12 research outputs found

    Long-term exposure to low-level air pollution and incidence of chronic obstructive pulmonary disease: The ELAPSE project.

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    BACKGROUND: Air pollution has been suggested as a risk factor for chronic obstructive pulmonary disease (COPD), but evidence is sparse and inconsistent. OBJECTIVES: We examined the association between long-term exposure to low-level air pollution and COPD incidence. METHODS: Within the 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE) study, we pooled data from three cohorts, from Denmark and Sweden, with information on COPD hospital discharge diagnoses. Hybrid land use regression models were used to estimate annual mean concentrations of particulate matter with a diameter < 2.5 µm (PM2.5), nitrogen dioxide (NO2), and black carbon (BC) in 2010 at participants' baseline residential addresses, which were analysed in relation to COPD incidence using Cox proportional hazards models. RESULTS: Of 98,058 participants, 4,928 developed COPD during 16.6 years mean follow-up. The adjusted hazard ratios (HRs) and 95% confidence intervals for associations with COPD incidence were 1.17 (1.06, 1.29) per 5 µg/m3 for PM2.5, 1.11 (1.06, 1.16) per 10 µg/m3 for NO2, and 1.11 (1.06, 1.15) per 0.5 10-5m-1 for BC. Associations persisted in subset participants with PM2.5 or NO2 levels below current EU and US limit values and WHO guidelines, with no evidence for a threshold. HRs for NO2 and BC remained unchanged in two-pollutant models with PM2.5, whereas the HR for PM2.5 was attenuated to unity with NO2 or BC. CONCLUSIONS: Long-term exposure to low-level air pollution is associated with the development of COPD, even below current EU and US limit values and possibly WHO guidelines. Traffic-related pollutants NO2 and BC may be the most relevant

    Can dispersion modeling of air pollution be improved by land-use regression? : An example from Stockholm, Sweden

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    Both dispersion modeling (DM) and land-use regression modeling (LUR) are often used for assessment of long-term air pollution exposure in epidemiological studies, but seldom in combination. We developed a hybrid DM-LUR model using 93 biweekly observations of NOx at 31 sites in greater Stockholm (Sweden). The DM was based on spatially resolved topographic, physiographic and emission data, and hourly meteorological data from a diagnostic wind model. Other data were from land use, meteorology and routine monitoring of NOx. We built a linear regression model for NOx, using a stepwise forward selection of covariates. The resulting model predicted observed NOx (R2=0.89) better than the DM without covariates (R2=0.68, P-interaction <0.001) and with minimal apparent bias. The model included (in descending order of importance) DM, traffic intensity on the nearest street, population (number of inhabitants) within 100 m radius, global radiation (direct sunlight plus diffuse or scattered light) and urban contribution to NOx levels (routine urban NOx, less routine rural NOx). Our results indicate that there is a potential for improving estimates of air pollutant concentrations based on DM, by incorporating further spatial characteristics of the immediate surroundings, possibly accounting for imperfections in the emission data

    Long-term air pollution exposure and Parkinson's disease mortality in a large pooled European cohort: An ELAPSE study

