title: Factors associated with cesarean sections in a public hospital in Rio de Janeiro, Brazil.
abstract: 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.affiliation: Centro de Ciências da Saúde, Universidade Federal de Santa Catarina, Florianópolis, Brasil. eleonora@ccs.ufsc.br
authors.forename: Eleonora
authors.initials: E
authors.lastname: D'Orsi
authors.forename: Dora
authors.initials: D
authors.lastname: Chor
authors.forename: Karen
authors.initials: K
authors.lastname: Giffin
authors.forename: Antonia
authors.initials: A
authors.lastname: Angulo-Tuesta
authors.forename: Gisele Peixoto
authors.initials: GP
authors.lastname: Barbosa
authors.forename: Andréa de Sousa
authors.initials: Ade S
authors.lastname: Gama
authors.forename: Ana Cristina
authors.initials: AC
authors.lastname: Reis
mesh_terms: D001938:Brazil; D016022:Case-Control Studies; D002585:Cesarean Section / Q000523:psychology / Q000706:statistics & numerical data*; D005260:Female; D006771:Hospitals, Maternity / Q000706:statistics & numerical data; D006779:Hospitals, Public / Q000706:statistics & numerical data; D006801:Humans; D015999:Multivariate Analysis; D011247:Pregnancy; D012044:Regression Analysis