Dataset Information

High resolution annual average air pollution concentration maps for the Netherlands.

ABSTRACT: Long-term exposure to air pollution is considered a major public health concern and has been related to overall mortality and various diseases such as respiratory and cardiovascular disease. Due to the spatial variability of air pollution concentrations, assessment of individual exposure to air pollution requires spatial datasets at high resolution. Combining detailed air pollution maps with personal mobility and activity patterns allows for an improved exposure assessment. We present high-resolution datasets for the Netherlands providing average ambient air pollution concentration values for the year 2009 for NO2, NOx, PM2.5, PM2.5absorbance and PM10. The raster datasets on 5×5 m grid cover the entire Netherlands and were calculated using the land use regression models originating from the European Study of Cohorts for Air Pollution Effects (ESCAPE) project. Additional datasets with nationwide and regional measurements were used to evaluate the generated concentration maps. The presented datasets allow for spatial aggregations on different scales, nationwide individual exposure assessment, and the integration of activity patterns in the exposure estimation of individuals.

SUBMITTER: Schmitz O

PROVIDER: S-EPMC6413687 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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High resolution annual average air pollution concentration maps for the Netherlands.

Schmitz Oliver O Beelen Rob R Strak Maciej M Hoek Gerard G Soenario Ivan I Brunekreef Bert B Vaartjes Ilonca I Dijst Martin J MJ Grobbee Diederick E DE Karssenberg Derek D

Scientific data 20190312

Long-term exposure to air pollution is considered a major public health concern and has been related to overall mortality and various diseases such as respiratory and cardiovascular disease. Due to the spatial variability of air pollution concentrations, assessment of individual exposure to air pollution requires spatial datasets at high resolution. Combining detailed air pollution maps with personal mobility and activity patterns allows for an improved exposure assessment. We present high-resol ...[more]

PMID: 30860500

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Project description:STUDY QUESTION:Does ambient air pollution affect fecundability? SUMMARY ANSWER:While cycle-average air pollution exposure was not associated with fecundability, we observed some associations for acute exposure around ovulation and implantation with fecundability. WHAT IS KNOWN ALREADY:Ambient air pollution exposure has been associated with adverse pregnancy outcomes and decrements in semen quality. STUDY DESIGN, SIZE, DURATION:The LIFE study (2005-2009), a prospective time-to-pregnancy study, enrolled 501 couples who were followed for up to one year of attempting pregnancy. PARTICIPANTS/MATERIALS, SETTING, METHODS:Average air pollutant exposure was assessed for the menstrual cycle before and during the proliferative phase of each observed cycle (n = 500 couples; n = 2360 cycles) and daily acute exposure was assessed for sensitive windows of each observed cycle (n = 440 couples; n = 1897 cycles). Discrete-time survival analysis modeled the association between fecundability and an interquartile range increase in each pollutant, adjusting for co-pollutants, site, age, race/ethnicity, parity, body mass index, smoking, income and education. MAIN RESULTS AND THE ROLE OF CHANCE:Cycle-average air pollutant exposure was not associated with fecundability. In acute models, fecundability was diminished with exposure to ozone the day before ovulation and nitrogen oxides 8 days post ovulation (fecundability odds ratio [FOR] 0.83, 95% confidence interval [CI]: 0.72, 0.96 and FOR 0.84, 95% CI: 0.71, 0.99, respectively). However, particulate matter ≤10 microns 6 days post ovulation was associated with greater fecundability (FOR 1.25, 95% CI: 1.01, 1.54). LIMITATIONS, REASONS FOR CAUTION:Although our study was unlikely to be biased due to confounding, misclassification of air pollution exposure and the moderate study size may have limited our ability to detect an association between ambient air pollution and fecundability. WIDER IMPLICATIONS OF THE FINDINGS:While no associations were observed for cycle-average ambient air pollution exposure, consistent with past research in the United States, exposure during critical windows of hormonal variability was associated with prospectively measured couple fecundability, warranting further investigation. STUDY FUNDING/COMPETING INTEREST(S):This work was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (Longitudinal Investigation of Fertility and the Environment study contract nos. #N01-HD-3-3355, NO1-HD-#-3356, N01-HD-3-3358 and the Air Quality and Reproductive Health Study Contract No. HHSN275200800002I, Task Order No. HHSN27500008). We declare no conflict of interest.

