Andrea Ranzi

Air pollution and lung cancer incidence in 17 European cohorts: prospective analyses from the European Study of Cohorts for Air Pollution Effects (ESCAPE)

BACKGROUND Ambient air pollution is suspected to cause lung cancer. We aimed to assess the association between long-term exposure to ambient air pollution and lung cancer incidence in European populations. METHODS This prospective analysis of data obtained by the European Study of Cohorts for Air Pollution Effects used data from 17 cohort studies based in nine European countries. Baseline addresses were geocoded and we assessed air pollution by land-use regression models for particulate matter (PM) with diameter of less than 10 μm (PM10), less than 2·5 μm (PM2·5), and between 2·5 and 10 μm (PMcoarse), soot (PM2·5absorbance), nitrogen oxides, and two traffic indicators. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effects models for meta-analyses. FINDINGS The 312 944 cohort members contributed 4 013 131 person-years at risk. During follow-up (mean 12·8 years), 2095 incident lung cancer cases were diagnosed. The meta-analyses showed a statistically significant association between risk for lung cancer and PM10 (hazard ratio [HR] 1·22 [95% CI 1·03-1·45] per 10 μg/m(3)). For PM2·5 the HR was 1·18 (0·96-1·46) per 5 μg/m(3). The same increments of PM10 and PM2·5 were associated with HRs for adenocarcinomas of the lung of 1·51 (1·10-2·08) and 1·55 (1·05-2·29), respectively. An increase in road traffic of 4000 vehicle-km per day within 100 m of the residence was associated with an HR for lung cancer of 1·09 (0·99-1·21). The results showed no association between lung cancer and nitrogen oxides concentration (HR 1·01 [0·95-1·07] per 20 μg/m(3)) or traffic intensity on the nearest street (HR 1·00 [0·97-1·04] per 5000 vehicles per day). INTERPRETATION Particulate matter air pollution contributes to lung cancer incidence in Europe. FUNDING European Communitys Seventh Framework Programme.

Effects of long-term exposure to air pollution on natural-cause mortality: an analysis of 22 European cohorts within the multicentre ESCAPE project

BACKGROUND Few studies on long-term exposure to air pollution and mortality have been reported from Europe. Within the multicentre European Study of Cohorts for Air Pollution Effects (ESCAPE), we aimed to investigate the association between natural-cause mortality and long-term exposure to several air pollutants. METHODS We used data from 22 European cohort studies, which created a total study population of 367,251 participants. All cohorts were general population samples, although some were restricted to one sex only. With a strictly standardised protocol, we assessed residential exposure to air pollutants as annual average concentrations of particulate matter (PM) with diameters of less than 2.5 μm (PM2.5), less than 10 μm (PM10), and between 10 μm and 2.5 μm (PMcoarse), PM2.5 absorbance, and annual average concentrations of nitrogen oxides (NO2 and NOx), with land use regression models. We also investigated two traffic intensity variables-traffic intensity on the nearest road (vehicles per day) and total traffic load on all major roads within a 100 m buffer. We did cohort-specific statistical analyses using confounder models with increasing adjustment for confounder variables, and Cox proportional hazards models with a common protocol. We obtained pooled effect estimates through a random-effects meta-analysis. FINDINGS The total study population consisted of 367,251 participants who contributed 5,118,039 person-years at risk (average follow-up 13.9 years), of whom 29,076 died from a natural cause during follow-up. A significantly increased hazard ratio (HR) for PM2.5 of 1.07 (95% CI 1.02-1.13) per 5 μg/m(3) was recorded. No heterogeneity was noted between individual cohort effect estimates (I(2) p value=0.95). HRs for PM2.5 remained significantly raised even when we included only participants exposed to pollutant concentrations lower than the European annual mean limit value of 25 μg/m(3) (HR 1.06, 95% CI 1.00-1.12) or below 20 μg/m(3) (1.07, 1.01-1.13). INTERPRETATION Long-term exposure to fine particulate air pollution was associated with natural-cause mortality, even within concentration ranges well below the present European annual mean limit value. FUNDING European Communitys Seventh Framework Program (FP7/2007-2011).

