Effect of PM2.5 pollution on perinatal mortality in China

Li, G; Li, L; Liu, D; Qin, J; Zhu, H

Effect of PM2.5 pollution on perinatal mortality in China

Li, G Li, L Liu, D

Qin, J Zhu, H

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Publisher:: NATURE RESEARCH
Publication Type:: Journal Article
Citation:: Scientific Reports, 2021, 11, (1), pp. 7596
Issue Date:: 2021-04-07

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Field	Value	Language
dc.contributor.author	Li, G
dc.contributor.author	Li, L
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1891-9352
dc.contributor.author	Qin, J
dc.contributor.author	Zhu, H
dc.date.accessioned	2021-09-21T02:25:01Z
dc.date.available	2021-03-23
dc.date.available	2021-09-21T02:25:01Z
dc.date.issued	2021-04-07
dc.identifier.citation	Scientific Reports, 2021, 11, (1), pp. 7596
dc.identifier.issn	2045-2322
dc.identifier.issn	2045-2322
dc.identifier.uri	http://hdl.handle.net/10453/150646
dc.description.abstract	Using ArcGIS to analyze satellite derived PM<sub>2.5</sub> estimates, this paper obtains the average concentration and maximum concentration of fine particulate matter (PM<sub>2.5</sub>) in China's 31 provinces from 2002 to 2015. We adopt fixed effects model and spatial Durbin model to investigate the association between PM<sub>2.5</sub> and perinatal mortality rates. The results indicate that PM<sub>2.5</sub> has a significantly positive association with perinatal mortality rates. A 1% increase of log-transformed average concentration and maximum concentrations of PM<sub>2.5</sub> is associated with 1.76‰ and 2.31‰ increase of perinatal mortality rates, respectively. In spatial econometrics analysis, we find PM<sub>2.5</sub> has significant spatial autocorrelation characteristics. The concentrations of log-transformed average and maximum PM<sub>2.5</sub> increase 1% is associated with a 2.49% increase in a 2.49‰ and 2.19‰ increase of perinatal mortality rates, respectively. The potential mechanism is that air pollution has an impact on infant weight to impact perinatal mortality rates.
dc.format	Electronic
dc.language	eng
dc.publisher	NATURE RESEARCH
dc.relation.ispartof	Scientific Reports
dc.relation.isbasedon	10.1038/s41598-021-87218-7
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Effect of PM2.5 pollution on perinatal mortality in China
dc.type	Journal Article
utslib.citation.volume	11
utslib.location.activity	England
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Strength - CHERE - Centre for Health Economics Research and Evaluation
utslib.copyright.status	open_access	*
dc.date.updated	2021-09-21T02:24:57Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	11
utslib.citation.issue	1

Abstract:

Using ArcGIS to analyze satellite derived PM_2.5 estimates, this paper obtains the average concentration and maximum concentration of fine particulate matter (PM_2.5) in China's 31 provinces from 2002 to 2015. We adopt fixed effects model and spatial Durbin model to investigate the association between PM_2.5 and perinatal mortality rates. The results indicate that PM_2.5 has a significantly positive association with perinatal mortality rates. A 1% increase of log-transformed average concentration and maximum concentrations of PM_2.5 is associated with 1.76‰ and 2.31‰ increase of perinatal mortality rates, respectively. In spatial econometrics analysis, we find PM_2.5 has significant spatial autocorrelation characteristics. The concentrations of log-transformed average and maximum PM_2.5 increase 1% is associated with a 2.49% increase in a 2.49‰ and 2.19‰ increase of perinatal mortality rates, respectively. The potential mechanism is that air pollution has an impact on infant weight to impact perinatal mortality rates.

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http://hdl.handle.net/10453/150646