PREVALENCE AND DETERMINANTS OF CESAREAN SECTION BASED ON ROBSON’S TEN-GROUP CLASSIFICATION: A CROSS-SECTIONAL STUDY
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Keywords
Cesarean section; Robson classification; prevalence; determinants; tertiary care hospital; India
Abstract
Background: Cesarean section (CS) rates have been increasing globally, raising concerns regarding overuse and associated maternal and neonatal risks. The Robson Ten-Group Classification System (TGCS) provides a standardized method to assess and compare CS rates across settings and identify contributing groups.
Objectives: To determine the prevalence of cesarean section and its determinants using the Robson classification in a tertiary care hospital in Bihar.
Methods: A hospital-based cross-sectional analytical study was conducted from January 2021 to December 2021 among 245 women admitted for delivery. Participants were classified into Robson’s ten groups based on obstetric characteristics. Data were collected using a pre-designed proforma and analyzed using SPSS version 25. Descriptive statistics were used to calculate prevalence, while associations between variables and mode of delivery were assessed using Chi-square test. A p-value <0.05 was considered statistically significant.
Results: The overall cesarean section rate was 42.9%. The largest proportion of women belonged to Robson Group 1 (25.3%), followed by Group 2 (20.4%) and Group 3 (19.6%). Group 5 (previous cesarean section) had the highest CS rate (87.8%) and was the major contributor to overall CS rates. Groups 2 and 1 also contributed substantially. Significant determinants of cesarean section included previous cesarean section (p<0.001), onset of labor (p<0.001), maternal age (p=0.042), parity (p=0.031), and fetal presentation (p=0.018).
Conclusion: Cesarean section rates were high in the study setting, with repeat cesarean sections being the predominant contributor. Targeted strategies focusing on reducing primary cesarean deliveries, promoting appropriate labor management, and utilizing Robson classification for regular audit are essential to optimize CS rates and improve obstetric care.
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Dr Aishwarya Lakshmi Sinha
Associate Professor, Department of Obstetrics and Gynaecology, M G M Medical College, Kishanganj, Bihar, India.
Dr Kumari Ruchika
Assistant Professor, Department of Obstetrics and Gynaecology, I-care Institute of Medical Sciences, Haldia, West Bengal, India.
Dr Richa Kumari
Assistant Professor, Department of Obstetrics and Gynaecology, M G M Medical College, Kishanganj, Bihar, India
