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- Cesaroni, Giulia, et al.
(författare)
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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
- 2014
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Ingår i: The BMJ. - : BMJ. - 1756-1833. ; 348, s. f7412-
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Tidskriftsartikel (refereegranskat)abstract
- 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 mu m (PM2.5), 2.5-10 mu m (PMcoarse), and <10 mu m (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 mu g/m(3) 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 mu g/m(3) 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 mu g/m(3) for PM2.5 (1.18, 1.01 to 1.39, for 5 mu g/m(3) increase in PM2.5) and below 40 mu g/m(3) for PM10 (1.12, 1.00 to 1.27, for 10 mu g/m(3) 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.
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- Wang, Meng, et al.
(författare)
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Performance of multi-city land use regression models for nitrogen dioxide and fine particles
- 2014
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Ingår i: 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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Tidskriftsartikel (refereegranskat)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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