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High bicycle ownership does not necessarily correlate with high bicycle use, with substantial health and environmental gains possible by worldwide pro-bicycle policy implementation, suggests a global compilation of bicycle ownership, production, trade and stock.

Background: The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures. Objectives: We used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy). Methods: Forty-two environmental exposures, collected at 18 months of age (N = 1989), were classified in 5 groups (lifestyle, diet, meteoclimatic, traffic-related, built environment).We performed cluster analysis to identify subjects sharing similar exposures, and intra-exposome-group Principal Component Analysis (PCA) to reduce the dimensionality. SEP at childbirth was measured through the Equivalised Household Income Indicator.SEP-exposome association was evaluated using: 1) an Exposome Wide Association Study (ExWAS), a one-exposure (SEP) one-outcome (exposome) approach; 2) multinomial regression of cluster membership on SEP; 3) regressions of each intra-exposome-group PC on SEP. Results: In the ExWAS, medium/low SEP children were more exposed to greenness, pet ownership, passive smoking, TV screen and sugar; less exposed to NO2, NOX, PM25abs, humidity, built environment, traffic load, unhealthy food facilities, fruit, vegetables, eggs, grain products, and childcare than high SEP children.Medium/low SEP children were more likely to belong to a cluster with poor diet, less air pollution, and to live in the suburbs than high SEP children.Medium/low SEP children were more exposed to lifestyle PC1 (unhealthy lifestyle) and diet PC2 (unhealthy diet), and less exposed to PC1s of the built environment (urbanization factors), diet (mixed diet), and traffic (air pollution) than high SEP children. Conclusions: The three approaches provided consistent and complementary results, suggesting that children with lower SEP are less exposed to urbanization factors and more exposed to unhealthy lifestyles and diet. The simplest method, the ExWAS, conveys most of the information and is more replicable in other populations. Clustering and PCA may facilitate results interpretation and communication.

Background: Urban areas are hot spots for human exposure to air pollution, which originates in large part from traffic. As the urban population continues to grow, a greater number of people risk exposure to traffic-related air pollution (TRAP) and its adverse, costly health effects. In many cities, there is a need and scope for air quality improvements through targeted policy interventions, which continue to grow including rapidly changing technologies. Objective: This systematic evidence map (SEM) examines and characterizes peer-reviewed evidence on urban-level policy interventions aimed at reducing traffic emissions and/or TRAP from on-road mobile sources, thus potentially reducing human exposures and adverse health effects and producing various co-benefits. Methods: This SEM follows a previously peer-reviewed and published protocol with minor deviations, explicitly outlined here. Articles indexed in Public Affairs Index, TRID, Medline and Embase were searched, limited to English, published between January 1, 2000, and June 1, 2020. Covidence was used to screen articles based on previously developed eligibility criteria. Data for included articles was extracted and manually documented into an Excel database. Data visualizations were created in Tableau. Results: We identified 7528 unique articles from database searches and included 376 unique articles in the final SEM. There were 58 unique policy interventions, and a total of 1,139 unique policy scenarios, comprising these interventions and different combinations thereof. The policy interventions fell under 6 overarching policy categories: 1) pricing, 2) land use, 3) infrastructure, 4) behavioral, 5) technology, and 6) management, standards, and services, with the latter being the most studied. For geographic location, 463 policy scenarios were studied in Europe, followed by 355 in Asia, 206 in North America, 57 in South America, 10 in Africa, and 7 in Australia. Alternative fuel technology was the most frequently studied intervention (271 times), followed by vehicle emission regulation (134 times). The least frequently studied interventions were vehicle ownership taxes, and studded tire regulations, studied once each. A mere 3 % of studies addressed all elements of the full-chain—traffic emissions, TRAP, exposures, and health. The evidence recorded for each unique policy scenario is hosted in an open-access, query-able Excel database, and a complementary interactive visualization tool. We showcase how users can find more about the effectiveness of the 1,139 included policy scenarios in reducing, increasing, having mixed or no effect on traffic emissions and/or TRAP. Conclusion: This is the first peer-reviewed SEM to compile international evidence on urban-level policy interventions to reduce traffic emissions and/or TRAP in the context of human exposure and health effects. We also documented reported enablers, barriers, and co-benefits. The open-access Excel database and interactive visualization tool can be valuable resources for practitioners, policymakers, and researchers. Future updates to this work are recommended. Protocol Registration: Sanchez, K.A., Foster, M., Nieuwenhuijsen, M.J., May, A.D., Ramani, T., Zietsman, J. and Khreis, H., 2020. Urban policy interventions to reduce traffic emissions and traffic-related air pollution: Protocol for a systematic evidence map. Environment international, 142, p.105826.

