The Superblock model: A review of an innovative urban model for sustainability, liveability, health and well-being.

INTRODUCTION: Current urban and transport planning practices have significant negative health, environmental, social and economic impacts in most cities. New urban development models and policies are needed to reduce these negative impacts. The Superblock model is one such innovative urban model that can significantly reduce these negative impacts through reshaping public spaces into more diverse uses such as increase in green space, infrastructure supporting social contacts and physical activity, and through prioritization of active mobility and public transport, thereby reducing air pollution, noise and urban heat island effects. This paper reviews key aspects of the Superblock model, its implementation and initial evaluations in Barcelona and the potential international uptake of the model in Europe and globally, focusing on environmental, climate, lifestyle, liveability and health aspects. METHODS: We used a narrative meta-review approach and PubMed and Google scholar databases were searched using specific terms. RESULTS: The implementation of the Super block model in Barcelona is slow, but with initial improvement in, for example, environmental, lifestyle, liveability and health indicators, although not so consistently. When applied on a large scale, the implementation of the Superblock model is not only likely to result in better environmental conditions, health and wellbeing, but can also contribute to the fight against the climate crisis. There is a need for further expansion of the program and further evaluation of its impacts and answers to related concerns, such as environmental equity and gentrification, traffic and related environmental exposure displacement. The implementation of the Superblock model gained a growing international reputation and variations of it are being planned or implemented in cities worldwide. Initial modelling exercises showed that it could be implemented in large parts of many cities. CONCLUSION: The Superblock model is an innovative urban model that addresses environmental, climate, liveability and health concerns in cities. Adapted versions of the Barcelona Superblock model are being implemented in cities around Europe and further implementation, monitoring and evaluation are encouraged. The Superblock model can be considered an important public health intervention that will reduce mortality and morbidity and generate cost savings for health and other sectors.

Shaping urban environments to improve respiratory health: recommendations for research, planning, and policy.

Urban areas carry a large burden of acute (infectious) and chronic respiratory diseases due to environmental conditions such as high levels of air pollution and high population densities. Car-dominated cities often lack walkable areas, which reduces opportunities for physical activity that are fundamentally important for healthy lungs. The already restricted amount of green space available-with often poorly selected plants-could produce pollen and subsequently provoke or worsen allergic diseases. Less affluent neighbourhoods often carry a larger respiratory disease burden. A multisectoral approach with more diverse policy measures and urban innovations is needed to reduce air pollution (eg, low emission zones), to increase public space for walking and cycling (eg, low traffic neighbourhoods, superblocks, 15-minute cities, and car-free cities), and to develop green cities (eg, planting of low-allergy trees). Stricter EU air quality guidelines can push these transformations to improve the respiratory health of citizens. Advocacy by medical respiratory societies can also make an important contribution to such changes.

Holistic approach to assess the association between the synergistic effect of physical activity, exposure to greenspace, and fruits and vegetable intake on health and wellbeing: Cross-sectional analysis of UK Biobank.

Background: Urban agriculture has been shown to contribute to healthy lifestyle behaviors, such as increased fruit and vegetable intake and greater exposure to greenspaces and there is plenty of evidence linking these lifestyle behaviors to better health and wellbeing. However, most evidence relates to assessing one behavior at a time despite available epidemiological research showing how the combined effects of multiple behaviors are associated with health and wellbeing. This research aims to examine the association of the interactions between various lifestyle behaviors and exposures related to urban agriculture and health and wellbeing. Methods: We used data from the UK Biobank baseline questionnaire (N~500, 000) to assess the association of two lifestyle behaviors (fruit and vegetable intake and physical activity) and greenspace exposure, with four health and wellbeing markers (blood pressure, BMI, self-health assessment, and self-reported loneliness) independently, and in combination. Associations between lifestyle behaviors, greenspace exposure, and the possible interactions with health and wellbeing were explored using general linear models (GLMs), adjusted for socio-demographic confounders including age, sex, educational qualifications, index of multiple deprivation, and ethnicity, and a lifestyle confounder: smoking status. Results: After removing missing data, as well as participants who did not meet the inclusion criteria, the final study sample was n = 204,478. The results indicate that meeting recommended levels of the World Health Organization (WHO) for fruits and vegetable intake, and the advice from the UK Chief Medical Officer for physical activity, is linked to better health and wellbeing markers. We found that UK Biobank participants who lived in greener areas and were physically active were more likely to feel alone and think their health was poor. Participants who were physically active and met the recommended intake of fruits and vegetables were more likely to have healthy blood pressure, feel less lonely, and rate their health as good. Evidence of three-way interactions was weak, and mostly was not associated with the health and wellbeing markers assessed here. Conclusion: Taken in combination, healthy diets, physical activity and exposure to greenspaces are associated with health and wellbeing. In some cases, these effects are synergistic, indicating associations above and beyond the mere additive effect of the behaviors considered independently. Promoting such behaviors together, for example, through urban agriculture, is therefore more likely to generate greater public health changes than if they are promoted through independent policies and programs. Inter-relationships between these pathways and different health and wellbeing markers, however, are complex, and require further investigation to understand optimal environments and conditions for urban health promotion.

