| 1. |
- Arthur Hvidtfeldt, Ulla, et al.
(författare)
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Long-term exposure to fine particle elemental components and lung cancer incidence in the ELAPSE pooled cohort
- 2021
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Ingår i: Environmental Research. - : Elsevier BV. - 0013-9351 .- 1096-0953. ; 193
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Tidskriftsartikel (refereegranskat)abstract
- Background: An association between long-term exposure to fine particulate matter (PM2.5) and lung cancer has been established in previous studies. PM2.5 is a complex mixture of chemical components from various sources and little is known about whether certain components contribute specifically to the associated lung cancer risk. The present study builds on recent findings from the Effects of Low-level Air Pollution: A Study in Europe (ELAPSE) collaboration and addresses the potential association between specific elemental components of PM2.5 and lung cancer incidence.Methods: We pooled seven cohorts from across Europe and assigned exposure estimates for eight components of PM2.5 representing non-tail pipe emissions (copper (Cu), iron (Fe), and zinc (Zn)), long-range transport (sulfur (S)), oil burning/industry emissions (nickel (Ni), vanadium (V)), crustal material (silicon (Si)), and biomass burning (potassium (K)) to cohort participants' baseline residential address based on 100 m by 100 m grids from newly developed hybrid models combining air pollution monitoring, land use data, satellite observations, and dispersion model estimates. We applied stratified Cox proportional hazards models, adjusting for potential confounders (age, sex, calendar year, marital status, smoking, body mass index, employment status, and neighborhood-level socio-economic status).Results: The pooled study population comprised 306,550 individuals with 3916 incident lung cancer events during 5,541,672 person-years of follow-up. We observed a positive association between exposure to all eight components and lung cancer incidence, with adjusted HRs of 1.10 (95% CI 1.05, 1.16) per 50 ng/m(3) PM2.5 K, 1.09 (95% CI 1.02, 1.15) per 1 ng/m3 PM2.5 Ni, 1.22 (95% CI 1.11, 1.35) per 200 ng/m(3) PM2.5 S, and 1.07 (95% CI 1.02, 1.12) per 200 ng/m(3) PM2.5 V. Effect estimates were largely unaffected by adjustment for nitrogen dioxide (NO2). After adjustment for PM2.5 mass, effect estimates of K, Ni, S, and V were slightly attenuated, whereas effect estimates of Cu, Si, Fe, and Zn became null or negative.Conclusions: Our results point towards an increased risk of lung cancer in connection with sources of combustion particles from oil and biomass burning and secondary inorganic aerosols rather than non-exhaust traffic emissions. Specific limit values or guidelines targeting these specific PM2.5 components may prove helpful in future lung cancer prevention strategies.
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| 2. |
- 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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| 3. |
- Castro-Giner, Francesc, et al.
(författare)
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Traffic-related air pollution, oxidative stress genes, and asthma (ECHRS)
- 2009
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Ingår i: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 117:12, s. 1919-1924
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Traffic-related air pollution is related with asthma, and this association may be modified by genetic factors. OBJECTIVES: We investigated the role of genetic polymorphisms potentially modifying the association between home outdoor levels of modeled nitrogen dioxide and asthma. METHODS: Adults from 13 cities of the second European Community Respiratory Health Survey (ECRHS II) were included (n = 2,920), for whom both DNA and outdoor NO(2) estimates were available. Home addresses were geocoded and linked to modeled outdoor NO(2) estimates, as a marker of local traffic-related pollution. We examined asthma prevalence and evaluated polymorphisms in genes involved in oxidative stress pathways [gluthatione S-transferases M1 (GSTM1), T1 (GSTT1), and P1 (GSTP1) and NAD(P)H:quinine oxidoreductase (NQO1)], inflammatory response [tumor necrosis factor alpha (TNFA)], immunologic response [Toll-like receptor 4 (TLR4)], and airway reactivity [adrenergic receptor beta2 (ADRB2)]. RESULTS: The association between modeled NO(2) and asthma prevalence was significant for carriers of the most common genotypes of NQO1 rs2917666 [odds ratio (OR) = 1.54; 95% confidence interval (CI), 1.10-2.24], TNFA rs2844484 (OR = 2.02; 95% CI, 1.30-3.27). For new-onset asthma, the effect of NO(2) was significant for the most common genotype of NQO1 rs2917666 (OR = 1.52; 95% CI, 1.09-2.16). A significant interaction was found between NQO1 rs2917666 and NO(2) for asthma prevalence (p = 0.02) and new-onset asthma (p = 0.04). CONCLUSIONS: Genetic polymorphisms in the NQO1 gene are related to asthma susceptibility among persons exposed to local traffic-related air pollution. This points to the importance of antioxidant pathways in the protection against the effects of air pollution on asthma.
