The caesarean section (C-section) is an essential obstetric intervention that has saved countless maternal and neonatal lives since its widespread adoption. Over the last few decades, however, the rate of caesarean deliveries has risen steadily across many regions of the world. While caesarean delivery can be lifesaving when medically indicated, excessive use carries well-documented risks for mothers and babies, increases healthcare costs and can signal gaps in obstetric care, decision-making, or access to evidence-based labor management [1]. Understanding whether high C-section rates reflect appropriate clinical need or potentially avoidable practice variability is therefore a priority for clinicians, hospital managers and policy makers alike. To meet this need for clear, comparable assessment, Robson’s Ten-Group Classification System has become widely accepted as a simple, robust method for categorizing deliveries and analysing caesarean rates. First proposed to standardize reporting by grouping women into ten mutually exclusive, totally inclusive categories based on parity, previous uterine scar, onset of labour, fetal presentation, plurality and gestational age, the Robson system enables apples-to-apples comparison between hospitals and regions and highlights which subgroups contribute most to overall C-section volumes [2,3]. This classification is not intended as a direct tool for clinical decision-making; rather, it is an audit and monitoring framework that helps identify where practice reviews, training or policy changes might reduce unnecessary interventions while protecting maternal and neonatal safety [3,4]. The World Health Organization and numerous international obstetric groups have recommended routine reporting of caesarean rates using the Robson classification precisely because it clarifies whether increases in overall rates are driven by particular clinical subgroups (for example, nulliparous term cephalic women induced for non-reassuring indications, or women with one or more previous caesarean scars) or are distributed more evenly across obstetric populations [5,6]. Importantly, trends in Robson group contributions can guide targeted interventions: for example, strategies to safely reduce primary caesareans in low-risk nulliparous women, improved labour management for induced labours, or enhanced vaginal birth after cesarean (VBAC) counselling and pathways where appropriate [7,8]. In the Indian context, rising caesarean rates have been reported across both public and private sectors, with the private sector frequently recording higher proportions than public facilities. Socioeconomic factors, changing reproductive patterns (including higher maternal age and previous caesarean prevalence), provider incentives, and patient preferences all interact to influence the local caesarean rate [9,10]. Because actionable improvement depends on local evidence, facility-level audits using a standard classification are crucial: they reveal hospital-specific drivers and allow quality improvement teams to focus efforts where they will have the greatest impact. Despite national and international attention, substantial heterogeneity persists between institutions and regions in how childbirth is managed and when caesarean delivery is chosen. Multi-country analyses using Robson’s classification have shown large variation both in the size of specific Robson groups and in the caesarean rates within groups, underlining the need for contextually appropriate audits rather than one-size-fits-all targets [6,11]. Local analyses are particularly important in tertiary referral centres and mixed public-private settings where case-mix, referral patterns and resource availability differ from community or low-resource hospitals. This study was therefore designed to provide a comprehensive, facility-level assessment of caesarean practice using Robson’s Ten-Group Classification at Kasturba Hospital and the district hospital in Tumakuru, Karnataka between September 2022 and November 2024. The primary objectives were to estimate the overall caesarean section rate, to quantify the contribution of each Robson group to the total number of caesarean deliveries, and to identify specific subgroups that may benefit from targeted monitoring, audit and quality improvement. Generating this evidence at the facility level allows clinical teams to prioritize interventions that are feasible within local practice patterns and resources. There are several reasons why such a local Robson analysis is timely and useful. First, when a facility’s overall caesarean rate substantially exceeds the WHO-recommended range, understanding which Robson groups account for the excess is the first step toward meaningful response [5]. Second, local analyses can reveal unexpected patterns — for example, a disproportionate rate of caesareans among induced nulliparas, or a rising contribution from women with previous caesareans — each of which points to different remedial actions, such as revising induction protocols, strengthening labour support, or developing VBAC pathways and counselling [7,12]. Third, presenting results in a standard format enables benchmarking against regional and national data and facilitates collaborative learning between institutions. In addition to its audit value, the Robson framework supports safer, evidence-based obstetric care by surfacing opportunities to reduce unnecessary primary caesareans. For instance, midwifery-led continuity models, targeted clinician education in labour management, and adherence to standardized indication criteria have all been associated with lower caesarean rates within specific Robson groups in different settings [13,14]. However, any strategy to reduce caesareans must be balanced with vigilance for neonatal and maternal outcomes; the goal is optimization rather than simple numeric reduction. The present prospective observational study draws on consecutive deliveries admitted to the labour wards during the study period and uses standardized data collection to assign each delivery to a Robson group and to record mode of delivery and immediate neonatal outcomes. By reporting both the size of each Robson group and the caesarean rate within groups, this analysis provides the granular detail needed to plan focused quality improvement initiatives at the study sites. The results are intended to inform local clinical governance, to serve as a baseline for future interventions, and to contribute to the wider literature on facility-level drivers of caesarean delivery in similar Indian settings. In the sections that follow we describe the study methods, present Robson group-specific caesarean contributions and related perinatal outcomes, and discuss implications for clinical practice and policy. Where particular groups are identified as major contributors to the overall caesarean rate, we consider evidence-based strategies that are feasible within the local context to safely reduce unnecessary caesareans and improve maternal-neonatal care.