Project description:BackgroundSubstantial research has investigated the adverse effects of traffic-related air pollutants (TRAP) on human health. Convincing associations between TRAP and respiratory and cardiovascular diseases are known, but the underlying biological mechanisms are not well established. High-resolution metabolomics (HRM) is a promising platform for untargeted characterization of molecular mechanisms between TRAP and health indexes.ObjectivesWe examined metabolic perturbations associated with short-term exposures to TRAP, including carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), fine particulate matter (PM2.5), organic carbon (OC), and elemental carbon (EC) among 180 participants of the Center for Health Discovery and Well-Being (CHDWB), a cohort of Emory University-affiliated employees.MethodsA cross-sectional study was conducted on baseline visits of 180 CHDWB participants enrolled during 2008-2012, in whom HRM profiling was determined in plasma samples using liquid chromatography-high-resolution mass spectrometry with positive and negative electrospray ionization (ESI) modes. Ambient pollution concentrations were measured at an ambient monitor near downtown Atlanta. Metabolic perturbations associated with TRAP exposures were assessed following an untargeted metabolome-wide association study (MWAS) framework using feature-specific Tobit regression models, followed by enriched pathway analysis and chemical annotation.ResultsSubjects were predominantly white (76.1%) and non-smokers (95.6%), and all had at least a high school education. In total, 7821 and 4123 metabolic features were extracted from the plasma samples by the negative and positive ESI runs, respectively. There are 3421 features significantly associated with at least one air pollutant by negative ion mode, and 1691 features by positive ion mode. Biological pathways enriched by features associated with the pollutants are primarily involved in nucleic acids damage/repair (e.g., pyrimidine metabolism), nutrient metabolism (e.g., fatty acid metabolism), and acute inflammation (e.g., histidine metabolism and tyrosine metabolism). NO2 and EC were associated most consistently with these pathways. We confirmed the chemical identity of 8 metabolic features in negative ESI and 2 features in positive ESI, including metabolites closely linked to oxidative stress and inflammation, such as histamine, tyrosine, tryptophan, and proline.ConclusionsWe identified a range of ambient pollutants, including components of TRAP, associated with differences in the metabolic phenotype among the cohort of 180 subjects. We found Tobit models to be a robust approach to handle missing data among the metabolic features. The results were encouraging of further use of HRM and MWAS approaches for characterizing molecular mechanisms underlying exposure to TRAP.

Project description:BackgroundHigh-resolution metabolomics (HRM) is emerging as a sensitive tool for measuring environmental exposures and biological responses. The aim of this analysis is to assess the ability of high-resolution metabolomics (HRM) to reflect internal exposures to complex traffic-related air pollution mixtures.MethodsWe used untargeted HRM profiling to characterize plasma and saliva collected from participants in the Dorm Room Inhalation to Vehicle Emission (DRIVE) study to identify metabolic pathways associated with traffic emission exposures. We measured a suite of traffic-related pollutants at multiple ambient and indoor sites at varying distances from a major highway artery for 12 weeks in 2014. In parallel, 54 students living in dormitories near (20 m) or far (1.4 km) from the highway contributed plasma and saliva samples. Untargeted HRM profiling was completed for both plasma and saliva samples; metabolite and metabolic pathway alternations were evaluated using a metabolome-wide association study (MWAS) framework with pathway analyses.ResultsWeekly levels of traffic pollutants were significantly higher at the near dorm when compared to the far dorm (p < 0.05 for all pollutants). In total, 20,766 metabolic features were extracted from plasma samples and 29,013 from saliva samples. 45% of features were detected and shared in both plasma and saliva samples. 1291 unique metabolic features were significantly associated with at least one or more traffic indicator, including black carbon, carbon monoxide, nitrogen oxides and fine particulate matter (p < 0.05 for all significant features), after controlling for confounding and false discovery rate. Pathway analysis of metabolic features associated with traffic exposure indicated elicitation of inflammatory and oxidative stress related pathways, including leukotriene and vitamin E metabolism. We confirmed the chemical identities of 10 metabolites associated with traffic pollutants, including arginine, histidine, γ‑linolenic acid, and hypoxanthine.ConclusionsUsing HRM, we identified and verified biological perturbations associated with primary traffic pollutant in panel-based setting with repeated measurement. Observed response was consistent with endogenous metabolic signaling related to oxidative stress, inflammation, and nucleic acid damage and repair. Collectively, the current findings provide support for the use of untargeted HRM in the development of metabolic biomarkers of traffic pollution exposure and response.

Dataset Information

High resolution annual average air pollution concentration maps for the Netherlands.

Publications

High resolution annual average air pollution concentration maps for the Netherlands.

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