Search

Introduction: Previous analysis from the large European multicentre ESCAPE study showed an association of ambient particulate matter <2.5 μm (PM 2.5 ) air pollution exposure at residence with the incidence of gastric cancer. It is unclear which components of PM are most relevant for gastric and also upper aerodigestive tract (UADT) cancer and some of them may not be strongly correlated with PM mass. We evaluated the association between long-term exposure to elemental components of PM 2.5 and PM 10 and gastric and UADT cancer incidence in European adults., Methods: Baseline addresses of individuals were geocoded and exposure was assessed by land-use regression models for copper (Cu), iron (Fe) and zinc (Zn) representing non-tailpipe traffic emissions; sulphur (S) indicating long-range transport; nickel (Ni) and vanadium (V) for mixed oil-burning and industry; silicon (Si) for crustal material and potassium (K) for biomass burning. Cox regression models with adjustment for potential confounders were used for cohort-specific analyses. Combined estimates were determined with random effects meta-analyses., Results: Ten cohorts in six countries contributed data on 227,044 individuals with an average follow-up of 14.9 years with 633 incident cases of gastric cancer and 763 of UADT cancer. The combined hazard ratio (HR) for an increase of 200 ng/m 3 of PM 2.5 &#95;S was 1.92 (95%-confidence interval (95%-CI) 1.13;3.27) for gastric cancer, with no indication of heterogeneity between cohorts (I 2  = 0%), and 1.63 (95%-CI 0.88;3.01) for PM 2.5 &#95;Zn (I 2  = 70%). For the other elements in PM 2.5 and all elements in PM 10 including PM 10 &#95;S, non-significant HRs between 0.78 and 1.21 with mostly wide CIs were seen. No association was found between any of the elements and UADT cancer. The HR for PM 2.5 &#95;S and gastric cancer was robust to adjustment for additional factors, including diet, and restriction to study participants with stable addresses over follow-up resulted in slightly higher effect estimates with a decrease in precision. In a two-pollutant model, the effect estimate for total PM 2.5 decreased whereas that for PM 2.5 &#95;S was robust., Conclusion: This large multicentre cohort study shows a robust association between gastric cancer and long-term exposure to PM 2.5 &#95;S but not PM 10 &#95;S, suggesting that S in PM 2.5 or correlated air pollutants may contribute to the risk of gastric cancer., (Copyright © 2018. Published by Elsevier Ltd.)

