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BACKGROUND: Risk factors for malignant tumours of the central nervous system (CNS) are largely unknown. METHODS: We pooled six European cohorts (N = 302,493) and assessed the association between residential exposure to nitrogen dioxide (NO2), fine particles (PM2.5), black carbon (BC), ozone (O3) and eight elemental components of PM2.5 (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) and malignant intracranial CNS tumours defined according to the International Classification of Diseases ICD-9/ICD-10 codes 192.1/C70.0, 191.0-191.9/C71.0-C71.9, 192.0/C72.2-C72.5. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level. RESULTS: During 5,497,514 person-years of follow-up (average 18.2 years), we observed 623 malignant CNS tumours. The results of the fully adjusted linear analyses showed a hazard ratio (95% confidence interval) of 1.07 (0.95, 1.21) per 10 μg/m³ NO2, 1.17 (0.96, 1.41) per 5 μg/m³ PM2.5, 1.10 (0.97, 1.25) per 0.5 10-5m-1 BC, and 0.99 (0.84, 1.17) per 10 μg/m³ O3. CONCLUSIONS: We observed indications of an association between exposure to NO2, PM2.5, and BC and tumours of the CNS. The PM elements were not consistently associated with CNS tumour incidence.

Background: The association between long-term exposure to air pollution and mortality from cardiorespiratory diseases is well established, yet the evidence for other diseases remains limited. Objectives: To examine the associations of long-term exposure to air pollution with mortality from diabetes, dementia, psychiatric disorders, chronic kidney disease (CKD), asthma, acute lower respiratory infection (ALRI), as well as mortality from all-natural and cardiorespiratory causes in the Danish nationwide administrative cohort. Methods: We followed all residents aged ≥ 30 years (3,083,227) in Denmark from 1 January 2000 until 31 December 2017. Annual mean concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and ozone (warm season) were estimated using European-wide hybrid land-use regression models (100 m × 100 m) and assigned to baseline residential addresses. We used Cox proportional hazard models to evaluate the association between air pollution and mortality, accounting for demographic and socioeconomic factors. We additionally applied indirect adjustment for smoking and body mass index (BMI). Results: During 47,023,454 person-years of follow-up, 803,881 people died from natural causes. Long-term exposure to PM2.5 (mean: 12.4 µg/m3), NO2 (20.3 µg/m3), and/or BC (1.0 × 10-5/m) was statistically significantly associated with all studied mortality outcomes except CKD. A 5 µg/m3 increase in PM2.5 was associated with higher mortality from all-natural causes (hazard ratio 1.11; 95% confidence interval 1.09–1.13), cardiovascular disease (1.09; 1.07–1.12), respiratory disease (1.11; 1.07–1.15), lung cancer (1.19; 1.15–1.24), diabetes (1.10; 1.04–1.16), dementia (1.05; 1.00–1.10), psychiatric disorders (1.38; 1.27–1.50), asthma (1.13; 0.94–1.36), and ALRI (1.14; 1.09–1.20). Associations with long-term exposure to ozone (mean: 80.2 µg/m3) were generally negative but became significantly positive for several endpoints in two-pollutant models. Generally, associations were attenuated but remained significant after indirect adjustment for smoking and BMI. Conclusion: Long-term exposure to PM2.5, NO2, and/or BC in Denmark were associated with mortality beyond cardiorespiratory diseases, including diabetes, dementia, psychiatric disorders, asthma, and ALRI. © 2022 The Authors

Background: Ambient air pollution exposure has been associated with higher mortality risk in numerous studies. We assessed potential variability in the magnitude of this association for non-accidental, cardiovascular disease, respiratory disease, and lung cancer mortality in a country-wide administrative cohort by exposure assessment method and by adjustment for geographic subdivisions. Methods: We used the Belgian 2001 census linked to population and mortality register including nearly 5.5 million adults aged ≥30 (mean follow-up: 9.97 years). Annual mean concentrations for fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) were assessed at baseline residential address using two exposure methods; Europe-wide hybrid land use regression (LUR) models [100x100m], and Belgium-wide interpolation-dispersion (RIO-IFDM) models [25x25m]. We used Cox proportional hazards models with age as the underlying time scale and adjusted for various individual and area-level covariates. We further adjusted main models for two different area-levels following the European Nomenclature of Territorial Units for Statistics (NUTS); NUTS-1 (n = 3), or NUTS-3 (n = 43). Results: We found no consistent differences between both exposure methods. We observed most robust associations with lung cancer mortality. Hazard Ratios (HRs) per 10 μg/m3 increase for NO2 were 1.060 (95%CI 1.042-1.078) [hybrid LUR] and 1.040 (95%CI 1.022-1.058) [RIO-IFDM]. Associations with non-accidental, respiratory disease and cardiovascular disease mortality were generally null in main models but were enhanced after further adjustment for NUTS-1 or NUTS-3. HRs for non-accidental mortality per 5 μg/m3 increase for PM2.5 for the main model using hybrid LUR exposure were 1.023 (95%CI 1.011-1.035). After including random effects HRs were 1.044 (95%CI 1.033-1.057) [NUTS-1] and 1.076 (95%CI 1.060-1.092) [NUTS-3]. Conclusion: Long-term air pollution exposure was associated with higher lung cancer mortality risk but not consistently with the other studied causes. Magnitude of associations varied by adjustment for geographic subdivisions, area-level socio-economic covariates and less by exposure assessment method. © 2021