Development of Land Use Regression Models for PM2.5, PM2.5 Absorbance, PM10 and PMcoarse in 20 European Study Areas; Results of the ESCAPE Project

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.

Long term exposure to ambient air pollution and incidence of acute coronary events: prospective cohort study and meta-analysis in 11 European cohorts from the ESCAPE Project

Objectives To study the effect of long term exposure to airborne pollutants on the incidence of acute coronary events in 11 cohorts participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE). Design Prospective cohort studies and meta-analysis of the results. Setting Cohorts in Finland, Sweden, Denmark, Germany, and Italy. Participants 100 166 people were enrolled from 1997 to 2007 and followed for an average of 11.5 years. Participants were free from previous coronary events at baseline. Main outcome measures Modelled concentrations of particulate matter <2.5 μm (PM2.5), 2.5-10 μm (PMcoarse), and <10 μm (PM10) in aerodynamic diameter, soot (PM2.5 absorbance), nitrogen oxides, and traffic exposure at the home address based on measurements of air pollution conducted in 2008-12. Cohort specific hazard ratios for incidence of acute coronary events (myocardial infarction and unstable angina) per fixed increments of the pollutants with adjustment for sociodemographic and lifestyle risk factors, and pooled random effects meta-analytic hazard ratios. Results 5157 participants experienced incident events. A 5 μg/m3 increase in estimated annual mean PM2.5 was associated with a 13% increased risk of coronary events (hazard ratio 1.13, 95% confidence interval 0.98 to 1.30), and a 10 μg/m3 increase in estimated annual mean PM10 was associated with a 12% increased risk of coronary events (1.12, 1.01 to 1.25) with no evidence of heterogeneity between cohorts. Positive associations were detected below the current annual European limit value of 25 μg/m3 for PM2.5 (1.18, 1.01 to 1.39, for 5 μg/m3 increase in PM2.5) and below 40 μg/m3 for PM10 (1.12, 1.00 to 1.27, for 10 μg/m3 increase in PM10). Positive but non-significant associations were found with other pollutants. Conclusions Long term exposure to particulate matter is associated with incidence of coronary events, and this association persists at levels of exposure below the current European limit values.

Development of Land Use Regression Models for Particle Composition in Twenty Study Areas in Europe

Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM10 and PM2.5) explaining on average between 67 and 79% of the concentration variance (R(2)) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM10 and PM2.5 fractions and Si, Ni, and K in the PM10 fraction performed moderately with R(2) ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R(2) under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE.

Long-term exposure to air pollution and cardiovascular mortality : An analysis of 22 European cohorts

Background: Air pollution has been associated with cardiovascular mortality, but it remains unclear as to whether specific pollutants are related to specific cardiovascular causes of death. Within the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE), we investigated the associations of long-term exposure to several air pollutants with all cardiovascular disease (CVD) mortality, as well as with specific cardiovascular causes of death. Methods: Data from 22 European cohort studies were used. Using a standardized protocol, study area–specific air pollution exposure at the residential address was characterized as annual average concentrations of the following: nitrogen oxides (NO2 and NOx); particles with diameters of less than 2.5 &mgr;m (PM2.5), less than 10 &mgr;m (PM10), and 10 &mgr;m to 2.5 &mgr;m (PMcoarse); PM2.5 absorbance estimated by land-use regression models; and traffic indicators. We applied cohort-specific Cox proportional hazards models using a standardized protocol. Random-effects meta-analysis was used to obtain pooled effect estimates. Results: The total study population consisted of 367,383 participants, with 9994 deaths from CVD (including 4,992 from ischemic heart disease, 2264 from myocardial infarction, and 2484 from cerebrovascular disease). All hazard ratios were approximately 1.0, except for particle mass and cerebrovascular disease mortality; for PM2.5, the hazard ratio was 1.21 (95% confidence interval = 0.87–1.69) per 5 &mgr;g/m3 and for PM10, 1.22 (0.91–1.63) per 10 &mgr;g/m3. Conclusion: In a joint analysis of data from 22 European cohorts, most hazard ratios for the association of air pollutants with mortality from overall CVD and with specific CVDs were approximately 1.0, with the exception of particulate mass and cerebrovascular disease mortality for which there was suggestive evidence for an association.