Methods Study setting: The study was conducted in the Kasturba Hospital, SS Puram road, Tumakuru, Karnataka, 572102 & District hospital, Tumakuru, Karnataka. Study design: This study was a Prospective observational study. Study population: All parturient women getting admitted to the labour room for confinement under the Kasturba Hospital, SS Puram road & District hospital Tumakuru, Karnataka, 572102, were considered as the study population. Sampling method: All eligible subjects were recruited into the study consecutively by convenient sampling till the sample size was reached. Data collection tool: A structured questionnaire was used as a data collection tool. Study period: The study was conducted between September 2022 to November 2024. Sample size: The following formula was used for sample size calculation n=Z2⋅P(1−P)d2n = \dfrac{Z^{2} \cdot P (1 - P)}{d^{2}}n=d2Z2⋅P(1−P) Where n = Sample size Z = Z statistic for a level of confidence = 1.96 P = Expected prevalence of proportion (If the expected prevalence is 20%, then P = 0.005) d = Precision (If the precision is 5%, then d = 0.003). As per the above calculation, the required sample size was 2124 women. To account for a loss of follow-up of about 5%, another 106 women were added to the sample. Hence, the final required sample was 2230. Inclusion criteria: Women undergoing Caesarean section/ normal vaginal delivery/ Operative vaginal delivery as the mode of delivery. Exclusion criteria: Women with maternal and neonatal adverse outcome that occurs after discharge from the hospital. Participants who did not give consent were excluded. Ethical considerations: The study was approved by the Institutional Ethics Committee. Informed written consent was obtained from all the study participants, and only those participants willing to sign the informed consent were included in the study. Confidentiality of the study participants was maintained. Statistical analysis: Descriptive analysis was carried out by frequency and proportion for categorical variables. Continuous variables were presented as mean ± SD. The chi-square/Fisher Exact test was used to test the statistical significance of cross-tabulation between categorical variables. P value < 0.05 was considered statistically significant. RStudio Desktop Version 2023.03.0+386 was used for statistical analysis. (Reference: RStudio Team (2023). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/.)

A total of 2,230 women admitted for delivery between September 2022 and November 2024 were included in the analysis. Maternal and pregnancy characteristics: Table 1 summarises baseline maternal and pregnancy characteristics for the cohort. The mean (±SD) maternal age was 29.23 ± 4.01 years and the mean (±SD) gestational age was 37.91 ± 2.08 weeks. Two measures of neonatal weight recorded at birth had means (±SD) of 2.88 ± 0.55 kg and 1.93 ± 0.48 kg, respectively. Table 1. Maternal and pregnancy characteristics (N = 2230) Variable Value Maternal age (years), mean ± SD 29.23 ± 4.01 Gestational age (weeks), mean ± SD 37.91 ± 2.08 Baby weight 1 (kg), mean ± SD 2.88 ± 0.55 Baby weight 2 (kg), mean ± SD 1.93 ± 0.48 ROBSON CLASSIFICATION Table 2 presents the distribution of deliveries according to the Robson ten group classification. Groups 1, 2a and 10 were among the largest contributors. Table 2. Robson classification distribution (N = 2230) Robson group n % 1 560 25.1 2a 464 20.8 2b 91 4.1 3 314 14.1 4a 61 2.7 4b 20 0.9 5 301 13.5 6 39 1.7 7 17 0.8 8 58 2.6 9 11 0.5 10 294 13.2 MODE OF DELIVERY: Overall mode-of-delivery frequencies are presented in Table 3. Vaginal delivery accounted for 48.5% of births while emergency and elective lower-segment caesarean sections (LSCS) accounted for 37.6% and 13.9%, respectively. Table 3. Mode of delivery (N = 2230) Mode of delivery n % Emergency LSCS 838 37.6 Elective LSCS 310 13.9 Vaginal delivery 1082 48.5 PROCEDURES WITHIN DELIVERY CATEGORIES: Table 4 details procedures performed within each delivery category (sterilisation, myomectomy, subtypes of vaginal delivery, etc.). These subtype