Influencing factors of preterm birth: a prospective cohort study

SHI Ying-jie; ZHAN Yong-le; CHEN Yun-li; JIANG Yu; MA Liang-kun

doi:10.16462/j.cnki.zhjbkz.2021.02.005

Volume 25 Issue 2

Feb. 2021

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Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2021 > 25(2): 143-148

SHI Ying-jie, ZHAN Yong-le, CHEN Yun-li, JIANG Yu, MA Liang-kun. Influencing factors of preterm birth: a prospective cohort study[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(2): 143-148. doi: 10.16462/j.cnki.zhjbkz.2021.02.005

Citation:

SHI Ying-jie, ZHAN Yong-le, CHEN Yun-li, JIANG Yu, MA Liang-kun. Influencing factors of preterm birth: a prospective cohort study[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(2): 143-148. doi: 10.16462/j.cnki.zhjbkz.2021.02.005

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Influencing factors of preterm birth: a prospective cohort study

doi: 10.16462/j.cnki.zhjbkz.2021.02.005

1.
Department of Epidemiology and Biostatistics, School of Population Medicine and Public health, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China
2.
Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China

Funds:

CAMS Innovation Fund for Medical Sciences 2019-I2M-2-007

More Information

Corresponding author: JIANG Yu, E-mail:jiangyu@pumc.edu.cn; MA Liang-kun, E-mail:maliangkun@pumch.cn
Received Date: 2020-09-01
Rev Recd Date: 2020-11-15
Publish Date: 2021-02-10

Abstract

Abstract

Objective To analyze the prevalence and risk factors of preterm birth in China and to provide reference for the prevention of preterm birth. Methods Data was from the Chinese Pregnant Women Cohort study (CPWCS). The basic information and delivery outcomes of pregnant women were collected through questionnaire surveys and hospital information system. The chi-square test and multivariate logistic regression analysis were conducted by SPSS 26.0 software. Results The prevalence of preterm birth among 5 671 pregnant women was 5.2%, and there was no significant difference in the prevalence of preterm birth among different regions (χ² =0.591, P=0.771). The results of multivariate logistic regression analysis showed that advanced age, history of diabetes, history of premature birth, placental abruption, premature rupture of membranes, fetal distress, hypertension during pregnancy, and twins were risk factors for preterm birth (all P < 0.05), while among pregnant women who give birth naturally, advanced age (OR=2.90, 95% CI: 1.67-5.06, P < 0.001), premature rupture of membranes (OR=6.17, 95% CI: 4.21-9.06, P < 0.001), and twins (OR=17.72, 95% CI: 3.23-97.25, P < 0.001) were risk factors for preterm birth. Conclusions There are many influencing factors of preterm birth. Accurately identifying risk factors and providing pregnant women with scientific and reasonable health education and individualized prevention and control measures are important means to prevent preterm birth.
- Pregnant women,
- Preterm birth,
- Risk factors,
- Cohort study

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References(23)

References

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