Cities are centres of innovation and wealth creation, but also hotspots of air pollution and noise, heat island effects and lack of green space, which are all detrimental to human health. They are also hotspots of COVID19. COVID19 has led to a rethink of urban public space. Therefore, is it time to re-think our urban models and reduce the health burden?We provide a narrative meta-review around a number of cutting edge and visionary urban models that that may affect health and that have been reported over the past few years.New urban concepts such as the Superblocks, the low traffic neighbourhood, 15 Minute city, Car free city or a mixture of these that may go some way in reducing the health burden related to current urban and transport practices. They will reduce air pollution and noise, heat island effects and increase green space and physical activity levels. What is still lacking though is a thorough evaluation of the effectiveness and acceptability of the schemes and the impacts on not only health, but also liveability and sustainability, although they are expected to be positive.Finally, the COVID19 pandemic may accelerate these developments and stimulus funding like the EU Next Generation funding should be used to make these changes.

The early-life exposome influences future health and accelerated biological aging has been proposed as one of the underlying biological mechanisms. We investigated the association between more than 100 exposures assessed during pregnancy and in childhood (including indoor and outdoor air pollutants, built environment, green environments, tobacco smoking, lifestyle exposures, and biomarkers of chemical pollutants), and epigenetic age acceleration in 1,173 children aged 7 years old from the Human Early-Life Exposome project. Age acceleration was calculated based on Horvath’s Skin and Blood clock using child blood DNA methylation measured by Infinium HumanMethylation450 BeadChips. We performed an exposure-wide association study between prenatal and childhood exposome and age acceleration. Maternal tobacco smoking during pregnancy was nominally associated with increased age acceleration. For childhood exposures, indoor particulate matter absorbance (PMabs) and parental smoking were nominally associated with an increase in age acceleration. Exposure to the organic pesticide dimethyl dithiophosphate and the persistent pollutant polychlorinated biphenyl-138 (inversely associated with child body mass index) were protective for age acceleration. None of the associations remained significant after multiple-testing correction. Pregnancy and childhood exposure to tobacco smoke and childhood exposure to indoor PMabs may accelerate epigenetic aging from an early age.

Abstract Background Cities are an important driving force to implement the Sustainable Development Goals (SDGs) and the New Urban Agenda. The SDGs provide an operational framework to consider urbanization globally, while providing local mechanisms for action and careful attention to closing the gaps in the distribution of health gains. While health and well-being are explicitly addressed in SDG 3, health is also present as a pre condition of SDG 11, that aims at inclusive, safe, resilient and sustainable cities. Health in All Policies (HiAP) is an approach to public policy across sectors that systematically takes into account the health implications of decisions, seeks synergies, and avoids harmful health impacts in order to improve population health and health equity. HiAP is key for local decision-making processes in the context of urban policies to promote public health interventions aimed at achieving SDG targets. HiAPs relies heavily on the use of scientific evidence and evaluation tools, such as health impact assessments (HIAs). HIAs may include city-level quantitative burden of disease, health economic assessments, and citizen and other stakeholders’ involvement to inform the integration of health recommendations in urban policies. The Barcelona Institute for Global Health (ISGlobal)‘s Urban Planning, Environment and Health Initiative provides an example of a successful model of translating scientific evidence into policy and practice with regards to sustainable and healthy urban development. The experiences collected through ISGlobal’s participation implementing HIAs in several cities worldwide as a way to promote HiAP are the basis for this analysis. Aim The aim of this article is threefold: to understand the links between social determinants of health, environmental exposures, behaviour, health outcomes and urban policies within the SDGs, following a HiAP rationale; to review and analyze the key elements of a HiAP approach as an accelerator of the SDGs in the context of urban and transport planning; and to describe lessons learnt from practical implementation of HIAs in cities across Europe, Africa and Latin-America. Methods We create a comprehensive, urban health related SDGs conceptual framework, by linking already described urban health dimensions to existing SDGs, targets and indicators. We discuss, taking into account the necessary conditions and steps to conduct HiAP, the main barriers and opportunities within the SDGs framework. We conclude by reviewing HIAs in a number of cities worldwide (based on the experiences collected by co-authors of this publication), including city-level quantitative burden of disease and health economic assessments, as practical tools to inform the integration of health recommendations in urban policies. Results A conceptual framework linking SDGs and urban and transportplanning, environmental exposures, behaviour and health outcomes, following a HiAP rationale, is designed. We found at least 38 SDG targets relevant to urban health, corresponding to 15 SDGs, while 4 important aspects contained in our proposed framework were not present in the SDGs (physical activity, noise, quality of life or social capital). Thus, a more comprehensive HiAP vision within the SDGs could be beneficial. Our analysis confirmed that the SDGs framework provides an opportunity to formulate and implement policies with a HiAP approach. Three important aspects are highlighted: 1) the importance of the intersectoral work and health equity as a cross-cutting issue in sustainable development endeavors; 2) policy coherence, health governance, and stakeholders’ participation as key issues; and 3) the need for high quality data. HIAs are a practical tool to implement HiAP. Opportunities and barriers related to the political, legal and health governance context, the capacity to inform policies in other sectors, the involvement of different stakeholders, and the availability of quality data are discussed based on our experience. Quantitative assessments can provide powerful data such as: estimates of annual preventable morbidity and disability-adjusted life-years (DALYs) under compliance with international exposure recommendations for physical activity, exposure to air pollution, noise, heat, and access to green spaces; the associated economic impacts in health care costs per year; and the number of preventable premature deaths when improvements in urban and transport planning are implemented. This information has been used to support the design of policies that promote cycling, walking, public, zero and low-emitting modes of transport, and the provision of urban greening or healthy public open spaces in Barcelona (e.g. Urban Mobility, Green Infrastructure and Biodiversity Plans, or the Superblocks’s model), the Bus Rapid Transit and Open Streets initiatives in several Latin American cities or targeted SDGs assessments in Morocco. Conclusions By applying tools such as HIA, HiAP can be implemented to inform and improve transport and urban planning to achieve the 2030 SDG Agenda. Such a framework could be potentially used in cities worldwide, including those of less developed regions or countries. Data availability, taking into account equity issues, strenghtening the communication between experts, decision makers and citizens, and the involvement of all major stakeholders are crucial elements for the HiAP approach to translate knowledge into SDG implementation.