Evidence for the association between long-term exposure to ambient particulate matter components and mortality from natural causes is sparse and inconsistent. We evaluated this association in six large administrative cohorts in the framework of the Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) project. We analyzed data from country-wide administrative cohorts in Norway, Denmark, the Netherlands, Belgium, Switzerland and in Rome (Italy). Annual 2010 mean concentrations of copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V) and zinc (Zn) in fine particulate matter (PM2.5) were estimated using 100 × 100 m Europe-wide hybrid land use regression models assigned to the participants' residential addresses. We applied cohort-specific Cox proportional hazard models controlling for area- and individual-level covariates to evaluate associations with natural mortality. Two pollutant models adjusting for PM2.5 total mass or nitrogen dioxide (NO2) were also applied. We pooled cohort-specific estimates using a random effects meta-analysis. We included almost 27 million participants contributing more than 240 million person-years. All components except Zn were significantly associated with natural mortality [pooled Hazard Ratios (HRs) (95% CI): 1.037 (1.014, 1.060) per 5 ng/m3 Cu; 1.069 (1.031, 1.108) per 100 ng/m3 Fe; 1.039 (1.018, 1.062) per 50 ng/m3 K; 1.024 (1.006, 1.043) per 1 ng/m3 Ni; 1.036 (1.016, 1.057) per 200 ng/m3 S; 1.152 (1.048, 1.266) per 100 ng/m3 Si; 1.020 (1.006, 1.034) per 2 ng/m3 V]. Only K and Si were robust to PM2.5 or NO2 adjustment [pooled HRs (95% CI) per 50 ng/m3 in K: 1.025 (1.008, 1.044), 1.020 (0.999, 1.042) and per 100 ng/m3 in Si: 1.121 (1.039, 1.209), 1.068 (1.022, 1.117) adjusted for PM2.5 and NO2 correspondingly]. Our findings indicate an association of natural mortality with most components, which was reduced after adjustment for PM2.5 and especially NO2. © 2021

Land use regression (LUR) and dispersion/chemical transport models (D/CTMs) are frequently applied to predict exposure to air pollution concentrations at a fine scale for use in epidemiological studies. Moreover, the use of satellite aerosol optical depth data has been a key predictor especially for particulate matter pollution and when studying large populations. Within the STEAM project we present a hybrid spatio-temporal modeling framework by a) incorporating predictions from dispersion modeling of nitrogen dioxide (NO2), ozone (O3) and particulate matter with an aerodynamic diameter equal or less than 10μm (PM10) and less than 2.5μm (PM2.5) into a spatio-temporal LUR model; and b) combining the predictions LUR and dispersion modeling and additionally, only for PM2.5, from an ensemble machine learning approach using a generalized additive model (GAM). We used air pollution measurements from 2009 to 2013 from 62 fixed monitoring sites for O3, 115 for particles and up to 130 for NO2, obtained from the dense network in the Greater London Area, UK. We assessed all models following a 10-fold cross validation (10-fold CV) procedure. The hybrid models performed better compared to separate LUR models. Incorporation of the dispersion estimates in the LUR models as a predictor, improved the LUR model fit: CV-R2 increased to 0.76 from 0.71 for NO2, to 0.79 from 0.57 for PM10, to 0.81 to 0.66 for PM2.5 and to 0.75 from 0.62 for O3. The CV-R2 obtained from the hybrid GAM framework was also increased compared to separate LUR models (CV-R2 = 0.80 for NO2, 0.76 for PM10, 0.79 for PM2.5 and 0.75 for O3). Our study supports the combined use of different air pollution exposure assessment methods in a single modeling framework to improve the accuracy of spatio-temporal predictions for subsequent use in epidemiological studies. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Background: We evaluated methods for the analysis of multi-level survival data using a pooled dataset of 14 cohorts participating in the ELAPSE project investigating associations between residential exposure to low levels of air pollution (PM2.5 and NO2) and health (natural-cause mortality and cerebrovascular, coronary and lung cancer incidence). Methods: We applied five approaches in a multivariable Cox model to account for the first level of clustering corresponding to cohort specification: (1) not accounting for the cohort or using (2) indicator variables, (3) strata, (4) a frailty term in frailty Cox models, (5) a random intercept under a mixed Cox, for cohort identification. We accounted for the second level of clustering due to common characteristics in the residential area by (1) a random intercept per small area or (2) applying variance correction. We assessed the stratified, frailty and mixed Cox approach through simulations under different scenarios for heterogeneity in the underlying hazards and the air pollution effects. Results: Effect estimates were stable under approaches used to adjust for cohort but substantially differed when no adjustment was applied. Further adjustment for the small area grouping increased the effect estimates’ standard errors. Simulations confirmed identical results between the stratified and frailty models. In ELAPSE we selected a stratified multivariable Cox model to account for between-cohort heterogeneity without adjustment for small area level, due to the small number of subjects and events in the latter. Conclusions: Our study supports the need to account for between-cohort heterogeneity in multi-center collaborations using pooled individual level data. © 2021 The Authors

Introduction: To characterize air pollution exposure at a fine spatial scale, different exposure assessment methods have been applied. Comparison of associations with health from different exposure methods are scarce. The aim of this study was to evaluate associations of air pollution based on hybrid, land-use regression (LUR) and dispersion models with natural cause and cause-specific mortality. Methods: We followed a Dutch national cohort of approximately 10.5 million adults aged 29+ years from 2008 until 2012. We used Cox proportional hazard models with age as underlying time scale and adjusted for several potential individual and area-level socio-economic status confounders to evaluate associations of annual average residential NO2, PM2.5 and BC exposure estimates based on two stochastic models (Dutch LUR, European-wide hybrid) and deterministic Dutch dispersion models. Results: Spatial variability of PM2.5 and BC exposure was smaller for LUR compared to hybrid and dispersion models. NO2 exposure variability was similar for the three methods. Pearson correlations between hybrid, LUR and dispersion modeled NO2 and BC ranged from 0.72 to 0.83; correlations for PM2.5 were slightly lower (0.61–0.72). In general, all three models showed stronger associations of air pollutants with respiratory disease and lung cancer mortality than with natural cause and cardiovascular disease mortality. The strength of the associations differed between the three exposure models. Associations of air pollutants estimated by LUR were generally weaker compared to associations of air pollutants estimated by hybrid and dispersion models. For natural cause mortality, we found a hazard ratio (HR) of 1.030 (95% confidence interval (CI): 1.019, 1.041) per 10 µg/m3 for hybrid modeled NO2, a HR of 1.003 (95% CI: 0.993, 1.013) per 10 µg/m3 for LUR modeled NO2 and a HR of 1.015 (95% CI: 1.005, 1.024) per 10 µg/m3 for dispersion modeled NO2. Conclusion: Air pollution was positively associated with natural cause and cause-specific mortality, but the strength of the associations differed between the three exposure models. Our study documents that the selected exposure model may contribute to heterogeneity in effect estimates of associations between air pollution and health. © 2020 The Authors