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    International audienceBackground: The link between exposure to ambient air pollution and mortality from cardiorespiratory diseases is well established, while evidence on neurodegenerative disorders including Parkinson's Disease (PD) remains limited. Objective: We examined the association between long-term exposure to ambient air pollution and PD mortality in seven European cohorts. Methods: Within the project ‘Effects of Low-Level Air Pollution: A Study in Europe’ (ELAPSE), we pooled data from seven cohorts among six European countries. Annual mean residential concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and ozone (O3), as well as 8 PM2.5 components (copper, iron, potassium, nickel, sulphur, silicon, vanadium, zinc), for 2010 were estimated using Europe-wide hybrid land use regression models. PD mortality was defined as underlying cause of death being either PD, secondary Parkinsonism, or dementia in PD. We applied Cox proportional hazard models to investigate the associations between air pollution and PD mortality, adjusting for potential confounders. Results: Of 271,720 cohort participants, 381 died from PD during 19.7 years of follow-up. In single-pollutant analyses, we observed positive associations between PD mortality and PM2.5 (hazard ratio per 5 µg/m3: 1.25; 95% confidence interval: 1.01–1.55), NO2 (1.13; 0.95–1.34 per 10 µg/m3), and BC (1.12; 0.94–1.34 per 0.5 × 10-5m-1), and a negative association with O3 (0.74; 0.58–0.94 per 10 µg/m3). Associations of PM2.5, NO2, and BC with PD mortality were linear without apparent lower thresholds. In two-pollutant models, associations with PM2.5 remained robust when adjusted for NO2 (1.24; 0.95–1.62) or BC (1.28; 0.96–1.71), whereas associations with NO2 or BC attenuated to null. O3 associations remained negative, but no longer statistically significant in models with PM2.5. We detected suggestive positive associations with the potassium component of PM2.5. Conclusion: Long-term exposure to PM2.5, at levels well below current EU air pollution limit values, may contribute to PD mortality

    Susceptibility to mortality related to temperature and heat and cold wave duration in the population of Stockholm County, Sweden

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    BACKGROUND: Ambient temperatures can cause an increase in mortality. A better understanding is needed of how health status and other factors modify the risk associated with high and low temperatures, to improve the basis of preventive measures. Differences in susceptibility to temperature and to heat and cold wave duration are relatively unexplored. OBJECTIVES: We studied the associations between mortality and temperature and heat and cold wave duration, stratified by age and individual and medical factors. METHODS: Deaths among all residents of Stockholm County between 1990 and 2002 were linked to discharge diagnosis data from hospital admissions, and associations were examined using the time stratified case-crossover design. Analyses were stratified by gender, age, pre-existing disease, country of origin, and municipality level wealth, and adjusted for potential confounding factors. Results : The effect on mortality by heat wave duration was higher for lower ages, in areas with lower wealth, for hospitalized patients younger than age 65. Odds were elevated among females younger than age 65, in groups with a previous hospital admission for mental disorders, and in persons with previous cardiovascular disease. Gradual increases in summer temperatures were associated with mortality in people older than 80 years, and with mortality in groups with a previous myocardial infarction and with chronic obstructive pulmonary disease (COPD) in the population younger than 65 years. During winter, mortality was associated with a decrease in temperature particularly in men and with the duration of cold spells for the population older than 80. A history of hospitalization for myocardial infarction increased the odds associated with cold temperatures among the population older than 65. Previous mental disease or substance abuse increased the odds of death among the population younger than 65. CONCLUSION: To increase effectiveness, we suggest preventive efforts should not assume susceptible groups are the same for warm and cold days and heat and cold waves, respectively

    Breast Cancer Incidence in Relation to Long-Term Low-Level Exposure to Air Pollution in the ELAPSE Pooled Cohort

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    International audienceBACKGROUND: Established risk factors for breast cancer include genetic disposition, reproductive factors, hormone therapy, and lifestyle-related factors such as alcohol consumption, physical inactivity, smoking, and obesity. More recently a role of environmental exposures, including air pollution, has also been suggested. The aim of this study, was to investigate the relationship between long-term air pollution exposure and breast cancer incidence. METHODS: We conducted a pooled analysis among six European cohorts (n = 199,719) on the association between long-term residential levels of ambient nitrogen dioxide (NO2), fine particles (PM2.5), black carbon (BC), and ozone in the warm season (O3) and breast cancer incidence in women. The selected cohorts represented the lower range of air pollutant concentrations in Europe. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level. RESULTS: During 3,592,885 person-years of follow-up, we observed a total of 9,659 incident breast cancer cases. The results of the fully adjusted linear analyses showed a HR (95% confidence interval) of 1.03 (1.00-1.06) per 10 μg/m³ NO2, 1.06 (1.01-1.11) per 5 μg/m³ PM2.5, 1.03 (0.99-1.06) per 0.5 10-5 m-1 BC, and 0.98 (0.94-1.01) per 10 μg/m³ O3. The effect estimates were most pronounced in the group of middle-aged women (50-54 years) and among never smokers. CONCLUSIONS: The results were in support of an association between especially PM2.5 and breast cancer. IMPACT: The findings of this study suggest a role of exposure to NO2, PM2.5, and BC in development of breast cancer