Long-term exposure to ambient air pollution and incidence of cerebrovascular events: results from 11 European cohorts within the ESCAPE project.

Background: Few studies have investigated effects of air pollution on the incidence of cerebrovascular events. Objectives: We assessed the association between long-term exposure to multiple air pollutants and the incidence of stroke in European cohorts. Methods: Data from 11 cohorts were collected, and occurrence of a first stroke was evaluated. Individual air pollution exposures were predicted from land-use regression models developed within the European Study of Cohorts for Air Pollution Effects (ESCAPE). The exposures were: PM2.5 [particulate matter (PM) ≤ 2.5 μm in diameter], coarse PM (PM between 2.5 and 10 μm), PM10 (PM ≤ 10 μm), PM2.5 absorbance, nitrogen oxides, and two traffic indicators. Cohort-specific analyses were conducted using Cox proportional hazards models. Random-effects meta-analysis was used for pooled effect estimation. Results: A total of 99,446 study participants were included, 3,086 of whom developed stroke. A 5-μg/m3 increase in annual PM2.5 exposure was associated with 19% increased risk of incident stroke [hazard ratio (HR) = 1.19, 95% CI: 0.88, 1.62]. Similar findings were obtained for PM10. The results were robust to adjustment for an extensive list of cardiovascular risk factors and noise coexposure. The association with PM2.5 was apparent among those ≥ 60 years of age (HR = 1.40, 95% CI: 1.05, 1.87), among never-smokers (HR = 1.74, 95% CI: 1.06, 2.88), and among participants with PM2.5 exposure < 25 μg/m3 (HR = 1.33, 95% CI: 1.01, 1.77). Conclusions: We found suggestive evidence of an association between fine particles and incidence of cerebrovascular events in Europe, even at lower concentrations than set by the current air quality limit value. Citation: Stafoggia M, Cesaroni G, Peters A, Andersen ZJ, Badaloni C, Beelen R, Caracciolo B, Cyrys J, de Faire U, de Hoogh K, Eriksen KT, Fratiglioni L, Galassi C, Gigante B, Havulinna AS, Hennig F, Hilding A, Hoek G, Hoffmann B, Houthuijs D, Korek M, Lanki T, Leander K, Magnusson PK, Meisinger C, Migliore E, Overvad K, Östenson CG, Pedersen NL, Pekkanen J, Penell J, Pershagen G, Pundt N, Pyko A, Raaschou-Nielsen O, Ranzi A, Ricceri F, Sacerdote C, Swart WJ, Turunen AW, Vineis P, Weimar C, Weinmayr G, Wolf K, Brunekreef B, Forastiere F. 2014. Long-term exposure to ambient air pollution and incidence of cerebrovascular events: results from 11 European cohorts within the ESCAPE project. Environ Health Perspect 122:919–925; http://dx.doi.org/10.1289/ehp.1307301

Long-term Exposure to Air Pollution and Cardiovascular Mortality An Analysis of 22 European Cohorts

Background: Air pollution has been associated with cardiovascular mortality, but it remains unclear as to whether specific pollutants are related to specific cardiovascular causes of death. Within the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE), we investigated the associations of long-term exposure to several air pollutants with all cardiovascular disease (CVD) mortality, as well as with specific cardiovascular causes of death. Methods: Data from 22 European cohort studies were used. Using a standardized protocol, study area–specific air pollution exposure at the residential address was characterized as annual average concentrations of the following: nitrogen oxides (NO2 and NOx); particles with diameters of less than 2.5 &mgr;m (PM2.5), less than 10 &mgr;m (PM10), and 10 &mgr;m to 2.5 &mgr;m (PMcoarse); PM2.5 absorbance estimated by land-use regression models; and traffic indicators. We applied cohort-specific Cox proportional hazards models using a standardized protocol. Random-effects meta-analysis was used to obtain pooled effect estimates. Results: The total study population consisted of 367,383 participants, with 9994 deaths from CVD (including 4,992 from ischemic heart disease, 2264 from myocardial infarction, and 2484 from cerebrovascular disease). All hazard ratios were approximately 1.0, except for particle mass and cerebrovascular disease mortality; for PM2.5, the hazard ratio was 1.21 (95% confidence interval = 0.87–1.69) per 5 &mgr;g/m3 and for PM10, 1.22 (0.91–1.63) per 10 &mgr;g/m3. Conclusion: In a joint analysis of data from 22 European cohorts, most hazard ratios for the association of air pollutants with mortality from overall CVD and with specific CVDs were approximately 1.0, with the exception of particulate mass and cerebrovascular disease mortality for which there was suggestive evidence for an association.

