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      Air Pollution Exposure and Lung Function in Children: The ESCAPE Project

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          Abstract

          Background: There is evidence for adverse effects of outdoor air pollution on lung function of children. Quantitative summaries of the effects of air pollution on lung function, however, are lacking due to large differences among studies.

          Objectives: We aimed to study the association between residential exposure to air pollution and lung function in five European birth cohorts with a standardized exposure assessment following a common protocol.

          Methods: As part of the European Study of Cohorts for Air Pollution Effects (ESCAPE) we analyzed data from birth cohort studies situated in Germany, Sweden, the Netherlands, and the United Kingdom that measured lung function at 6–8 years of age ( n = 5,921). Annual average exposure to air pollution [nitrogen oxides (NO 2, NO x), mass concentrations of particulate matter with diameters < 2.5, < 10, and 2.5–10 μm (PM 2.5, PM 10, and PM coarse), and PM 2.5 absorbance] at the birth address and current address was estimated by land-use regression models. Associations of lung function with estimated air pollution levels and traffic indicators were estimated for each cohort using linear regression analysis, and then combined by random effects meta-analysis.

          Results: Estimated levels of NO 2, NO x, PM 2.5 absorbance, and PM 2.5 at the current address, but not at the birth address, were associated with small decreases in lung function. For example, changes in forced expiratory volume in 1 sec (FEV 1) ranged from –0.86% (95% CI: –1.48, –0.24%) for a 20-μg/m 3 increase in NO x to –1.77% (95% CI: –3.34, –0.18%) for a 5-μg/m 3 increase in PM 2.5.

          Conclusions: Exposure to air pollution may result in reduced lung function in schoolchildren.

          Citation: Gehring U, Gruzieva O, Agius RM, Beelen R, Custovic A, Cyrys J, Eeftens M, Flexeder C, Fuertes E, Heinrich J, Hoffmann B, de Jongste JC, Kerkhof M, Klümper C, Korek M, Mölter A, Schultz ES, Simpson A, Sugiri D, Svartengren M, von Berg A, Wijga AH, Pershagen G, Brunekreef B. 2013. Air pollution exposure and lung function in children: the ESCAPE project. Environ Health Perspect 121:1357–1364;  http://dx.doi.org/10.1289/ehp.1306770

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          Development of Land Use Regression models for PM(2.5), PM(2.5) absorbance, PM(10) and PM(coarse) in 20 European study areas; results of the ESCAPE project.

          Marloes Eeftens, Rob Beelen, Kees de Hoogh … (2012)
          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.
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            Stability of measured and modelled spatial contrasts in NO(2) over time.

            Marloes Eeftens, Bert Brunekreef, Kees Meliefste … (2011)
            Land use regression (LUR) modelling is a popular method to estimate outdoor air pollution concentrations at the home and/or work addresses of individual subjects in epidemiological studies. Typically, such models are constructed using measurements from dedicated monitoring campaigns lasting up to 1 year. It is unknown to what extent such models can adequately predict concentrations in earlier or later time periods. We tested the stability of measured and modelled spatial contrasts in outdoor nitrogen dioxide (NO(2)) pollution across the Netherlands over 8 years. NO(2) measurements were conducted at 40 locations in the Netherlands in 1999-2000. In 2007, NO(2) was again measured at 144 locations, of which 35 were the same as in 1999-2000. This enabled us to compare measurements as well as model predictions between the two time periods. NO(2) measurements conducted in 2007 agreed well with NO(2) measurements taken in 1999-2000 at the same locations (R(2)=0.86). LUR models from 1999-2000 and 2007 explained 85% and 86% of observed spatial variance, respectively. The 2007 LUR model explained 77% of spatial variability in the 1999-2000 measurements and the 1999-2000 model explained 81% of variability in the 2007 measurements. We found good agreement between measured spatial contrasts in outdoor NO(2) in 1999-2000 and 2007. LUR models predicted spatial contrast 8 years in the past (2007 model) and 8 years in the future (1999-2000 model) well. This supports the use of LUR models in epidemiological studies with health data available for a later or earlier timepoint.
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              Nitrogen dioxide levels estimated from land use regression models several years apart and association with mortality in a large cohort study