BACKGROUND: Inconsistent associations between long-term exposure to particles with an aerodynamic diameter ≤2:5 lm [fine particulate matter (PM2:5)] components and mortality have been reported, partly related to challenges in exposure assessment. OBJECTIVES: We investigated the associations between long-term exposure to PM2:5 elemental components and mortality in a large pooled European cohort; to compare health effects of PM2:5 components estimated with two exposure modeling approaches, namely, supervised linear regression (SLR) and random forest (RF) algorithms. METHODS: We pooled data from eight European cohorts with 323,782 participants, average age 49 y at baseline (1985–2005). Residential exposure to 2010 annual average concentration of eight PM2:5 components [copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)] was estimated with Europe-wide SLR and RF models at a 100 × 100 m scale. We applied Cox proportional hazards models to investigate the associations between components and natural and cause-specific mortality. In addition, two-pollutant analyses were conducted by adjusting each component for PM2:5 mass and nitrogen dioxide (NO2) separately. RESULTS: We observed 46,640 natural-cause deaths with 6,317,235 person-years and an average follow-up of 19.5 y. All SLR-modeled components were statistically significantly associated with natural-cause mortality in single-pollutant models with hazard ratios (HRs) from 1.05 to 1.27. Similar HRs were observed for RF-modeled Cu, Fe, K, S, V, and Zn with wider confidence intervals (CIs). HRs for SLR-modeled Ni, S, Si, V, and Zn remained above unity and (almost) significant after adjustment for both PM2:5 and NO2. HRs only remained (almost) significant for RF-modeled K and V in two-pollutant models. The HRs for V were 1.03 (95% CI: 1.02, 1.05) and 1.06 (95% CI: 1.02, 1.10) for SLR-and RF-modeled exposures, respectively, per 2 ng=m3, adjusting for PM2:5 mass. Associations with cause-specific mortality were less consistent in two-pollutant models. CONCLUSION: Long-term exposure to V in PM2:5 was most consistently associated with increased mortality. Associations for the other components were weaker for exposure modeled with RF than SLR in two-pollutant models. https://doi.org/10.1289/EHP8368. © 2021, Public Health Services, US Dept of Health and Human Services. All rights reserved.

BACKGROUND: Long-term exposure to outdoor air pollution increases the risk of cardiovascular disease, but evidence is unclear on the health effects of exposure to pollutant concentrations lower than current EU and US standards and WHO guideline limits. Within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), we investigated the associations of long-term exposures to fine particulate matter (PM2·5), nitrogen dioxide (NO2), black carbon, and warm-season ozone (O3) with the incidence of stroke and acute coronary heart disease. METHODS: We did a pooled analysis of individual data from six population-based cohort studies within ELAPSE, from Sweden, Denmark, the Netherlands, and Germany (recruited 1992-2004), and harmonised individual and area-level variables between cohorts. Participants (all adults) were followed up until migration from the study area, death, or incident stroke or coronary heart disease, or end of follow-up (2011-15). Mean 2010 air pollution concentrations from centrally developed European-wide land use regression models were assigned to participants' baseline residential addresses. We used Cox proportional hazards models with increasing levels of covariate adjustment to investigate the association of air pollution exposure with incidence of stroke and coronary heart disease. We assessed the shape of the concentration-response function and did subset analyses of participants living at pollutant concentrations lower than predefined values. FINDINGS: From the pooled ELAPSE cohorts, data on 137 148 participants were analysed in our fully adjusted model. During a median follow-up of 17·2 years (IQR 13·8-19·5), we observed 6950 incident events of stroke and 10 071 incident events of coronary heart disease. Incidence of stroke was associated with PM2·5 (hazard ratio 1·10 [95% CI 1·01-1·21] per 5 μg/m3 increase), NO2 (1·08 [1·04-1·12] per 10 μg/m3 increase), and black carbon (1·06 [1·02-1·10] per 0·5 10-5/m increase), whereas coronary heart disease incidence was only associated with NO2 (1·04 [1·01-1·07]). Warm-season O3 was not associated with an increase in either outcome. Concentration-response curves indicated no evidence of a threshold below which air pollutant concentrations are not harmful for cardiovascular health. Effect estimates for PM2·5 and NO2 remained elevated even when restricting analyses to participants exposed to pollutant concentrations lower than the EU limit values of 25 μg/m3 for PM2·5 and 40 μg/m3 for NO2. INTERPRETATION: Long-term air pollution exposure was associated with incidence of stroke and coronary heart disease, even at pollutant concentrations lower than current limit values. FUNDING: Health Effects Institute. Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Background: An association between long-term exposure to fine particulate matter (PM2.5) and lung cancer has been established in previous studies. PM2.5 is a complex mixture of chemical components from various sources and little is known about whether certain components contribute specifically to the associated lung cancer risk. The present study builds on recent findings from the “Effects of Low-level Air Pollution: A Study in Europe” (ELAPSE) collaboration and addresses the potential association between specific elemental components of PM2.5 and lung cancer incidence. Methods: We pooled seven cohorts from across Europe and assigned exposure estimates for eight components of PM2.5 representing non-tail pipe emissions (copper (Cu), iron (Fe), and zinc (Zn)), long-range transport (sulfur (S)), oil burning/industry emissions (nickel (Ni), vanadium (V)), crustal material (silicon (Si)), and biomass burning (potassium (K)) to cohort participants’ baseline residential address based on 100 m by 100 m grids from newly developed hybrid models combining air pollution monitoring, land use data, satellite observations, and dispersion model estimates. We applied stratified Cox proportional hazards models, adjusting for potential confounders (age, sex, calendar year, marital status, smoking, body mass index, employment status, and neighborhood-level socio-economic status). Results: The pooled study population comprised 306,550 individuals with 3916 incident lung cancer events during 5,541,672 person-years of follow-up. We observed a positive association between exposure to all eight components and lung cancer incidence, with adjusted HRs of 1.10 (95% CI 1.05, 1.16) per 50 ng/m3 PM2.5 K, 1.09 (95% CI 1.02, 1.15) per 1 ng/m3 PM2.5 Ni, 1.22 (95% CI 1.11, 1.35) per 200 ng/m3 PM2.5 S, and 1.07 (95% CI 1.02, 1.12) per 200 ng/m3 PM2.5 V. Effect estimates were largely unaffected by adjustment for nitrogen dioxide (NO2). After adjustment for PM2.5 mass, effect estimates of K, Ni, S, and V were slightly attenuated, whereas effect estimates of Cu, Si, Fe, and Zn became null or negative. Conclusions: Our results point towards an increased risk of lung cancer in connection with sources of combustion particles from oil and biomass burning and secondary inorganic aerosols rather than non-exhaust traffic emissions. Specific limit values or guidelines targeting these specific PM2.5 components may prove helpful in future lung cancer prevention strategies. © 2020 Elsevier Inc.

