Population Exposure to Ambient PM2.5 at the Subdistrict Level in China.
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ABSTRACT:
SUBMITTER: Long Y
PROVIDER: S-EPMC6313548 | biostudies-literature | 2018 Nov
REPOSITORIES: biostudies-literature
Publications
Population Exposure to Ambient PM<sub>2.5</sub> at the Subdistrict Level in China.
Long Ying Y Wang Jianghao J Wu Kang K Zhang Junjie J
International journal of environmental research and public health 20181128 12
Fine-particulate pollution is a major public health concern in China. Accurate assessment of the population exposed to PM<sub>2.5</sub> requires high-resolution pollution and population information. This paper assesses China's potential population exposure to PM<sub>2.5</sub>, maps its spatiotemporal variability, and simulates the effects of the recent air pollution control policy. We relate satellite-based Aerosol Optical Depth (AOD) retrievals to ground-based PM<sub>2.5</sub> observations. We ...[more]
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Project description:BackgroundThe metabolomic signatures of short- and long-term exposure to PM2.5 have been reported and linked to inflammation and oxidative stress. However, little is known about the relative contribution of the specific PM2.5 species (hence sources) that drive these metabolomic signatures.ObjectivesWe aimed to determine the relative contribution of the different species of PM2.5 exposure to the perturbed metabolic pathways related to changes in the plasma metabolome.MethodsWe performed mass-spectrometry based metabolomic profiling of plasma samples among men from the Normative Aging Study to identify metabolic pathways associated with PM2.5 species. The exposure windows included short-term (one, seven-, and thirty-day moving average) and long-term (one year moving average). We used linear mixed-effect regression with subject-specific intercepts while simultaneously adjusting for PM2.5, NO2, O3, temperature, relative humidity, and covariates and correcting for multiple testing. We also used independent component analysis (ICA) to examine the relative contribution of patterns of PM2.5 species.ResultsBetween 2000 and 2016, 456 men provided 648 blood samples, in which 1158 metabolites were quantified. We chose 305 metabolites for the short-term and 288 metabolites for the long-term exposure in this analysis that were significantly associated (p-value < 0.01) with PM2.5 to include in our PM2.5 species analysis. On average, men were 75.0 years old and their body mass index was 27.7 kg/m2. Only 3% were current smokers. In the adjusted models, ultrafine particles (UFPs) were the most significant species of short-term PM2.5 exposure followed by nickel, vanadium, potassium, silicon, and aluminum. Black carbon, vanadium, zinc, nickel, iron, copper, and selenium were the significant species of long-term PM2.5 exposure. We identified several metabolic pathways perturbed with PM2.5 species including glycerophospholipid, sphingolipid, and glutathione. These pathways are involved in inflammation, oxidative stress, immunity, and nucleic acid damage and repair. Results were overlapped with the ICA.ConclusionsWe identified several significant perturbed plasma metabolites and metabolic pathways associated with exposure to PM2.5 species. These species are associated with traffic, fuel oil, and wood smoke. This is the largest study to report a metabolomic signature of PM2.5 species' exposure and the first to use ICA.
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