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.

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.

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.

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.

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.

Contrasts in active transport behaviour across four countries: how do they translate into public health benefits?

OBJECTIVE: Countries and regions vary substantially in transport related physical activity that people gain from walking and cycling and in how this varies by age and gender. This study aims to quantify the population health impacts of differences between four settings. METHOD: The Integrated Transport and Health Model (ITHIM) was used to estimate health impacts from changes to physical activity that would arise if adults in urban areas in England and Wales adopted travel patterns of Switzerland, the Netherlands, and California. The model was parameterised with data from travel surveys from each setting and estimated using Monte Carlo simulation. Two types of scenarios were created, one in which the total travel time budget was assumed to be fixed and one where total travel times varied. RESULTS: Substantial population health benefits would accrue if people in England and Wales gained as much transport related physical activity as people in Switzerland or the Netherlands, whilst smaller but still considerable harms would occur if active travel fell to the level seen in California. The benefits from achieving the travel patterns of the high cycling Netherlands or high walking Switzerland were similar. CONCLUSION: Differences between high income countries in how people travel have important implications for population health.

Health impact assessment of active transportation: A systematic review.

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.

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.

Systematic review and meta-analysis of reduction in all-cause mortality from walking and cycling and shape of dose response relationship.

BACKGROUND AND OBJECTIVE: Walking and cycling have shown beneficial effects on population risk of all-cause mortality (ACM). This paper aims to review the evidence and quantify these effects, adjusted for other physical activity (PA). DATA SOURCES: We conducted a systematic review to identify relevant studies. Searches were conducted in November 2013 using the following health databases of publications: Embase (OvidSP); Medline (OvidSP); Web of Knowledge; CINAHL; SCOPUS; SPORTDiscus. We also searched reference lists of relevant texts and reviews. STUDY ELIGIBILITY CRITERIA AND PARTICIPANTS: Eligible studies were prospective cohort design and reporting walking or cycling exposure and mortality as an outcome. Only cohorts of individuals healthy at baseline were considered eligible. STUDY APPRAISAL AND SYNTHESIS METHODS: Extracted data included study population and location, sample size, population characteristics (age and sex), follow-up in years, walking or cycling exposure, mortality outcome, and adjustment for other co-variables. We used random-effects meta-analyses to investigate the beneficial effects of regular walking and cycling. RESULTS: Walking (18 results from 14 studies) and cycling (8 results from 7 studies) were shown to reduce the risk of all-cause mortality, adjusted for other PA. For a standardised dose of 11.25 MET.hours per week (or 675 MET.minutes per week), the reduction in risk for ACM was 11% (95% CI = 4 to 17%) for walking and 10% (95% CI = 6 to 13%) for cycling. The estimates for walking are based on 280,000 participants and 2.6 million person-years and for cycling they are based on 187,000 individuals and 2.1 million person-years. The shape of the dose-response relationship was modelled through meta-analysis of pooled relative risks within three exposure intervals. The dose-response analysis showed that walking or cycling had the greatest effect on risk for ACM in the first (lowest) exposure interval. CONCLUSIONS AND IMPLICATIONS: The analysis shows that walking and cycling have population-level health benefits even after adjustment for other PA. Public health approaches would have the biggest impact if they are able to increase walking and cycling levels in the groups that have the lowest levels of these activities. REVIEW REGISTRATION: The review protocol was registered with PROSPERO (International database of prospectively registered systematic reviews in health and social care) PROSPERO 2013: CRD42013004266.

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 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.

Home outdoor NO2 and new onset of self-reported asthma in adults.

BACKGROUND: 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. METHODS: 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). RESULTS: 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). CONCLUSIONS: We found an association between a marker of traffic-related air pollution and asthma incidence in European adults.

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.

Long-term effects of ambient air pollution on lung function: a review.

Lung function is an important measure of respiratory health and a predictor of cardiorespiratory morbidity and mortality. Over the past 2 decades, more than 50 publications have investigated long-term effects of ambient air pollution on lung function with most finding adverse effects. Several studies have also suggested effects from traffic-related air pollution. There is strong support for air pollution effects on the development of lung function in children and adolescents. It remains unclear whether subjects with slower development of lung function compensate by prolonging the growth phase, or whether they end their development at a lower plateau, thus entering the decline phase with a reduced lung function. In adults, the evidence for long-term air pollution effects is mostly based on cross-sectional comparisons. One recent longitudinal study observed that decreasing pollution attenuated the decline of lung function in adults. Earlier inconclusive cohort studies were based on limited data. There is great diversity in study designs, markers of air pollution, approaches to the measurement of exposure, and choices in lung function measures. These limit the comparability of studies and impede quantitative summaries. New studies should use individual-level exposure assessment to clarify the role of traffic and to preclude potential community-level confounding. Further research is needed on the relevance of specific pollution sources, particularly with regard to susceptible populations and relevant exposure periods throughout life.

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.