Background: \ud Various spatiotemporal models have been proposed for predicting ambient particulate exposure for inclusion in epidemiological analyses. We investigated the effect of measurement error in the prediction of particulate matter with diameter

Using modeled air pollutant predictions as exposure variables in epidemiological analyses can produce bias in health effect estimation. We used statistical simulation to estimate these biases and compare different air pollution models for London. Methods: Our simulations were based on a sample of 1,000 small geographical areas within London, United Kingdom. "True" pollutant data (daily mean nitrogen dioxide [NO2] and ozone [O3]) were simulated to include spatio-temporal variation and spatial covariance. All-cause mortality and cardiovascular hospital admissions were simulated from "true" pollution data using prespecified effect parameters for short and long-term exposure within a multilevel Poisson model. We compared: land use regression (LUR) models, dispersion models, LUR models including dispersion output as a spline (hybrid1), and generalized additive models combining splines in LUR and dispersion outputs (hybrid2). Validation datasets (model versus fixed-site monitor) were used to define simulation scenarios. Results: For the LUR models, bias estimates ranged from -56% to +7% for short-term exposure and -98% to -68% for long-term exposure and for the dispersion models from -33% to -15% and -52% to +0.5%, respectively. Hybrid1 provided little if any additional benefit, but hybrid2 appeared optimal in terms of bias estimates for short-term (-17% to +11%) and long-term (-28% to +11%) exposure and in preserving coverage probability and statistical power. Conclusions: Although exposure error can produce substantial negative bias (i.e., towards the null), combining outputs from different air pollution modeling approaches may reduce bias in health effect estimation leading to improved impact evaluation of abatement policies.

Background: Using modeled air pollutant predictions as exposure variables in epidemiological analyses can produce bias in health effect estimation. We used statistical simulation to estimate these biases and compare different air pollution models for London. Methods: Our simulations were based on a sample of 1,000 small geographical areas within London, United Kingdom. "True" pollutant data (daily mean nitrogen dioxide [NO2] and ozone [O3]) were simulated to include spatio-temporal variation and spatial covariance. All-cause mortality and cardiovascular hospital admissions were simulated from "true" pollution data using prespecified effect parameters for short and long-term exposure within a multilevel Poisson model. We compared: land use regression (LUR) models, dispersion models, LUR models including dispersion output as a spline (hybrid1), and generalized additive models combining splines in LUR and dispersion outputs (hybrid2). Validation datasets (model versus fixed-site monitor) were used to define simulation scenarios. Results: For the LUR models, bias estimates ranged from -56% to +7% for short-term exposure and -98% to -68% for long-term exposure and for the dispersion models from -33% to -15% and -52% to +0.5%, respectively. Hybrid1 provided little if any additional benefit, but hybrid2 appeared optimal in terms of bias estimates for short-term (-17% to +11%) and long-term (-28% to +11%) exposure and in preserving coverage probability and statistical power. Conclusions: Although exposure error can produce substantial negative bias (i.e., towards the null), combining outputs from different air pollution modeling approaches may reduce bias in health effect estimation leading to improved impact evaluation of abatement policies. © 2020 Wolters Kluwer Health. All rights reserved.

Background: Various spatiotemporal models have been proposed for predicting ambient particulate exposure for inclusion in epidemiological analyses. We investigated the effect of measurement error in the prediction of particulate matter with diameter

Background: Although there is evidence on the effects of short-term ozone (O3) exposures on children's respiratory health, few studies have reported results on the effects of long-term exposures. We report the effects of long-term exposure to O3 on respiratory health outcomes in 10–11-year old children. Methods: We conducted a panel study in a sample of the general population of school children in two cities with high average O3 concentrations, Athens and Thessaloniki, Greece. All 186 participating students were followed up intensively for 5 weeks spreading across a school year. Data was collected through questionnaires, weekly personal O3 measurements, spirometry, FeNO and time-activity diaries. Long-term O3 exposure was assessed using fixed site measurements and modeling, calibrated for personal exposures. The associations between measured lung function parameters and lung function growth over the study period, as well as FeNO and the occurrence of symptoms with long-term O3 exposure were assessed through the application of multiple mixed effects 2-level regression models, adjusting for confounders and for short-term exposures. Results: A 10 μg/m3 increase in calibrated long-term O3exposure, using measurements from fixed site monitors was associated with lower FVC and FEV1 by 17 mL (95% Confidence Interval: 5–28) and 13 mL (3–21) respectively and small decreases in lung growth: 0.008% (0.002–0.014%) for FVC and 0.006% (0.000–0.012%) in FEV1 over the study period. No association was observed with PEF, FeNO or the occurrence of symptoms. A similar pattern was observed when the exposure estimates from the dispersion models were employed. Conclusions: Our study provides evidence that long-term O3 exposure is associated with reduced lung volumes and growth. © 2019 Elsevier Inc.