counts are reported as counts and percentages within each delivery category. Table 4. Detailed breakdown of modes and procedures within delivery categories Delivery category Subcategory n % (of category) Emergency LSCS (n = 838) Emergency LSCS 749 89.4 Emergency LSCS with sterilization 86 10.3 Emergency LSCS with myomectomy 2 0.2 Laparotomy hysterectomy 1 0.1 Elective LSCS (n = 310) Elective LSCS 180 58.1 Elective LSCS with sterilization 129 41.6 Elective LSCS with myomectomy 1 0.3 Vaginal delivery (n = 1082) Normal with episiotomy 647 59.8 Instrumental with episiotomy 417 38.5 Normal with perineal tear degree 1 9 0.8 Normal with perineal tear degree 2 4 0.4 Normal with intact perineum 4 0.4 Assisted breech with episiotomy 1 0.1 NEONATAL OUTCOMES Neonatal condition and immediate outcomes are summarised in Table 5. Among 2,282 neonates assessed, 88.5% were recorded as in good condition and 11.5% required NICU admission. There were 2 deaths recorded (1 intrauterine death and 1 stillbirth) and the remaining neonates were live births (n = 2,280). Table 5. Neonatal condition by mode of delivery (N = 2282) Neonatal condition Emergency LSCS (n = 838) Elective LSCS (n = 310) Vaginal delivery (n = 1082) Good 694 (82.8%) 286 (92.3%) 1010 (93.3%) NICU 144 (17.2%) 24 (7.7%) 72 (6.7%) P value < 0.001 MODE OF DELIVERY BY ROBSON GROUP: Table 6 displays mode-of-delivery patterns stratified by Robson group. This subgroup analysis highlights the variation in caesarean and vaginal delivery rates across clinically defined groups. Table 6. Mode of delivery according to Robson category (values are n and % within each Robson group) Robson group (n) Emergency LSCS, n (%) Elective LSCS, n (%) Vaginal delivery, n (%) 1 (560) 159 (28.4) 1 (0.2) 400 (71.4) 2a (464) 241 (51.9) 0 (0.0) 223 (48.1) 2b (91) 32 (35.2) 59 (64.8) 0 (0.0) 3 (314) 21 (6.7) 1 (0.3) 292 (93.0) 4a (61) 10 (16.4) 0 (0.0) 51 (83.6) 4b (20) 10 (50.0) 10 (50.0) 0 (0.0) 5 (301) 116 (38.5) 170 (56.5) 15 (5.0) 6 (39) 23 (59.0) 16 (41.0) 0 (0.0) 7 (17) 12 (70.6) 5 (29.4) 0 (0.0) 8 (58) 42 (72.4) 12 (20.7) 4 (6.9) 9 (11) 10 (90.9) 1 (9.1) 0 (0.0) 10 (294) 162 (55.1) 35 (11.9) 97 (33.0)

In this prospective observational study of 2,230 deliveries conducted between September 2022 and November 2024 at Kasturba Hospital and the District Hospital, Tumakuru, the overall caesarean section (CS) rate was 51.5%, considerably higher than the WHO-recommended rate of 10–15% [22]. Robson groups 1, 2a, 3, and 5 were the largest contributors to the overall CS rate. Almost half of the women (48.5%) delivered vaginally, and 62.2% were nulliparous. The majority were term pregnancies (mean gestational age 37.91 ± 2.08 weeks) with a mean maternal age of 29.23 ± 4.01 years, consistent with reproductive-age norms in comparable Indian cohorts [23]. The high overall CS rate in the present study aligns with findings from Akadri et al. [24], who reported a 51.2% CS rate in a private tertiary setting, but is higher than the 28% reported by Anshu Baser et al. [25] and other public-sector facilities. Such variability reflects contextual factors including maternal preference, provider practice, institutional policy, and case-mix characteristics [26]. Identifying specific Robson groups that disproportionately contribute to CS rates allows institutions to tailor audit and intervention efforts to their own clinical populations [27]. In this study, Groups 1 and 2a (nulliparous, term, cephalic, spontaneous or induced labour) and Group 5 (previous CS, term, singleton, cephalic) together accounted for a significant proportion of the total caesarean deliveries. These findings are consistent with prior reports where these groups contribute most to the CS burden [28]. The relatively high contribution of Groups 1 and 2a highlights the importance of strengthening labour management, particularly through appropriate induction protocols, continuous labour support, and use of partograph monitoring. Group 5’s contribution underscores the growing challenge of repeat caesarean sections and limited acceptance of vaginal