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Träfflista för sökning "WFRF:(Nieuwenhuijsen Mark) ;pers:(Cesaroni Giulia)"

Sökning: WFRF:(Nieuwenhuijsen Mark) > Cesaroni Giulia

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1.
  • Beelen, Rob, et al. (författare)
  • Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe : the ESCAPE project
  • 2013
  • Ingår i: Atmospheric Environment. - : Elsevier. - 1352-2310 .- 1873-2844. ; 72, s. 10-23
  • Tidskriftsartikel (refereegranskat)abstract
    • Estimating within-city variability in air pollution concentrations is important. Land use regression (LUR) models are able to explain such small-scale within-city variations. Transparency in LUR model development methods is important to facilitate comparison of methods between different studies. We therefore developed LUR models in a standardized way in 36 study areas in Europe for the ESCAPE (European Study of Cohorts for Air Pollution Effects) project.Nitrogen dioxide (NO2) and nitrogen oxides (NOx) were measured with Ogawa passive samplers at 40 or 80 sites in each of the 36 study areas. The spatial variation in each area was explained by LUR modeling. Centrally and locally available Geographic Information System (GIS) variables were used as potential predictors. A leave-one out cross-validation procedure was used to evaluate the model performance.There was substantial contrast in annual average NO2 and NOx concentrations within the study areas. The model explained variances (R2) of the LUR models ranged from 55% to 92% (median 82%) for NO2 and from 49% to 91% (median 78%) for NOx. For most areas the cross-validation R2 was less than 10% lower than the model R2. Small-scale traffic and population/household density were the most common predictors. The magnitude of the explained variance depended on the contrast in measured concentrations as well as availability of GIS predictors, especially traffic intensity data were important. In an additional evaluation, models in which local traffic intensity was not offered had 10% lower R2 compared to models in the same areas in which these variables were offered.Within the ESCAPE project it was possible to develop LUR models that explained a large fraction of the spatial variance in measured annual average NO2 and NOx concentrations. These LUR models are being used to estimate outdoor concentrations at the home addresses of participants in over 30 cohort studies.
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2.
  • Beelen, Rob, et al. (författare)
  • Effects of long-term exposure to air pollution on natural-cause mortality : an analysis of 22 European cohorts within the multicentre ESCAPE project
  • 2014
  • Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 383:9919, s. 785-795
  • Tidskriftsartikel (refereegranskat)abstract
    • 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 mu m (PM2.5), less than 10 mu m (PM10), and between 10 mu m and 2.5 mu m (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 buff er. 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 mu g/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 mu g/m(3) (HR 1.06, 95% CI 1.00-1.12) or below 20 mu g/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.
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3.
  • Beelen, Rob, et al. (författare)
  • Long-term Exposure to Air Pollution and Cardiovascular Mortality An Analysis of 22 European Cohorts
  • 2014
  • Ingår i: Epidemiology. - : Lippincott Williams & Wilkins. - 1044-3983 .- 1531-5487. ; 25:3, s. 368-378
  • Tidskriftsartikel (refereegranskat)abstract
    • 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 mu m (PM2.5), less than 10 mu m (PM10), and 10 mu m to 2.5 mu 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 mu g/m(3) and for PM10, 1.22 (0.91-1.63) per 10 mu g/m(3). 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.
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4.
  • Beelen, Rob, et al. (författare)
  • Natural-Cause Mortality and Long-Term Exposure to Particle Components : An Analysis of 19 European Cohorts within the Multi-Center ESCAPE Project
  • 2015
  • Ingår i: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 123:6, s. 525-533
  • Forskningsöversikt (refereegranskat)abstract
    • Background: Studies have shown associations between mortality and long-term exposure to particulate matter air pollution. Few cohort studies have estimated the effects of the elemental composition of particulate matter on mortality. Objectives: Our aim was to study the association between natural-cause mortality and long-term exposure to elemental components of particulate matter. Methods: Mortality and confounder data from 19 European cohort studies were used. Residential exposure to eight a priori-selected components of particulate matter ( PM) was characterized following a strictly standardized protocol. Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc within PM size fractions <= 2.5 mu m (PM2.5) and <= 10 mu m (PM10) were estimated using land-use regression models. Cohort-specific statistical analyses of the associations between mortality and air pollution were conducted using Cox proportional hazards models using a common protocol followed by meta-analysis. Results: The total study population consisted of 291,816 participants, of whom 25,466 died from a natural cause during follow-up (average time of follow-up, 14.3 years). Hazard ratios were positive for almost all elements and statistically significant for PM2.5 sulfur (1.14; 95% CI: 1.06, 1.23 per 200ng/m(3)). In a two-pollutant model, the association with PM2.5 sulfur was robust to adjustment for PM2.5 mass, whereas the association with PM2.5 mass was reduced. Conclusions: Long-term exposure to PM2.5 sulfur was associated with natural-cause mortality. This association was robust to adjustment for other pollutants and PM2.5.
