Associations between satellite-derived estimates of PM2.5 species concentrations for organic carbon, elemental carbon, nitrate, and sulfate with birth weight and preterm birth in California during 2005-2014.
Patrick S Reuther, Guannan Geng, Yang Liu, Lyndsey A Darrow, Matthew J Strickland
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引用次数: 0
Abstract
Background: Characterizing the spatial distribution of PM2.5 species concentrations is challenging due to the geographic sparsity of the stationary monitoring network. Recent advances have enabled valid estimation of PM2.5 species concentrations using satellite remote sensing data for use in epidemiologic studies.
Objective: In this study, we used satellite-based estimates of ambient PM2.5 species concentrations to estimate associations with birth weight and preterm birth in California.
Methods: Daily 24 h averaged ground-level PM2.5 species concentrations of organic carbon, elemental carbon, nitrate, and sulfate were estimated during 2005-2014 in California at 1 km resolution. Birth records were linked to ambient pollutant exposures based on maternal residential zip code. Linear regression and Cox regression were conducted to estimate the effect of 1 µg/m3 increases in PM2.5 species concentrations on birth weight and preterm birth.
Results: Analyses included 4.7 million live singleton births having a median 28 days with exposure measurements per pregnancy. In single pollutant models, the observed changes in mean birth weight (per 1 µg/m3 increase in speciated PM2.5 concentrations) were: organic carbon -3.12 g (CI: -4.71, -1.52), elemental carbon -14.20 g (CI: -18.76, -9.63), nitrate -5.51 g (CI: -6.79, -4.23), and sulfate 9.26 g (CI: 7.03, 11.49). Results from multipollutant models were less precise due to high correlation between pollutants. Associations with preterm birth were null, save for a negative association between sulfate and preterm birth (Hazard Ratio per 1 µg/m3 increase: 0.973 CI: 0.958, 0.987).
期刊介绍:
Journal of Exposure Science and Environmental Epidemiology (JESEE) aims to be the premier and authoritative source of information on advances in exposure science for professionals in a wide range of environmental and public health disciplines.
JESEE publishes original peer-reviewed research presenting significant advances in exposure science and exposure analysis, including development and application of the latest technologies for measuring exposures, and innovative computational approaches for translating novel data streams to characterize and predict exposures. The types of papers published in the research section of JESEE are original research articles, translation studies, and correspondence. Reported results should further understanding of the relationship between environmental exposure and human health, describe evaluated novel exposure science tools, or demonstrate potential of exposure science to enable decisions and actions that promote and protect human health.