Lancet子刊:权威数据揭示2012-2018年我国早产率变化
创作:Epi汪 审核:Epi汪 2021年08月27日
  • 利用我国NMNMSS系统中2012-2018年的数据,包括964万余名女性孕产数据,其中6.1%是早产;
  • 总体早产率从2012年的5.9%上升到2018年的6.4%,其中晚期早产(34-36周)和极早产(28-31周)的率增加明显;
  • 与2012年分娩的女性相比,2018年的女性表现出年龄更大、有更多的产前检查次数、产前并发症和内科疾病患病率更高和更低的剖宫产率;
  • 二孩政策生效后,早产率的增幅有所增高。
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Epi汪
中国国家妇幼健康监测办公室和四川大学合作团队在《The Lancet Global Health》上发表重磅研究,全面揭示我国2012-2018年孕妇早产发生率情况。随着三胎政策的落地和实行,未来早产等不良妊娠结局问题可能需要更多的关注,并采取切实可行的措施降低孕产妇不良妊娠结局风险。
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Preterm births in China between 2012 and 2018: an observational study of more than 9 million women

2012-2018年中国早产:一项对900多万名妇女的观察性研究

10.1016/S2214-109X(21)00298-9

2021-09-01, Article

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Background : Preterm birth rates have increased significantly worldwide over the past decade. Few epidemiological studies on the incidence of preterm birth and temporal trends are available in China. This study used national monitoring data from China’s National Maternal Near Miss Surveillance System (NMNMSS) to estimate the rate of preterm birth and trends between 2012 and 2018 in China and to assess risk factors associated with preterm birth.
Methods: In this observational study, data were sourced from the NMNMSS between Jan 1, 2012, and Dec 31, 2018. Pregnancies with at least one livebirth, with the baby born at 28 weeks of gestation or more or 1000 g or more birthweight were included. We estimated the rates of overall preterm, very preterm (born between 28 and 31 weeks’ gestation), moderate preterm (born between 32 and 33 weeks’ gestation), and late preterm (born between 34 and 36 weeks’ gestation) births in singleton and multiple pregnancies and assessed their trends over time. We used logistic regression analysis to examine the associations between preterm birth and sociodemographic characteristics and obstetric complications, considering the sampling strategy and clustering of births within hospitals. Interrupted time series analysis was used to assess the changes in preterm birth rates during the period of the universal two child policy intervention.
Findings: From Jan 1, 2012, to Dec 31, 2018, 9 645646 women gave birth to at least one live baby, of whom 665 244 (6·1%) were born preterm. In all pregnancies, the overall preterm birth rate increased from 5·9% in 2012 to 6·4% in 2018 (8·8% increase; annual rate of increase [ARI] 1·3 [95% CI 0·6 to 2·1]). Late preterm births (8·8%; ARI 1·5% [0·9 to 2·2]) and very preterm births (13·3%; ARI 1·8% [0·5 to 3·0]) significantly increased from 2012 to 2018, whereas moderate preterm births did not (3·8%; ARI 0·3% [95% CI –0·9 to 1·5]). In singleton pregnancies, the overall preterm birth rate showed a small but significant 6·4% increase (ARI 1·0% [0·4 to 1·7]) over the 7 year period. In multiple pregnancies, the overall preterm birth rate significantly increased from 46·8% in 2012 to 52·7% in 2018 (12·4% increase; ARI 1·9% [1·2 to 2·6]). Compared with women who gave birth in 2012, those who gave birth in 2018 were more likely to be older (aged ≥35 years; 7·4% in 2012 vs 15·9% in 2018), have multiples (1·6% vs 1·9%), have seven or more antenatal visits (50·2% vs 70·7%), and have antepartum complications and medical disease (17·9% vs 35·1%), but they were less likely to deliver via caesarean section (47·5% vs 45·0%). Compared with the baseline period (January, 2012 to June, 2016), a higher increase in preterm birth was observed after the universal two child policy came into effect in July, 2016 (β=0·034; p=0·03).
Interpretation: An increase in preterm births was noted for both singleton and multiple pregnancies between 2012 and 2018 in China. China’s strategic investment in maternal and neonatal health has been crucial for the prevention of preterm birth. Due to rapid changes in sociodemographic and obstetric factors related to preterm birth—particularly within the context of the universal two child policy—such as advanced maternal age at delivery, maternal complications, and multiple pregnancies, greater efforts to reduce the burden of preterm birth are urgently needed.

First Authors:
Kui Deng,Juan Liang

Correspondence Authors:
Jun Zhu,Hanmin Liu

All Authors:
Kui Deng,Juan Liang,Yi Mu,Zheng Liu,Yanping Wang,Mingrong Li,Xiaohong Li,Li Dai,Qi Li,Peiran Chen,Yanxia Xie,Jun Zhu,Hanmin Liu

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