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5.
  • Cyrys, Josef, et al. (författare)
  • Variation of NO2 and NOx concentrations between and within 36 European study areas : Results from the ESCAPE study
  • 2012
  • Ingår i: Atmospheric Environment. - : Elsevier BV. - 1352-2310 .- 1873-2844. ; 62, s. 374-390
  • Tidskriftsartikel (refereegranskat)abstract
    • The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates long-term effects of exposure to air pollution on human health in Europe. This paper documents the spatial variation of measured NO2 and NOx concentrations between and within 36 ESCAPE study areas across Europe.In all study areas NO2 and NOx were measured using standardized methods between October 2008 and April 2011. On average, 41 sites were selected per study area, including regional and urban background as well as street sites. The measurements were conducted in three different seasons, using Ogawa badges. Average concentrations for each site were calculated after adjustment for temporal variation using data obtained from a routine monitor background site.Substantial spatial variability was found in NO2 and NOx concentrations between and within study areas; 40% of the overall NO2 variance was attributable to the variability between study areas and 60% to variability within study areas. The corresponding values for NOx were 30% and 70%. The within-area spatial variability was mostly determined by differences between street and urban background concentrations. The street/urban background concentration ratio for NO2 varied between 1.09 and 3.16 across areas. The highest median concentrations were observed in Southern Europe, the lowest in Northern Europe.In conclusion, we found significant contrasts in annual average NO2 and NOx concentrations between and especially within 36 study areas across Europe. Epidemiological long-term studies should therefore consider different approaches for better characterization of the intra-urban contrasts, either by increasing of the number of monitors or by modelling.
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6.
  • de Hoogh, Kees, et al. (författare)
  • Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies
  • 2014
  • Ingår i: Environment International. - : Elsevier BV. - 0160-4120 .- 1873-6750. ; 73, s. 382-392
  • Tidskriftsartikel (refereegranskat)abstract
    • 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.
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7.
  • de Hoogh, Kees, et al. (författare)
  • Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data
  • 2016
  • Ingår i: Environmental Research. - : Elsevier BV. - 0013-9351 .- 1096-0953. ; 151, s. 1-10
  • Tidskriftsartikel (refereegranskat)abstract
    • Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models, all including local traffic and land use variables, were compared (LUR without SAT or CTM, with SAT only, with CTM only, and with both SAT and CTM). LUR models were developed using two monitoring data sets: PM2.5 and NO2 ground level measurements from the European Study of Cohorts for Air Pollution Effects (ESCAPE) and from the European AIRBASE network. LUR PM2.5 models including SAT and SAT+CTM explained ~60% of spatial variation in measured PM2.5 concentrations, substantially more than the LUR model without SAT and CTM (adjR(2): 0.33-0.38). For NO2 CTM improved prediction modestly (adjR(2): 0.58) compared to models without SAT and CTM (adjR(2): 0.47-0.51). Both monitoring networks are capable of producing models explaining the spatial variance over a large study area. SAT and CTM estimates of PM2.5 and NO2 significantly improved the performance of high spatial resolution LUR models at the European scale for use in large epidemiological studies.
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8.
  • Guxens, Monica, et al. (författare)
  • Air pollution exposure during pregnancy and childhood autistic traits in four European population-based cohort studies : the ESCAPE project
  • 2016
  • Ingår i: Environmental Health Perspectives. - Stockholm : Karolinska Institutet, Dept of Medical Epidemiology and Biostatistics. - 0091-6765 .- 1552-9924.
