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.
h i g h l i g h t s < LUR models were developed in 36 study areas in Europe using a standardized approach. < NO 2 models explained a large fraction of concentration variability (median R 2 82%). < Local traffic intensity data were important predictors for LUR model development.
PM 2.5 : mass concentration of particles less than 2.5 µm in size PM 10 : mass concentration of particles less than 10 µm in size RB: Regional Background site SOP: Standard Operating Procedure ST: Street site TRAPCA: Traffic-Related Air Pollution and Childhood Asthma UB: Urban Background site ABSTRACT The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates long-term effects on human health of exposure to air pollution in Europe. Various health endpoints are analysed by using prospective cohort studies in the study areas. This paper documents the spatial variation of measured NO 2 and NO x concentrations between and within 36 study areas across Europe. In 36 study areas NO 2 and NO x were measured using standardized methods between October 2008 and April 2011. In each study area 14 to 80 sites were selected, which represented a wide range of regional, urban and nearby traffic related pollution contrast. The measurements were conducted for two weeks per site in three different seasons, using Ogawa badges. Results for each site were adjusted for temporal variation using data obtained from a routine monitor background site, which operated continuously, and averaged. Substantial spatial variability was found in NO 2 and NO x concentrations between and within study areas. Analysis of variance showed that 40% of the overall NO 2 variance is attributable to the variability between the study areas and 60% is caused by the variability within the study areas. The corresponding values for NO x are 30% (between the study areas) and 70% (within the study areas). The within-area spatial variability was mostly determined by the differences between traffic and urban background concentrations. The traffic/urban background concentration ratio varied between 1.09 and 3.16 across Europe. The NO 2 / NO x ratio varied between 0.47 (Verona) and 0.72 (Heraklion) across study areas. In study areas in southern Europe the highest median concentrations were observed (Barcelona: NO 2 55 µg/m³), followed by densely populated areas in Western Europe (Ruhr area, The Netherlands). The lowest concentrations were observed in all areas in Northern Europe (e.g. Umeå: NO 2 7 µg/m³). In conclusion, we found significant contrast in annual average NO 2 and NO x concentration between and especially within 36 study areas across Europe. Epidemiological studies should therefore characterize intra-urban contrasts. The use of traffic indicators such as "living close to major road" as an exposure variable in epidemiological studies results in different actual NO 2 contrasts. We would like to thank Kees Meliefste, Geert de Vrieze, Marjan Tewis (IRAS, Utrecht University, The Netherlands) for the sampler preparation, analysis and data management. Furthermore, we thank all those who were responsible for air pollution measurements, data management and project supervision in all study areas and especially:
Background: Recent studies have shown an association of short-term exposure to fine particulate matter (PM) with transient increases in blood pressure (BP), but it is unclear whether long-term exposure has an effect on arterial BP and hypertension.Objectives: We investigated the cross-sectional association of residential long-term PM exposure with arterial BP and hypertension, taking short-term variations of PM and long-term road traffic noise exposure into account.Methods: We used baseline data (2000–2003) on 4,291 participants, 45–75 years of age, from the Heinz Nixdorf Recall Study, a population-based prospective cohort in Germany. Urban background exposure to PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10) was assessed with a dispersion and chemistry transport model. We used generalized additive models, adjusting for short-term PM, meteorology, traffic proximity, and individual risk factors.Results: An interquartile increase in PM2.5 (2.4 μg/m3) was associated with estimated increases in mean systolic and diastolic BP of 1.4 mmHg [95% confidence interval (CI): 0.5, 2.3] and 0.9 mmHg (95% CI: 0.4, 1.4), respectively. The observed relationship was independent of long-term exposure to road traffic noise and robust to the inclusion of many potential confounders. Residential proximity to high traffic and traffic noise exposure showed a tendency toward higher BP and an elevated prevalence of hypertension.Conclusions: We found an association of long-term exposure to PM with increased arterial BP in a population-based sample. This finding supports our hypothesis that long-term PM exposure may promote atherosclerosis, with air-pollution–induced increases in BP being one possible biological pathway.