Background: The evidence from observational epidemiological studies of a link between long-term air pollution exposure and diabetes prevalence and incidence is currently mixed. Some studies found the strongest associations of diabetes with fine particles, other studies with nitrogen dioxide and some studies found no associations., Objectives: Our aim was to investigate associations between long-term exposure to multiple air pollutants and diabetes prevalence in a large national survey in the Netherlands., Methods: We performed a cross-sectional analysis using the 2012 Dutch national health survey to investigate the associations between the 2009 annual average concentrations of multiple air pollutants (PM 10 , PM 2.5 , PM 10-2.5 , PM 2.5 absorbance, OP DTT , OP ESR and NO 2 ) and diabetes prevalence, among 289,703 adults. Air pollution exposure was assessed by land use regression models. Diabetes was defined based on a combined measure of self-reported physician diagnosis and medication prescription from an external database. Using logistic regression, we adjusted for potential confounders, including neighborhood- and individual socio-economic status and lifestyle-related risk factors such as smoking habits, alcohol consumption, physical activity and BMI., Results: After adjustment for potential confounders, all pollutants (except PM 2.5 ) were associated with diabetes prevalence. In two-pollutant models, NO 2 and OP DTT remained associated with increased diabetes prevalence. For NO 2 and OP DTT , single-pollutant ORs per interquartile range were 1.07 (95% CI: 1.05, 1.09) and 1.08 (95% CI: 1.05, 1.10), respectively. Stratified analysis showed no consistent effect modification by any of the included known diabetes risk factors., Conclusions: Long-term residential air pollution exposure was associated with diabetes prevalence in a large health survey in the Netherlands, strengthening the evidence of air pollution being an important diabetes risk factor. Most consistent associations were observed for NO 2 and oxidative potential of PM 2.5 measured by the DTT assay. The finding of an association with the oxidative potential of fine particles but not with PM 2.5 , suggests that particle composition may be important for a potential effect on diabetes., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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: Childhood blood pressure is an important predictor of hypertension and cardiovascular disease in adulthood. Evidence for an association between ambient particulate matter (PM) exposure and blood pressure is increasing, but little is known about the relevance of different PM constituents., Objectives: We investigated the association between particulate matter composition and blood pressure at age 12 years., Methods: Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc in particles with diameters of less than 2.5μm (PM2.5) and 10μm (PM10) were estimated by land-use regression modeling for the home addresses of the participants of the prospective PIAMA birth cohort study. Associations between element concentrations and blood pressure measurements performed at age 12 years were investigated by linear regression with and without adjustment for confounders., Results: After adjustment for potential confounders we found statistically significant positive associations of diastolic blood pressure with iron, silicon, and potassium in PM10 in children who lived at the same address since birth [mean difference (95% confidence interval) 0.67 (0.02;1.31) mmHg, 0.85 (0.18;1.52) mmHg, and 0.75 (0.09;1.41) mmHg, respectively, per interquartile range increase in exposure]. Also, we found marginally significant (p<0.1) positive associations between iron and silicon in PM2.5 and diastolic blood pressure. Part of the observed effects was found to be attributable to NO2, a marker of exhaust traffic emissions., Conclusions: Exposure to particulate matter constituents, in particular iron may increase blood pressure in children. The possible association with iron may indicate the health relevance of non-exhaust emissions of traffic., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Background: Epidemiological studies have associated long-term exposure to ambient particulate matter with increased mortality from cardiovascular and respiratory disorders. Systemic inflammation is a plausible biological mechanism behind this association. However, it is unclear how the chemical composition of PM affects inflammatory responses., Objectives: To investigate the association between long-term exposure to elemental components of PM and the inflammatory blood markers high-sensitivity C-reactive protein (hsCRP) and fibrinogen as part of the European ESCAPE and TRANSPHORM multi-center projects., Methods: In total, 21,558 hsCRP measurements and 17,428 fibrinogen measurements from cross-sections of five and four cohort studies were available, respectively. Residential long-term concentrations of particulate matter <10μm (PM10) and <2.5μm (PM2.5) in diameter and selected elemental components (copper, iron, potassium, nickel, sulfur, silicon, vanadium, zinc) were estimated based on land-use regression models. Associations between components and inflammatory markers were estimated using linear regression models for each cohort separately. Cohort-specific results were combined using random effects meta-analysis. As a sensitivity analysis the models were additionally adjusted for PM mass., Results: A 5ng/m(3) increase in PM2.5 copper and a 500ng/m(3) increase in PM10 iron were associated with a 6.3% [0.7; 12.3%] and 3.6% [0.3; 7.1%] increase in hsCRP, respectively. These associations between components and fibrinogen were slightly weaker. A 10ng/m(3) increase in PM2.5 zinc was associated with a 1.2% [0.1; 2.4%] increase in fibrinogen; confidence intervals widened when additionally adjusting for PM2.5., Conclusions: Long-term exposure to transition metals within ambient particulate matter, originating from traffic and industry, may be related to chronic systemic inflammation providing a link to long-term health effects of particulate matter., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Long-term exposure to ambient air pollution can lead to chronic health effects such as cancer, cardiovascular and respiratory disease. Systemic inflammation has been hypothesized as a putative biological mechanism contributing to these adverse health effects. We evaluated the effect of long-term exposure to air pollution on blood markers of systemic inflammation. We measured a panel of 28 inflammatory markers in peripheral blood samples from 587 individuals that were biobanked as part of a prospective study. Participants were from Varese and Turin (Italy) and Umea (Sweden). Long-term air pollution estimates of nitrogen oxides (NOx) were available from the European Study of Cohorts for Air Pollution Effects (ESCAPE). Linear mixed models adjusted for potential confounders were applied to assess the association between NOx and the markers of inflammation. Long-term exposure to NOx was associated with decreased levels of interleukin (IL)-2, IL-8, IL-10 and tumor necrosis factor-α in Italy, but not in Sweden. NOx exposure levels were considerably lower in Sweden than in Italy (Sweden: median (5th, 95th percentiles) 6.65 μg/m(3) (4.8, 19.7); Italy: median (5th, 95th percentiles) 94.2 μg/m(3) (7.8, 124.5)). Combining data from Italy and Sweden we only observed a significant association between long-term exposure to NOx and decreased levels of circulating IL-8. We observed some indication for perturbations in the inflammatory markers due to long-term exposure to NOx. Effects were stronger in Italy than in Sweden, potentially reflecting the difference in air pollution levels between the two cohorts., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

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: 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.)

Background: Associations between long-term exposure to ambient particulate matter (PM) and cardiovascular (CVD) mortality have been widely recognized. However, health effects of long-term exposure to constituents of PM on total CVD mortality have been explored in a single study only., Aims: The aim of this study was to examine the association of PM composition with cardiovascular mortality., Methods: We used data from 19 European ongoing cohorts within the framework of the ESCAPE (European Study of Cohorts for Air Pollution Effects) and TRANSPHORM (Transport related Air Pollution and Health impacts--Integrated Methodologies for Assessing Particulate Matter) projects. Residential annual average exposure to elemental constituents within particle matter smaller than 2.5 and 10 μm (PM2.5 and PM10) was estimated using Land Use Regression models. Eight elements representing major sources were selected a priori (copper, iron, potassium, nickel, sulfur, silicon, vanadium and zinc). Cohort-specific analyses were conducted using Cox proportional hazards models with a standardized protocol. Random-effects meta-analysis was used to calculate combined effect estimates., Results: The total population consisted of 322,291 participants, with 9545 CVD deaths. We found no statistically significant associations between any of the elemental constituents in PM2.5 or PM10 and CVD mortality in the pooled analysis. Most of the hazard ratios (HRs) were close to unity, e.g. for PM10 Fe the combined HR was 0.96 (0.84-1.09). Elevated combined HRs were found for PM2.5 Si (1.17, 95% CI: 0.93-1.47), and S in PM2.5 (1.08, 95% CI: 0.95-1.22) and PM10 (1.09, 95% CI: 0.90-1.32)., Conclusion: In a joint analysis of 19 European cohorts, we found no statistically significant association between long-term exposure to 8 elemental constituents of particles and total cardiovascular mortality., (Copyright © 2014 Elsevier Ltd. All rights reserved.)