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| 4. |
- de Hoogh, Kees, et al.
(författare)
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Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies
- 2014
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Ingår i: Environment International. - : Elsevier BV. - 0160-4120 .- 1873-6750. ; 73, s. 382-392
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Tidskriftsartikel (refereegranskat)abstract
- Background: Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods. Objectives: Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5. Methods: The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20-40 ESCAPE monitoring sites in each area. Results: The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19-0.89), 0.39 (0.23-0.66) and 0.29 (0.22-0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519(4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74(0.09-0.86) for NO2; 0.58 (0.36-0.88) for PM10 and 0.58 (0.39-0.66) for PM2.5. Conclusions: LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5.
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| 5. |
- de Hoogh, Kees, et al.
(författare)
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Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data
- 2016
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Ingår i: Environmental Research. - : Elsevier BV. - 0013-9351 .- 1096-0953. ; 151, s. 1-10
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Tidskriftsartikel (refereegranskat)abstract
- Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models, all including local traffic and land use variables, were compared (LUR without SAT or CTM, with SAT only, with CTM only, and with both SAT and CTM). LUR models were developed using two monitoring data sets: PM2.5 and NO2 ground level measurements from the European Study of Cohorts for Air Pollution Effects (ESCAPE) and from the European AIRBASE network. LUR PM2.5 models including SAT and SAT+CTM explained ~60% of spatial variation in measured PM2.5 concentrations, substantially more than the LUR model without SAT and CTM (adjR(2): 0.33-0.38). For NO2 CTM improved prediction modestly (adjR(2): 0.58) compared to models without SAT and CTM (adjR(2): 0.47-0.51). Both monitoring networks are capable of producing models explaining the spatial variance over a large study area. SAT and CTM estimates of PM2.5 and NO2 significantly improved the performance of high spatial resolution LUR models at the European scale for use in large epidemiological studies.
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| 6. |
- Fuertes, Elaine, et al.
(författare)
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Residential air pollution does not modify the positive association between physical activity and lung function in current smokers in the ECRHS study
- 2018
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Ingår i: Environment International. - : Elsevier. - 0160-4120 .- 1873-6750. ; 120, s. 364-372
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Very few studies have examined whether a long-term beneficial effect of physical activity on lung function can be influenced by living in polluted urban areas.OBJECTIVE: We assessed whether annual average residential concentrations of nitrogen dioxide (NO2) and particulate matter with aerodynamic diameters < 2.5 μm (PM2.5) and <10 μm (PM10) modify the effect of physical activity on lung function among never- (N = 2801) and current (N = 1719) smokers in the multi-center European Community Respiratory Health Survey.METHODS: Associations between repeated assessments (at 27-57 and 39-67 years) of being physically active (physical activity: ≥2 times and ≥1 h per week) and forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) were evaluated using adjusted mixed linear regression models. Models were conducted separately for never- and current smokers and stratified by residential long-term NO2, PM2.5 mass and PM10 mass concentrations (≤75th percentile (low/medium) versus >75th percentile (high)).RESULTS: Among current smokers, physical activity and lung function were positively associated regardless of air pollution levels. Among never-smokers, physical activity was associated with lung function in areas with low/medium NO2, PM2.5 mass and PM10 mass concentrations (e.g. mean difference in FVC between active and non-active subjects was 43.0 mL (13.6, 72.5), 49.5 mL (20.1, 78.8) and 49.7 mL (18.6, 80.7), respectively), but these associations were attenuated in high air pollution areas. Only the interaction term of physical activity and PM10 mass for FEV1 among never-smokers was significant (p-value = 0.03).CONCLUSIONS: Physical activity has beneficial effects on adult lung function in current smokers, irrespective of residential air pollution levels in Western Europe. Trends among never-smokers living in high air pollution areas are less clear.
