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- Beelen, Rob, et al.
(författare)
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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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Ingår i: Atmospheric Environment. - : Elsevier. - 1352-2310 .- 1873-2844. ; 72, s. 10-23
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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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- Fuks, Kateryna B., et al.
(författare)
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Arterial blood pressure and long-term exposure to traffic-related air pollution : an analysis in the European Study of Cohorts for Air Pollution Effects (ESCAPE)
- 2014
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Ingår i: Journal of Environmental Health Perspectives. - : National Institute of Environmental Health Sciences (NIEHS). - 0091-6765 .- 1552-9924. ; 122:9, s. 896-905
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Forskningsöversikt (refereegranskat)abstract
- BACKGROUND: Long-term exposure to air pollution is hypothesized to elevate arterial blood pressure (BP). The existing evidence is scarce and country-specific. OBJECTIVES: We investigated the cross-sectional association of long-term traffic-related air pollution with BP and prevalent hypertension in European populations. METHODS: Fifteen population-based cohorts, participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE), were analysed. Residential exposure to particulate matter and nitrogen oxides was modelled with land use regression using a uniform protocol. Traffic exposure was assessed with traffic indicator variables. We analysed systolic and diastolic BP in participants medicated and non-medicated with BP lowering medication (BPLM) separately, adjusting for personal and area-level risk factors and environmental noise. Prevalent hypertension was defined as ≥ 140 mmHg systolic, or ≥ 90 mmHg diastolic BP, or intake of BPLM. We combined cohort-specific results using random-effects meta-analysis. RESULTS: In the main meta-analysis of 113,926 participants, traffic load on major roads within 100 m of the residence was associated with increased systolic and diastolic BP in non-medicated participants (0.35 mmHg [95% CI: 0.02-0.68] and 0.22 mmHg [95% CI: 0.04-0.40] per 4,000,000 vehicles × m/day, respectively). The estimated odds ratio for prevalent hypertension was 1.05 [95% CI: 0.99-1.11] per 4,000,000 vehicles × m/day. Modelled air pollutants and BP were not clearly associated. CONCLUSIONS: In this first comprehensive meta-analysis of European population-based cohorts we observed a weak positive association of high residential traffic exposure with BP in non-medicated participants, and an elevated OR for prevalent hypertension. The relationship of modelled air pollutants with BP was inconsistent.
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