Aim: There is growing interest in the health effects following exposure to ambient particles with a diameter

A limited number of studies have addressed environmental inequality, using various study designs and methodologies and often reaching contradictory results. Following a standardized multi-city data collection process within the European project EURO-HEALTHY, we conducted an ecological study to investigate the spatial association between nitrogen dioxide (NO2), as a surrogate for traffic related air pollution, and ten socioeconomic indicators at local administrative unit level in nine European Metropolitan Areas. We applied mixed models for the associations under investigation with random intercepts per Metropolitan Area, also accounting for the spatial correlation. The stronger associations were observed between NO2 levels and population density, population born outside the European Union (EU28), total crimes per 100,000 inhabitants and unemployment rate that displayed a highly statistically significant trend of increasing concentrations with increasing levels of the indicators. Specifically, the highest vs the lowest quartile of each indicator above was associated with 48.7% (95% confidence interval (CI): 42.9%, 54.8%), 30.9% (95%CI: 22.1%, 40.2%), 19.8% (95%CI: 13.4%, 26.6%) and 15.8% (95%CI: 9.9%, 22.1%) increase in NO2 respectively. The association with population density most probably reflects the higher volume in vehicular traffic, which is the main source of NO2 in urban areas. Higher pollution levels in areas with higher percentages of people born outside EU28, crime or unemployment rates indicate that worse air quality is typically encountered in deprived European urban areas. Policy makers should consider spatial environmental inequalities to better inform actions aiming to lower urban air pollution levels that will subsequently lead to improved quality of life, public health and health equity across the population. © 2019 Elsevier Ltd

Urban areas in Europe are facing a range of environmental public health challenges, such as air pollution, traffic noise and road injuries. The identification and quantification of the public health risks associated with exposure to environmental conditions is important for prioritising policies and interventions that aim to diminish the risks and improve the health of the population. With this purpose in mind, the EURO-HEALTHY project used a consistent approach to assess the impact of key environmental risk factors and urban environmental determinants on public health in European metropolitan areas. A number of environmental public health indicators, which are closely tied to the physical and built environment, were identified through stakeholder consultation; data were collected from six European metropolitan areas (Athens, Barcelona, Lisbon, London, Stockholm and Turin) covering the period 2000–2014, and a health impact assessment framework enabled the quantification of health effects (attributable deaths) associated with these indicators. The key environmental public health indicators were related to air pollution and certain urban environmental conditions (urban green spaces, road safety). The air pollution was generally the highest environmental public health risk; the associated number of deaths in Athens, Barcelona and London ranged between 800 and 2300 attributable deaths per year. The number of victims of road traffic accidents and the associated deaths were lowest in the most recent year compared with previous years. We also examined the positive impacts on health associated with urban green spaces by calculating reduced mortality impacts for populations residing in areas with greater green space coverage; results in Athens showed reductions of all-cause mortality of 26 per 100,000 inhabitants for populations with benefits of local greenspace. Based on our analysis, we discuss recommendations of potential interventions that could be implemented to reduce the environmental public health risks in the European metropolitan areas covered by this study. © 2018 Elsevier B.V.

Background: Evidence on the association between short-term exposure to desert dust and health outcomes is controversial. Objectives: We aimed to estimate the short-term effects of particulate matter ≤ 10 μm (PM10) on mortality and hospital admissions in 13 Southern European cities, distinguishing between PM10 originating from the desert and from other sources. Methods: We identified desert dust advection days in multiple Mediterranean areas for 2001–2010 by combining modeling tools, back-trajectories, and satellite data. For each advection day, we estimated PM10 concentrations originating from desert, and computed PM10 from other sources by difference. We fitted city-specific Poisson regression models to estimate the association between PM from different sources (desert and non-desert) and daily mortality and emergency hospitalizations. Finally, we pooled city-specific results in a random-effects meta-analysis. Results: On average, 15% of days were affected by desert dust at ground level (desert PM10 > 0 μg/m3). Most episodes occurred in spring–summer, with increasing gradient of both frequency and intensity north–south and west–east of the Mediterranean basin. We found significant associations of both PM10 concentrations with mortality. Increases of 10 μg/m3 in non-desert and desert PM10 (lag 0–1 days) were associated with increases in natural mortality of 0.55% (95% CI: 0.24, 0.87%) and 0.65% (95% CI: 0.24, 1.06%), respectively. Similar associations were estimated for cardio-respiratory mortality and hospital admissions. Conclusions: PM10 originating from the desert was positively associated with mortality and hospitalizations in Southern Europe. Policy measures should aim at reducing population exposure to anthropogenic airborne particles even in areas with large contribution from desert dust advections. © 2016, Public Health Services, US Dept of Health and Human Services. All Rights Reserved.

Background: Assessment of the cumulative effect of correlated exposures is an open methodological issue in environmental epidemiology. Most previous studies have applied regression models with interaction terms or dimension reduction methods. The combined effect of pollutants has been also evaluated through the use of exposure scores that incorporate weights based on the strength of the component-specific associations with health outcomes. Methods: We compared three approaches addressing multi-pollutant exposures in epidemiological models: main effects models, the adaptive least absolute shrinkage and selection operator (LASSO) and a weighted exposure score. We assessed the performance of the methods by simulations under various scenarios for the pollutants’ correlations. We further applied these methods to time series data from Athens, Greece in 2007-12 to investigate the combined effect of short-term exposure to six regulated pollutants on all-cause and respiratory mortality. Results: The exposure score provided the least biased estimate under all correlation scenarios for both mortality outcomes. The adaptive LASSO performed well in the case of low and medium correlation between exposures while the main effect model resulted in severe bias. In the real data application, the cumulative effect estimate was similar between approaches for all-cause mortality ranging from 0.7% increase per interquartile range (IQR) (score) to 1.1% (main effects), while for respiratory mortality conclusions were contradictive and ranged from − 0.6% (adaptive LASSO) to 2.8% (score). Conclusions: Τhe use of a weighted exposure score to address cumulative effects of correlated metrics may perform well under different exposure correlation and variability in the health outcomes. © 2018 Elsevier Inc.