Background: Asthma is one of the leading chronic airway diseases among children in the United States (US). Emerging evidence indicates that Traffic Related Air Pollution (TRAP), as opposed to ambient air pollution, leads to the onset of childhood asthma. We estimated the number of incident asthma cases among children attributable to TRAP in the contiguous US, for the years 2000 and 2010. Methods: The number of incident childhood asthma cases and percentage due to TRAP were estimated using standard burden of disease assessment methods. We combined children (

Satellite data is increasingly used to characterize green space for health outcome studies. Literature suggests that green space within 500 m of home is often used to represent neighborhood suitable for walking, air pollution and noise reduction, and natural healing. In this paper, we used satellite data of different spatial resolutions to derive normalized difference vegetation index (NDVI), an indicator of surface greenness, at buffer distances of 50, 100, 250 and 500 m. Data included those of 2 m spatial resolution from WorldView2, 5 m resolution from RapidEye and 30 m resolution from Landsat. We found that, after radiometric calibrations, the RapidEye and WorldView2 sensors had similar NDVI values, while Landsat imagery tended to have greater NDVI; however, these sensors showed similar vegetation distribution: locations high in vegetation cover being high in NDVI, and vice versa. We linked the green space estimates to a health survey, and identified that higher NDVI values were significantly associated with better health outcomes. We further investigated the impacts of buffer size and sensor spatial resolution on identified associations between NDVI and health outcomes. Overall, the identified health outcomes were similar across sensors of different spatial resolutions, but a mean trend was identified in bigger buffer size being associated with greater health outcome. Keywords: Normalized difference vegetation index, WorldView2, RapidEye, LandSat, Spatial resolution, Buffer distance, Health outcomes, Barcelona

To assess environmental exposures at the individual level, new assessment methods and tools are required. We developed an exposure assessment system (ExpoApp) for smartphones. ExpoApp integrates: (i) geo-location and accelerometry measurements from a waist attached smartphone, (ii) data from portable monitors, (iii) geographic information systems, and (iv) individual's information. ExpoApp calculates time spent in microenvironments, physical activity level, inhalation rate, and environmental exposures and doses (e.g., green spaces, inhaled ultrafine particles- UFP). We deployed ExpoApp in a panel study of 158 adults from five cities (Amsterdam and Utrecht- the Netherlands, Basel- Switzerland, Norwich- UK, and Torino- Italy) with an UFP monitor. To evaluate ExpoApp, participants also carried a reference accelerometer (ActiGraph) and completed a travel-activity diary (TAD). System reliability and validity of measurements were evaluated by comparing the monitoring failure rate and the agreement on time spent in microenvironments and physical activity with the reference tools. There were only significant failure rate differences between ExpoApp and ActiGraph in Norwich. Agreement on time in microenvironments and physical activity level between ExpoApp and reference tools was 86.6% (86.5–86.7) and 75.7% (71.5–79.4), respectively. ExpoApp estimated that participants inhaled 16.5 × 1010 particles/day of UFP and had almost no contact with green spaces (24% of participants spent ≥30 min/day in green spaces). Participants with more contact with green spaces had higher inhaled dose of UFP, except for the Netherlands, where the relationship was the inverse. ExpoApp is a reliable system and provides accurate individual's measurements, which may help to understand the role of environmental exposures on the origin and course of diseases. Keywords: Personal exposure monitoring, Ultrafine particles, Inhalation, Green spaces, Microenvironments

