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By 2050, nearly 70% of the global population is projected to live in urban areas. Because the environments we inhabit affect our health, urban and transport designs that promote healthy living are needed. We estimated the number of premature deaths preventable under compliance with international exposure recommendations for physical activity (PA), air pollution, noise, heat, and access to green spaces. We developed and applied the Urban and TranspOrt Planning Health Impact Assessment (UTOPHIA) tool to Barcelona, Spain. Exposure estimates and mortality data were available for 1,357,361 residents. We compared recommended with current exposure levels. We quantified the associations between exposures and mortality and calculated population attributable fractions to estimate the number of premature deaths preventable. We also modeled life-expectancy and economic impacts. We estimated that annually, nearly 20% of mortality could be prevented if international recommendations for performance of PA; exposure to air pollution, noise, and heat; and access to green space were followed. Estimations showed that the greatest portion of preventable deaths was attributable to increases in PA, followed by reductions of exposure to air pollution, traffic noise, and heat. Access to green spaces had smaller effects on mortality. Compliance was estimated to increase the average life expectancy by 360 (95% CI: 219, 493) days and result in economic savings of 9.3 (95% CI: 4.9, 13.2) billion EUR/year. PA factors and environmental exposures can be modified by changes in urban and transport planning. We emphasize the need for a) the reduction of motorized traffic through the promotion of active and public transport and b) the provision of green infrastructure, both of which are suggested to provide opportunities for PA and for mitigation of air pollution, noise, and heat. Citation: Mueller N, Rojas-Rueda D, Basagaña X, Cirach M, Cole-Hunter T, Dadvand P, Donaire-Gonzalez D, Foraster M, Gascon M, Martinez D, Tonne C, Triguero-Mas M, Valentín A, Nieuwenhuijsen M. 2017. Urban and transport planning related exposures and mortality: a health impact assessment for cities. Environ Health Perspect 125:89-96; http://dx.doi.org/10.1289/EHP220.

Waste-to-energy (WtE) processes, or the combustion of refuse-derived fuel (RDF) for energy generation, has the potential to reduce landfill volume while providing a renewable energy source. We aimed to systematically review and summarise current evidence on the potential health effects (benefits and risks) of exposure to WtE/RDF-related combustion emissions. We searched PubMed and Google Scholar using terms related to health and WtE/RDF combustion emissions, following PRISMA guidelines. Two authors independently screened titles, abstracts and then full-texts of original, peer-reviewed research articles published until 20th March 2020, plus their relevant references. Overall quality of included epidemiological studies were rated using an amended Navigation framework. We found 19 articles from 269 search results that met our inclusion criteria, including two epidemiological studies, five environmental monitoring studies, seven health impact or risk assessments (HIA/HRA), and five life-cycle assessments. We found a dearth of health studies related to the impacts of exposure to WtE emissions. The limited evidence suggests that well-designed and operated WtE facilities using sorted feedstock (RDF) are critical to reduce potential adverse health (cancer and non-cancer) impacts, due to lower hazardous combustion-related emissions, compared to landfill or unsorted incineration. Poorly fed WtE facilities may emit concentrated toxins with serious potential health risks, such as dioxins/furans and heavy metals; these toxins may remain problematic in bottom ash as a combustion by-product. Most modelling studies estimate that electricity (per unit) generated from WtE generally emits less health-relevant air pollutants (also less greenhouse gases) than from combustion of fossil fuels (e.g. coal). Some modelled estimates vary due to model sensitivity for type of waste processed, model inputs used, and facility operational conditions. We conclude that rigorous assessment (e.g. HRA including sensitivity analyses) of WtE facility/technological characteristics and refuse type used is necessary when planning/proposing facilities to protect human health as the technology is adopted worldwide.

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. 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. 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. 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. 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.

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.

