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Background: Air pollution is the leading environmental risk factor for health. Assessing outdoor air pollution exposure with detailed spatial and temporal variability in urban areas is crucial for evaluating its health effects., Aim: We developed and compared Land Use Regression (LUR), dispersion (DM), and hybrid (HM) models to estimate outdoor concentrations for NO 2 , PM 2.5 , black carbon (BC), and PM 2.5-constituents (Fe, Cu, Zn) in Barcelona., Methods: Two monitoring campaigns were conducted. In the first, NO 2 concentrations were measured twice at 984 home addresses and in the second, NO 2 , PM 2.5 , and BC were measured four times at 34 points across Barcelona. LUR and DM were constructed using conventional techniques, while HM was developed using Random Forest (RF). Model performance was evaluated using leave-one-out cross-validation (LOOCV) and 10-fold cross-validation (10-CV) for LUR and HM, and by comparing DM and LUR estimates with routine monitoring stations. NO 2 levels estimated by all models were externally validated using the home monitoring campaign. Agreement between models was assessed using Spearman correlation (rs) and Bland-Altman (BA) plots., Results: Models showed moderate to good performance. LUR exhibited R 2 LOOCV of 0.62 (NO 2 ), 0.45 (PM 2.5 ), 0.83 (BC), and 0.85 to 0.89 (PM 2.5-constituents ). DM model comparison showed R 2 values of 0.39 (NO 2 ), 0.26 (PM 2.5 ), and 0.65 (BC). HM models had higher R 2 10-CV 0.64 (NO 2 ), 0.66 (PM 2.5 ), 0.86 (BC), and 0.44 to 0.70 (PM 2.5-constituents ). Validation for NO 2 showed R 2 values of 0.56 (LUR), 0.44 (DM), and 0.64 (HM). Correlations between models varied from -0.38 to 0.92 for long-term exposure, and - 0.23 to 0.94 for short-term exposure. BA plots showed good agreement between models, especially for NO 2 and BC., Conclusions: Our models varied substantially, with some models performing better in validation samples (NO 2 and BC). Future health studies should use the most accurate methods to minimize bias from exposure measurement error., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Built environment characteristics and related environmental exposures and behaviors have been, separately, implicated in the development of poor mental health. However, it is unclear how these factors act together in relation to mental health. We studied these factors simultaneously to evaluate the impact of the built environment, and the mediating role of environmental exposures and physical activity, on mental health, while also studying moderation by sex, age, and length of residence. We used a cross-sectional population-based sample of 3145 individuals aged 15-97 years from Barcelona, Spain. Time spent walking and mental health status were assessed with validated questionnaires, administered through a face-to-face interview. We characterized the built environment (e.g., building, population and intersection density and green space), road traffic noise, and ambient air pollution at the residential level using land cover maps, remote sensing, noise maps and land use regression models. Adjusted regression models accounting for spatial clustering were analyzed to study associations between built environment attributes and mental health, and mediation and moderation effects. Density attributes were directly or indirectly, through air pollution and less consistently through walking, associated with poor mental health. Green space indicators were associated with lower prevalence of poor mental health, partly through lower air pollution exposure and more walking. In some cases, these associations differed by sex, age or length of residence. Non-linear associations of density indicators with environmental exposures, and of particulate matter with poor mental health indicated threshold effects. We conclude that living in dense areas with high air pollution concentrations was associated with poor mental health. On the other hand, green areas with lower air pollution concentrations were protective against poor mental health. Greater urban density might benefit health, but might only do so when air pollution concentrations are low., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Environmental epidemiology studies require models of multiple exposures to adjust for co-exposure and explore interactions. We estimated spatiotemporal exposure to surface air temperature and pollution (PM 2.5 , PM 10 , NO 2 , O 3 ) at high spatiotemporal resolution (daily, 250 m) for 2018-2020 in Catalonia. Innovations include the use of TROPOMI products, a data split for remote sensing gap-filling evaluation, estimation of prediction uncertainty, and use of explainable machine learning. We compiled meteorological and air quality station measurements, climate and atmospheric composition reanalyses, remote sensing products, and other spatiotemporal data. We performed gap-filling of remotely-sensed products using Random Forest (RF) models and validated them using Out-Of-Bag (OOB) samples and a structured data split. The exposure modelling workflow consisted of: 1) PM 2.5 station imputation with PM 10 data; 2) quantile RF (QRF) model fitting; and 3) geostatistical residual spatial interpolation. Prediction uncertainty was estimated using QRF. SHAP values were used to examine variable importance and the fitted relationships. Model performance was assessed via nested CV at the station level. Evaluation of the gap-filling models using the structured split showed error underestimation when using OOB. Temperature models had the best performance (R 2 =0.98) followed by the gaseous air pollutants (R 2 =0.81 for NO 2 and 0.86 for O 3 ), while the performance of the PM 2.5 and PM 10 models was lower (R 2 =0.57 and 0.63 respectively). Predicted exposure patterns captured urban heat island effects, dust advection events, and NO 2 hotspots. SHAP values estimated a high importance of TROPOMI tropospheric NO 2 columns in PM and NO 2 models, and confirmed that the fitted associations conformed to prior knowledge. Our work highlights the importance of correctly validating gap-filling models and the potential of TROPOMI measurements. Moderate performance in PM models can be partly explained by the poor station coverage. Our exposure estimates can be used in epidemiological studies potentially accounting for exposure uncertainty., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Environmental exposures are associated with children's health. Schools are often urban exposure 'hotspots' for pollution, noise, lack of green space and un-walkable built environments. The aim of this systematic review was to explore the impact of school-based interventions on the modification of indoor and outdoor stressors related to the built and natural environment on children's exposure and health. A systematic review of seven databases was performed. We included quantitative studies on children aged 5-12, which reported intervention delivered within school settings aimed at addressing key environmental exposures including air pollution, green spaces, traffic noise or active travel; and reported physical and mental health, physical activity or active travel behavior. The quality of studies was assessed and interventions were described using a standardized framework. A narrative synthesis approach was used to describe the findings. Thirty-nine papers were included on three main intervention types: improve indoor air quality by the increase of ventilation rates in classrooms; increase children's green time or greening schools, and multicomponent interventions to increase active travel to school by changes in pedestrian facilities. No eligible intervention to reduce traffic noise at school was found. Increasing ventilation rates improved short-term indoor air quality in classrooms, but the effect on cognitive performance was inconsistent. Greening schools and increasing children's green time have consistent positive effects on cognition and physical activity, but not in behavior. Multi-component interventions can increase walking and cycling after three years. Overall, the studies were rated as having poor quality owing to weak study designs. We found modest evidence that school-based built and natural environment interventions can improve children's exposure and health.