Our study shows a clear association of long-term exposure to PM(2.5) with atherosclerosis. This finding strengthens the hypothesized role of PM(2.5) as a risk factor for atherogenesis.
In this population-based cohort, we found associations of long-term exposure to PM with markers of inflammation (hs-CRP) and coagulation (platelets). This finding supports the hypothesis that inflammatory processes might contribute to chronic effects of air pollution on cardiovascular disease.
BackgroundStudies investigating the link between long-term exposure to air pollution and incidence of diabetes are still scarce and results are inconsistent, possibly due to different compositions of the particle mixture. We investigate the long-term effect of traffic-specific and total particulate matter (PM) and road proximity on cumulative incidence of diabetes mellitus (mainly type 2) in a large German cohort.MethodsWe followed prospectively 3607 individuals without diabetes at baseline (2000–2003) from the Heinz Nixdorf Recall Study in Germany (mean follow-up time 5.1 years). Mean annual exposures to total as well as traffic-specific PM10 and PM2.5 at residence were estimated using a chemistry transport model (EURAD, 1 km2 resolution). Effect estimates for an increase of 1 μg/m3 in PM were obtained with Poisson regression adjusting for sex, age, body mass index, lifestyle factors, area-level and individual-level socio-economic status, and city.Results331 incident cases developed. Adjusted RRs for total PM10 and PM2.5 were 1.05 (95 %-CI: 1.00;1.10) and 1.03 (95 %-CI: 0.95;1.12), respectively. Markedly higher point estimates were found for local traffic-specific PM with RRs of 1.36 (95 %-CI: 0.98;1.89) for PM10 and 1.36 (95 %-CI: 0.97;1.89) for PM2.5. Individuals living closer than 100 m to a busy road had a more than 30 % higher risk (1.37;95 %-CI: 1.04;1.81) than those living further than 200 m away.ConclusionsLong-term exposure to total PM increases type two diabetes risk in the general population, as does living close to a major road. Local traffic-specific PM was related to higher risks for type two diabetes than total PM.Electronic supplementary materialThe online version of this article (doi:10.1186/s12940-015-0031-x) contains supplementary material, which is available to authorized users.
Daily to monthly variations in fine particulate matter have been linked to systemic inflammatory responses. It has been hypothesized that smaller particles resulting from combustion processes confer higher toxicity. We aim to analyze the association between short-term exposure to ultrafine and fine particles and systemic inflammation. We use baseline data (2000-2003) of the Heinz Nixdorf Recall Study, a population-based cohort study of 4,814 participants in the Ruhr Area in Germany. A chemistry transport model was applied to model daily surface concentrations of particulate air pollutants on a grid of 1 km(2). Exposure included particle number (PN) and particulate matter mass concentration with an aerodynamic diameter < or = 2.5 microm (PM(2.5)) and < or = 10 microm (PM(10)). Generalized additive models were used to explore the relation of air pollutants using single day lags and averaging times of up to 28 days with high-sensitivity C-reactive protein (hs-CRP). We adjusted for meteorology, season, time trend, and personal characteristics. Median hs-CRP level in the 3,999 included participants was 1.5 mg/l. Median daily concentration of PN was 8,414 x 10(4)/ml (IQR 4,580 x 10(4)/ml), of PM(2.5) 14.5 microg/m(3) (IQR 11.5 microg/m(3)) and of PM(10) 18.5 microg/m(3) (IQR 13.9 microg/m(3)). A positive association between PN and hs-CRP could be observed only for single day lags and for averaged PN concentrations with higher estimates for longer averaging times. The highest hs-CRP-increase of 7.1% (95%-CI: 1.9, 12.6%) was found for the 21-day average. These results support the hypothesis that short-term exposure to traffic-related particles might lead to detrimental cardiovascular health effects via an inflammatory mechanism.
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