Background: Ambient particulate matter (PM) has an adverse effect on respiratory morbidity. Desert dust outbreaks contribute to increased PM levels but the toxicity of desert dust mixed with anthropogenic pollutants needs clarification. Methods: We identified 132 days with desert dust episodes and 177 matched days by day of the week, season, temperature and humidity between 2001 and 2006 in Athens, Greece. We collected data on regulated pollutants and daily emergency outpatient visits and admissions for respiratory causes. We applied Poisson regression models adjusting for confounding effects of seasonality, meteorology, holidays and influenza epidemics. We evaluated the sensitivity of our results to co-pollutant exposures and effect modification by age and sex. Results: A 10 μg/m3 increase in PM10 concentration was associated with 1.95% (95% confidence interval (CI): 0.02%, 3.91%) increase in respiratory emergency room visits. No significant interaction with desert dust episodes was observed. Compared with non-dust days, there was a 47% (95% CI: 29%, 68%) increase in visits in dust days not adjusting for PM10. Desert dust days were associated with higher numbers of emergency room visits for asthma, chronic obstructive pulmonary disease and respiratory infections with increases of 38%, 57% and 60%, respectively (p < 0.001 for all comparisons). Analyses of respiratory hospital admissions provided similar results. PM10 effects decreased when adjusting for desert dust days and were further confounded by co-pollutants. Conclusions: Desert dust episode days are associated with higher respiratory emergency room visits and hospital admissions. This effect is insufficiently explained by increased PM10 levels. © 2017 The Author(s).

Previous time series or panel studies of asthmatics have reported respiratory health effects following short-Term exposure to ozone (O3). We followed 186 children aged 10 years old in Athens and Thessaloniki, Greece for 5 weeks during the academic year 2013-2014 and recorded daily their respiratory symptoms, absenteeism and peak expiratory flow (PEF). We applied mixed models controlling for various possible confounders to investigate the daily associations between O3 exposure - derived from weekly personal and fixed school site measurements calibrated using daily values of the fixed monitoring site nearest to the child's school location -And PEF, presence of any symptom, cough and stuffy nose, as well as absenteeism. We tested the robustness of our findings to varying modeling assumptions and confounders and investigated effect modification patterns by medication use, time spent outdoors and prevalence of asthma. A 10 μg/m3 increase in O3 personal exposure was associated with increased odds of any symptom (odds ratio (OR): 1.19, 95% confidence interval (CI): 0.98, 1.44), largely attributed to the increase in the odds of stuffy nose (OR: 1.23, 95% CI: 1.00, 1.51). PEF and absenteeism were not related to O3 exposure. Our results were robust to several sensitivity analyses. Effects were modified by medication use as presence of symptoms but also decreases in PEF were mainly reported among non-users, while our effect estimates were not driven by the asthmatic subgroup of children. Our findings indicate that short-Term O3 exposure may be associated with respiratory symptoms extending previously reported results for asthmatics to the general population. © 2017 Nature America, Inc., part of Springer Nature. All rights reserved.

Background/Aim: Acidification of exhaled breath condensate (EBC), reflecting airway inflammation and oxidative stress, has been reported in lung cancer patients undergoing lobectomy. We undertook this study to examine EBC pH changes during surgery for abdominal cancer. Patients and Methods: EBC pH was measured from 20 patients undergoing abdominal cancer resection before and during surgery. Repeated-measures of ANOVA and randomeffects linear models were applied to compare mean EBC pH values in samples collected at different times. Cox and linear regression models were used to determine the association of EBC pH with occurrence of acute bronchospasm intraoperatively and the duration of hospitalization. Results: Significant acidification of EBC was observed during surgery (p=0.007) associated with 0.77% (95% confidence interval=-0.14-1.68, p-value=0.097) increase in the risk for developing acute bronchospasm, after adjustment for potential confounders. Conclusion: EBC acidification occurs in patients undergoing abdominal cancer resection and is associated with the occurrence of acute bronchospasm intraoperatively.

Background In the wider framework of the RESPOZE (ReSPiratory effects of OZone Exposure in Greek children) panel study, we investigated possible determinants of O3exposure of school children, measured with personal passive samplers, in Athens and Thessaloniki, Greece. Methods Personal exposure to O3was measured for five weeks spread along the academic year 2013-14, in 186 school children in Athens and Thessaloniki, Greece. At the same time, at-school outdoor measurements were performed and ambient levels of 8-h daily maximum O3from fixed sites were collected. We also collected information on lifestyle and housing characteristics through an extended general questionnaire (GQ) and each participant completed daily time activity diaries (TADs) during the study period. Results Mean outdoor concentrations were higher during the warmer months, in the suburbs of the cities and in Athens. Personal exposure concentrations were significantly lower compared to outdoor. Daily levels of at-school outdoor and ambient levels of O3from fixed sites were significant determinants of personal exposure to O3. For a 10 μg/m3increase in at-school outdoor O3concentrations and PM10measurements a 20.9% (95% CI: 13%, 28%) increase in personal exposure to O3was found. For a half an hour more spent in transportation an average increase of 7% (95% CI: 0.3%, 14.6%) in personal exposure to O3was observed. Among other possible determinants, time spent in transportation (TAD variable) and duration of open windows were the ones associated with personal O3exposure levels. Conclusions Our results support the use of outdoor and ambient measurements from fixed sites in epidemiological studies as a proxy of personal exposure to O3, but this has to be calibrated taking into account personal measurements and time-activity patterns. © 2016 Elsevier Inc.