Background: In areas with moderate to severe air pollution, pollutant concentrations are associated with dementia risk. It is unclear whether the same relationship is present in regions with lower ambient air pollution., Objective: To determine whether exposure to air pollution is associated with risk of incident dementia in general, and Alzheimer's disease and vascular dementia in particular, in older men living in a relatively low ambient air pollution region., Methods: The cohort comprised 11,243 men residing in Perth, Australia. Participants were aged ≥65 years and free of a dementia diagnosis at time of recruitment in 1996-1999. Incident dementia was identified from recruitment to 2018 via ICD diagnosis codes and subsequent study waves. Concentrations for three air pollutants, nitrogen dioxide (NO 2 ), fine particulate matter less than 2.5 μm in diameter (PM 2.5 ), and black carbon (BC) were estimated at participants' home addresses using land-use regression models. We used Cox proportional hazards regression models adjusting for smoking status, physical activity, BMI, education, and socio-economic status., Results: Of 3053 (27.2%) incident cases of dementia, 1670 (54.7%) and 355 (11.6%) had documented Alzheimer's disease and vascular dementia. The average concentration of NO 2 was 13.5 (SD 4.4) μg/m 3 , of PM 2.5 was 4.54 (SD 1.6) μg/m 3 and of BC was 0.97 (SD 0.29) ×10 -5  m -1 . None of the air pollutants were associated with incident dementia or Alzheimer's disease. In the unadjusted model, increased exposure to PM 2.5 was associated with an increased risk of vascular dementia (for a 5 μg/m 3 increase: HR 1.62, 95% CI 1.13, 2.31). However, this association was attenuated following adjustment for confounders (HR 1.39, 95% CI 0.93, 2.08). NO 2 and BC were not associated with vascular dementia incidence., Discussion: Exposure to air pollution is not associated with increased risk of incident dementia in older men living in a region with relatively low ambient air pollution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: The association between air pollution and green spaces with breast cancer risk stratified by menopausal status has not been frequently investigated despite its importance given the different impact of risk factors on breast cancer risk depending on menopausal status., Objectives: To study the association between air pollution, green spaces and pre and postmenopausal breast cancer risk., Methods: We conducted a population-based cohort study using electronic primary care records in Catalonia. We included women aged 17-85 years free of cancer at study entry between 2009 and 2017. Our exposures were particulate matter <2.5 μm (PM 2.5 ) & <10 μm (PM 10 ), nitrogen dioxide (NO 2 ), normalized difference vegetation index (NDVI), and percentage of green spaces estimated at the census tract level. Breast cancer was identified with ICD-10 code C50. We estimated cause-specific hazard ratios (HR) for the relationship between each individual exposure and pre and postmenopausal breast cancer risk, using linear and non-linear models., Results: Of the 1,054,180 pre and 744,658 postmenopausal women followed for a median of 10 years, 6,126 and 17,858 developed breast cancer, respectively. Among premenopausal women, only very high levels of PM 10 (≥46 μg/m 3 ) were associated with increased cancer risk (compared to lower levels) in non-linear models. Among postmenopausal women, an interquartile range increase in PM 2.5 (HR:1.03; 95%CI:1.01-1.04), PM 10 (1.03; 1.01-1.05), and NO 2 (1.05; 1.02-1.08) were associated with higher cancer risk. NDVI was negatively associated with decreased cancer risk only among postmenopausal women who did not change residence during follow-up (0.84; 0.71-0.99) or who were followed for at least three years (0.82; 0.69-0.98)., Discussion: Living in areas with high concentrations of PM 2.5 , PM 10 , and NO 2 increases breast cancer risk in postmenopausal women while long-term exposure to green spaces may decrease this risk. Only very high concentrations of PM 10 increase breast cancer risk in premenopausal women., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Exposure to air pollution influences children's health, however, the biological mechanisms underlying these effects are not completely elucidated. We investigated the association between short- and medium-term outdoor air pollution exposure with protein profiles and their link with blood pressure in 1170 HELIX children aged 6-11 years. Different air pollutants (NO 2 , PM 10 , PM 2.5 , and PM 2.5abs ) were estimated based on residential and school addresses at three different windows of exposure (1-day, 1-week, and 1-year before clinical and molecular assessment). Thirty-six proteins, including adipokines, cytokines, or apolipoproteins, were measured in children's plasma using Luminex. Systolic and diastolic blood pressure (SBP and DBP) were measured following a standardized protocol. We performed an association study for each air pollutant at each location and time window and each outcome, adjusting for potential confounders. After correcting for multiple-testing, hepatocyte growth factor (HGF) and interleukin 8 (IL8) levels were positively associated with 1-week home exposure to some of the pollutants (NO 2 , PM 10 , or PM 2.5 ). NO 2 1-week home exposure was also related to higher SBP. The mediation study suggested that HGF could explain 19% of the short-term effect of NO 2 on blood pressure, but other study designs are needed to prove the causal directionality between HGF and blood pressure., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

The airway macrophages carbon loading (AMCL) has been suggested to be a biomarker of the long-term exposure to air pollution; however, to date no study has characterized AMCL for the pregnancy period. Therefore, this study aimed to assess the determinants of AMCL during pregnancy in Iran, a middle-income country. This study was based on a sample of 234 pregnant women with term and normal vaginal delivery who were residing in Sabzevar, Iran (2019). We characterized 35 potential determinants of personal exposure to air pollution for each participant, including six personal, nine indoor, and 20 home-outdoor factors. We applied Deletion/Substitution/Addition algorithm to identify the most relevant determinants that could predict AMCL levels. The median (IQR) of AMCL level was 0.12 (0.30) μm 2 with a successful sputum induction in 82.9% (194) of participants. Ambient residential PM 2.5 levels were positively associated with higher AMCL levels. On the other hand, increased residential distance to the traffic lights, squares and ring-roads, the duration of opening window per day, and opening window during cooking were inversely associated with AMCL levels. Our findings provide novel insights on the different personal, indoor, and outdoor determinants of personal exposure to air pollution during pregnancy in a middle-income country., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

We present outcomes from a large-scale air quality citizen science campaign (xAire, 725 measurements) to demonstrate its positive contribution in the interplay between advances in exposure assessment and developments in policy or collective action. A broad partnership with 1,650 people from communities around 18 primary schools across Barcelona provided the capacity to obtain unprecedented high-resolution NO 2 levels and an updated asthma Health Impact Assessment. It is shown that NO 2 levels vary considerably with at some cases very high levels. More than a 1,000 new cases of childhood asthma could be prevented each year by lowering NO 2 levels. Representativity of site selection and the minimal number of samplers for land use regression modelling are considered. Enhancement of community knowledge and attitudes towards collective response were observed and identified as key drivers for successful large-scale monitoring campaigns. The results encourage strengthening collaboration with local communities when exploring environmental health issues., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

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 (PM 2.5 ) 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., (Copyright © 2020 World Health Organization. Published by Elsevier Ltd.. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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 NO 2 (β = -16.4; p = 0.05) and PM 10 (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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The human exposome affects child development and health later in life, but its personal external levels, variability, and correlations are largely unknown. We characterized the personal external exposome of pregnant women and children in eight European cities. Panel studies included 167 pregnant women and 183 children (aged 6-11 years). A personal exposure monitoring kit composed of smartphone, accelerometer, ultraviolet (UV) dosimeter, and two air pollution monitors were used to monitor physical activity (PA), fine particulate matter (PM 2.5 ), black carbon, traffic-related noise, UV-B radiation, and natural outdoor environments (NOE). 77% of women performed the adult recommendation of ≥150 min/week of moderate to vigorous PA (MVPA), while only 3% of children achieved the childhood recommendation of ≥60 min/day MVPA. 11% of women and 17% of children were exposed to daily PM 2.5 levels higher than recommended (≥25μg/m 3 ). Mean exposure to noise ranged from Lden 51.1 dB in Kaunas to Lden 65.2 dB in Barcelona. 4% of women and 23% of children exceeded the recommended maximum of 2 Standard-Erythemal-Dose of UV-B at least once a week. 33% of women and 43% of children never reached the minimum NOE contact recommendation of ≥30 min/week. The variations in air and noise pollution exposure were dominated by between-city variability, while most of the variation observed for NOE contact and PA was between-participants. The correlations between all personal exposures ranged from very low to low (Rho < 0.30). The levels of personal external exposures in both pregnant women and children are above the health recommendations, and there is little correlation between the different exposures. The assessment of the personal external exposome is feasible but sampling requires from one day to more than one year depending on exposure due to high variability between and within cities and participants., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Aim: To assess the main and interaction effects of black carbon and physical activity on arterial blood pressure in a healthy adult population from three European cities using objective personal measurements over short-term (hours and days) and long-term exposure., Methods: A panel study of 122 healthy adults was performed in three European cities (Antwerp, Barcelona, and London). In 3 seasons between March 2015 and March 2016, each participant wore sensors for one week to objectively measure their exposure to black carbon and monitor their physical activity continuously. Blood pressure was assessed three times during the week: at the beginning (day 0), in the middle (day 4), and at the end (day 7). Associations of black carbon and physical activity with blood pressure and their interactions were investigated with linear regression models and multiplicative interaction terms, adjusting for all the potential confounders., Results: In multiple exposure models, we did not see any effects of black carbon on blood pressure but did see effects on systolic blood pressure of moderate-to-vigorous physical activity effect that were statistically significant from 1 h to 8 h after exposure and for long-term exposure. For a 1METhour increase of moderate-to-vigorous physical activity, the difference in the expected mean systolic blood pressure varied from -1.46 mmHg (95%CI -2.11, -0.80) for 1 h mean exposure, to -0.29 mmHg (95%CI -0.55, -0.03) for 8 h mean exposure, and -0.05 mmHg (95%CI -0.09, -0.00) for long-term exposure. There were little to no interaction effects., Conclusions: Results from this study provide evidence that short-term and long-term exposure to moderate-to-vigorous physical activity is associated with a decrease in systolic blood pressure levels. We did not find evidence for a consistent main effect of black carbon on blood pressure, nor any interaction between black carbon and physical activity levels., (Copyright © 2019 Elsevier Inc. All rights reserved.)

