Literature DB >> 28738475

[Trend of caesarean section rate and puerpera characteristics: based on Robson classification].

J X Wang1, H Q Sun2, K Huang3, X F Zheng4, F B Tao3.   

Abstract

Objective: To analyze the trend in caesarean section rate and puerpera characteristics in hospital, and provide valuable information for maternal and child health policy making and clinical practice.
Methods: A total of 12 041 women who delivered in the affiliated Chaohu Hospital of Anhui Medical University from October 1, 2010 to September 30, 2016 were selected. Based on Robson classification system, changes in the rate of caesarean delivery as well as its relationship with two-child policy and infant sex ratio were analyzed.
Results: The overall caesarean section rate gradually decreased from 66.9% to 44.2% during the past six years. Respectively, the caesarean section rate in primiparae with singleton term babies decreased to 32.1% and the rate in multiparas without uterine scar decreased to 14.2%, and the rate in premature delivery decreased to 22.9%, the differences were significant (P<0.01). The proportion of vaginal delivery (R1, R3), multiparas with uterine scar (R5) and twins pregnancy (R8) increased. the differences were significant (P<0.01). The annual overall newly-born sex ratio ranged from 110∶100 to 128∶100. In group R1, more babies were girls, the proportion was stable, more women with premature delivery and multiparas had boy babies, but the boy babies by multiparas without uterine scar obviously decreased in the last 2 years. Conclusions: Primiparae with singleton head birth, multipara without uterine scar and women with premature deliveries are the key population in the effort of reduction of caesarean section rate. The caesarean section rate and proportion were unstable in multiparas with uterine scar, breech deliveries and twin deliveries. The application of Robson classification system can improve the comparability of the surveillance data.

Entities:  

Keywords:  Caesarean section; Maternal characteristics; Robson classification

Mesh:

Year:  2017        PMID: 28738475     DOI: 10.3760/cma.j.issn.0254-6450.2017.07.023

Source DB:  PubMed          Journal:  Zhonghua Liu Xing Bing Xue Za Zhi        ISSN: 0254-6450


  2 in total

1.  Trend Prediction for Cesarean Deliveries Based on Robson Classification System at a Tertiary Referral Unit of North India.

Authors:  Pratima Mittal; Divya Pandey; Jyotsna Suri; Rekha Bharti
Journal:  J Obstet Gynaecol India       Date:  2019-10-11

2.  Incidence and trend of preterm birth in China, 1990-2016: a systematic review and meta-analysis.

Authors:  Shiwen Jing; Chang Chen; Yuexin Gan; Joshua Vogel; Jun Zhang
Journal:  BMJ Open       Date:  2020-12-12       Impact factor: 2.692

  2 in total

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