Background Road traffic noise has been linked to increased risk of ischemic heart disease, yet evidence on stroke shows mixed results. We examine the association between long-term exposure to road traffic noise and incidence of stroke, overall and by subtype (ischemic or hemorrhagic), after adjustment for air pollution. Methods Twenty-five thousand six hundred and sixty female nurses from the Danish Nurse Cohort recruited in 1993 or 1999 were followed for stroke-related first-ever hospital contact until December 31st, 2014. Full residential address histories since 1970 were obtained and annual means of road traffic noise (L den [dB]) and air pollutants (particulate matter with diameter < 2.5 μm and < 10 μm [PM 2.5 and PM 10 ], nitrogen dioxide [NO 2 ], nitrogen oxides [NOx]) were determined using validated models. Time-varying Cox regression models were used to estimate hazard ratios (HR) (95% confidence intervals [CI]) for the associations of one-, three-, and 23-year running means of L den preceding stroke (all, ischemic or hemorrhagic), adjusting for stroke risk factors and air pollutants. The World Health Organization and the Danish government’s maximum exposure recommendations of 53 and 58 dB, respectively, were explored as potential L den thresholds. Results Of 25,660 nurses, 1237 developed their first stroke (1089 ischemic, 148 hemorrhagic) during 16 years mean follow-up. For associations between a 1-year mean of L den and overall stroke incidence, the estimated HR (95% CI) in the fully adjusted model was 1.06 (0.98–1.14) per 10 dB, which attenuated to 1.01 (0.93–1.09) and 1.00 (0.91–1.09) in models further adjusted for PM 2.5 or NO 2 , respectively. Associations for other exposure periods or separately for ischemic or hemorrhagic stroke were similar. There was no evidence of a threshold association between L den and stroke. Conclusions Long-term exposure to road traffic noise was suggestively positively associated with the risk of overall stroke, although not after adjusting for air pollution.

The dynamics of speed selection as a function of distance, or pacing, are used in recreational, competitive, and scientific research situations as an indirect measure of the psycho-physiological status of an individual. The purpose of this study was to determine pacing on level, uphill and downhill sections of participants in a long (>80 km) ultramarathon performed on trails in hilly terrain. Fifteen ultramarathon runners competed in a  173 km event (five finished at  103 km) carrying a Global-Positioning System (GPS) device. Using the GPS data, we determined the speed, relative to average total speed, in level (LEV), uphill (UH) and downhill (DH) gradient categories as a function of total distance, as well as the correlation between overall performance and speed variability, speed loss, and total time stopped. There were no significant differences in normality, variances or means in the relative speed in 173-km and 103-km participants. Relative speed decreased in LEV, UH and DH. The main component of speed loss occurred between 5% and 50% of the event distance in LEV, and between 5% and 95% in UH and DH. There were no significant correlations between overall performance and speed loss, the variability of speed, or total time stopped. Positive pacing was observed at all gradients, with the main component of speed loss occurring earlier (mixed pacing) in LEV compared to UH and DH. A speed reserve (increased speed in the last section) was observed in LEV and UH. The decrease in speed and variability of speed were more important in LEV and DH than in UH. The absence of a significant correlation between overall performance and descriptors of pacing is novel and indicates that pacing in ultramarathons in trails and hilly terrain differs to other types of running events.

Background Bicycle commuting in an urban environment of high air pollution is known to be a potential health risk, especially for susceptible individuals. While risk management strategies aimed to reduce exposure to motorised traffic emissions have been suggested, only limited studies have assessed the utility of such strategies in real-world circumstances. Objectives The potential to lower exposure to ultrafine particles (UFP; < 0.1 μm) during bicycle commuting by reducing proximity to motorised traffic was investigated with real-time air pollution and intermittent acute inflammatory measurements in healthy individuals using their typical higher proximity, and an alternative lower proximity, bicycle commute route. Methods Thirty-five healthy adults (mean ± SD: age = 39 ± 11 yr; 29% female) completed two return trips, one each in the condition of their typical route (HIGH) and a pre-determined alternative route of lower proximity to motorised traffic (LOW); proximity being determined by the proportion of on-road cycle paths. Particle number concentration (PNC) and diameter (PD) were monitored in-commute in real-time. Acute inflammatory indices of respiratory symptoms (as a scalar of frequency from very low to very high / 1 to 5), lung function and spontaneous sputum (for inflammatory cell analyses) were collected immediately pre-commute, and immediately and three hours post-commute. Results In the condition of LOW, compared to in the condition of HIGH, there was a significant decrease in mean PNC (1.91 x e 4 ± 0.93 × e 4 ppcc vs. 2.95 × e 4 ± 1.50 × e 4 ppcc; p ≤ 0.001), and the mean frequency of in-commute offensive odour detection (2.1 vs. 2.8; p = 0.019), dust and soot observation (1.7 vs. 2.3; p = 0.038) and nasopharyngeal irritation (1.5 vs. 1.9; p = 0.007). There were no significant differences between LOW and HIGH in the commute distance and duration (12.8 ± 7.1 vs. 12.0 ± 6.9 km and 44 ± 17 vs. 42 ± 17 min, respectively), or other indices of acute airway inflammation. Conclusions Exposure to PNC and offensive odour, and nasopharyngeal irritation, can be significantly lowered when utilising a route of lower proximity to motorised traffic whilst bicycle commuting, without significantly affecting commute distance or duration. This may bring health benefits for both healthy and susceptible individuals.