Abstract Background Exposure to ambient airborne particulate matter is a major risk factor for mortality and morbidity, associated with asthma, lung cancer, heart disease, myocardial infarction, and stroke, and more recently type 2 diabetes, dementia and loss of cognitive function. Less is understood about differential effects of particulate matter from different sources. Underground railways are used by millions of people on a daily basis in many cities. Poor air exchange with the outside environment means that underground railways often have an unusually high concentration of airborne particulate matter, while a high degree of railway-associated mechanical activity produces particulate matter which is physicochemically highly distinct from ambient particulate matter. The implications of this for the health of exposed commuters and employees is unclear. Main body A literature search found 27 publications directly assessing the potential health effects of underground particulate matter, including in vivo exposure studies, in vitro toxicology studies, and studies of particulate matter which might be similar to that found in underground railways. The methodology, findings, and conclusions of these studies were reviewed in depth, along with further publications directly relevant to the initial search results. In vitro studies suggest that underground particulate matter may be more toxic than exposure to ambient/urban particulate matter, especially in terms of endpoints related to reactive oxygen species generation and oxidative stress. This appears to be predominantly a result of the metal-rich nature of underground particulate matter, which is suggestive of increased health risks. However, while there are measureable effects on a variety of endpoints following exposure in vivo, there is a lack of evidence for these effects being clinically significant as may be implied by the in vitro evidence. Conclusion There is little direct evidence that underground railway particulate matter exposure is more harmful than ambient particulate matter exposure. This may be due to disparities between in vivo exposures and in vitro models, and differences in exposure doses, as well as statistical under powering of in vivo studies of chronic exposure. Future research should focus on outcomes of chronic in vivo exposure, as well as further work to understand mechanisms and potential biomarkers of exposure.

Dataset from a large-scale air quality citizen science campaign is presented (xAire, 725 measurements, see Ref. [1]). A broad partnership with 1650 citizens from communities around 18 primary schools across Barcelona (Spain) provided the capacity to obtain unprecedented high-resolution NO2 levels which had in turn the capacity to provide an updated asthma Health Impact Assessment. Nitrogen dioxide levels being obtained in a 4-week period during February and March 2018 with Palmes’ diffusion samplers are herein provided. Dataset includes NO2 levels from outdoor locations n=671, playgrounds n=31, and inside school buildings (mostly classrooms) n=23. Data was calibrated and annualized with concentration levels from automatic reference stations. It is shown that NO2 levels vary considerably with at some cases very high levels. Strong differences might also however be explained by the fact that ambient air pollution is reduced exponentially with distance from an emission source like traffic meaning that two samplers located about 100 m away can measure a tenfold difference concentration level.

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.

Abstract Introduction Urban environmental exposures might contribute to the incidence of Alzheimer's disease (AD). Our aim was to identify structural brain imaging correlates of urban environmental exposures in cognitively unimpaired individuals at increased risk of AD. Methods Two hundred twelve participants with brain scans and residing in Barcelona, Spain, were included. Land use regression models were used to estimate residential exposure to air pollutants. The daily average noise level was obtained from noise maps. Residential green exposure indicators were also generated. A cerebral 3D‐T1 was acquired to obtain information on brain morphology. Voxel‐based morphometry statistical analyses were conducted to determine the areas of the brain in which regional gray matter (GM) and white matter (WM) volumes were associated with environmental exposures. Results Exposure to nitrogen dioxide was associated with lower GM volume in the precuneus and greater WM volume in the splenium of the corpus callosum and inferior longitudinal fasciculus. In contrast, exposure to fine particulate matter was associated with greater GM in cerebellum and WM in the splenium of corpus callosum, the superior longitudinal fasciculus, and cingulum cingulate gyrus. Noise was positively associated with WM volume in the body of the corpus callosum. Exposure to greenness was associated with greater GM volume in the middle frontal, precentral, and the temporal pole. Discussion In cognitively unimpaired adults with increased risk of AD, exposure to air pollution, noise, and green areas are associated with GM and WM volumes of specific brain areas known to be affected in AD, thus potentially conferring a higher vulnerability to the disease.

Introduction: Cities are the world’s engines of economic growth, innovation, and social change, but they are also hot spots for human exposure to air pollution, mainly originating from road traffic. As the urban population continues to grow, a greater quantity of people risk exposure to traffic-related air pollution (TRAP), and therefore also risk adverse health effects. In many cities, there is scope for further improvement in air quality through targeted urban policy interventions. The objective of this protocol is to detail the methods that will be used for a systematic evidence map (SEM) which will identify and characterize the evidence on policy interventions that can be implemented at the urban-level to reduce traffic emissions and/or TRAP from on-road mobile sources, thus reducing human exposures and adverse health impacts. Methods: Articles will be searched for and selected based on a predetermined search strategy and eligibility criteria. A variety of databases will be searched for relevant articles published in English between January 1, 2000 and June 1, 2020 to encompass the interdisciplinary nature of this SEM, and articles will be stored and screened using Rayyan QCRI. Predetermined study characteristics will be extracted and coded from included studies in a Microsoft Excel sheet, which will serve as an open access, interactive database, and two authors will review the coded data for consistency. The database will be queryable, and various interactive charts, graphs, and maps will be created using Tableau Public for data visualization. The results of the evidence mapping will be detailed via narrative summary. Conclusion: This protocol serves to increase transparency of the SEM methods and provides an example for researchers pursuing future SEMs.