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 (<18 years) counts and pollutant exposures at populated US census blocks with a national asthma incidence rate and meta-analysis derived concentration response functions (CRF). NO 2 , PM 2.5 and PM 10 were used as surrogates of TRAP exposures, with NO 2 being most specific. Annual average concentrations were obtained from previously validated land-use regression (LUR) models. Asthma incidence rate and a CRF for each pollutant were obtained from the literature. Estimates were stratified by urban or rural living and by median household income. We also estimated the number of preventable cases among blocks that exceeded the limit for two counterfactual scenarios. The first scenario used the recommended air quality annual averages from the World Health Organization (WHO) as a limit. The second scenario used the minimum modeled concentration for each pollutant, in either year, as a limit., Results: Average concentrations in 2000 and 2010, respectively, were 20.6 and 13.2 μg/m 3 for NO 2 , 12.1 and 9 μg/m 3 for PM 2.5 and 21.5 and 17.9 μg/m 3 for PM 10 . Attributable number of cases ranged between 209,100-331,200 for the year 2000 and 141,900-286,500 for 2010, depending on the pollutant. Asthma incident cases due to TRAP represented 27%-42% of all cases in 2000 and 18%-36% in 2010. Percentage of cases due to TRAP were higher (1) in urban areas than rural areas, and (2) in block groups with lowest median household income. Online open-access interactive maps and tables summarizing findings at the county level and 498 major US cities, are available at [https://carteehdata.org/l/s/TRAP-burden-of-childhood-asthma]. Assuming that pollutants did not exceed WHO air quality recommendations, the number of incident cases that could have been prevented ranged between 300 and 53,400, depending on the pollutant and year. Assuming that pollutant levels were limited to the minimum modeled concentration, the number of childhood asthma incident cases that could have been prevented ranged between 127,700 and 317,600, depending on the pollutant and year., Conclusion: This is the first study to estimate the burden of incident childhood asthma attributable to TRAP at a national scale in the US. The attributable burden of childhood asthma dropped by 33% between 2000 and 2010. However, a significant proportion of cases can be prevented., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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 × 10 10 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., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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.

Introduction : Cities often experience high air pollution and noise levels and lack of natural outdoor environments, which may be detrimental to health. The aim of this study was to evaluate the effects of air pollution, noise, and blue and green space on premature all-cause mortality in Barcelona using a mega cohort approach. Methods : Both men and women of 18 years and above registered on 1 January 2010 by the Sistema d'Informació pel Desenvolupament de la Investigació en Atenció Primària (SIDIAP) and living in the city of Barcelona were included in the cohort and followed up until 31 December 2014 or until death ( n = 2,939,067 person years). The exposure assessment was conducted at the census tract level ( n = 1061). We assigned exposure to long term ambient levels of nitrogen dioxides (NO₂), nitrogen oxides (NO x ), particulate matter with aerodynamic diameter less than 2.5 µm (PM 2.5 ), between 2.5 µm and 10 µm (PM 2.5⁻10 , i.e., coarse particulate matter), less than 10 µm (PM 10 ) and PM 2.5 light absorption (hereafter referred to as PM 2.5 absorbance) based on land use regressions models. Normalized Difference Vegetation Index (NDVI) was assigned based on remote sensing data, percentage green space and blue space were calculated based on land use maps and modelled road traffic noise was available through the strategic noise map for Barcelona. Results : In this large prospective study ( n = 792,649) in an urban area, we found a decreased risk of all-cause mortality with an increase in green space measured as NDVI (hazard ratio (HR) = 0.92, 95% CI 0.89⁻0.97 per 0.1) and increased risks of mortality with an increase in exposure to blue space (HR = 1.04, 95% CI 1.01⁻1.06 per 1%), NO₂ (HR = 1.01, 95% CI 1.00⁻1.02 per 5 ug/m³) but no risk with noise (HR = 1.00, 95% CI 0.98⁻1.02 per 5 dB(A)). The increased risks appeared to be more pronounced in the more deprived areas. Results for NDVI, and to a lesser extent NO₂, remained most consistent after mutual adjustment for other exposures. The NDVI estimate was a little attenuated when NO₂ was included in the model. The study had some limitations including e.g., the assessment of air pollution, noise, green space and socioeconomic status (SES) on census tract level rather than individual level and residual confounding. Conclusion : This large study provides new insights on the relationship between green and blue space, noise and air pollution and premature all-cause mortality.

Background: Asthma is the most common chronic disease in children. Traffic-related air pollution (TRAP) may be an important exposure contributing to its development. In the UK, Bradford is a deprived city suffering from childhood asthma rates higher than national and regional averages and TRAP is of particular concern to the local communities., Aims: We estimated the burden of childhood asthma attributable to air pollution and specifically TRAP in Bradford. Air pollution exposures were estimated using a newly developed full-chain exposure assessment model and an existing land-use regression model (LUR)., Methods: We estimated childhood population exposure to NO x and, by conversion, NO 2 at the smallest census area level using a newly developed full-chain model knitting together distinct traffic (SATURN), vehicle emission (COPERT) and atmospheric dispersion (ADMS-Urban) models. We compared these estimates with measurements and estimates from ESCAPE's LUR model. Using the UK incidence rate for childhood asthma, meta-analytical exposure-response functions, and estimates from the two exposure models, we estimated annual number of asthma cases attributable to NO 2 and NO x in Bradford, and annual number of asthma cases specifically attributable to traffic., Results: The annual average census tract levels of NO 2 and NO x estimated using the full-chain model were 15.41 and 25.68 μg/m 3 , respectively. On average, 2.75 μg/m 3 NO 2 and 4.59 μg/m 3 NO x were specifically contributed by traffic, without minor roads and cold starts. The annual average census tract levels of NO 2 and NO x estimated using the LUR model were 21.93 and 35.60 μg/m 3 , respectively. The results indicated that up to 687 (or 38% of all) annual childhood asthma cases in Bradford may be attributable to air pollution. Up to 109 cases (6%) and 219 cases (12%) may be specifically attributable to TRAP, with and without minor roads and cold starts, respectively., Conclusions: This is the first study undertaking full-chain health impact assessment of TRAP and childhood asthma in a disadvantaged population with public concern about TRAP. It further adds to scarce literature exploring the impact of different exposure assessments. In conservative estimates, air pollution and TRAP are estimated to cause a large, but largely preventable, childhood asthma burden. Future progress with childhood asthma requires a move beyond the prevalent disease control-based approach toward asthma prevention., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Objectives: Particulate air pollution is linked to adverse cardiovascular effects. The aim of the study was to investigate the effect of short-term exposure to indoor particles on blood pressure (BP)., Methods: We analyzed the association of particle emissions from indoor sources (candle burning, toasting bread, frying sausages) with BP changes in 54 healthy volunteers in a randomized cross-over controlled exposure study. Particle mass concentration (PMC), size-specific particle number concentration (PNC) and lung-deposited particle surface area concentration (PSC) were measured during the 2h exposure. Systolic and diastolic blood pressure were measured before, during, directly, 2, 4 and 24h after exposure. We performed multiple mixed linear regression analyses of different particle metrics and BP., Results: BP significantly increased with increasing PMC, PSC and PNC resulting from toasting bread. For example, an increase per 10µg/m 3 PM 10 and PM 2.5 , systolic BP increased at all time points with largest changes 1h after exposure initiation of 1.5mmHg (95%-CI: 1.1; 1.9) and of 2.2mmHg (95%-CI: 1.3; 3.1), respectively., Conclusions: Our study suggests an association of short-term exposure to fine and ultrafine particles emitted from toasting bread with increases in BP. Particles emitted from frying sausages and candle burning did not consistently affect BP., (Copyright © 2017. Published by Elsevier Inc.)

