Document Detail


Factors associated with cesarean sections in a public hospital in Rio de Janeiro, Brazil.
MedLine Citation:
PMID:  16951878     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Brazil has one of the world's highest cesarean section rates. Contributing factors include the organization of obstetric practice, physicians' attitudes, and women's preferences and decisions. This study aimed to identify factors associated with cesarean sections in a public maternity hospital in Rio de Janeiro. A case-control study was conducted with 231 cesarean sections (cases) and 230 vaginal deliveries (controls). Hierarchical logistic regression analysis was performed, based on a conceptual model. Factors associated with increased odds of cesarean section were: primiparity; mother's age 20-34; last birth by cesarean; cervical dilatation < 3cm at admission; patient request; daytime birth; male attending obstetrician; obstetrician on duty for more than 24 hours a week; obstetrician with private practice; gestational hypertension; non-cephalic presentation; and gestational age > 41 weeks. Factors associated with lower odds of cesarean were: gestational age < 37 weeks; leaving home with signs of labor, use of oxytocin; and amniotomy. In this hospital, interventions aimed to modify the above-mentioned factors can help lower the cesarean rate.
Authors:
Eleonora D'Orsi; Dora Chor; Karen Giffin; Antonia Angulo-Tuesta; Gisele Peixoto Barbosa; Andréa de Sousa Gama; Ana Cristina Reis
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Cadernos de saúde pública     Volume:  22     ISSN:  0102-311X     ISO Abbreviation:  Cad Saude Publica     Publication Date:  2006 Oct 
Date Detail:
Created Date:  2006-09-04     Completed Date:  2007-05-03     Revised Date:  2013-03-18    
Medline Journal Info:
Nlm Unique ID:  8901573     Medline TA:  Cad Saude Publica     Country:  Brazil    
Other Details:
Languages:  eng     Pagination:  2067-78     Citation Subset:  IM    
Affiliation:
Centro de Ciências da Saúde, Universidade Federal de Santa Catarina, Florianópolis, Brasil. eleonora@ccs.ufsc.br
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MeSH Terms
Descriptor/Qualifier:
Brazil
Case-Control Studies
Cesarean Section / psychology,  statistics & numerical data*
Female
Hospitals, Maternity / statistics & numerical data
Hospitals, Public / statistics & numerical data
Humans
Multivariate Analysis
Pregnancy
Regression Analysis

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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