              Giulia Cesaroni, Daniela Porta, Chiara Badaloni … (2012)
              Background Land Use Regression models (LUR) are useful to estimate the spatial variability of air pollution in urban areas. Few studies have evaluated the stability of spatial contrasts in outdoor nitrogen dioxide (NO2) concentration over several years. We aimed to compare measured and estimated NO2 levels 12 years apart, the stability of the exposure estimates for members of a large cohort study, and the association of the exposure estimates with natural mortality within the cohort. Methods We measured NO2 at 67 locations in Rome in 1995/96 and 78 sites in 2007, over three one-week-long periods. To develop LUR models, several land-use and traffic variables were used. NO2 concentration at each residential address was estimated for a cohort of 684,000 adults. We used Cox regression to analyze the association between the two estimated exposures and mortality. Results The mean NO2 measured concentrations were 45.4 μg/m3 (SD 6.9) in 1995/96 and 44.6 μg/m3 (SD 11.0) in 2007, respectively. The correlation of the two measurements was 0.79. The LUR models resulted in adjusted R2 of 0.737 and 0.704, respectively. The correlation of the predicted exposure values for cohort members was 0.96. The association of each 10 μg/m3 increase in NO2 with mortality was 6 % for 1995/96 and 4 % for 2007 LUR models. The increased risk per an inter-quartile range change was identical (4 %, 95 % CI:3–6 %) for both estimates of NO2. Conclusions Measured and predicted NO2 values from LUR models, from samples collected 12 years apart, had good agreement, and the exposure estimates were similarly associated with mortality in a large cohort study.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Environ Health Perspect
                Journal ID (publisher-id): EHP
                Title: Environmental Health Perspectives
                Publisher: National Institute of Environmental Health Sciences
                ISSN (Print): 0091-6765
                ISSN (Electronic): 1552-9924
                Publication date (Electronic): 27 September 2013
                Publication date (Print): 01 December 2013
                Volume: 121
                Issue: 11-12
                Pages: 1357-1364
                Affiliations
                [1 ]Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
                [2 ]Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
                [3 ]Centre for Epidemiology, Institute of Population Health, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, United Kingdom
                [4 ]Institute of Inflammation and Repair, Manchester Academic Health Science Centre, The University of Manchester and University Hospital of South Manchester NHS Foundation Trust, Manchester, United Kingdom
                [5 ]Institute of Epidemiology II, Helmholtz Zentrum, München, German Research Centre for Environmental Health, Neuherberg, Germany
                [6 ]Environment Science Center, The University of Augsburg, Augsburg, Germany
                [7 ]Institute of Epidemiology I, Helmholtz Zentrum, München, German Research Centre for Environmental Health, Neuherberg, Germany
                [8 ]IUF-Leibniz Research Institute for Environmental Medicine at the University of Düsseldorf, Düsseldorf, Germany
                [9 ]Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
                [10 ]Department of Pediatrics, Division of Respiratory Medicine, Erasmus University Medical Center/Sophia Children’s Hospital, Rotterdam, the Netherlands
                [11 ]Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
                [12 ]Department of Medical Sciences, Uppsala University, Uppsala, Sweden
                [13 ]Department of Pediatrics, Research Institute, Marien Hospital Wesel, Wesel, Germany
                [14 ]Center for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, Bilthoven, the Netherlands
                [15 ]Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
                Author notes
                Address correspondence to U. Gehring, Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, the Netherlands. Telephone: 31 (0)30 253 9486. E-mail: u.gehring@ 123456uu.nl
                Article
                Publisher ID: ehp.1306770
                DOI: 10.1289/ehp.1306770
                PMC ID: 3855518
                PubMed ID: 24076757
                SO-VID: ac8a2e94-1e68-4a06-84b0-7c6459292633
                License:

                Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, “Reproduced with permission from Environmental Health Perspectives”); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.

                History
                Date received : 07 March 2013
                Date accepted : 24 September 2013
                Date: 27 September 2013
                Date: 01 December 2013
                Categories
                Subject: Research

                ScienceOpen disciplines: Public health
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                ScienceOpen disciplines: Public health

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