BACKGROUND: The association of ozone exposure with respiratory outcomes has been investigated in epidemiologic studies mainly including asthmatic children. The findings reported had methodological gaps and inconsistencies. OBJECTIVES: We aimed to investigate effects of personal ozone exposure on various respiratory outcomes in school-age children generally representative of the population during their normal activities. METHODS: We conducted a panel study in a representative sample of school-age children in the two major cities of Greece, Athens and Thessaloniki. We followed 188, 10- to 11-y-old, elementary school students for 5 wk spread throughout the 2013–2014 academic year, during which ozone was measured using personal samplers. At the end of each study week, spirometry was performed by trained physicians, and the fractional concentration of nitric oxide in exhaled air (F) was measured. Students kept a daily time–activity–symptom diary and measured PEF (peak expiratory flow) using peak flow meters. Mixed modelseNO accounting for repeated measurements were applied. RESULTS: An increase of 10 μg/m3 in weekly ozone concentration was associated with a decrease in FVC (forced vital capacity) and FEV1 (forced expiratory volume in 1 s) of 0:03 L [95% confidence interval (CI): −0:05, −0:01] and 0:01 L (95% CI: −0:03, 0.003) respectively. The same increase in exposure was associated with a 11.10% (95% CI: 4.23, 18.43) increase in FeNO and 19% (95% CI: −0:53, 42.75) increase in days with any symptom. The effect estimates were robust to PM10 adjustment. No inverse association was found between ozone exposure and PEF. CONCLUSIONS: The study provides evidence that airway inflammation and the frequency of respiratory symptoms increase, whereas lung function decreases with increased ozone exposure in schoolchildren. © 2017, Public Health Services, US Dept of Health and Human Services. All rights reserved.

BACKGROUND: Evidence on the association between short-term exposure to desert dust and health outcomes is controversial. OBJECTIVES: We aimed to estimate the short-term effects of particulate matter 0 mu g/m(3)). Most episodes occurred in spring-summer, with increasing gradient of both frequency and intensity north-south and west-east of the Mediterranean basin. We found significant associations of both PM10 concentrations with mortality. Increases of 10 mu g/m(3) in non-desert and desert PM10 (lag 0-1 days) were associated with increases in natural mortality of 0.55% (95% CI: 0.24, 0.87%) and 0.65% (95% CI: 0.24, 1.06%), respectively. Similar associations were estimated for cardio-respiratory mortality and hospital admissions. CONCLUSIONS: PM10 originating from the desert was positively associated with mortality and hospitalizations in Southern Europe. Policy measures should aim at reducing population exposure to anthropogenic airborne particles even in areas with large contribution from desert dust advections.

Background: Few studies have investigated the independent health effects of different size fractions of particulate matter (PM) in multiple locations, especially in Europe. Objectives: We estimated the short-term effects of PM with aerodynamic diameter ≤ ; 10; μm (PM10), ≤ 2.5; μm (PM2.5), and between 2.5 and 10; μm (PM2.5-10) on all-cause, cardiovascular, and respiratory mortality in 10 European Mediterranean metropolitan areas within the MED-PARTICLES project. Methods: We analyzed data from each city using Poisson regression models, and combined city-specific estimates to derive overall effect estimates. We evaluated the sensitivity of our estimates to co-pollutant exposures and city-specific model choice, and investigated effect modification by age, sex, and season. We applied distributed lag and threshold models to investigate temporal patterns of associations. Results: A 10-μg/m3 increase in PM2.5 was associated with a 0.55% (95% CI: 0.27, 0.84%) increase in all-cause mortality (0-1 day cumulative lag), and a 1.91% increase (95% CI: 0.71, 3.12%) in respiratory mortality (0-5 day lag). In general, associations were stronger for cardiovascular and respiratory mortality than all-cause mortality, during warm versus cold months, and among those ≥ 75 versus < 75 years of age. Associations with PM2.5-10 were positive but not statistically significant in most analyses, whereas associations with PM10 seemed to be driven by PM2.5. Conclusions: We found evidence of adverse effects of PM2.5 on mortality outcomes in the European Mediterranean region. Associations with PM2.5-10 were positive but smaller in magnitude. Associations were stronger for respiratory mortality when cumulative exposures were lagged over 0-5 days, and were modified by season and age.

BACKGROUND: Few recent studies examined acute effects on health of individual chemical species in the particulate matter (PM) mixture, and most of them have been conducted in North America. Studies in Southern Europe are scarce. The aim of this study is to examine the relationship between particulate matter constituents and daily hospital admissions and mortality in five cities in Southern Europe. METHODS: The study included five cities in Southern Europe, three cities in Spain: Barcelona (2003-2010), Madrid (2007-2008) and Huelva (2003-2010); and two cities in Italy: Rome (2005-2007) and Bologna (2011-2013). A case-crossover design was used to link cardiovascular and respiratory hospital admissions and total, cardiovascular and respiratory mortality with a pre-defined list of 16 PM10 and PM2.5 constituents. Lags 0 to 2 were examined. City-specific results were combined by random-effects meta-analysis. RESULTS: Most of the elements studied, namely EC, SO4(2-), SiO2, Ca, Fe, Zn, Cu, Ti, Mn, V and Ni, showed increased percent changes in cardiovascular and/or respiratory hospitalizations, mainly at lags 0 and 1. The percent increase by one interquartile range (IQR) change ranged from 0.69% to 3.29%. After adjustment for total PM levels, only associations for Mn, Zn and Ni remained significant. For mortality, although positive associations were identified (Fe and Ti for total mortality; EC and Mg for cardiovascular mortality; and NO3(-) for respiratory mortality) the patterns were less clear. CONCLUSIONS: The associations found in this study reflect that several PM constituents, originating from different sources, may drive previously reported results between PM and hospital admissions in the Mediterranean area. The research described in this article was conducted under the grant agreement European Commission, Environment LIFE10/IT/327. We thank the Instituto Nacional de Estadística and the Agència de Salut Pública de Barcelona for providing the mortality data, the Consorci Sanitari de Barcelona (Cat-Salut) for providing hospitalization data for Barcelona and the Agencia Estatal de Meteorologia (Ministerio de Agricultura, Alimentación y Medio Ambiente) for providing the weather data for Spain. Sí