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.

Assessing the Health Benefits of Physical Activity Due to Active Commuting in a French Energy Transition Scenario.

Objectives: Energy transition scenarios are prospective outlooks describing combinations of changes in socio-economic systems that are compatible with climate targets. These changes could have important health co-benefits. We aimed to quantify the health benefits of physical activity caused by active transportation on all-cause mortality in the French negaWatt scenario over the 2021-2050 period. Methods; Relying on a health impact assessment framework, we quantified the health benefits of increased walking, cycling and E-biking projected in the negaWatt scenario. The negaWatt scenario assumes increases of walking and cycling volumes of +11% and +612%, respectively, over the study period. Results: As compared to a scenario with no increase in volume of active travel, we quantified that the negaWatt scenario would prevent 9,797 annual premature deaths in 2045 and translate into a 3-month increase in life expectancy in the general population. These health gains would generate €34 billion of economic benefits from 2045 onwards. Conclusion: Increased physical activity implied in the negaWatt transition scenario would generate substantial public health benefits, which are comparable to the gain expected by large scale health prevention interventions.

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

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

Study protocol of the European Urban Burden of Disease Project: a health impact assessment study.

INTRODUCTION: Cities have long been known to be society's predominant engine of innovation and wealth creation, yet they are also hotspots of pollution and disease partly due to current urban and transport practices. The aim of the European Urban Burden of Disease project is to evaluate the health burden and its determinants related to current and future potential urban and transport planning practices and related exposures in European cities and make this evidence available for policy and decision making for healthy and sustainable futures. METHODS AND ANALYSIS: Drawing on an established comparative risk assessment methodology (ie, Urban and Transport Planning Health Impact Assessment) tool), in nearly 1000 European cities we will (1) quantify the health impacts of current urban and transport planning related exposures (eg, air pollution, noise, excess heat, lack of green space) (2) and evaluate the relationship between current levels of exposure, health impacts and city characteristics (eg, size, density, design, mobility) (3) rank and compare the cities based on exposure levels and the health impacts, (4) in a number of selected cities assess in-depth the linkages between urban and transport planning, environment, physical activity and health, and model the health impacts of alternative and realistic urban and transport planning scenarios, and, finally, (5) construct a healthy city index and set up an effective knowledge translation hub to generate impact in society and policy. ETHICS AND DISSEMINATION: All data to be used in the project are publicly available data and do not need ethics approval. We will request consent for personal data on opinions and views and create data agreements for those providing information on current and future urban and transport planning scenarios.For dissemination and to generate impact, we will create a knowledge translation hub with information tailored to various stakeholders.

Barriers and Enablers for Integrating Public Health Cobenefits in Urban Climate Policy.

Urban climate policy offers a significant opportunity to promote improved public health. The evidence around climate and health cobenefits is growing but has yet to translate into widespread integrated policies. This article presents two systematic reviews: first, looking at quantified cobenefits of urban climate policies, where transportation, land use, and buildings emerge as the most studied sectors; and second, looking at review papers exploring the barriers and enablers for integrating these health cobenefits into urban policies. The latter reveals wide agreement concerning the need to improve the evidence base for cobenefits and consensus about the need for greater political will and leadership on this issue. Systems thinking may offer a way forward to help embrace complexity and integrate health cobenefits into decision making. Knowledge coproduction to bring stakeholders together and advance policy-relevant research for urban health will also be required. Action is needed to bring these two important policy agendas together.

Urban Climate Policy and Action through a Health Lens-An Untapped Opportunity.

Motivated by a growing recognition of the climate emergency, reflected in the 26th Conference of the Parties (COP26), we outline untapped opportunities to improve health through ambitious climate actions in cities. Health is a primary reason for climate action yet is rarely integrated in urban climate plans as a policy goal. This is a missed opportunity to create sustainable alliances across sectors and groups, to engage a broad set of stakeholders, and to develop structural health promotion. In this statement, we first briefly review the literature on health co-benefits of urban climate change strategies and make the case for health-promoting climate action; we then describe barriers to integrating health in climate action. We found that the evidence-base is often insufficiently policy-relevant to be impactful. Research rarely integrates the complexity of real-world systems, including multiple and dynamic impacts of strategies, and consideration of how decision-making processes contend with competing interests and short-term electoral cycles. Due to siloed-thinking and restrictive funding opportunities, research often falls short of the type of evidence that would be most useful for decision-making, and research outputs can be cryptic to decision makers. As a way forward, we urge researchers and stakeholders to engage in co-production and systems thinking approaches. Partnering across sectors and disciplines is urgently needed so pathways to climate change mitigation and adaptation fully embrace their health-promoting potential and engage society towards the huge transformations needed. This commentary is endorsed by the International Society for Environmental Epidemiology (ISEE) and the International Society for Urban Health (ISUH) and accompanies a sister statement oriented towards stakeholders (published on the societies' websites).