Background : Current levels of traffic-related air pollution (TRAP) are associated with the development of childhood asthma, although some inconsistencies and heterogeneity remain. An important part of the uncertainty in studies of TRAP-associated asthma originates from uncertainties in the TRAP exposure assessment and assignment methods. In this work, we aim to systematically review the exposure assessment methods used in the epidemiology of TRAP and childhood asthma, highlight recent advances, remaining research gaps and make suggestions for further research. Methods : We systematically reviewed epidemiological studies published up until 8 September 2016 and available in Embase, Ovid MEDLINE (R), and "Transport database". We included studies which examined the association between children's exposure to TRAP metrics and their risk of "asthma" incidence or lifetime prevalence, from birth to the age of 18 years old. Results : We found 42 studies which examined the associations between TRAP and subsequent childhood asthma incidence or lifetime prevalence, published since 1999. Land-use regression modelling was the most commonly used method and nitrogen dioxide (NO₂) was the most commonly used pollutant in the exposure assessments. Most studies estimated TRAP exposure at the residential address and only a few considered the participants' mobility. TRAP exposure was mostly assessed at the birth year and only a few studies considered different and/or multiple exposure time windows. We recommend that further work is needed including e.g., the use of new exposure metrics such as the composition of particulate matter, oxidative potential and ultra-fine particles, improved modelling e.g., by combining different exposure assessment models, including mobility of the participants, and systematically investigating different exposure time windows. Conclusions : Although our previous meta-analysis found statistically significant associations for various TRAP exposures and subsequent childhood asthma, further refinement of the exposure assessment may improve the risk estimates, and shed light on critical exposure time windows, putative agents, underlying mechanisms and drivers of heterogeneity.

Atmospheric pollutants and meteorological conditions are suspected to be causes of preterm birth. We aimed to characterize their possible association with the risk of preterm birth (defined as birth occurring before 37 completed gestational weeks). We pooled individual data from 13 birth cohorts in 11 European countries (71,493 births from the period 1994-2011, European Study of Cohorts for Air Pollution Effects (ESCAPE)). City-specific meteorological data from routine monitors were averaged over time windows spanning from 1 week to the whole pregnancy. Atmospheric pollution measurements (nitrogen oxides and particulate matter) were combined with data from permanent monitors and land-use data into seasonally adjusted land-use regression models. Preterm birth risks associated with air pollution and meteorological factors were estimated using adjusted discrete-time Cox models. The frequency of preterm birth was 5.0%. Preterm birth risk tended to increase with first-trimester average atmospheric pressure (odds ratio per 5-mbar increase = 1.06, 95% confidence interval: 1.01, 1.11), which could not be distinguished from altitude. There was also some evidence of an increase in preterm birth risk with first-trimester average temperature in the -5°C to 15°C range, with a plateau afterwards (spline coding, P = 0.08). No evidence of adverse association with atmospheric pollutants was observed. Our study lends support for an increase in preterm birth risk with atmospheric pressure., (© The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The available evidence of the effects of air pollution and noise on behavioral development is limited, and it overlooks exposure at schools, where children spend a considerable amount of time., Objective: We aimed to investigate the associations of exposure to traffic-related air pollutants (TRAPs) and noise at school on behavioral development of schoolchildren., Methods: We evaluated children 7-11 years of age in Barcelona (Catalonia, Spain) during 2012-2013 within the BREATHE project. Indoor and outdoor concentrations of elemental carbon (EC), black carbon (BC), and nitrogen dioxide (NO2) were measured at schools in two separate 1-week campaigns. In one campaign we also measured noise levels inside classrooms. Parents filled out the strengths and difficulties questionnaire (SDQ) to assess child behavioral development, while teachers completed the attention deficit/hyperactivity disorder criteria of the DSM-IV (ADHD-DSM-IV) list to assess specific ADHD symptomatology. Negative binomial mixed-effects models were used to estimate associations between the exposures and behavioral development scores., Results: Interquartile range (IQR) increases in indoor and outdoor EC, BC, and NO2 concentrations were positively associated with SDQ total difficulties scores (suggesting more frequent behavioral problems) in adjusted multivariate models, whereas noise was significantly associated with ADHD-DSM-IV scores., Conclusion: In our study population of 7- to 11-year-old children residing in Barcelona, exposure to TRAPs at school was associated with increased behavioral problems in schoolchildren. Noise exposure at school was associated with more ADHD symptoms., Citation: Forns J, Dadvand P, Foraster M, Alvarez-Pedrerol M, Rivas I, López-Vicente M, Suades-Gonzalez E, Garcia-Esteban R, Esnaola M, Cirach M, Grellier J, Basagaña X, Querol X, Guxens M, Nieuwenhuijsen MJ, Sunyer J. 2016. Traffic-related air pollution, noise at school, and behavioral problems in Barcelona schoolchildren: a cross-sectional study. Environ Health Perspect 124:529-535; http://dx.doi.org/10.1289/ehp.1409449.

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements. We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning. PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10. Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10&#95;Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Background: Exposure to ambient air pollution has been associated with reduced size of newborns; however, the modifying effect of maternal ethnicity remains little explored among South Asians., Objectives: We investigated ethnic differences in the association between ambient air pollution and newborn's size., Method: Pregnant women were recruited between 2007 and 2010 for the Born in Bradford cohort study, in England. Exposures to particulate matter (≤ 10 μm, PM10; ≤ 2.5 μm, PM2.5), PM2.5 absorbance, and nitrogen oxides (NOx, NO2) were estimated using land-use regressions models. Using multivariate linear regression models, we evaluated effect modification by maternal ethnicity ("white British" or "Pakistani origin," self-reported) on the associations of air pollution and birth weight, head circumference, and triceps and subscapular skinfold thickness., Results: A 5-μg/m3 increase in mean third trimester PM2.5 was associated with significantly lower birth weight and smaller head circumference in children of white British mothers (-43 g; 95% CI: -76, -10 and -0.28 cm; 95% CI: -0.39, -0.17, respectively), but not in children of Pakistani origin (9 g; 95% CI: -17, 35 and -0.08 cm; 95% CI: -0.17, 0.01, respectively) (p(int) = 0.03 and < 0.001). In contrast, PM2.5 was associated with significantly larger triceps and subscapular skinfold thicknesses in children of Pakistani origin (0.17 mm; 95% CI: 0.08, 0.25 and 0.21 mm; 95% CI: 0.12, 0.29, respectively), but not in white British children (-0.02 mm; 95% CI: -0.14, 0.01 and 0.06 mm; 95% CI: -0.06, 0.18, respectively) (p(int) = 0.06 and 0.11). Patterns of associations for PM10 and PM2.5 absorbance according to ethnicity were similar to those for PM2.5, but associations of the outcomes with NO2 and NOx were mostly nonsignificant in both ethnic groups., Conclusions: Our results suggest that associations of ambient PM exposures with newborn size and adiposity differ between white British and Pakistani origin infants., Citation: Schembari A, de Hoogh K, Pedersen M, Dadvand P, Martinez D, Hoek G, Petherick ES, Wright J, Nieuwenhuijsen MJ. 2015. Ambient air pollution and newborn size and adiposity at birth: differences by maternal ethnicity (the Born in Bradford study cohort). Environ Health Perspect 123:1208-1215; http://dx.doi.org/10.1289/ehp.1408675.

Greenness has been reported to improve mental and physical health. Reduction in exposure to air pollution has been suggested to underlie the health benefits of greenness; however, the available evidence on the mitigating effect of greenness on air pollution remains limited and inconsistent. We investigated the association between greenness within and surrounding school boundaries and monitored indoor and outdoor levels of traffic-related air pollutants (TRAPs) including NO2, ultrafine particles, black carbon, and traffic-related PM2.5 at 39 schools across Barcelona, Spain, in 2012. TRAP levels at schools were measured twice during two one-week campaigns separated by 6months. Greenness within and surrounding school boundaries was measured as the average of satellite-derived normalized difference vegetation index (NDVI) within boundaries of school and a 50m buffer around the school, respectively. Mixed effects models were used to quantify the associations between school greenness and TRAP levels, adjusted for relevant covariates. Higher greenness within and surrounding school boundaries was consistently associated with lower indoor and outdoor TRAP levels. Reduction in indoor TRAP levels was partly mediated by the reduction in outdoor TRAP levels. We also observed some suggestions for stronger associations between school surrounding greenness and outdoor TRAP levels for schools with higher number of trees around them. Our observed reduction of TRAP levels at schools associated with school greenness can be of public importance, considering the burden of health effects of exposure to TRAPs in schoolchildren., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Background: Studies have shown associations between mortality and long-term exposure to particulate matter air pollution. Few cohort studies have estimated the effects of the elemental composition of particulate matter on mortality., Objectives: Our aim was to study the association between natural-cause mortality and long-term exposure to elemental components of particulate matter., Methods: Mortality and confounder data from 19 European cohort studies were used. Residential exposure to eight a priori-selected components of particulate matter (PM) was characterized following a strictly standardized protocol. Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc within PM size fractions ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10) were estimated using land-use regression models. Cohort-specific statistical analyses of the associations between mortality and air pollution were conducted using Cox proportional hazards models using a common protocol followed by meta-analysis., Results: The total study population consisted of 291,816 participants, of whom 25,466 died from a natural cause during follow-up (average time of follow-up, 14.3 years). Hazard ratios were positive for almost all elements and statistically significant for PM2.5 sulfur (1.14; 95% CI: 1.06, 1.23 per 200 ng/m3). In a two-pollutant model, the association with PM2.5 sulfur was robust to adjustment for PM2.5 mass, whereas the association with PM2.5 mass was reduced., Conclusions: Long-term exposure to PM2.5 sulfur was associated with natural-cause mortality. This association was robust to adjustment for other pollutants and PM2.5.

Background: Short-term exposure to air pollution has adverse effects among patients with asthma, but whether long-term exposure to air pollution is a cause of adult-onset asthma is unclear., Objective: We aimed to investigate the association between air pollution and adult onset asthma., Methods: Asthma incidence was prospectively assessed in six European cohorts. Exposures studied were annual average concentrations at home addresses for nitrogen oxides assessed for 23,704 participants (including 1,257 incident cases) and particulate matter (PM) assessed for 17,909 participants through ESCAPE land-use regression models and traffic exposure indicators. Meta-analyses of cohort-specific logistic regression on asthma incidence were performed. Models were adjusted for age, sex, overweight, education, and smoking and included city/area within each cohort as a random effect., Results: In this longitudinal analysis, asthma incidence was positively, but not significantly, associated with all exposure metrics, except for PMcoarse. Positive associations of borderline significance were observed for nitrogen dioxide [adjusted odds ratio (OR) = 1.10; 95% CI: 0.99, 1.21 per 10 μg/m3; p = 0.10] and nitrogen oxides (adjusted OR = 1.04; 95% CI: 0.99, 1.08 per 20 μg/m3; p = 0.08). Nonsignificant positive associations were estimated for PM10 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 10 μg/m3), PM2.5 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 5 μg/m3), PM2.5absorbance (adjusted OR = 1.06; 95% CI: 0.95, 1.19 per 10-5/m), traffic load (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 4 million vehicles × meters/day on major roads in a 100-m buffer), and traffic intensity (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 5,000 vehicles/day on the nearest road). A nonsignificant negative association was estimated for PMcoarse (adjusted OR = 0.98; 95% CI: 0.87, 1.14 per 5 μg/m3)., Conclusions: Results suggest a deleterious effect of ambient air pollution on asthma incidence in adults. Further research with improved personal-level exposure assessment (vs. residential exposure assessment only) and phenotypic characterization is needed.

Background: Bulky DNA adducts reflect genotoxic exposures, have been associated with lower birth weight, and may predict cancer risk., Objective: We selected factors known or hypothesized to affect in utero adduct formation and repair and examined their associations with adduct levels in neonates., Methods: Pregnant women from Greece, Spain, England, Denmark, and Norway were recruited in 2006-2010. Cord blood bulky DNA adduct levels were measured by the 32P-postlabeling technique (n = 511). Diet and maternal characteristics were assessed via questionnaires. Modeled exposures to air pollutants and drinking-water disinfection by-products, mainly trihalomethanes (THMs), were available for a large proportion of the study population., Results: Greek and Spanish neonates had higher adduct levels than the northern European neonates [median, 12.1 (n = 179) vs. 6.8 (n = 332) adducts per 108 nucleotides, p < 0.001]. Residence in southern European countries, higher maternal body mass index, delivery by cesarean section, male infant sex, low maternal intake of fruits rich in vitamin C, high intake of dairy products, and low adherence to healthy diet score were statistically significantly associated with higher adduct levels in adjusted models. Exposure to fine particulate matter and nitrogen dioxide was associated with significantly higher adducts in the Danish subsample only. Overall, the pooled results for THMs in water show no evidence of association with adduct levels; however, there are country-specific differences in results with a suggestion of an association in England., Conclusion: These findings suggest that a combination of factors, including unknown country-specific factors, influence the bulky DNA adduct levels in neonates.

Novel technologies, such as smartphones and small personal continuous air pollution sensors, can now facilitate better personal estimates of air pollution in relation to location. Such information can provide us with a better understanding about whether and how personal exposures relate to residential air pollution estimates, which are normally used in epidemiological studies. The aims of this study were to examine (1) the variability in personal air pollution levels during the day and (2) the relationship between modeled home and school estimates and continuously measured personal air pollution exposure levels in different microenvironments (e.g., home, school, and commute). We focused on black carbon as an indicator of traffic-related air pollution. We recruited 54 school children (aged 7-11) from 29 different schools around Barcelona as part of the BREATHE study, an epidemiological study of the relation between air pollution and brain development. For 2 typical week days during 2012-2013, the children were given a smartphone with CalFit software to obtain information on their location and physical activity level and a small sensor, the micro-aethalometer model AE51, to measure their black carbon levels simultaneously and continuously. We estimated their home and school exposure to PM2.5 filter absorbance, which is well-correlated with black carbon, using a temporally adjusted PM2.5 absorbance land use regression (LUR) model. We found considerable variation in the black carbon levels during the day, with the highest levels measured during commuting periods (geometric mean = 2.8 μg/m(3)) and the lowest levels at home (geometric mean = 1.3 μg/m(3)). Hourly temporally adjusted LUR model estimates for the home and school showed moderate to good correlation with measured personal black carbon levels at home and school (r = 0.59 and 0.68, respectively) and lower correlation with commuting trips (r = 0.32 and 0.21, respectively). The correlation between modeled home estimates and overall personal black carbon levels was 0.62. Personal black carbon levels vary substantially during the day. The correlation between modeled and measured black carbon levels was generally good, with the exception of commuting times. In conclusion, novel technologies, such as smartphones and sensors, provide insights in personal exposure to air pollution.

The chronic impact of ambient air pollutants on lung function in adults is not fully understood. The objective of this study was to investigate the association of long-term exposure to ambient air pollution with lung function in adult participants from five cohorts in the European Study of Cohorts for Air Pollution Effects (ESCAPE). Residential exposure to nitrogen oxides (NO₂, NOx) and particulate matter (PM) was modelled and traffic indicators were assessed in a standardised manner. The spirometric parameters forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC) from 7613 subjects were considered as outcomes. Cohort-specific results were combined using meta-analysis. We did not observe an association of air pollution with longitudinal change in lung function, but we observed that a 10 μg·m(-3) increase in NO₂ exposure was associated with lower levels of FEV₁ (-14.0 mL, 95% CI -25.8 to -2.1) and FVC (-14.9 mL, 95% CI -28.7 to -1.1). An increase of 10 μg·m(-3) in PM10, but not other PM metrics (PM2.5, coarse fraction of PM, PM absorbance), was associated with a lower level of FEV₁ (-44.6 mL, 95% CI -85.4 to -3.8) and FVC (-59.0 mL, 95% CI -112.3 to -5.6). The associations were particularly strong in obese persons. This study adds to the evidence for an adverse association of ambient air pollution with lung function in adults at very low levels in Europe., (Copyright ©ERS 2015.)

Land use regression (LUR) models have been used to model concentrations of mainly traffic-related air pollutants (nitrogen oxides (NOx), particulate matter (PM) mass or absorbance). Few LUR models are published of PM composition, whereas the interest in health effects related to particle composition is increasing. The aim of our study was to evaluate LUR models of polycyclic aromatic hydrocarbons (PAH), hopanes/steranes, and elemental and organic carbon (EC/OC) content of PM2.5. In 10 European study areas, PAH, hopanes/steranes, and EC/OC concentrations were measured at 16-40 sites per study area. LUR models for each study area were developed on the basis of annual average concentrations and predictor variables including traffic, population, industry, natural land obtained from geographic information systems. The highest median model explained variance (R(2)) was found for EC - 84%. The median R(2) was 51% for OC, 67% for benzo[a]pyrene, and 38% for sum of hopanes/steranes, with large variability between study areas. Traffic predictors were included in most models. Population and natural land were included frequently as additional predictors. The moderate to high explained variance of LUR models and the overall moderate correlation with PM2.5 model predictions support the application of especially the OC and PAH models in epidemiological studies.

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., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Background: Green spaces have been associated with improved mental health in children; however, available epidemiological evidence on their impact on child behavioral development is scarce., Objectives: We investigated the impact of contact with green spaces and blue spaces (beaches) on indicators of behavioral development and symptoms of attention deficit/hyperactivity disorder (ADHD) in schoolchildren., Methods: This study was based on a sample of 2,111 schoolchildren (7-10 years of age) from 36 schools in Barcelona in 2012. We obtained data on time spent in green spaces and beaches and Strengths and Difficulties Questionnaires (SDQ) from parents, and ADHD/DSM-IV questionnaires from teachers. Surrounding greenness was abstracted as the average Normalized Difference Vegetation Index (NDVI) in buffers of 100 m, 250 m, and 500 m around each home address. Proximity to green spaces was defined as living within 300 m of a major green space (≥ 0.05 km2). We applied quasi-Poisson mixed-effects models (with school random effect) to separately estimate associations between indicators of contact with green spaces and SDQ and ADHD total and subscale scores., Results: We generally estimated beneficial associations between behavioral indicators and longer time spent in green spaces and beaches, and with residential surrounding greenness. Specifically, we found statistically significant inverse associations between green space playing time and SDQ total difficulties, emotional symptoms, and peer relationship problems; between residential surrounding greenness and SDQ total difficulties and hyperactivity/inattention and ADHD/DSM-IV total and inattention scores; and between annual beach attendance and SDQ total difficulties, peer relationship problems, and prosocial behavior. For proximity to major green spaces, the results were not conclusive., Conclusion: Our findings support beneficial impacts of contact with green and blue spaces on behavioral development in schoolchildren.

Background: Long-term exposure to air pollution has been hypothesized to elevate arterial blood pressure (BP). The existing evidence is scarce and country specific., Objectives: We investigated the cross-sectional association of long-term traffic-related air pollution with BP and prevalent hypertension in European populations., Methods: We analyzed 15 population-based cohorts, participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE). We modeled residential exposure to particulate matter and nitrogen oxides with land use regression using a uniform protocol. We assessed traffic exposure with traffic indicator variables. We analyzed systolic and diastolic BP in participants medicated and nonmedicated with BP-lowering medication (BPLM) separately, adjusting for personal and area-level risk factors and environmental noise. Prevalent hypertension was defined as ≥ 140 mmHg systolic BP, or ≥ 90 mmHg diastolic BP, or intake of BPLM. We combined cohort-specific results using random-effects meta-analysis., Results: In the main meta-analysis of 113,926 participants, traffic load on major roads within 100 m of the residence was associated with increased systolic and diastolic BP in nonmedicated participants [0.35 mmHg (95% CI: 0.02, 0.68) and 0.22 mmHg (95% CI: 0.04, 0.40) per 4,000,000 vehicles × m/day, respectively]. The estimated odds ratio (OR) for prevalent hypertension was 1.05 (95% CI: 0.99, 1.11) per 4,000,000 vehicles × m/day. Modeled air pollutants and BP were not clearly associated., Conclusions: In this first comprehensive meta-analysis of European population-based cohorts, we observed a weak positive association of high residential traffic exposure with BP in nonmedicated participants, and an elevated OR for prevalent hypertension. The relationship of modeled air pollutants with BP was inconsistent.

The role of air pollution in chronic obstructive pulmonary disease (COPD) remains uncertain. The aim was to assess the impact of chronic exposure to air pollution on COPD in four cohorts using the standardised ESCAPE exposure estimates. Annual average particulate matter (PM), nitrogen oxides (NOx) and road traffic exposure were assigned to home addresses using land-use regression models. COPD was defined by NHANES reference equation (forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) less than the lower limit of normal) and the Global Initiative for Chronic Obstructive Lung Disease criterion (FEV1/FVC <0.70) and categorised by severity in non-asthmatics. We included 6550 subjects with assigned NOx and 3692 with PM measures. COPD was not associated with NO2 or PM10 in any individual cohort. In meta-analyses only NO2, NOx, PM10 and the traffic indicators were positively, although not significantly, associated with COPD. The only statistically significant associations were seen in females (COPD prevalence using GOLD: OR 1.57, 95% CI 1.11-2.23; and incidence: OR 1.79, 95% CI 1.21-2.68). None of the principal results were statistically significant, the weak positive associations of exposure with COPD and the significant subgroup findings need to be evaluated in further well standardised cohorts followed up for longer time, and with time-matched exposure assignments., (©ERS 2014.)

The origin(s) of systemic inflammation in patients with chronic obstructive pulmonary disease (COPD) is unclear. We investigated the impact of exposure to ambient air pollution on systemic biomarkers of inflammation (C-reactive protein (CRP), tumour necrosis factor-α, interleukin (IL)-6, IL-8 and fibrinogen) and tissue repair (hepatocyte growth factor (HGF)) in 242 clinically stable COPD patients (mean age 67.8 years and forced expiratory volume in 1 s 71.3% predicted) in Barcelona, Spain, in 2004-2006. A spatiotemporal exposure assessment framework was applied to predict ambient nitrogen dioxide (NO2) and levels of particles with a 50% cut-off aerodynamic diameter of 2.5 μm (PM2.5) at each participant's home address during 10 periods of 24 h (lags 1-10) and 1 year prior to the blood sampling date. We used linear regression models to estimate associations between biomarkers and exposure levels. An interquartile range (IQR) increase in NO2 exposure in lag 5 was associated with 51%, 10% and 9% increases in CRP, fibrinogen and HGF levels respectively. We also observed 12% and 8% increases in IL-8 associated with an IQR increase in NO2 exposure in lag 3 and over the year before sampling, respectively. These increases were larger in former smokers. The results for PM2.5 were not conclusive. These results show that exposure to ambient NO2 increases systemic inflammation in COPD patients, especially in former smokers., (©ERS 2014.)

Background: Some reports have suggested effects of air pollution on semen quality and success rates of in vitro fertilization (IVF) in humans and lower fertility rates in mice. However, no studies have evaluated the impact of air pollution on human fertility rates., Aims: We assessed the association between traffic related air pollution and fertility rates in humans in Barcelona, Spain (2011-2012). We hypothesized that higher air pollution levels would be associated with lower fertility rates., Methods: We calculated the general fertility rate which is the number of live births per 1000 women between the ages of 15 and 44 years per census tract. We used land use regression (LUR) modeling to estimate the air pollution concentrations (particulate matter, NO2/NOx) per census tract. We used Besag-York-Mollié models to quantify the relationship between air pollution and fertility rates with adjustment for a number of potential confounders such as maternal age and area level socio-economic status., Results: We found a statistically significant reduction of fertility rates with an increase in traffic related air pollution levels, particularly for the coarse fraction of particulate matter (IRR=0.87 95% CI 0.82, 0.94 per IQR)., Conclusion: This is the first study in humans to show an association between reduced fertility rates and higher traffic related air pollution levels., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Introduction: The exposome encompasses the totality of human environmental exposures. Recent developments in sensor technology have made it possible to better measure personal exposure to environmental pollutants and other factors. We aimed to discuss and demonstrate the recent developments in personal sensors to measure multiple exposures and possible acute health responses, and discuss the main challenges ahead., Methods: We searched for a range of sensors to measure air pollution, noise, temperature, UV, physical activity, location, blood pressure, heart rate and lung function and to obtain information on green space and emotional status/mood and put it on a person., Results and Conclusions: We discussed the recent developments and main challenges for personal sensors to measure multiple exposures. We found and put together a personal sensor set that measures a comprehensive set of personal exposures continuously over 24 h to assess part of the current exposome and acute health responses. We obtained data for a whole range of exposures and some acute health responses, but many challenges remain to apply the methodology for extended time periods and larger populations including improving the ease of wear, e.g., through miniaturization and extending battery life, and the reduction of costs. However, the technology is moving fast and opportunities will come closer for further wide spread use to assess, at least part of the exposome.

Background: Land use regression (LUR) models have been developed mostly to explain intraurban variations in air pollution based on often small local monitoring campaigns. Transferability of LUR models from city to city has been investigated, but little is known about the performance of models based on large numbers of monitoring sites covering a large area., Objectives: We aimed to develop European and regional LUR models and to examine their transferability to areas not used for model development., Methods: We evaluated LUR models for nitrogen dioxide (NO2) and particulate matter (PM; PM2.5, PM2.5 absorbance) by combining standardized measurement data from 17 (PM) and 23 (NO2) ESCAPE (European Study of Cohorts for Air Pollution Effects) study areas across 14 European countries for PM and NO2. Models were evaluated with cross-validation (CV) and hold-out validation (HV). We investigated the transferability of the models by successively excluding each study area from model building., Results: The European model explained 56% of the concentration variability across all sites for NO2, 86% for PM2.5, and 70% for PM2.5 absorbance. The HV R2s were only slightly lower than the model R2 (NO2, 54%; PM2.5, 80%; PM2.5 absorbance, 70%). The European NO2, PM2.5, and PM2.5 absorbance models explained a median of 59%, 48%, and 70% of within-area variability in individual areas. The transferred models predicted a modest-to-large fraction of variability in areas that were excluded from model building (median R2: NO2, 59%; PM2.5, 42%; PM2.5 absorbance, 67%)., Conclusions: Using a large data set from 23 European study areas, we were able to develop LUR models for NO2 and PM metrics that predicted measurements made at independent sites and areas reasonably well. This finding is useful for assessing exposure in health studies conducted in areas where no measurements were conducted.

Background: A recent meta-analysis suggested evidence for an effect of exposure to ambient air pollutants on risk of certain congenital heart defects. However, few studies have investigated the effects of traffic-related air pollutants with sufficient spatial accuracy., Objectives: We estimated associations between congenital anomalies and exposure to traffic-related air pollution in Barcelona, Spain., Method: Cases with nonchromosomal anomalies (n = 2,247) and controls (n = 2,991) were selected from the Barcelona congenital anomaly register during 1994-2006. Land use regression models from the European Study of Cohorts for Air Pollution Effects (ESCAPE), were applied to residential addresses at birth to estimate spatial exposure to nitrogen oxides and dioxide (NOx, NO2), particulate matter with diameter ≤ 10 μm (PM10), 10-2.5 μm (PMcoarse), ≤ 2.5 μm (PM2.5), and PM2.5 absorbance. Spatial estimates were adjusted for temporal trends using data from routine monitoring stations for weeks 3-8 of each pregnancy. Logistic regression models were used to calculate odds ratios (ORs) for 18 congenital anomaly groups associated with an interquartile-range (IQR) increase in exposure estimates., Results: In spatial and spatiotemporal exposure models, we estimated statistically significant associations between an IQR increase in NO2 (12.2 μg/m3) and coarctation of the aorta (ORspatiotemporal = 1.15; 95% CI: 1.01, 1.31) and digestive system defects (ORspatiotemporal = 1.11; 95% CI: 1.00, 1.23), and between an IQR increase in PMcoarse (3.6 μg/m3) and abdominal wall defects (ORspatiotemporal = 1.93; 95% CI: 1.37, 2.73). Other statistically significant increased and decreased ORs were estimated based on the spatial model only or the spatiotemporal model only, but not both., Conclusions: Our results overall do not indicate an association between traffic-related air pollution and most groups of congenital anomalies. Findings for coarctation of the aorta are consistent with those of the previous meta-analysis., Citation: Schembari A, Nieuwenhuijsen MJ, Salvador J, de Nazelle A, Cirach M, Dadvand P, Beelen R, Hoek G, Basagaña X, Vrijheid M. 2014. Traffic-related air pollution and congenital anomalies in Barcelona. Environ Health Perspect 122:317-323; http://dx.doi.org/10.1289/ehp.1306802.

Background: A growing body of evidence has associated maternal exposure to air pollution with adverse effects on fetal growth; however, the existing literature is inconsistent., Objectives: We aimed to quantify the association between maternal exposure to particulate air pollution and term birth weight and low birth weight (LBW) across 14 centers from 9 countries, and to explore the influence of site characteristics and exposure assessment methods on between-center heterogeneity in this association., Methods: Using a common analytical protocol, International Collaboration on Air Pollution and Pregnancy Outcomes (ICAPPO) centers generated effect estimates for term LBW and continuous birth weight associated with PM(10) and PM(2.5) (particulate matter ≤ 10 and 2.5 µm). We used meta-analysis to combine the estimates of effect across centers (~ 3 million births) and used meta-regression to evaluate the influence of center characteristics and exposure assessment methods on between-center heterogeneity in reported effect estimates., Results: In random-effects meta-analyses, term LBW was positively associated with a 10-μg/m3 increase in PM10 [odds ratio (OR) = 1.03; 95% CI: 1.01, 1.05] and PM(2.5) (OR = 1.10; 95% CI: 1.03, 1.18) exposure during the entire pregnancy, adjusted for maternal socioeconomic status. A 10-μg/m3 increase in PM(10) exposure was also negatively associated with term birth weight as a continuous outcome in the fully adjusted random-effects meta-analyses (-8.9 g; 95% CI: -13.2, -4.6 g). Meta-regressions revealed that centers with higher median PM(2.5) levels and PM(2.5):PM(10) ratios, and centers that used a temporal exposure assessment (compared with spatiotemporal), tended to report stronger associations., Conclusion: Maternal exposure to particulate pollution was associated with LBW at term across study populations. We detected three site characteristics and aspects of exposure assessment methodology that appeared to contribute to the variation in associations reported by centers.