IntroductionActive commuting — walking and bicycling for travel to and/or from work or educational addresses — may facilitate daily, routine physical activity. Several studies have investigated the relationship between active commuting and commuting stress; however, there are no studies examining the relationship between solely bicycle commuting and perceived stress, or studies that account for environmental determinants of bicycle commuting and stress. The current study evaluated the relationship between bicycle commuting, among working or studying adults in a dense urban setting, and perceived stress.MethodsA cross-sectional study was performed with 788 adults who regularly travelled to work or study locations (excluding those who only commuted on foot) in Barcelona, Spain. Participants responded to a comprehensive telephone survey concerning their travel behaviour from June 2011 through to May 2012. Participants were categorised as either bicycle commuters or non-bicycle commuters, and (based on the Perceived Stress Scale, PSS-4) as either stressed or non-stressed. Multivariate Poisson regression with robust variance models of stress status based on exposures with bicycle commuting were estimated and adjusted for potential confounders.ResultsBicycle commuters had significantly lower risk of being stressed than non-bicycle commuters (Relative Risk; RR (95% CI)=0.73 (0.60 to 0.89), p=0.001). Bicycle commuters who bicycled 4 days per week (RR (95% CI)=0.42 (0.24 to 0.73), p=0.002) and those who bicycled 5 or more days per week (RR (95% CI)=0.57 (0.42 to 0.77), p<0.001) had lower risk of being stressed than those who bicycled less than 4 days. This relationship remained statistically significant after adjusting for individual and environmental confounders and when using different cut-offs of perceived stress.ConclusionsStress reduction may be an important consequence of routine bicycle use and should be considered by decision makers as another potential benefit of its promotion.

Associations between long-term exposure to air pollution and road traffic noise have been established for ischemic heart disease, but findings have been mixed for atrial fibrillation (AF). The goal of the study was to examine associations of long-term exposure to road traffic noise and air pollution with AF. Time-varying Cox regression models were used to estimate associations of 1-, 3-, and 23-y mean road traffic noise and air pollution exposures with AF incidence in 23,528 women enrolled in the Danish Nurse Cohort (age at baseline in 1993 or 1999). AF diagnoses were ascertained via the Danish National Patient Register. Annual mean weighted 24-h average road traffic noise levels ( ) at the nurses' residences, since 1970, were estimated using the Nord2000 model, and annual mean levels of particulate matter with a diameter ( ) and nitrogen dioxide ( ) were estimated using the DEHM/UBM/AirGIS model. Of 23,528 nurses with no prior AF diagnosis at the cohort baseline, 1,522 developed AF during follow-up. In a fully adjusted model (including ), the estimated risk of AF was 18% higher [hazard ratio (HR); 95% confidence interval (CI): 1.18; 1.02, 1.36] in nurses with residential 3-y mean levels vs. , with similar findings for 1-y mean exposures. A increase in 3-y mean was associated with incident AF before and after adjustment for concurrent exposure to road traffic noise (HR 1.09; 95% CI: 1.00, 1.20 and 1.08; 95% CI: 0.97, 1.19, respectively). Associations with 1-y mean exposures were positive but closer to the null and not significant. Associations with were null for all time periods before and after adjustment for road traffic noise and inverse when adjusted for concurrent . Our analysis of prospective data from a cohort of Danish female nurses followed for up to 14 y provided suggestive evidence of independent associations between incident AF and 1- and 3-y exposures to road traffic noise and . https://doi.org/10.1289/EHP8090.

The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented.