Effect of PM2.5 pollution on perinatal mortality in China

Abstract Using ArcGIS to analyze satellite derived PM2.5 estimates, this paper obtains the average concentration and maximum concentration of fine particulate matter (PM2.5) in China's 31 provinces from 2002 to 2015. We adopt fixed effects model and spatial Durbin model to investigate the assoc...

Full description

Bibliographic Details
Main Authors: Guangqin Li, Lingyu Li, Dan Liu, Jiahong Qin, Hongjun Zhu
Format: Article
Language:English
Published: Nature Publishing Group 2021-04-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-87218-7
id doaj-d69918fcf7e14c66a1e4e2d31e8ee0ff
record_format Article
spelling doaj-d69918fcf7e14c66a1e4e2d31e8ee0ff2021-04-11T11:32:42ZengNature Publishing GroupScientific Reports2045-23222021-04-0111111210.1038/s41598-021-87218-7Effect of PM2.5 pollution on perinatal mortality in ChinaGuangqin Li0Lingyu Li1Dan Liu2Jiahong Qin3Hongjun Zhu4College of International Trade and Economics, Anhui University of Finance and EconomicsInstitute of Finance and Economics Research, Shanghai University of Finance and EconomicsCentre for Health Economics Research and Evaluation, University of Technology SydneyInstitute of Finance and Economics Research, Shanghai University of Finance and EconomicsSchool of Physical Education and Sports Science, South China Normal UniversityAbstract Using ArcGIS to analyze satellite derived PM2.5 estimates, this paper obtains the average concentration and maximum concentration of fine particulate matter (PM2.5) in China's 31 provinces from 2002 to 2015. We adopt fixed effects model and spatial Durbin model to investigate the association between PM2.5 and perinatal mortality rates. The results indicate that PM2.5 has a significantly positive association with perinatal mortality rates. A 1% increase of log-transformed average concentration and maximum concentrations of PM2.5 is associated with 1.76‰ and 2.31‰ increase of perinatal mortality rates, respectively. In spatial econometrics analysis, we find PM2.5 has significant spatial autocorrelation characteristics. The concentrations of log-transformed average and maximum PM2.5 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.https://doi.org/10.1038/s41598-021-87218-7
collection DOAJ
language English
format Article
sources DOAJ
author Guangqin Li
Lingyu Li
Dan Liu
Jiahong Qin
Hongjun Zhu
spellingShingle Guangqin Li
Lingyu Li
Dan Liu
Jiahong Qin
Hongjun Zhu
Effect of PM2.5 pollution on perinatal mortality in China
Scientific Reports
author_facet Guangqin Li
Lingyu Li
Dan Liu
Jiahong Qin
Hongjun Zhu
author_sort Guangqin Li
title Effect of PM2.5 pollution on perinatal mortality in China
title_short Effect of PM2.5 pollution on perinatal mortality in China
title_full Effect of PM2.5 pollution on perinatal mortality in China
title_fullStr Effect of PM2.5 pollution on perinatal mortality in China
title_full_unstemmed Effect of PM2.5 pollution on perinatal mortality in China
title_sort effect of pm2.5 pollution on perinatal mortality in china
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-04-01
description Abstract Using ArcGIS to analyze satellite derived PM2.5 estimates, this paper obtains the average concentration and maximum concentration of fine particulate matter (PM2.5) in China's 31 provinces from 2002 to 2015. We adopt fixed effects model and spatial Durbin model to investigate the association between PM2.5 and perinatal mortality rates. The results indicate that PM2.5 has a significantly positive association with perinatal mortality rates. A 1% increase of log-transformed average concentration and maximum concentrations of PM2.5 is associated with 1.76‰ and 2.31‰ increase of perinatal mortality rates, respectively. In spatial econometrics analysis, we find PM2.5 has significant spatial autocorrelation characteristics. The concentrations of log-transformed average and maximum PM2.5 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.
url https://doi.org/10.1038/s41598-021-87218-7
work_keys_str_mv AT guangqinli effectofpm25pollutiononperinatalmortalityinchina
AT lingyuli effectofpm25pollutiononperinatalmortalityinchina
AT danliu effectofpm25pollutiononperinatalmortalityinchina
AT jiahongqin effectofpm25pollutiononperinatalmortalityinchina
AT hongjunzhu effectofpm25pollutiononperinatalmortalityinchina
_version_ 1721530960525131776