Introduction: Half the world population lives in cities and this is likely to increase to 70% over the next 20 years. Suboptimal urban and transport planning has led to e.g. high levels of air pollution and noise, heat island effects and lack of green space and physical activity and thereby an increase in morbidity and premature mortality. How can better urban and transport planning improve public health? Methods: A narrative meta-review around a number of cutting edge and visionary studies and practices on how to improve public health through better urban and transport planning reported in the literature and from meetings over the past few years. Results: We describe the latest quantitative evidence of how cities can become healthier through better urban and transport planning. It focuses and provides evidence for important interventions, policies and actions that can improve public health, including the need for land use changes, reduce car dependency and move towards public and active transportation, greening of cities, visioning, citizen involvement, collaboration, leadership and investment and systemic approaches. Health impact assessment studies have recently provided new powerful quantitative evidence on how to make cities healthier and will be used as examples. At the same time these measures make also our cities more sustainable (i.e. carbon neutral) and liveable creating multiple benefits. Conclusion: Better urban and transport planning can lead to carbon neutral, more liveable and healthier cities, particularly through land use changes, a move from private motorised transportation to public and active transportation and greening of cities.

Swimming in pools during pregnancy may expose the fetus to water disinfection by-products (DBP). As yet, our understanding of the impacts on DBPs on the fetus is uncertain. Individuals with public water systems are typically exposed to DBPs through drinking, showering and bathing, whereas among those on private water systems, swimming in pools may be the primary exposure source. We analyzed the effects of maternal swimming on birth outcomes and cord blood epigenetic changes in the New Hampshire Birth Cohort Study, a cohort of pregnant women with households on private water systems. Information about swimming in pools during pregnancy was obtained from 1033 women via questionnaires. Swimming pool use and duration were modeled using linear regression with newborn weight, length, and head circumference (z-scores) and genome wide cord blood DNA methylation as the outcomes and with adjustment for potential confounders. Overall 19.7% of women reported swimming in a pool during pregnancy. Among swimmers, duration of swimming was inversely related to head circumference (−0.02 z-score per 10% increase in duration, P = 0.004). No associations were observed with birth weight, length or DNA methylation modifications. Our findings suggest swimming pool exposure may impact the developing fetus although longer-term studies are needed.

Characterization of the “exposome”, the set of all environmental factors that one is exposed to from conception onwards, has been advocated to better understand the role of environmental factors on chronic diseases.Here, we aimed to describe the early-life exposome. Specifically, we focused on the correlations between multiple environmental exposures, their patterns and their variability across European regions and across time (pregnancy and childhood periods). We relied on the Human Early-Life Exposome (HELIX) project, in which 87 environmental exposures during pregnancy and 122 during the childhood period (grouped in 19 exposure groups) were assessed in 1301 pregnant mothers and their children at 6–11 years in 6 European birth cohorts.Some correlations between exposures in the same exposure group reached high values above 0.8. The median correlation within exposure groups was >0.3 for many exposure groups, reaching 0.69 for water disinfection by products in pregnancy and 0.67 for the meteorological group in childhood. Median correlations between different exposure groups rarely reached 0.3. Some correlations were driven by cohort-level associations (e.g. air pollution and chemicals). Ten principal components explained 45% and 39% of the total variance in the pregnancy and childhood exposome, respectively, while 65 and 90 components were required to explain 95% of the exposome variability. Correlations between maternal (pregnancy) and childhood exposures were high (>0.6) for most exposures modeled at the residential address (e.g. air pollution), but were much lower and even close to zero for some chemical exposures.In conclusion, the early life exposome was high dimensional, meaning that it cannot easily be measured by or reduced to fewer components. Correlations between exposures from different exposure groups were much lower than within exposure groups, which have important implications for co-exposure confounding in multiple exposure studies. Also, we observed the early life exposome to be variable over time and to vary by cohort, so measurements at one time point or one place will not capture its complexities. Keywords: Exposome, Environmental exposures, Early life, Pregnancy, Children