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| 7. |
- Hvidtfeldt, Ulla Arthur, et al.
(författare)
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Long-term low-level ambient air pollution exposure and risk of lung cancer - A pooled analysis of 7 European cohorts
- 2021
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Ingår i: Environment International. - : Elsevier BV. - 0160-4120 .- 1873-6750. ; 146
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Tidskriftsartikel (refereegranskat)abstract
- Background/aim: Ambient air pollution has been associated with lung cancer, but the shape of the exposure-response function - especially at low exposure levels - is not well described. The aim of this study was to address the relationship between long-term low-level air pollution exposure and lung cancer incidence.Methods: The Effects of Low-level Air Pollution: a Study in Europe (ELAPSE) collaboration pools seven cohorts from across Europe. We developed hybrid models combining air pollution monitoring, land use data, satellite observations, and dispersion model estimates for nitrogen dioxide (NO2), fine particulate matter (PM2.5), black carbon (BC), and ozone (O-3) to assign exposure to cohort participants' residential addresses in 100 m by 100 m grids. We applied stratified Cox proportional hazards models, adjusting for potential confounders (age, sex, calendar year, marital status, smoking, body mass index, employment status, and neighborhood-level socioeconomic status). We fitted linear models, linear models in subsets, Shape-Constrained Health Impact Functions (SCHIF), and natural cubic spline models to assess the shape of the association between air pollution and lung cancer at concentrations below existing standards and guidelines.Results: The analyses included 307,550 cohort participants. During a mean follow-up of 18.1 years, 3956 incident lung cancer cases occurred. Median (Q1, Q3) annual (2010) exposure levels of NO2, PM2.5, BC and O-3 (warm season) were 24.2 mu g/m(3) (19.5, 29.7), 15.4 mu g/m(3) (12.8, 17.3), 1.6 10(-5)m(-1) (1.3, 1.8), and 86.6 mu g/m(3) (78.5, 92.9), respectively. We observed a higher risk for lung cancer with higher exposure to PM2.5 (HR: 1.13, 95% CI: 1.05, 1.23 per 5 mu g/m(3)). This association was robust to adjustment for other pollutants. The SCHIF, spline and subset analyses suggested a linear or supra-linear association with no evidence of a threshold. In subset analyses, risk estimates were clearly elevated for the subset of subjects with exposure below the EU limit value of 25 mu g/m(3). We did not observe associations between NO2, BC or O-3 and lung cancer incidence.Conclusions: Long-term ambient PM2.5 exposure is associated with lung cancer incidence even at concentrations below current EU limit values and possibly WHO Air Quality Guidelines.
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| 8. |
- Jacquemin, Benedicte, et al.
(författare)
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Ambient Air Pollution and Adult Asthma Incidence in Six European Cohorts (ESCAPE)
- 2015
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Ingår i: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 123:6, s. 613-621
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Short-term exposure to air pollution has adverse effects among patients with asthma, but whether long-term exposure to air pollution is a cause of adult-onset asthma is unclear. OBJECTIVE: We aimed to investigate the association between air pollution and adult onset asthma. METHODS: Asthma incidence was prospectively assessed in six European cohorts. Exposures studied were annual average concentrations at home addresses for nitrogen oxides assessed for 23,704 participants (including 1,257 incident cases) and particulate matter (PM) assessed for 17,909 participants through ESCAPE land-use regression models and traffic exposure indicators. Meta-analyses of cohort-specific logistic regression on asthma incidence were performed. Models were adjusted for age, sex, overweight, education, and smoking and included city/area within each cohort as a random effect. RESULTS: In this longitudinal analysis, asthma incidence was positively, but not significantly, associated with all exposure metrics, except for PMcoarse. Positive associations of borderline significance were observed for nitrogen dioxide [adjusted odds ratio (OR) = 1.10; 95% CI: 0.99, 1.21 per 10 mu g/m(3); p = 0.10] and nitrogen oxides (adjusted OR = 1.04; 95% CI: 0.99, 1.08 per 20 mu g/m(3); p = 0.08). Nonsignificant positive associations were estimated for PM10 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 10 mu g/m(3)), PM2.5 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 5 mu g/m(3)), PM2.5absorbance (adjusted OR = 1.06; 95% CI: 0.95, 1.19 per 10(-5)/m), traffic load (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 4 million vehicles x meters/day on major roads in a 100-m buffer), and traffic intensity (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 5,000 vehicles/day on the nearest road). A nonsignificant negative association was estimated for PMcoarse (adjusted OR = 0.98; 95% CI: 0.87, 1.14 per 5 mu g/m(3)). CONCLUSIONS: Results suggest a deleterious effect of ambient air pollution on asthma incidence in adults. Further research with improved personal-level exposure assessment (vs. residential exposure assessment only) and phenotypic characterization is needed.
