| 1. |
- Beelen, Rob, et al.
(author)
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Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe : the ESCAPE project
- 2013
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In: Atmospheric Environment. - : Elsevier. - 1352-2310 .- 1873-2844. ; 72, s. 10-23
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Journal article (peer-reviewed)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.
(author)
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Long-term Exposure to Air Pollution and Cardiovascular Mortality An Analysis of 22 European Cohorts
- 2014
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In: Epidemiology. - : Lippincott Williams & Wilkins. - 1044-3983 .- 1531-5487. ; 25:3, s. 368-378
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Journal article (peer-reviewed)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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| 3. |
- Burte, Emilie, et al.
(author)
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Association between air pollution and rhinitis incidence in two European cohorts
- 2018
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In: Environment International. - : Elsevier. - 0160-4120 .- 1873-6750. ; 115, s. 257-266
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Journal article (peer-reviewed)abstract
- The association between air pollution and rhinitis is not well established.Aim: The aim of this longitudinal analysis was to study the association between modeled air pollution at the subjects' home addresses and self-reported incidence of rhinitis.Methods: We used data from 1533 adults from two multicentre cohorts' studies (EGEA and ECRHS). Rhinitis incidence was defined as reporting rhinitis at the second follow-up (2011 to 2013) but not at the first follow-up (2000 to 2007). Annual exposure to NO2, PM10 and PM2.5 at the participants' home addresses was estimated using land-use regression models developed by the ESCAPE project for the 2009-2010 period. Incidence rate ratios (IRR) were computed using Poisson regression. Pooled analysis, analyses by city and meta-regression testing for heterogeneity were carried out.Results: No association between long-term air pollution exposure and incidence of rhinitis was found (adjusted IRR (aIRR) for an increase of 10 mu g center dot m(-3) of NO2: 1.00 [0.91-1.09], for an increase of 5 mu g center dot m(-3) of PM2.5: 0.88 [0.73-1.04]). Similar results were found in the two-pollutant model (aIRR for an increase of 10 mu g center dot m(-3) of NO2: 1.01 [0.87-1.17], for an increase of 5 mu g center dot m(-3) of PM2.5: 0.87 [0.68-1.08]). Results differed depending on the city, but no regional pattern emerged for any of the pollutants.Conclusions: This study did not find any consistent evidence of an association between long-term air pollution and incident rhinitis.
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| 4. |
- Burte, Emilie, et al.
(author)
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Long-term air pollution exposure is associated with increased severity of rhinitis in 2 European cohorts
- 2020
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In: Journal of Allergy and Clinical Immunology. - : Elsevier. - 0091-6749 .- 1097-6825. ; 145:3, s. 834-842.e6
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Journal article (peer-reviewed)abstract
- BACKGROUND: Very few studies have examined the association between long-term outdoor air pollution and rhinitis severity in adults.OBJECTIVE: We sought to assess the cross-sectional association between individual long-term exposure to air pollution and severity of rhinitis.METHODS: Participants with rhinitis from 2 multicenter European cohorts (Epidemiological Study on the Genetics and Environment on Asthma and the European Community Respiratory Health Survey) were included. Annual exposure to NO2, PM10, PM2.5, and PMcoarse (calculated by subtracting PM2.5 from PM10) was estimated using land-use regression models derived from the European Study of Cohorts for Air Pollution Effects project, at the participants' residential address. The score of rhinitis severity (range, 0-12), based on intensity of disturbance due to symptoms reported by questionnaire, was categorized into low (reference), mild, moderate, and high severity. Polytomous logistic regression models with a random intercept for city were used.RESULTS: A total of 1408 adults with rhinitis (mean age, 52 years; 46% men, 81% from the European Community Respiratory Health Survey) were included. The median (1st quartile-3rd quartile) score of rhinitis severity was 4 (2-6). Higher exposure to PM10 was associated with higher rhinitis severity (adjusted odds ratio [95% CI] for a 10 μg/m3 increase in PM10: for mild: 1.20 [0.88-1.64], moderate: 1.53 [1.07-2.19], and high severity: 1.72 [1.23-2.41]). Similar results were found for PM2.5. Higher exposure to NO2 was associated with an increased severity of rhinitis, with similar adjusted odds ratios whatever the level of severity. Adjusted odds ratios were higher among participants without allergic sensitization than among those with, but interaction was found only for NO2. CONCLUSIONS: People with rhinitis who live in areas with higher levels of pollution are more likely to report more severe nasal symptoms. Further work is required to elucidate the mechanisms of this association.
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| 5. |
- de Hoogh, Kees, et al.