Personal Interventions for Reducing Exposure and Risk for Outdoor Air Pollution: An Official American Thoracic Society Workshop Report.

Poor air quality affects the health and wellbeing of large populations around the globe. Although source controls are the most effective approaches for improving air quality and reducing health risks, individuals can also take actions to reduce their personal exposure by staying indoors, reducing physical activity, altering modes of transportation, filtering indoor air, and using respirators and other types of face masks. A synthesis of available evidence on the efficacy, effectiveness, and potential adverse effects or unintended consequences of personal interventions for air pollution is needed by clinicians to assist patients and the public in making informed decisions about use of these interventions. To address this need, the American Thoracic Society convened a workshop in May of 2018 to bring together a multidisciplinary group of international experts to review the current state of knowledge about personal interventions for air pollution and important considerations when helping patients and the general public to make decisions about how best to protect themselves. From these discussions, recommendations were made regarding when, where, how, and for whom to consider personal interventions. In addition to the efficacy and safety of the various interventions, the committee considered evidence regarding the identification of patients at greatest risk, the reliability of air quality indices, the communication challenges, and the ethical and equity considerations that arise when discussing personal interventions to reduce exposure and risk from outdoor air pollution.

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

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

Assessing the Policy Environment for Active Mobility in Cities-Development and Feasibility of the PASTA Cycling and Walking Policy Environment Score.

The importance of setting a policy focus on promoting cycling and walking as sustainable and healthy modes of transport is increasingly recognized. However, to date a science-driven scoring system to assess the policy environment for cycling and walking is lacking. In this study, spreadsheet-based scoring systems for cycling and walking were developed, including six dimensions (cycling/walking culture, social acceptance, perception of traffic safety, advocacy, politics and urban planning). Feasibility was tested using qualitative data from pre-specified sections of semi-standardized interview and workshop reports from a European research project in seven cities, assessed independently by two experts. Disagreements were resolved by discussions of no more than 75 minutes per city. On the dimension "perception of traffic safety", quantitative panel data were used. While the interrater agreement was fair, feasibility was confirmed in general. Validity testing against social norms towards active travel, modal split and network length was encouraging for the policy area of cycling. Rating the policy friendliness for cycling and walking separately was found to be appropriate, as different cities received the highest scores for each. Replicating this approach in a more standardized way would pave the way towards a transparent, evidence-based system for benchmarking policy approaches of cities towards cycling and walking.

A guide to value of information methods for prioritising research in health impact modelling.

Health impact simulation models are used to predict how a proposed policy or scenario will affect population health outcomes. These models represent the typically-complex systems that describe how the scenarios affect exposures to risk factors for disease or injury (e.g. air pollution or physical inactivity), and how these risk factors are related to measures of population health (e.g. expected survival). These models are informed by multiple sources of data, and are subject to multiple sources of uncertainty. We want to describe which sources of uncertainty contribute most to uncertainty about the estimate or decision arising from the model. Furthermore, we want to decide where further research should be focused to obtain further data to reduce this uncertainty, and what form that research might take. This article presents a tutorial in the use of Value of Information methods for uncertainty analysis and research prioritisation in health impact simulation models. These methods are based on Bayesian decision-theoretic principles, and quantify the expected benefits from further information of different kinds. The expected value of partial perfect information about a parameter measures sensitivity of a decision or estimate to uncertainty about that parameter. The expected value of sample information represents the expected benefit from a specific proposed study to get better information about the parameter. The methods are applicable both to situationswhere the model is used to make a decision between alternative policies, and situations where the model is simply used to estimate a quantity (such as expected gains in survival under a scenario). This paper explains how to calculate and interpret the expected value of information in the context of a simple model describing the health impacts of air pollution from motorised transport. We provide a general-purpose R package and full code to reproduce the example analyses.

Air pollution, physical activity and health: A mapping review of the evidence.

