Literature DB >> 29902628

Effect of the 2008 cold spell on preterm births in two subtropical cities of Guangdong Province, Southern China.

Zhijiang Liang1, Peng Wang2, Qingguo Zhao3, Bei-Qi Wang2, Yuanzhu Ma4, Hualiang Lin5, Jianpeng Xiao6, Ji-Yuan Zhou7.   

Abstract

BACKGROUND: A few studies have reported that low temperatures were associated with an increased risk of preterm birth. However, the effect of extreme weather events, such as cold spell, on preterm birth has not been studied in China.
OBJECTIVE: This study was conducted to evaluate the impact of the 2008 cold spell on preterm birth in two subtropical cities of Guangdong Province.
METHODS: Data of daily preterm birth, air pollution and meteorological variables from 2006 to 2010 were collected in Dongguan and Shenzhen. A Poisson regression with a distributed lag nonlinear model was used to investigate the association between the 2008 cold spell and daily rate of preterm birth for each city.
RESULTS: During the 2008 cold spell, total vaginal preterm births were increased by 22.44% and 21.25% in Dongguan and Shenzhen, respectively. The effect of the cold spell on preterm births lasted for more than 1 week, the lag0-6 days cumulative relative risk (RR) is 1.32 (95% CI: 1.10-1.58) and 1.40 (95% CI: 1.18-1.68) in Dongguan and Shenzhen, respectively. The effects were found to be more pronounced for the pregnant women with 34-36 gestation weeks, maternal age < 35 years group.
CONCLUSION: This study demonstrates that cold spell could increase the risk of preterm births in Dongguan and Shenzhen, and the effect lasts for more than 1 week. Specific measures should be considered to protect the pregnant women, especially the vulnerable subgroups.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cold spell; Distributed lag nonlinear model; Preterm birth; Time-series study

Mesh:

Year:  2018        PMID: 29902628     DOI: 10.1016/j.scitotenv.2018.06.026

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  6 in total

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