(author)
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Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data
- 2016
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In: Environmental Research. - : Elsevier BV. - 0013-9351 .- 1096-0953. ; 151, s. 1-10
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Journal article (peer-reviewed)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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| 6. |
- Dimakopoulou, Konstantina, et al.
(author)
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Air Pollution and Nonmalignant Respiratory Mortality in 16 Cohorts within the ESCAPE Project
- 2014
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In: American Journal of Respiratory and Critical Care Medicine. - : American Thoracic Society. - 1073-449X .- 1535-4970. ; 189:6, s. 684-696
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Journal article (peer-reviewed)abstract
- Rationale: Prospective cohort studies have shown that chronic exposure to particulate matter and traffic-related air pollution is associated with reduced survival. However, the effects on nonmalignant respiratory mortality are less studied, and the data reported are less consistent. Objectives: We have investigated the relationship of long-term exposure to air pollution and nonmalignant respiratory mortality in 16 cohorts with individual level data within the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE). Methods: Data from 16 ongoing cohort studies from Europe were used. The total number of subjects was 307,553. There were 1,559 respiratory deaths during follow-up. Measurements and Main Results: Air pollution exposure was estimated by land use regression models at the baseline residential addresses of study participants and traffic-proximity variables were derived from geographical databases following a standardized procedure within, the ESCAPE study. Cohort-specific hazard ratios obtained by Cox proportional hazard models from standardized individual cohort analyses were combined using metaanalyses. We found no significant associations between air pollution exposure and nonmalignant respiratory mortality. Most hazard ratios were slightly below unity, with the exception of the traffic-proximity indicators. Conclusions: In this study of 16 cohorts, there was no-association between air pollution exposure and nonmalignant respiratory mortality.
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| 7. |
- Jacquemin, Benedicte, et al.
(author)
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Ambient Air Pollution and Adult Asthma Incidence in Six European Cohorts (ESCAPE)
- 2015
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In: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 123:6, s. 613-621
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Journal article (peer-reviewed)abstract
- BACKGROUND: Short-term exposure to air pollution has adverse effects among patients with asthma, but whether long-term exposure to air pollution is a cause of adult-onset asthma is unclear. OBJECTIVE: We aimed to investigate the association between air pollution and adult onset asthma. METHODS: Asthma incidence was prospectively assessed in six European cohorts. Exposures studied were annual average concentrations at home addresses for nitrogen oxides assessed for 23,704 participants (including 1,257 incident cases) and particulate matter (PM) assessed for 17,909 participants through ESCAPE land-use regression models and traffic exposure indicators. Meta-analyses of cohort-specific logistic regression on asthma incidence were performed. Models were adjusted for age, sex, overweight, education, and smoking and included city/area within each cohort as a random effect. RESULTS: In this longitudinal analysis, asthma incidence was positively, but not significantly, associated with all exposure metrics, except for PMcoarse. Positive associations of borderline significance were observed for nitrogen dioxide [adjusted odds ratio (OR) = 1.10; 95% CI: 0.99, 1.21 per 10 mu g/m(3); p = 0.10] and nitrogen oxides (adjusted OR = 1.04; 95% CI: 0.99, 1.08 per 20 mu g/m(3); p = 0.08). Nonsignificant positive associations were estimated for PM10 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 10 mu g/m(3)), PM2.5 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 5 mu g/m(3)), PM2.5absorbance (adjusted OR = 1.06; 95% CI: 0.95, 1.19 per 10(-5)/m), traffic load (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 4 million vehicles x meters/day on major roads in a 100-m buffer), and traffic intensity (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 5,000 vehicles/day on the nearest road). A nonsignificant negative association was estimated for PMcoarse (adjusted OR = 0.98; 95% CI: 0.87, 1.14 per 5 mu g/m(3)). CONCLUSIONS: Results suggest a deleterious effect of ambient air pollution on asthma incidence in adults. Further research with improved personal-level exposure assessment (vs. residential exposure assessment only) and phenotypic characterization is needed.
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| 8. |
- Keidel, Dirk, et al.
(author)
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The Role of Socioeconomic Status in the Association of Lung Function and Air Pollution : A Pooled Analysis of Three Adult ESCAPE Cohorts
- 2019
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In: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 16:11
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Journal article (peer-reviewed)abstract
- Ambient air pollution is a leading environmental risk factor and its broad spectrum of adverse health effects includes a decrease in lung function. Socioeconomic status (SES) is known to be associated with both air pollution exposure and respiratory function. This study assesses the role of SES either as confounder or effect modifier of the association between ambient air pollution and lung function. Cross-sectional data from three European multicenter adult cohorts were pooled to assess factors associated with lung function, including annual means of home outdoor NO2. Pre-bronchodilator lung function was measured according to the ATS-criteria. Multiple mixed linear models with random intercepts for study areas were used. Three different factors (education, occupation and neighborhood unemployment rate) were considered to represent SES. NO2 exposure was negatively associated with lung function. Occupation and neighborhood unemployment rates were not associated with lung function. However, the inclusion of the SES-variable education improved the models and the air pollution-lung function associations got slightly stronger. NO2 associations with lung function were not substantially modified by SES-variables. In this multicenter European study we could show that SES plays a role as a confounder in the association of ambient NO2 exposure with lung function.