BACKGROUND: Exposure to air pollution and physical inactivity are both significant risk factors for non-communicable diseases (NCDs). These risk factors are also linked so that the change in exposure in one will impact risks and benefits of the other. These links are well captured in the active transport (walking, cycling) health impact models, in which the increases in active transport leading to increased inhaled dose of air pollution. However, these links are more complex and go beyond the active transport research field. Hence, in this study, we aimed to summarize the empirical evidence on the links between air pollution and physical activity, and their combined effect on individual and population health. OBJECTIVES AND METHODS: We conducted a non-systematic mapping review of empirical and modelling evidence of the possible links between exposure to air pollution and physical activity published until Autumn 2019. We reviewed empirical evidence for the (i) impact of exposure to air pollution on physical activity behaviour, (ii) exposure to air pollution while engaged in physical activity and (iii) the short-term and (iv) long-term health effects of air pollution exposure on people engaged in physical activity. In addition, we reviewed (v) public health modelling studies that have quantified the combined effect of air pollution and physical activity. These broad research areas were identified through expert discussions, including two public events performed in health-related conferences. RESULTS AND DISCUSSION: The current literature suggests that air pollution may decrease physical activity levels during high air pollution episodes or may prevent people from engaging in physical activity overall in highly polluted environments. Several studies have estimated fine particulate matter (PM2.5) exposure in active transport environment in Europe and North-America, but the concentration in other regions, places for physical activity and for other air pollutants are poorly understood. Observational epidemiological studies provide some evidence for a possible interaction between air pollution and physical activity for acute health outcomes, while results for long-term effects are mixed with several studies suggesting small diminishing health gains from physical activity due to exposure to air pollution for long-term outcomes. Public health modelling studies have estimated that in most situations benefits of physical activity outweigh the risks of air pollution, at least in the active transport environment. However, overall evidence on all examined links is weak for low- and middle-income countries, for sensitive subpopulations (children, elderly, pregnant women, people with pre-existing conditions), and for indoor air pollution. CONCLUSIONS: Physical activity and air pollution are linked through multiple mechanisms, and these relations could have important implications for public health, especially in locations with high air pollution concentrations. Overall, this review calls for international collaboration between air pollution and physical activity research fields to strengthen the evidence base on the links between both and on how policy options could potentially reduce risks and maximise health benefits.

A systematic review of the leaf traits considered to contribute to removal of airborne particulate matter pollution in urban areas.

Global urban planning has promoted green infrastructure (GI) such as street trees, shrubs or other greenspace in order to mitigate air pollution. Although considerable attention has been paid to understanding particulate matter (PM) deposition on GI, there has been little focus on identifying which leaf traits might maximise airborne PM removal. This paper examines existing literature to synthesize the state of knowledge on leaf traits most relevant to PM removal. We systematically reviewed measurement studies that evaluated particulate matter accumulated on leaves on street trees, shrubs green roofs, and green walls, for a variety of leaf traits. Our final selection included 62 papers, most from field studies and a handful from wind tunnel studies. The following were variously promoted as useful traits: coniferous needle leaves; small, rough and textured broadleaves; lanceolate and ovate shapes; waxy coatings, and high-density trichomes. Consideration of these leaf traits, many of which are also associated with drought tolerance, may help to maximise PM capture. Although effective leaf traits were identified, there is no strong or consistent evidence to identify which is the most influential leaf trait in capturing PM. The diversity in sampling methods, wide comparison groups and lack of background PM concentration measures in many studies limited our ability to synthesize results. We found that several ancillary factors contribute to variations in the accumulation of PM on leaves, thus cannot recommend that selection of urban planting species be based primarily on leaf traits. Further research into the vegetation structural features and standardization of the method to measure PM on leaves is needed.

Estimating traffic contribution to particulate matter concentration in urban areas using a multilevel Bayesian meta-regression approach.

Quantifying traffic contribution to air pollution in urban settings is required to inform traffic management strategies and environmental policies that aim at improving air quality. Assessments and comparative analyses across multiple urban areas are challenged by the lack of datasets and methods available for global applications. In this study, we quantify the traffic contribution to particulate matter concentration in multiple cities worldwide by synthesising 155 previous studies reported in the World Health Organization (WHO)'s air pollution source apportionment data for PM10 and PM2.5. We employed a Bayesian multilevel meta-regression that accounts for uncertainties and captures both within- and between-study variations (in estimation methods, study protocols, etc.) through study-specific and location-specific explanatory variables. The final sample analysed in this paper covers 169 cities worldwide. Based on our analysis, traffic contribution to air pollution (particulate matter) varies from 5% to 61% in cities worldwide, with an average of 27%. We found that variability in the traffic contribution estimates reported worldwide can be explained by the region of study, publication year, PM size fraction, and population. Specifically, traffic contribution to air pollution in cities located in Europe, North America, or Oceania is on average 36% lower relative to the rest of the world. Traffic contribution is 28% lower among studies published after 2005 than those published on or before 2005. Traffic contribution is on average 24% lower among cities with less than 500,000 inhabitants and 19% higher when estimated based on PM10 relative to PM2.5. This quantitative summary overcomes challenges in the data and provides useful information for health impact modellers and decision-makers to assess impacts of traffic reduction policies.

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.