Background: Air quality might contribute to incidence of dementia-related disorders, including Alzheimer’s dementia (AD). The aim of our study is to evaluate the effect of urban environmental exposures (including exposure to air pollution, noise and green space) on cognitive performance and brain structure of cognitively unimpaired individuals at risk for AD. Participants and methods: The ALFA (ALzheimer and FAmilies) study is a prospective cohort of middle-age, cognitively unimpaired subjects, many of them offspring of AD patients. Cognitive performance was measured by the administration of episodic memory and executive function tests (N = 958). Structural brain imaging was performed in a subsample of participants to obtain morphological information of brain areas, specially focused on cortical thickness, known to be affected by AD (N = 228). Land Use Regression models were used to estimate residential exposure to air pollutants. The daily average noise level at the street nearest to each participant's residential address was obtained from noise maps. For each participant residential green exposure indicators, such as surrounding greenness or amount of green, were generated. General linear models were conducted to assess the association between environmental exposures, cognitive performance and brain structure in a cross-sectional analysis. Results: No significant associations were observed between urban environmental exposures and the cognitive composite (p > 0.1). Higher exposure to air pollutants, but not noise, was associated with lower cortical thickness in brain regions known to be affected by AD, especially NO2 (β = −16.4; p = 0.05) and PM10 (β = −5.34; p = 0.05). On the other hand, increasing greenness indicators was associated with greater thickness in these same areas (β = 0.08; p = 0.03). Conclusion: In cognitively unimpaired adults with increased risk for AD, increased exposure to air pollution was suggested to be associated with greater global atrophy and reduced volume and thickness in specific brain areas known to be affected in AD, thus suggesting a potential link between environmental exposures and cerebral vulnerability to AD. Although more research in the field is needed, air pollution reduction is crucial for decreasing the burden of age-related disorders. Keywords: Alzheimer’s dementia, Prevention, Risk factors, Urban environment, Air pollution, Green space, Noise, Cognitive performance, Brain structure, Regions of interest

There is increasing evidence of the health benefits of exposure to natural environments, including green and blue spaces. The association with physical functioning and its decline at older age remains to be explored. The aim of the present study was to investigate the longitudinal association between the natural environment and the decline in physical functioning in older adults. We based our analyses on three follow-ups (2002−2013) of the Whitehall II study, including 5759 participants (aged 50 to 74 years at baseline) in the UK. Exposure to natural environments was assessed at each follow-up as (1) residential surrounding greenness across buffers of 500 and 1000 m around the participants' address using satellite-based indices of greenness (Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI)) and (2) the distance from home to the nearest natural environment, separately for green and blue spaces, using a land cover map. Physical functioning was characterized by walking speed, measured three times, and grip strength, measured twice. Linear mixed effects models were used to quantify the impact of green and blue space on physical functioning trajectories, controlled for relevant covariates.We found higher residential surrounding greenness (EVI and NDVI) to be associated with slower 10-year decline in walking speed. Furthermore, proximity to natural environments (green and blue spaces combined) was associated with slower decline in walking speed and grip strength. We observed stronger associations between distance to natural environments and decline in physical functioning in areas with higher compared to lower area-level deprivation. However, no association was observed with distance to green or blue spaces separately. The associations with decline in physical functioning were partially mediated by social functioning and mental health.Our results suggest that higher residential surrounding greenness and living closer to natural environments contribute to better physical functioning at older ages. Keywords: Physical capability, Functional status, Sea, NDVI, Built environment, Ageing

Background: Commuting routes with natural features could promote walking or cycling for commuting. Commuting through natural environments (NE) could have mental health benefits as exposure to NE can reduce stress and improve mental health, but there is little evidence. This study evaluates the association between NE and commuting, whether active or not, and the association between commuting (through NE), whether active or not, and mental health. We also evaluate the moderating effect of NE quality on the association between NE commuting and mental health. Methods: This cross-sectional study was based on adult respondents (n = 3599) of the Positive Health Effects of the Natural Outdoor Environment in Typical Populations in Different Regions in Europe (PHENOTYPE) project. Data were collected in four European cities in Spain, the Netherlands, Lithuania and the United Kingdom. Data on commuting behavior (active commuting at least one day/week, daily NE commuting) and mental health were collected with questionnaires. Associations were estimated with multilevel analyses including random intercepts at city- and neighborhood level. Results: Adjusted multilevel analyses showed that daily NE commuters were more often active commuters (OR 1.42; 95% CI 1.19, 1.70). There was no association between active commuting and mental health, but daily NE commuters had on average a 2.74 (95% CI 1.66, 3.82) point higher mental health score than those not commuting through NE. The association with mental health was stronger among active commuters (4.03, 95% CI 2.13, 5.94) compared to non-active commuters (2.21; 95% CI 0.90, 3.51) when daily commuting through NE, but NE quality did not have a moderating effect. Conclusions: Daily NE commuting was associated with better mental health, especially for active commuters. Daily NE commuters were likely to be active commuters. Active commuting itself was not associated with mental health. These findings suggest that cities should invest in commuting routes with nature for cycling and walking.