Short-term associations between fine and coarse particulate matter and hospitalizations in Southern Europe: results from the MED-PARTICLES project.

Background: Evidence on the short-term effects of fine and coarse particles on morbidity in Europe is scarce and inconsistent. Objectives: We aimed to estimate the association between daily concentrations of fine and coarse particles with hospitalizations for cardiovascular and respiratory conditions in eight Southern European cities, within the MED-PARTICLES project. Methods: City-specific Poisson models were fitted to estimate associations of daily concentrations of particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and their difference (PM2.5–10) with daily counts of emergency hospitalizations for cardiovascular and respiratory diseases. We derived pooled estimates from random-effects meta-analysis and evaluated the robustness of results to co-pollutant exposure adjustment and model specification. Pooled concentration–response curves were estimated using a meta-smoothing approach. Results: We found significant associations between all PM fractions and cardiovascular admissions. Increases of 10 μg/m3 in PM2.5, 6.3 μg/m3 in PM2.5–10, and 14.4 μg/m3 in PM10 (lag 0–1 days) were associated with increases in cardiovascular admissions of 0.51% (95% CI: 0.12, 0.90%), 0.46% (95% CI: 0.10, 0.82%), and 0.53% (95% CI: 0.06, 1.00%), respectively. Stronger associations were estimated for respiratory hospitalizations, ranging from 1.15% (95% CI: 0.21, 2.11%) for PM10 to 1.36% (95% CI: 0.23, 2.49) for PM2.5 (lag 0–5 days). Conclusions: PM2.5 and PM2.5–10 were positively associated with cardiovascular and respiratory admissions in eight Mediterranean cities. Information on the short-term effects of different PM fractions on morbidity in Southern Europe will be useful to inform European policies on air quality standards. Citation: Stafoggia M, Samoli E, Alessandrini E, Cadum E, Ostro B, Berti G, Faustini A, Jacquemin B, Linares C, Pascal M, Randi G, Ranzi A, Stivanello E, Forastiere F, the MED-PARTICLES Study Group. 2013. Short-term associations between fine and coarse particulate matter and hospitalizations in Southern Europe: results from the MED-PARTICLES project. Environ Health Perspect 121:1026–1033; http://dx.doi.org/10.1289/ehp.1206151

Comparison of regression models with land-use and emissions data to predict the spatial distribution of traffic-related air pollution in Rome

Spatial modeling of traffic-related air pollution typically involves either regression modeling of land-use and traffic data or dispersion modeling of emissions data, but little is known to what extent land-use regression models might be improved by incorporating emissions data. The aim of this study was to develop a land-use regression model to predict nitrogen dioxide (NO2) concentrations and compare its performance with a model including emissions data. The association between each land-use variable and NO2 concentrations at 68 locations in Rome in 1995 and 1996 was assessed by univariate linear regression and a multiple linear regression model that was constructed based on the importance of each variable. Traffic emissions (particulate matter, carbon monoxide, nitrogen oxides, and benzene) were estimated for 164 areas of the city based on vehicle type, traffic counts and driving patterns. Mean NO2 concentration across the 68 sites was 46.8 μg/m3 (SD 9.8 μg/m3; inter-quartile range 11.5 μg/m3; min 24 μg/m3; max 73 μg/m3). The most important predicting variables were the circular traffic zones (main ring road, green strip, inner ring road, traffic-limited zone), distance from busy streets, size of the census block, the inverse population density, and altitude. A multiple regression model including these variables resulted in an R2 of 0.686. The best-fitting model adding an emission term of benzene resulted in an R2 of 0.690, but was not significantly different from the model without emissions (P=0.147). In conclusion, these results suggest that a land-use regression model explains the traffic-related air pollution levels with reasonable accuracy and that emissions data do not significantly improve the model.