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      Ambient air pollution is associated with airway inflammation in older women: a nested cross-sectional analysis

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          Abstract

          Background

          Air pollution is a risk factor for chronic obstructive pulmonary disease (COPD). Fraction of exhaled nitric oxide (FeNO) could be a useful biomarker for health effects of air pollutants. However, there were limited data from older populations with higher prevalence of COPD and other inflammatory conditions.

          Methods

          We obtained data from the German Study on the influence of Air pollution on Lung function, Inflammation and Ageing. Spirometry and FeNO were measured by standard techniques. Air pollutant exposures were estimated following the European Study of Cohorts for Air Pollution Effects protocols, and ozone (O 3) measured at the closest ground level monitoring station. Multiple linear regression models were fitted to FeNO with each pollutant separately and adjusted for potential confounders.

          Results

          In 236 women (mean age 74.6 years), geometric mean FeNO was 15.2ppb. Almost a third (n=71, 30.1%) of the women had some chronic inflammatory respiratory condition. A higher FeNO concentration was associated with exposures to fine particles (PM 2.5), PM 2.5absorbance and respirable particles (PM 10). There were no significant associations with PM coarse, NO 2, NO x, O 3 or length of major roads within a 1 km buffer. Restricting the analysis to participants with a chronic inflammatory respiratory condition, with or without impaired lung function produced similar findings. Adjusting for diabetes did not materially alter the findings. There were no significant interactions between individual pollutants and asthma or current smoking.

          Conclusions

          This study adds to the evidence to reduce ambient PM 2.5 concentrations as low as possible to protect the health of the general population.

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          Most cited references29

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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.

          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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            Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe – The ESCAPE project

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              Long-term air pollution exposure and living close to busy roads are associated with COPD in women

              Background Lung function and exacerbations of chronic obstructive pulmonary disease (COPD) have been associated with short-term exposure to air pollution. However, the effect of long-term exposure to particulate matter from industry and traffic on COPD as defined by lung function has not been evaluated so far. Our study was designed to investigate the influence of long-term exposure to air pollution on respiratory symptoms and pulmonary function in 55-year-old women. We especially focused on COPD as defined by GOLD criteria and additionally compared the effects of air pollution on respiratory symptoms by questionnaire data and by lung function measurements. Methods In consecutive cross sectional studies conducted between 1985–1994, we investigated 4757 women living in the Rhine-Ruhr Basin of Germany. NO2 and PM10 exposure was assessed by measurements done in an 8 km grid, and traffic exposure by distance from the residential address to the nearest major road using Geographic Information System data. Lung function was determined and COPD was defined by using the GOLD criteria. Chronic respiratory symptoms and possible confounders were defined by questionnaire data. Linear and logistic regressions, including random effects were used to account for confounding and clustering on city level. Results The prevalence of COPD (GOLD stages 1–4) was 4.5%. COPD and pulmonary function were strongest affected by PM10 and traffic related exposure. A 7 μg/m3 increase in five year means of PM10 (interquartile range) was associated with a 5.1% (95% CI 2.5%–7.7%) decrease in FEV1, a 3.7% (95% CI 1.8%–5.5%) decrease in FVC and an odds ratio (OR) of 1.33 (95% CI 1.03–1.72) for COPD. Women living less than 100 m from a busy road also had a significantly decreased lung function and COPD was 1.79 times more likely (95% CI 1.06–3.02) than for those living farther away. Chronic symptoms as based on questionnaire information showed effects in the same direction, but less pronounced. Conclusion Chronic exposure to PM10, NO2 and living near a major road might increase the risk of developing COPD and can have a detrimental effect on lung function.
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                Author and article information

                Journal
                BMJ Open Respir Res
                BMJ Open Respir Res
                bmjresp
                bmjopenrespres
                BMJ Open Respiratory Research
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2052-4439
                2020
                24 March 2020
                : 7
                : 1
                Affiliations
                [1 ]departmentSchool of Public Health and Preventive Medicine , Monash University , Melbourne, Victoria, Australia
                [2 ]departmentEnvironmental Epidemiology of Lung, Brain and Skin Aging , Leibniz Research Institute for Environmental Medicine , Dusseldorf, Nordrhein-Westfalen, Germany
                Author notes
                [Correspondence to ] Dr Tamara Schikowski; Tamara.Schikowski@ 123456IUF-Duesseldorf.de
                Article
                bmjresp-2019-000549
                10.1136/bmjresp-2019-000549
                7206912
                32209644
                79bfa950-8b65-46b8-b803-e36015e3ee84
                © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                Product
                Funding
                Funded by: German Statutory Accident Insurance (DGUV);
                Award ID: 617.0-FP266
                Funded by: FundRef http://dx.doi.org/10.13039/100011199, FP7 Ideas: European Research Council;
                Award ID: FP 7/2007-2011 Grant 211250
                Categories
                Environmental Exposure
                1506
                2219
                Custom metadata
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                copd epidemiology,exhaled airway markers
                copd epidemiology, exhaled airway markers

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