Cesarean sections and early-term births according to Robson classification: a population-based study with more than 17 million births in Brazil.


Journal

BMC pregnancy and childbirth
ISSN: 1471-2393
Titre abrégé: BMC Pregnancy Childbirth
Pays: England
ID NLM: 100967799

Informations de publication

Date de publication:
03 Aug 2023
Historique:
received: 28 09 2022
accepted: 22 06 2023
medline: 7 8 2023
pubmed: 4 8 2023
entrez: 3 8 2023
Statut: epublish

Résumé

Cesarean section (CS) rates are increasing worldwide and are associated with negative maternal and child health outcomes when performed without medical indication. However, there is still limited knowledge about the association between high CS rates and early-term births. This study explored the association between CSs and early-term births according to the Robson classification. A population-based, cross-sectional study was performed with routine registration data of live births in Brazil between 2012 and 2019. We used the Robson classification system to compare groups with expected high and low CS rates. We used propensity scores to compare CSs to vaginal deliveries (1:1) and estimated associations with early-term births using logistic regression. A total of 17,081,685 live births were included. Births via CS had higher odds of early-term birth (OR 1.32; 95% CI 1.32-1.32) compared to vaginal deliveries. Births by CS to women in Group 2 (OR 1.50; 95% CI 1.49-1.51) and 4 (OR 1.57; 95% CI 1.56-1.58) showed the highest odds of early-term birth, compared to vaginal deliveries. Increased odds of an early-term birth were also observed among births by CS to women in Group 3 (OR 1.30, 95% CI 1.29-1.31), compared to vaginal deliveries. In addition, live births by CS to women with a previous CS (Group 5 - OR 1.36, 95% CI 1.35-1.37), a single breech pregnancy (Group 6 - OR 1.16; 95% CI 1.11-1.21, and Group 7 - OR 1.19; 95% CI 1.16-1.23), and multiple pregnancies (Group 8 - OR 1.46; 95% CI 1.40-1.52) had high odds of an early-term birth, compared to live births by vaginal delivery. CSs were associated with increased odds of early-term births. The highest odds of early-term birth were observed among those births by CS in Robson Groups 2 and 4.

Sections du résumé

BACKGROUND BACKGROUND
Cesarean section (CS) rates are increasing worldwide and are associated with negative maternal and child health outcomes when performed without medical indication. However, there is still limited knowledge about the association between high CS rates and early-term births. This study explored the association between CSs and early-term births according to the Robson classification.
METHODS METHODS
A population-based, cross-sectional study was performed with routine registration data of live births in Brazil between 2012 and 2019. We used the Robson classification system to compare groups with expected high and low CS rates. We used propensity scores to compare CSs to vaginal deliveries (1:1) and estimated associations with early-term births using logistic regression.
RESULTS RESULTS
A total of 17,081,685 live births were included. Births via CS had higher odds of early-term birth (OR 1.32; 95% CI 1.32-1.32) compared to vaginal deliveries. Births by CS to women in Group 2 (OR 1.50; 95% CI 1.49-1.51) and 4 (OR 1.57; 95% CI 1.56-1.58) showed the highest odds of early-term birth, compared to vaginal deliveries. Increased odds of an early-term birth were also observed among births by CS to women in Group 3 (OR 1.30, 95% CI 1.29-1.31), compared to vaginal deliveries. In addition, live births by CS to women with a previous CS (Group 5 - OR 1.36, 95% CI 1.35-1.37), a single breech pregnancy (Group 6 - OR 1.16; 95% CI 1.11-1.21, and Group 7 - OR 1.19; 95% CI 1.16-1.23), and multiple pregnancies (Group 8 - OR 1.46; 95% CI 1.40-1.52) had high odds of an early-term birth, compared to live births by vaginal delivery.
CONCLUSIONS CONCLUSIONS
CSs were associated with increased odds of early-term births. The highest odds of early-term birth were observed among those births by CS in Robson Groups 2 and 4.

Identifiants

pubmed: 37537549
doi: 10.1186/s12884-023-05807-y
pii: 10.1186/s12884-023-05807-y
pmc: PMC10399022
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

562

Subventions

Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 213589/Z/18/Z
Pays : United Kingdom

Informations de copyright

© 2023. BioMed Central Ltd., part of Springer Nature.

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Auteurs

Aline S Rocha (AS)

School of Nutrition, Federal University of Bahia (UFBA), Araújo Pinho - No. 32, Canela, Salvador, Bahia, Brazil. linny_rochaa@hotmail.com.
Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil. linny_rochaa@hotmail.com.

Enny S Paixao (ES)

Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.
Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.

Flavia Jôse O Alves (FJO)

Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.
Institute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.

Ila R Falcão (IR)

School of Nutrition, Federal University of Bahia (UFBA), Araújo Pinho - No. 32, Canela, Salvador, Bahia, Brazil.
Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.

Natanael J Silva (NJ)

Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.
Barcelona Institute for Global Health, Hospital Clínic, Barcelona, Spain.

Camila S S Teixeira (CSS)

Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.
Institute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.

Naiá Ortelan (N)

Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.

Rosemeire L Fiaccone (RL)

Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.
Department of Statistics, Federal University of Bahia (UFBA), Salvador, Brazil.

Laura C Rodrigues (LC)

Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.
Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.

Maria Yury Ichihara (MY)

Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.

Mauricio L Barreto (ML)

Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.
Institute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.

Marcia F de Almeida (MF)

School of Public Health, University of São Paulo (USP), São Paulo, Brazil.

Rita de Cássia Ribeiro-Silva (R)

School of Nutrition, Federal University of Bahia (UFBA), Araújo Pinho - No. 32, Canela, Salvador, Bahia, Brazil.
Center for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.
Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.

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