: 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. RECENT FINDINGS: 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.

Towards a Comprehensive Conceptual Framework of Active Travel Behavior: a Review and Synthesis of Published Frameworks.

PURPOSE OF REVIEW: This paper reviews the use of conceptual frameworks in research on active travel, such as walking and cycling. Generic framework features and a wide range of contents are identified and synthesized into a comprehensive framework of active travel behavior, as part of the Physical Activity through Sustainable Transport Approaches project (PASTA). PASTA is a European multinational, interdisciplinary research project on active travel and health. RECENT FINDINGS: Along with an exponential growth in active travel research, a growing number of conceptual frameworks has been published since the early 2000s. Earlier frameworks are simpler and emphasize the distinction of environmental vs. individual factors, while more recently several studies have integrated travel behavior theories more thoroughly. Based on the reviewed frameworks and various behavioral theories, we propose the comprehensive PASTA conceptual framework of active travel behavior. We discuss how it can guide future research, such as data collection, data analysis, and modeling of active travel behavior, and present some examples from the PASTA project.

Physical activity and sedentary behaviour in daily life: A comparative analysis of the Global Physical Activity Questionnaire (GPAQ) and the SenseWear armband.

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 (p<0.05) compared to the SenseWear, yet these variables showed significant correlations ranging from 0.45 to 0.64. Estimates of vigorous-intensity physical activity in particular showed high similarity (r>0.59). Results for sedentary behaviour did not differ, yet were poorly correlated (r<0.25). The differences between all variables were reproducible across repeated measurements. In addition, we observed a relationship between these differences and BMI, body fat and physical activity domain. Due to the lack of a standardized protocol, results from different studies measuring physical activity and sedentary behaviour are difficult to compare. Therefore, we suggested an easy-to-implement approach for future studies adding the GPAQ to the wearable of choice as a basis for comparisons.

Health benefits of a reduction of PM10 and NO2 exposure after implementing a clean air plan in the Agglomeration Lausanne-Morges.

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.

Wearable Sensors for Personal Monitoring and Estimation of Inhaled Traffic-Related Air Pollution: Evaluation of Methods.

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.

Can air pollution negate the health benefits of cycling and walking?

Active travel (cycling, walking) is beneficial for the health due to increased physical activity (PA). However, active travel may increase the intake of air pollution, leading to negative health consequences. We examined the risk-benefit balance between active travel related PA and exposure to air pollution across a range of air pollution and PA scenarios. The health effects of active travel and air pollution were estimated through changes in all-cause mortality for different levels of active travel and air pollution. Air pollution exposure was estimated through changes in background concentrations of fine particulate matter (PM2.5), ranging from 5 to 200µg/m3. For active travel exposure, we estimated cycling and walking from 0 up to 16h per day, respectively. These refer to long-term average levels of active travel and PM2.5 exposure. For the global average urban background PM2.5 concentration (22µg/m3) benefits of PA by far outweigh risks from air pollution even under the most extreme levels of active travel. In areas with PM2.5 concentrations of 100µg/m3, harms would exceed benefits after 1h 30min of cycling per day or more than 10h of walking per day. If the counterfactual was driving, rather than staying at home, the benefits of PA would exceed harms from air pollution up to 3h 30min of cycling per day. The results were sensitive to dose-response function (DRF) assumptions for PM2.5 and PA. PA benefits of active travel outweighed the harm caused by air pollution in all but the most extreme air pollution concentrations.

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

INTRODUCTION: Only 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 (active mobility, AM) are well suited to provide regular PA. The European research project Physical Activity through Sustainable Transport Approaches (PASTA) pursues the following aims: (1) to investigate correlates and interrelations of AM, PA, air pollution and crash risk; (2) to evaluate the effectiveness of selected interventions to promote AM; (3) to improve health impact assessment (HIA) of AM; (4) to foster the exchange between the disciplines of public health and transport planning, and between research and practice. METHODS AND ANALYSIS: PASTA pursues a mixed-method and multilevel approach that is consistently applied in seven case study cities. Determinants of AM and the evaluation of measures to increase AM are investigated through a large scale longitudinal survey, with overall 14,000 respondents participating in Antwerp, Barcelona, London, Örebro, Rome, Vienna and Zurich. Contextual factors are systematically gathered in each city. PASTA generates empirical findings to improve HIA for AM, for example, with estimates of crash risks, factors on AM-PA substitution and carbon emissions savings from mode shifts. Findings from PASTA will inform WHO's online Health Economic Assessment Tool on the health benefits from cycling and/or walking. The study's wide scope, the combination of qualitative and quantitative methods and health and transport methods, the innovative survey design, the general and city-specific analyses, and the transdisciplinary composition of the consortium and the wider network of partners promise highly relevant insights for research and practice. ETHICS AND DISSEMINATION: Ethics approval has been obtained by the local ethics committees in the countries where the work is being conducted, and sent to the European Commission before the start of the survey. The PASTA website (http://www.pastaproject.eu) is at the core of all communication and dissemination activities.

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

BACKGROUND: Physical 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/DESIGN: A 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. DISCUSSION: The 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.