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Effects of air pollution on neonatal prematurity in guangzhou of china: a time-series study

BACKGROUND: Over the last decade, a few studies have investigated the possible adverse effects of ambient air pollution on preterm birth. However, the correlation between them still remains unclear, due to insufficient evidences. METHODS: The correlation between air pollution and preterm birth in Gu...

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Detalles Bibliográficos
Autores principales: Zhao, Qingguo, Liang, Zhijiang, Tao, Shijuan, Zhu, Juan, Du, Yukai
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024279/
https://www.ncbi.nlm.nih.gov/pubmed/21214958
http://dx.doi.org/10.1186/1476-069X-10-2
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author Zhao, Qingguo
Liang, Zhijiang
Tao, Shijuan
Zhu, Juan
Du, Yukai
author_facet Zhao, Qingguo
Liang, Zhijiang
Tao, Shijuan
Zhu, Juan
Du, Yukai
author_sort Zhao, Qingguo
collection PubMed
description BACKGROUND: Over the last decade, a few studies have investigated the possible adverse effects of ambient air pollution on preterm birth. However, the correlation between them still remains unclear, due to insufficient evidences. METHODS: The correlation between air pollution and preterm birth in Guangzhou city was examined by using the Generalized Additive Model (GAM) extended Poisson regression model in which we controlled the confounding factors such as meteorological factors, time trends, weather and day of the week (DOW). We also adjusted the co linearity of air pollutants by using Principal Component Analysis. The meteorological data and air pollution data were obtained from the Meteorological Bureau and the Environmental Monitoring Centre, while the medical records of newborns were collected from the perinatal health database of all obstetric institutions in Guangzhou, China in 2007. RESULTS: In 2007, the average daily concentrations of NO(2), PM(10 )and SO(2 )in Guangzhou, were 61.04, 82.51 and 51.67 μg/m(3 )respectively, where each day an average of 21.47 preterm babies were delivered. Pearson correlation analysis suggested a negative correlation between the concentrations of NO(2), PM(10), SO(2, )and temperature as well as relative humidity. As for the time-series GAM analysis, the results of single air pollutant model suggested that the cumulative effects of NO(2), PM(10 )and SO(2 )reached its peak on day 3, day 4 and day 3 respectively. An increase of 100 μg/m(3 )of air pollutants corresponded to relative risks (RRs) of 1.0542 (95%CI: 1.0080 ~1.1003), 1.0688 (95%CI: 1.0074 ~1.1301) and 1.1298 (95%CI: 1.0480 ~1.2116) respectively. After adjusting co linearity by using the Principal Component Analysis, the GAM model of the three air pollutants suggested that an increase of 100 μg/m(3 )of air pollutants corresponded to RRs of 1.0185 (95%CI: 1.0056~1.0313), 1.0215 (95%CI: 1.0066 ~1.0365) and 1.0326 (95%CI: 1.0101 ~1.0552) on day 0; and RRs of the three air pollutants, at their strongest cumulative effects, were 1.0219 (95%CI: 1.0053~1.0386), 1.0274 (95%CI: 1.0066~1.0482) and 1.0388 (95%CI: 1.0096 ~1.0681) respectively. CONCLUSIONS: This study indicates that the daily concentrations of air pollutants such as NO(2), PM(10 )and SO(2 )have a positive correlation with the preterm births in Guangzhou, China.
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spelling pubmed-30242792011-01-21 Effects of air pollution on neonatal prematurity in guangzhou of china: a time-series study Zhao, Qingguo Liang, Zhijiang Tao, Shijuan Zhu, Juan Du, Yukai Environ Health Research BACKGROUND: Over the last decade, a few studies have investigated the possible adverse effects of ambient air pollution on preterm birth. However, the correlation between them still remains unclear, due to insufficient evidences. METHODS: The correlation between air pollution and preterm birth in Guangzhou city was examined by using the Generalized Additive Model (GAM) extended Poisson regression model in which we controlled the confounding factors such as meteorological factors, time trends, weather and day of the week (DOW). We also adjusted the co linearity of air pollutants by using Principal Component Analysis. The meteorological data and air pollution data were obtained from the Meteorological Bureau and the Environmental Monitoring Centre, while the medical records of newborns were collected from the perinatal health database of all obstetric institutions in Guangzhou, China in 2007. RESULTS: In 2007, the average daily concentrations of NO(2), PM(10 )and SO(2 )in Guangzhou, were 61.04, 82.51 and 51.67 μg/m(3 )respectively, where each day an average of 21.47 preterm babies were delivered. Pearson correlation analysis suggested a negative correlation between the concentrations of NO(2), PM(10), SO(2, )and temperature as well as relative humidity. As for the time-series GAM analysis, the results of single air pollutant model suggested that the cumulative effects of NO(2), PM(10 )and SO(2 )reached its peak on day 3, day 4 and day 3 respectively. An increase of 100 μg/m(3 )of air pollutants corresponded to relative risks (RRs) of 1.0542 (95%CI: 1.0080 ~1.1003), 1.0688 (95%CI: 1.0074 ~1.1301) and 1.1298 (95%CI: 1.0480 ~1.2116) respectively. After adjusting co linearity by using the Principal Component Analysis, the GAM model of the three air pollutants suggested that an increase of 100 μg/m(3 )of air pollutants corresponded to RRs of 1.0185 (95%CI: 1.0056~1.0313), 1.0215 (95%CI: 1.0066 ~1.0365) and 1.0326 (95%CI: 1.0101 ~1.0552) on day 0; and RRs of the three air pollutants, at their strongest cumulative effects, were 1.0219 (95%CI: 1.0053~1.0386), 1.0274 (95%CI: 1.0066~1.0482) and 1.0388 (95%CI: 1.0096 ~1.0681) respectively. CONCLUSIONS: This study indicates that the daily concentrations of air pollutants such as NO(2), PM(10 )and SO(2 )have a positive correlation with the preterm births in Guangzhou, China. BioMed Central 2011-01-10 /pmc/articles/PMC3024279/ /pubmed/21214958 http://dx.doi.org/10.1186/1476-069X-10-2 Text en Copyright ©2011 Zhao et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Zhao, Qingguo
Liang, Zhijiang
Tao, Shijuan
Zhu, Juan
Du, Yukai
Effects of air pollution on neonatal prematurity in guangzhou of china: a time-series study
title Effects of air pollution on neonatal prematurity in guangzhou of china: a time-series study
title_full Effects of air pollution on neonatal prematurity in guangzhou of china: a time-series study
title_fullStr Effects of air pollution on neonatal prematurity in guangzhou of china: a time-series study
title_full_unstemmed Effects of air pollution on neonatal prematurity in guangzhou of china: a time-series study
title_short Effects of air pollution on neonatal prematurity in guangzhou of china: a time-series study
title_sort effects of air pollution on neonatal prematurity in guangzhou of china: a time-series study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024279/
https://www.ncbi.nlm.nih.gov/pubmed/21214958
http://dx.doi.org/10.1186/1476-069X-10-2
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