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| 9. |
- Temam, Sofia, et al.
(author)
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Socioeconomic position and outdoor nitrogen dioxide (NO2) exposure in Western Europe : a multi-city analysis
- 2017
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In: Environment International. - : Elsevier BV. - 0160-4120 .- 1873-6750. ; 101, s. 117-124
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Journal article (peer-reviewed)abstract
- BACKGROUND: Inconsistent associations between socioeconomic position (SEP) and outdoor air pollution have been reported in Europe, but methodological differences prevent any direct between-study comparison.OBJECTIVES: Assess and compare the association between SEP and outdoor nitrogen dioxide (NO2) exposure as a marker of traffic exhaust, in 16 cities from eight Western European countries.METHODS: Three SEP indicators, two defined at individual-level (education and occupation) and one at neighborhood-level (unemployment rate) were assessed in three European multicenter cohorts. NO2 annual concentration exposure was estimated at participants' addresses with land use regression models developed within the European Study of Cohorts for Air Pollution Effects (ESCAPE; http://www.escapeproject.eu/). Pooled and city-specific linear regressions were used to analyze associations between each SEP indicator and NO2. Heterogeneity across cities was assessed using the Higgins' I-squared test (I(2)).RESULTS: The study population included 5692 participants. Pooled analysis showed that participants with lower individual-SEP were less exposed to NO2. Conversely, participants living in neighborhoods with higher unemployment rate were more exposed. City-specific results exhibited strong heterogeneity (I(2)>76% for the three SEP indicators) resulting in variation of the individual- and neighborhood-SEP patterns of NO2 exposure across cities. The coefficients from a model that included both individual- and neighborhood-SEP indicators were similar to the unadjusted coefficients, suggesting independent associations.CONCLUSIONS: Our study showed for the first time using homogenized measures of outcome and exposure across 16 cities the important heterogeneity regarding the association between SEP and NO2 in Western Europe. Importantly, our results showed that individual- and neighborhood-SEP indicators capture different aspects of the association between SEP and exposure to air pollution, stressing the importance of considering both in air pollution health effects studies.
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| 10. |
- Wang, Meng, et al.
(author)
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Performance of multi-city land use regression models for nitrogen dioxide and fine particles
- 2014
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In: Journal of Environmental Health Perspectives. - : Public Health Services, US Dept of Health and Human Services. - 0091-6765 .- 1552-9924. ; 122:8, s. 843-849
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Journal article (peer-reviewed)abstract
- BACKGROUND: Land use regression (LUR) models have been developed mostly to explain intraurban variations in air pollution based on often small local monitoring campaigns. Transferability of LUR models from city to city has been investigated, but little is known about the performance of models based on large numbers of monitoring sites covering a large area.OBJECTIVES: We aimed to develop European and regional LUR models and to examine their transferability to areas not used for model development.METHODS: We evaluated LUR models for nitrogen dioxide (NO2) and particulate matter (PM; PM2.5, PM2.5 absorbance) by combining standardized measurement data from 17 (PM) and 23 (NO2) ESCAPE (European Study of Cohorts for Air Pollution Effects) study areas across 14 European countries for PM and NO2. Models were evaluated with cross-validation (CV) and hold-out validation (HV). We investigated the transferability of the models by successively excluding each study area from model building.RESULTS: The European model explained 56% of the concentration variability across all sites for NO2, 86% for PM2.5, and 70% for PM2.5 absorbance. The HV R2s were only slightly lower than the model R2 (NO2, 54%; PM2.5, 80%; PM2.5 absorbance, 70%). The European NO2, PM2.5, and PM2.5 absorbance models explained a median of 59%, 48%, and 70% of within-area variability in individual areas. The transferred models predicted a modest-to-large fraction of variability in areas that were excluded from model building (median R2: NO2, 59%; PM2.5, 42%; PM2.5 absorbance, 67%).CONCLUSIONS: Using a large data set from 23 European study areas, we were able to develop LUR models for NO2 and PM metrics that predicted measurements made at independent sites and areas reasonably well. This finding is useful for assessing exposure in health studies conducted in areas where no measurements were conducted.
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