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...
Main Authors: | , , , , |
---|---|
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 |