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).
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Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Notes
Crosswalk tables to match non-geographically bound zip codes to a ZCTA, such as the Uniform Data System Mapper (https://udsmapper.org/zip-code-to-zcta-crosswalk/), are available; however, we could not guarantee the mother would physically reside in the matched ZCTA, so we elected to not match the non-geographically bound zip codes to a ZCTA.
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Funding
Sources of financial support: NIH grants R01ES028346 and R01ES029528, and support from the MAIA science team at JPL, California Institute of Technology (Subcontract #1588347).
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PR analyzed the data and was the primary manuscript author. GG and YL provided access to satellite data and modeled the ground-level pollution estimates. LD and MS were both major contributors to the final manuscript. All authors read and approved the final manuscript.
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The authors declare no competing interests.
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This research was performed in accordance with the approval given by the following ethics committees: California Committee for the Protection of Human Subjects IRB# 2019-027 and the University of Nevada, Reno IRB# 1164285-13.
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Reuther, P.S., Geng, G., Liu, Y. et al. 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. J Expo Sci Environ Epidemiol (2024). https://doi.org/10.1038/s41370-024-00673-y
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DOI: https://doi.org/10.1038/s41370-024-00673-y