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Prenatal exposure to air pollutants has been suggested as a possible etiologic factor for the occurrence of autism spectrum disorder. Objectives: We aimed to assess whether prenatal air pollution exposure is associated with childhood autistic traits in the general population. Methods: Ours was a collaborative study of four European population-based birth/child cohorts— CATSS (Sweden), Generation R (the Netherlands), GASPII (Italy), and INMA (Spain). Nitrogen oxides (NO2, NOx) and particulate matter (PM) with diameters of ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and between 2.5 and 10 μm (PMcoarse), and PM2.5 absorbance were estimated for birth addresses by land-use regression models based on monitoring campaigns performed between 2008 and 2011. Levels were extrapolated back in time to exact pregnancy periods. We quantitatively assessed autistic traits when the child was between 4 and 10 years of age. Children were classified with autistic traits within the borderline/clinical range and within the clinical range using validated cut-offs. Adjusted cohort-specific effect estimates were combined using random-effects meta-analysis. Results: A total of 8,079 children were included. Prenatal air pollution exposure was not associated with autistic traits within the borderline/clinical range (odds ratio = 0.94; 95% CI: 0.81, 1.10 per each 10‑μg/m3 increase in NO2 pregnancy levels). Similar results were observed in the different cohorts, for the other pollutants, and in assessments of children with autistic traits within the clinical range or children with autistic traits as a quantitative score. Conclusions: Prenatal exposure to NO2 and PM was not associated with autistic traits in children from 4 to 10 years of age in four European population-based birth/child cohort studies.
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9.
  • Pedersen, Marie, et al. (författare)
  • Is There an Association Between Ambient Air Pollution and Bladder Cancer Incidence? Analysis of 15 European Cohorts
  • 2018
  • Ingår i: European Urology Focus. - : Elsevier BV. - 2405-4569. ; 4:1, s. 113-120
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Ambient air pollution contains low concentrations of carcinogens implicated in the etiology of urinary bladder cancer (BC). Little is known about whether exposure to air pollution influences BC in the general population. Objective: To evaluate the association between long-term exposure to ambient air pollution and BC incidence. Design, setting and participants: We obtained data from 15 population-based cohorts enrolled between 1985 and 2005 in eight European countries (N = 303 431; mean follow-up 14.1 yr). We estimated exposure to nitrogen oxides (NO2 and NOx), particulate matter (PM) with diameter <10 mu m (PM10), <2.5 mu m (PM2.5). between 2.5 and 10 mu m (PM2.5-10). PM2.5 absorbance (soot), elemental constituents of PM, organic carbon, and traffic density at baseline home addresses using standardized land-use regression models from the European Study of Cohorts for Air Pollution Effects project. Outcome measurements and statistical analysis: We used Cox proportional-hazards models with adjustment for potential confounders for cohort-specific analyses and meta-analyses to estimate summary hazard ratios (HRS) for BC incidence. Results and limitations: During follow-up, 943 incident BC cases were diagnosed. In the meta-analysis, none of the exposures were associated with BC risk. The summary HRs associated with a 10-mu g/m(3) increase in NO2 and 51-mu g/m(3) increase in PM2.5 were 0.98 (95% confidence interval [CI] 0.89-1.08) and 0.86 (95% CI 0.63-1.18), respectively. Limitations include the lack of information about lifetime exposure. Conclusions: There was no evidence of an association between exposure to outdoor air pollution levels at place of residence and risk of BC. Patient summary: We assessed the link between outdoor air pollution at place of residence and bladder cancer using the largest study population to date and extensive assessment of exposure and comprehensive data on personal risk factors such as smoking. We found no association between the levels of outdoor air pollution at place of residence and bladder cancer risk.
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10.
  • Raaschou-Nielsen, Ole, et al. (författare)
  • Air pollution and lung cancer incidence in 17 European cohorts : prospective analyses from the European Study of Cohorts for Air Pollution Effects (ESCAPE)
  • 2013
  • Ingår i: The Lancet Oncology. - 1470-2045 .- 1474-5488. ; 14:9, s. 813-822
  • Tidskriftsartikel (refereegranskat)abstract
    • 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 Community's Seventh Framework Programme.
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