Objectives: While several studies have reported associations of daily exposures to PM2.5 (particles less than 2.5 μm) with mortality, few studies have examined the impact of its constituents such as black carbon (BC), which is also a significant contributor to global climate change. Methods: We assessed the association between daily concentrations of BC and total, cardiovascular and respiratory mortality in two southern Mediterranean cities. Daily averages of BC were collected for 2 years in Barcelona, Spain and Athens, Greece. We used case-crossover analysis and examined single and cumulative lags up to 3 days. Results: We observed associations between BC and all mortality measures. For a 3-day moving average, cardiovascular mortality increased by 4.5% (95% CI 0.7 to 8.5) and 2.0% (95% CI 0 to 4.0) for an interquartile change in BC in Athens and Barcelona, respectively. Considerably higher effects for respiratory mortality and for those above age 65 were observed. In addition, BC exhibited much greater toxicity per microgram than generic PM2.5. Conclusions: Our findings suggest that BC, derived in western industrialised nations primarily from diesel engines and biomass burning, poses a significant burden to public health, particularly in European cities with high-traffic density.

Background: Few recent studies examined acute effects on health of individual chemical species in the particulate matter (PM) mixture, and most of them have been conducted in North America. Studies in Southern Europe are scarce. The aim of this study is to examine the relationship between particulate matter constituents and daily hospital admissions and mortality in five cities in Southern Europe. Methods: The study included five cities in Southern Europe, three cities in Spain: Barcelona (2003-2010), Madrid (2007-2008) and Huelva (2003-2010); and two cities in Italy: Rome (2005-2007) and Bologna (2011-2013). A case-crossover design was used to link cardiovascular and respiratory hospital admissions and total, cardiovascular and respiratory mortality with a pre-defined list of 16 PM10and PM2.5constituents. Lags 0 to 2 were examined. City-specific results were combined by random-effects meta-analysis. Results: Most of the elements studied, namely EC, SO4 2-, SiO2,Ca, Fe, Zn, Cu, Ti, Mn, V and Ni, showed increased percent changes in cardiovascular and/or respiratory hospitalizations, mainly at lags 0 and 1. The percent increase by one interquartile range (IQR) change ranged from 0.69% to 3.29%. After adjustment for total PM levels, only associations for Mn, Zn and Ni remained significant. For mortality, although positive associations were identified (Fe and Ti for total mortality; EC and Mg for cardiovascular mortality; and NO3 -for respiratory mortality) the patterns were less clear. Conclusions: The associations found in this study reflect that several PM constituents, originating from different sources, may drive previously reported results between PM and hospital admissions in the Mediterranean area. © 2014 Elsevier Ltd.

Background: An association between occurrence of wildfires and mortality in the exposed population has been observed in several studies with controversial results for cause-specific mortality. In the Mediterranean area, forest fires usually occur during spring-summer, they overlap with Saharan outbreaks, are associated with increased temperature and their health effects are probably due to an increase in particulate matter. Aim and methods: We analysed the effects of wildfires and particulate matter (PM10) on mortality in 10 southern European cities in Spain, France, Italy and Greece (2003-2010), using satellite data for exposure assessment and Poisson regression models, simulating a case-crossover approach. Results: We found that smoky days were associated with increased cardiovascular mortality (lag 0-5, 6.29%, 95% CIs 1.00 to 11.85). When the effect of PM10 (per 10 mg/m3) was evaluated, there was an increase in natural mortality (0.49%), cardiovascular mortality (0.65%) and respiratory mortality (2.13%) on smoke-free days, but PM10-related mortality was higher on smoky days (natural mortality up to 1.10% and respiratory mortality up to 3.90%) with a suggestion of effect modification for cardiovascular mortality (3.42%, p value for effect modification 0.055), controlling for Saharan dust advections. Conclusions: Smoke is associated with increased cardiovascular mortality in urban residents, and PM10 on smoky days has a larger effect on cardiovascular and respiratory mortality than on other days.

Background: Heart disease and stroke mortality and morbidity rates in Arkansas are among the highest in the U.S. While the effect of air pollution on cardiovascular health was identified in traffic-dominated metropolitan areas, there is a lack of studies for populations with variable exposure profiles, demographic and disease characteristics. Objective: Determine the short-term effects of air pollution on cardiovascular and respiratory morbidity in the stroke and heart failure belt. Methods: We investigated the associations of fine particles and ozone with respiratory and cardiovascular emergency room visits during the 2002-2012 period for adults in Central Arkansas using Poisson generalized models adjusted for temporal, seasonal and meteorological effects. We evaluated sensitivity of the associations to mutual pollutant adjustment and effect modification patterns by sex, age, race and season. Results: We found effects on cardiovascular and respiratory emergencies for PM2.5 (1.52% [95% (confidence interval) CI: -1.10%, 4.20%]; 1.45% [95%CI: -2.64%, 5.72%] per 10μg/m3) and O3 (0.93% [95%CI: -0.87%, 2.76%]; 0.76 [95%CI: -1.92%, 3.52%] per 10ppbv) during the cold period (October-March). The effects were stronger among whites, except for the respiratory effects of O3 that were higher among Blacks/African-Americans. Effect modification patterns by age and sex differed by association. Both pollutants were associated with increases in emergency room visits for hypertension, heart failure and asthma. Effects on cardiovascular and respiratory emergencies were observed during the cold period when particulate matter was dominated by secondary nitrate and wood burning. Conclusion: Outdoor particulate pollution during winter had an effect on cardiovascular morbidity in central Arkansas, the region with high stroke and heart disease incidence rates. © 2015 Elsevier B.V.