Desert dust is one of the natural contributors to atmospheric particulate matter worldwide. Although particulate pollution has been shown to adversely affect pregnancy, the available evidence on the impact of dust episodes on pregnancy is very scarce. The aim of this study was to evaluate the impact of Saharan dust episodes on pregnancy complications (preeclampsia and bacteriuria) and outcomes (birth weight and gestational age at delivery). This study was based on a cohort of births (N = 3565) that occurred in a major university hospital in Barcelona during 2003-2005. To determine Saharan dust episodes, we developed a two-stage approach based on meteorological evidence of the presence of Saharan dust cloud over the region and unusually high levels of particulate levels on the ground while taking account of traffic sources. The associations between the number of Saharan dust episodes during whole pregnancy as well as each pregnancy trimester and pregnancy complications and outcomes were analysed. There were 152 days (out of 838 days) with Saharan dust cloud over the region from which 45 days were determined as episodic days. We did not observe any statistically significant harmful effect of Saharan dust episodes on our included pregnancy complications and outcomes. However, we observed a small but statistically significant increase in gestational age at delivery in association with the number of episodic days during the third trimester and whole pregnancy (0.8 and 0.5 days respectively). Our findings were not suggestive for any adverse effect of Saharan dust episodes on our included pregnancy complications and outcomes.

Background: There is growing evidence that traffic-related air pollution reduces birth weight. Improving exposure assessment is a key issue to advance in this research area., Objective: We investigated the effect of prenatal exposure to traffic-related air pollution via geographic information system (GIS) models on birth weight in 570 newborns from the INMA (Environment and Childhood) Sabadell cohort., Methods: We estimated pregnancy and trimester-specific exposures to nitrogen dioxide and aromatic hydrocarbons [benzene, toluene, ethylbenzene, m/p-xylene, and o-xylene (BTEX)] by using temporally adjusted land-use regression (LUR) models. We built models for NO(2) and BTEX using four and three 1-week measurement campaigns, respectively, at 57 locations. We assessed the relationship between prenatal air pollution exposure and birth weight with linear regression models. We performed sensitivity analyses considering time spent at home and time spent in nonresidential outdoor environments during pregnancy., Results: In the overall cohort, neither NO(2) nor BTEX exposure was significantly associated with birth weight in any of the exposure periods. When considering only women who spent < 2 hr/day in nonresidential outdoor environments, the estimated reductions in birth weight associated with an interquartile range increase in BTEX exposure levels were 77 g [95% confidence interval (CI), 7-146 g] and 102 g (95% CI, 28-176 g) for exposures during the whole pregnancy and the second trimester, respectively. The effects of NO(2) exposure were less clear in this subset., Conclusions: The association of BTEX with reduced birth weight underscores the negative role of vehicle exhaust pollutants in reproductive health. Time-activity patterns during pregnancy complement GIS-based models in exposure assessment.

Background: Air pollution from road traffic is a serious health hazard, and people with preexisting respiratory disease may be at increased risk. We investigated the effects of short-term exposure to diesel traffic in people with asthma in an urban, roadside environment., Methods: We recruited 60 adults with either mild or moderate asthma to participate in a randomized, crossover study. Each participant walked for 2 hours along a London street (Oxford Street) and, on a separate occasion, through a nearby park (Hyde Park). We performed detailed real-time exposure, physiological, and immunologic measurements., Results: Participants had significantly higher exposures to fine particles (<2.5 microm in aerodynamic diameter), ultrafine particles, elemental carbon, and nitrogen dioxide on Oxford Street than in Hyde Park. Walking for 2 hours on Oxford Street induced asymptomatic but consistent reductions in the forced expiratory volume in 1 second (FEV1) (up to 6.1%) and forced vital capacity (FVC) (up to 5.4%) that were significantly larger than the reductions in FEV1 and FVC after exposure in Hyde Park (P=0.04 and P=0.01, respectively, for the overall effect of exposure, and P<0.005 at some time points). The effects were greater in subjects with moderate asthma than in those with mild asthma. These changes were accompanied by increases in biomarkers of neutrophilic inflammation (sputum myeloperoxidase, 4.24 ng per milliliter after exposure in Hyde Park vs. 24.5 ng per milliliter after exposure on Oxford Street; P=0.05) and airway acidification (maximum decrease in pH, 0.04% after exposure in Hyde Park and 1.9% after exposure on Oxford Street; P=0.003). The changes were associated most consistently with exposures to ultrafine particles and elemental carbon., Conclusions: Our observations serve as a demonstration and explanation of the epidemiologic evidence that associates the degree of traffic exposure with lung function in asthma., (Copyright 2007 Massachusetts Medical Society.)

Runcorn, North West England, has been a site of industrial activity for over 100 years. Preliminary investigations have revealed excess risk of renal mortality in the population living closest to several sources of pollution. Exposure to airborne mercury has been highlighted as a possible cause, although there is also concomitant exposure to solvents and other heavy metals in this population. The authors used validated air dispersion modeling to identify mercury-exposed populations. Standardized mortality ratios for kidney disease were computed using the North West government region as the reference. There was a significant exposure-response relation between modeled estimates of mercury exposure and risk of kidney disease mortality (test for trend: p = 0.02 for men and p = 0.03 for women), and this relation was more pronounced for estimated historical exposure (test for trend: p = 0.01 for men and p < 0.001 for women). These findings suggest that exposure to mercury is a possible cause of the excess kidney disease mortality in this population, indicating that there might still be a health legacy of the historically high levels of industrial activity in the Runcorn area.

Exposure analysis is a crucial part of effective management of public health risks caused by pollutants and chemicals in our environment. During the last decades, more data required for exposure analysis has become available, but the need for direct population based measurements of exposures is still clear. The current work (i) describes the European EXPOLIS study, designed to produce this kind of exposure data for major air pollutants in Europe, and the database created to make the collected data available for researchers (ii) reviews the exposure analysis conducted and results published so far using these data and (iii) discusses the implications of the results from the point of view of research and environmental policy in Europe. Fine particle (with 37 elements and black smoke), nitrogen dioxide, volatile organic compounds (30 compounds) and carbon monoxide inhalation exposures and exposure-related questionnaire data were measured in seven European cities during 1996-2000. The EXPOLIS database has been used for exposure analysis of these pollutants for 4 years now and results have been published in approximately 30 peer-reviewed journal papers, demonstrating the versatility, usability and scientific value of such a data set. The multipollutant exposure data from the same subjects in the random population samples allows for analyses of the determinants, microenvironments and sources of exposures to multipollutant mixtures and associations between the different air pollutants. This information is necessary and useful for developing effective policies and control strategies for healthier environment.

To assess the arsenic exposure of a population living in the vicinity of a coal-burning power plant with high arsenic emission in the Prievidza District, Slovakia, 548 spot urine samples were speciated for inorganic As (Asinorg), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), and their sum (Assum). The urine samples were collected from the population of a case-control study on nonmelanoma skin cancer (NMSC). A total of 411 samples with complete As speciations and sufficient urine quality and without fish consumption were used for statistical analysis. Although current environmental As exposure and urinary As concentrations were low (median As in soil within 5 km distance to the power plant, 41 micro g/g; median urinary Assum, 5.8 microg/L), there was a significant but weak association between As in soil and urinary Assum(r = 0.21, p < 0.01). We performed a multivariate regression analysis to calculate adjusted regression coefficients for environmental As exposure and other determinants of urinary As. Persons living in the vicinity of the plant had 27% higher Assum values (p < 0.01), based on elevated concentrations of the methylated species. A 32% increase of MMA occurred among subjects who consumed homegrown food (p < 0.001). NMSC cases had significantly higher levels of Assum, DMA, and Asinorg. The methylation index Asinorg/(MMA + DMA) was about 20% lower among cases (p < 0.05) and in men (p < 0.05) compared with controls and females, respectively.