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| 9. |
- Jacquemin, Bénédicte, et al.
(författare)
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Home outdoor NO2 and new onset of self-reported asthma in adults
- 2009
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Ingår i: Epidemiology. - 1044-3983 .- 1531-5487. ; 20:1, s. 119-126
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Few studies have investigated new onset of asthma in adults in relation to air pollution. The aim of this study is to investigate the association between modeled background levels of traffic-related air pollution at the subjects' home addresses and self-reported asthma incidence in a European adult population. METHODS: Adults from the European Respiratory Health Survey were included (n = 4185 from 17 cities). Subjects' home addresses were geocoded and linked to outdoor nitrogen dioxide (NO2) estimates, as a marker of local traffic-related pollution. We obtained this information from the 1-km background NO2 surface modeled in APMoSPHERE (Air Pollution Modelling for Support to Policy on Health and Environmental Risk in Europe). Asthma incidence was defined as reporting asthma in the follow-up (1999 to 2001) but not in the baseline (1991 to 1993). RESULTS: A positive association was found between NO2 and asthma incidence (odds ratio 1.43; 95% confidence interval = 1.02 to 2.01) per 10 microg/m. Results were homogeneous among centers (P value for heterogeneity = 0.59). CONCLUSIONS: We found an association between a marker of traffic-related air pollution and asthma incidence in European adults.
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| 10. |
- Liu, Shuo, et al.
(författare)
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Long-term exposure to low-level air pollution and incidence of asthma : the ELAPSE project
- 2021
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Ingår i: European Respiratory Journal. - : European Respiratory Society (ERS). - 0903-1936 .- 1399-3003. ; 57:6
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Tidskriftsartikel (refereegranskat)abstract
- Background: Long-term exposure to ambient air pollution has been linked to childhood-onset asthma, although evidence is still insufficient. Within the multicentre project Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), we examined the associations of long-term exposures to particulate matter with a diameter <2.5 mu m (PM2.5), nitrogen dioxide (NO2) and black carbon (BC) with asthma incidence in adults.Methods: We pooled data from three cohorts in Denmark and Sweden with information on asthma hospital diagnoses. The average concentrations of air pollutants in 2010 were modelled by hybrid land-use regression models at participants' baseline residential addresses. Associations of air pollution exposures with asthma incidence were explored with Cox proportional hazard models, adjusting for potential confounders.Results: Of 98326 participants, 1965 developed asthma during a mean follow-up of 16.6 years. We observed associations in fully adjusted models with hazard ratios of 1.22 (95% CI 1.04-1.43) per 5 mu g.m(-3) for PM2.5, 1.17 (95% CI 1.10-1.25) per 10 mu g.m(-3) for NO2 and 1.15 (95% CI 1.08-1.23) per 0.5 x 10(-5) m(-1) for BC. Hazard ratios were larger in cohort subsets with exposure levels below the European Union and US limit values and possibly World Health Organization guidelines for PM2.5 and NO2. NO 2 and BC estimates remained unchanged in two-pollutant models with PM2.5, whereas PM2.5 estimates were attenuated to unity. The concentration-response curves showed no evidence of a threshold.Conclusions: Long-term exposure to air pollution, especially from fossil fuel combustion sources such as motorised traffic, was associated with adult-onset asthma, even at levels below the current limit values.
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