    Long-Term Exposure to Source-Specific Fine Particles and Mortality-A Pooled Analysis of 14 European Cohorts within the ELAPSE Project

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    International audienceWe assessed mortality risks associated with source-specific fine particles (PM2.5) in a pooled European cohort of 323,782 participants. Cox proportional hazard models were applied to estimate mortality hazard ratios (HRs) for source-specific PM2.5identified through a source apportionment analysis. Exposure to 2010 annual average concentrations of source-specific PM2.5components was assessed at baseline residential addresses. The source apportionment resulted in the identification of five sources: traffic, residual oil combustion, soil, biomass and agriculture, and industry. In single-source analysis, all identified sources were significantly positively associated with increased natural mortality risks. In multisource analysis, associations with all sources attenuated but remained statistically significant with traffic, oil, and biomass and agriculture. The highest association per interquartile increase was observed for the traffic component (HR: 1.06; 95% CI: 1.04 and 1.08 per 2.86 μg/m3increase) across five identified sources. On a 1 μg/m3basis, the residual oil-related PM2.5had the strongest association (HR: 1.13; 95% CI: 1.05 and 1.22), which was substantially higher than that for generic PM2.5mass, suggesting that past estimates using the generic PM2.5exposure response function have underestimated the potential clean air health benefits of reducing fossil-fuel combustion. Source-specific associations with cause-specific mortality were in general consistent with findings of natural mortality

    Long-term exposure to low-level air pollution and incidence of asthma: The ELAPSE project

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    International audienceBackground: 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 &lt;2.5 µm (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 μg·m−3 for PM2.5, 1.17 (95% CI 1.10-1.25) per 10 µg·m−3 for NO2 and 1.15 (95% CI 1.08-1.23) per 0.5×10−5 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. NO2 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

    Exposure to surrounding greenness and natural-cause and cause-specific mortality in the ELAPSE pooled cohort

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    International audienceBackground: The majority of studies have shown higher greenness exposure associated with reduced mortality risks, but few controlled for spatially correlated air pollution and traffic noise exposures. We aim to address this research gap in the ELAPSE pooled cohort. Methods: Mean Normalized Difference Vegetation Index (NDVI) in a 300-m grid cell and 1-km radius were assigned to participants’ baseline home addresses as a measure of surrounding greenness exposure. We used Cox proportional hazards models to estimate the association of NDVI exposure with natural-cause and cause-specific mortality, adjusting for a number of potential confounders including socioeconomic status and lifestyle factors at individual and area-levels. We further assessed the associations between greenness exposure and mortality after adjusting for fine particulate matter (PM2.5), nitrogen dioxide (NO2) and road traffic noise. Results: The pooled study population comprised 327,388 individuals who experienced 47,179 natural-cause deaths during 6,374,370 person-years of follow-up. The mean NDVI in the pooled cohort was 0.33 (SD 0.1) and 0.34 (SD 0.1) in the 300-m grid and 1-km buffer. In the main fully adjusted model, 0.1 unit increment of NDVI inside 300-m grid was associated with 5% lower risk of natural-cause mortality (Hazard Ratio (HR) 0.95 (95% CI: 0.94, 0.96)). The associations attenuated after adjustment for air pollution [HR (95% CI): 0.97 (0.96, 0.98) adjusted for PM2.5; 0.98 (0.96, 0.99) adjusted for NO2]. Additional adjustment for traffic noise hardly affected the associations. Consistent results were observed for NDVI within 1-km buffer. After adjustment for air pollution, NDVI was inversely associated with diabetes, respiratory and lung cancer mortality, yet with wider 95% confidence intervals. No association with cardiovascular mortality was found. Conclusions: We found a significant inverse association between surrounding greenness and natural-cause mortality, which remained after adjusting for spatially correlated air pollution and traffic noise
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