Abstract Background An increasing number of children are exposed to road traffic noise levels that may lead to adverse effects on health and daily functioning. Childhood is a period of intense growth and brain maturation, and children may therefore be especially vulnerable to road traffic noise. The objective of the present study was to examine whether road traffic noise was associated with reported inattention symptoms in children, and whether this association was mediated by sleep duration. Methods This study was based on the Norwegian Mother and Child Cohort Study conducted by the Norwegian Institute of Public Health. Parental reports of children’s inattention at age 8 were linked to modelled levels of residential road traffic noise. We investigated the association between inattention and noise exposure during pregnancy (n = 1934), noise exposure averaged over 5 years (age 3 to 8 years; n = 1384) and noise exposure at age 8 years (n = 1384), using fractional logit response models. The participants were children from Oslo, Norway. Results An association with inattention at age 8 years was found for road traffic noise exposure at age 8 years (coef = .0083, CI = [.0012, .0154]; 1.2% point increase in inattention score per 10 dB increase in noise level), road traffic noise exposure average for the last 5 years (coef = .0090, CI = [.0016, .0164]; 1.3% point increase/10 dB), and for pregnancy road traffic noise exposure for boys (coef = .0091, CI = [.0010, .0171]), but not girls (coef = −.0021, CI = [−.0094, .0053]). Criteria for doing mediation analyses were not fulfilled. Conclusion Results indicate that road traffic noise has a negative impact on children’s inattention. We found no mediation by sleep duration.

Abstract Background The World Health Organization recognises the importance of natural environments for human health. Evidence for natural environment-health associations comes largely from single countries or regions, with varied approaches to measuring natural environment exposure. We present a standardised approach to measuring neighbourhood natural environment exposure in cities in different regions of Europe. Methods The Positive Health Effects of the Natural Outdoor environment in TYPical populations of different regions in Europe (PHENOTYPE) study aimed to explore the mechanisms linking natural environment exposure and health in four European cities (Barcelona, Spain; Doetinchem, the Netherlands; Kaunas, Lithuania; and Stoke-on-Trent, UK). Common GIS protocols were used to develop a hierarchy of natural environment measures, from simple measures (e.g., NDVI, Urban Atlas) using Europe-wide data sources, to detailed measures derived from local data that were specific to mechanisms thought to underpin natural environment-health associations (physical activity, social interaction, stress reduction/restoration). Indicators were created around residential addresses for a range of straight line and network buffers (100 m–1 km). Results For simple indicators derived from Europe-wide data, we observed differences between cities, which varied with different indicators (e.g., Kaunas and Doetinchem had equal highest mean NDVI within 100 m buffer, but mean distance to nearest natural environment in Kaunas was more twice that in Doetinchem). Mean distance to nearest natural environment for all cities suggested that most participants lived close to some kind of natural environments (64 ± 58–363 ± 281 m; mean 180 ± 204 m). The detailed classification highlighted marked between-city differences in terms of prominent types of natural environment. Indicators specific to mechanisms derived from this classification also captured more variation than the simple indicators. Distance to nearest and count indicators showed clear differences between cities, and those specific to the mechanisms showed within-city differences for Barcelona and Doetinchem. Conclusions This paper demonstrates the feasibility and challenges of creating comparable GIS-derived natural environment exposure indicators across diverse European cities. Mechanism-specific indicators showed within- and between-city variability that supports their utility for ecological studies, which could inform more specific policy recommendations than the traditional proxies for natural environment access.

Exposure to natural outdoor environments (NOE) has been shown in population-level studies to reduce anxiety and psychological distress. This study investigated how exposure to one’s everyday natural outdoor environments over one week influenced mood among residents of four European cities including Barcelona (Spain), Stoke-on-Trent (United Kingdom), Doetinchem (The Netherlands) and Kaunas (Lithuania). Participants (n = 368) wore a smartphone equipped with software applications to track location and mood (using mobile ecological momentary assessment (EMA) software), for seven consecutive days. We estimated random-effects ordered logistic regression models to examine the association between mood (positive and negative affect), and exposure to green space, represented by two binary variables indicating exposure versus no exposure to NOE using GPS tracking and satellite and aerial imagery, 10 and 30 min prior to participants’ completing the EMA. Models were adjusted for home city, day of the week, hour of the day, EMA survey type, residential NOE exposure, and sex, age, education level, mental health status and neighbourhood socioeconomic status. In addition, we tested for heterogeneity of effect by city, sex, age, residential NOE exposure and mental health status. Within 10 min of NOE exposure, compared to non-exposure, we found that overall there was a positive relationship with positive affect (OR: 1.39, 95% CI: 1.06, 1.81) of EMA surveys, and non-significant negative association with negative affect (OR: 0.80, 95% CI: 0.58, 1.10). When stratifying, associations were consistently found for Stoke-on-Trent inhabitants and men, while findings by age group were inconsistent. Weaker and less consistent associations were found for exposure 30 min prior to EMA. Our findings support increasing evidence of psychological and mental health benefits of exposure to natural outdoor environments, especially among urban populations such as those included in our study. Keywords: Ecological momentary assessment, Green space and health, Mood

Background Physical activity enhances the uptake of air pollutants, possibly reducing its beneficial effects. We examined the effects of leisure‐time and transport‐related physical activities on the risk of myocardial infarction (MI), and whether potential benefits on MI are reduced by exposure to traffic‐related air pollution. Methods and Results A group of 57 053 participants (50–65 years of age) from the Danish Diet, Cancer, and Health cohort reported physical activity at baseline (1993–1997) and were linked to registry data on hospital contacts and out‐of‐hospital deaths caused by MI, until December 2015. Nitrogen dioxide levels were estimated at participants’ baseline residences. We used Cox regressions to associate participation in sports, cycling, walking, and gardening with incident and recurrent MI, and tested for interaction by nitrogen dioxide. Of 50 635 participants without MI at baseline, 2936 developed incident MI, and of 1233 participants with MI before baseline, 324 had recurring MI during follow‐up. Mean nitrogen dioxide concentration was 18.7 μg/m3 at baseline (1993–1997). We found inverse statistically significant associations between participation in sports (hazard ratio; 95% confidence interval: 0.85; 0.79–0.92), cycling (0.91; 0.84–0.98), gardening (0.87; 0.80–0.95), and incident MI, while the association with walking was statistically nonsignificant (0.95; 0.83–1.08). Recurrent MI was statistically nonsignificantly inversely associated with cycling (0.80; 0.63–1.02), walking (0.82, 0.57–1.16), and gardening (0.91; 0.71–1.18), and positively with sports (1.06; 0.83–1.35). There was no effect modification of the associations between physical activity and MI by nitrogen dioxide. Conclusions Benefits of physical activity on both the incidence and the recurrence of MI are not reduced by exposure to high levels of air pollution.

During 2003–2004, United Utilities water company in North West England introduced enhanced coagulation (EC) to four treatment works to mitigate disinfection by-product (DBP) formation. This enabled examination of the relation between DBPs and birth outcomes whilst reducing socioeconomic confounding. We compared stillbirth, and low and very low birth weight rates three years before (2000–2002) with three years after (2005–2007) the intervention, and in relation to categories of THM change.We created exposure metrics for EC and trihalomethane (THM) concentration change (n = 258 water zones). We linked 429,599 live births and 2279 stillbirths from national birth registers to the water zone at birth. We used Poisson regression to model the differences in birth outcome rates with an interaction between before/after the intervention and EC or THM change.EC treatment reduced chloroform concentrations more than non-treatment (mean -29.7 µg/l vs. -14.5 µg/l), but not brominated THM concentrations. Only 6% of EC water zones received 100% EC water, creating exposure misclassification concerns. EC intervention was not associated with a statistically significant reduction in birth outcome rates. Areas with the highest chloroform decrease (30 – 65 μg/l) had the greatest percentage decrease in low -9 % (-12, -5) and very low birth weight -16% (-24, -8) rates. The interaction between before/after intervention and chloroform change was statistically significant only for very low birth weight, p = 0.02. There were no significant decreases in stillbirth rates.In a novel approach for studying DBPs and adverse reproductive outcomes, the EC intervention to reduce DBPs did not affect birth outcome rates. However, a measured large decrease in chloroform concentrations was associated with statistically significant reductions in very low birth weight rates. Keywords: Chloroform, Disinfection by-products, Trihalomethanes, Drinking-water, Low birth weight, Stillbirth

Background: Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods. Objectives: Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5. Methods: The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20–40 ESCAPE monitoring sites in each area. Results: The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19–0.89), 0.39 (0.23–0.66) and 0.29 (0.22–0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09–0.86) for NO2; 0.58 (0.36–0.88) for PM10 and 0.58 (0.39–0.66) for PM2.5. Conclusions: LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5. Keywords: Land use regression, Dispersion modelling, Air pollution, Exposure, Cohort

Objectives: Low participation rates in the selection of population controls are an increasing concern for the validity of case-control studies worldwide. Methods: We conducted a pilot study to assess two approaches to recruiting population controls in a study of colorectal cancer, including a face-to-face interview and blood sample collection. In the first approach, persons identified through a population roster were invited to participate through a telephone call by an interviewer telephoning on behalf of our research center. In the second approach, individuals were identified from the lists of selected family practitioners and were telephoned on behalf of the family practitioner. Results: When the second method was used, participation rates increased from 42% to 57% and the percentage of refusals decreased from 47% to 13%. The reasons for refusing to participate did not differ significantly between the two methods. Conclusions: Contact through the family practitioner yielded higher response rates in population controls in the study area.Objetivos: Las bajas tasas de participación de controles poblacionales son una preocupación para la validez de los estudios de casos y controles. Métodos: Realizamos un estudio piloto utilizando dos estrategias de reclutamiento de controles poblacionales en un estudio de cáncer colorrectal, incluyendo una entrevista personal y una extracción de sangre. Con la primera estrategia, una entrevistadora llamaba en nombre del centro de investigación a los sujetos de un censo. Con la segunda estrategia, los sujetos fueron seleccionados a partir de los listados de población asignada a los médicos de familia y la llamada se hacía en nombre del médico. Resultados: Las tasas de participación aumentaron del 42% al 57% usando el segundo método; el porcentaje de rechazos disminuyó del 47% al 13%. Las razones de rechazo no diferían según la estrategia. Conclusiones: El contacto a través del médico de familia reportó mayores tasas de respuesta para los controles poblacionales del área de estudio.