birth after caesarean (VBAC) in many facilities [29]. Comparison with other regional and global data demonstrates heterogeneity in the distribution of CS among Robson groups. Bismeen et al. [30] found Groups 5, 6, and 10 as predominant contributors, differing from the present results where Groups 1, 2a, and 3 were more prominent. This variation reaffirms that Robson classification serves best as a local audit framework, guiding hospital-specific quality improvement rather than global benchmarking [31]. Analysis of neonatal outcomes revealed significant variation by delivery mode. Vaginal births were associated with the highest rate of neonates in good condition (93.3%), while emergency LSCS had the highest NICU admission rate (17.2%). The difference was statistically significant (p < 0.001). These results suggest that while emergency caesareans are often performed for fetal distress, they carry increased risk of neonatal compromise, emphasising the need for early identification and timely intervention in labour [32]. Several factors have contributed to the rising CS trend across India, including delayed childbearing, patient preferences, medicolegal pressures, and limited VBAC acceptance [33]. The higher rates observed in private hospitals compared to public facilities have been reported in multiple national analyses [34]. As shown in international studies, interventions such as adherence to evidence-based induction protocols, midwifery-led continuity of care, and strict audit of CS indications can safely reduce CS rates without compromising outcomes [35,36]. Although this study provides robust local evidence, certain limitations should be noted. It was a single-centre observational study based on convenience sampling, which may limit generalisability. Longitudinal, multicentre studies would provide stronger evidence regarding changing patterns and causative factors. Additionally, outcomes beyond the immediate postpartum period were not evaluated, and further research into long-term maternal and neonatal effects of delivery mode is warranted.

This prospective facility-based study found a caesarean section rate of 51.5%, exceeding WHO recommendations. Robson Groups 1, 2a, 3, and 5 were the major contributors to the CS burden. These findings highlight a need for targeted audit and intervention efforts focusing on these high-contribution groups, particularly to reduce unnecessary primary CSs and to promote safe VBAC where feasible. Continuous clinical monitoring, provider education, and patient counselling are essential to ensure rational use of CS without compromising perinatal outcomes. Future multicentre studies with larger sample sizes are recommended to validate these findings and to establish region-specific strategies for optimising delivery practices.

1. Sung S, Mahdy H. Cesarean Section. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2023. Available from: http://www.ncbi.nlm.nih.gov/books/NBK546707/ 2. Parveen R, Khakwani M, Naz A, Bhatti R. Analysis of Cesarean Sections using Robson’s Ten Group Classification System. Pak J Med Sci. 2021;37(2):567–71. 3. Betrán AP, Vindevoghel N, Souza JP, Gülmezoglu AM, Torloni MR. A Systematic Review of the Robson Classification for Caesarean Section: What Works, Doesn’t Work and How to Improve It. PLoS ONE. 2014 Jun 3;9(6):e97769. 4. Kazmi T, Saiseema S, Khan S. Analysis of Cesarean Section Rate - According to Robson’s 10-group Classification. Oman Med J. 2012 Sep;27(5):415–7. 5. WHO. Appropriate technology for birth. Lancet. 2015. (WHO guidance document). 6. Vogel JP, Betrán AP, Vindevoghel N, Souza JP, Torloni MR, Zhang J, et al. Use of the Robson classification to assess caesarean section trends in 21 countries: a secondary analysis of two WHO multicountry surveys. Lancet Glob Health. 2015 May;3(5):e260–70. 7. Tontus HO, Nebioglu S. Improving the Caesarean Decision by Robson Classification: A Population-Based Study. Ann Glob Health. 2018;86(1):101. 8. Negrini R, D’Albuquerque IMSC, de Cássia Sanchez e Oliveira R, Ferreira RD da S, De Stefani LFB, Podgaec S. Strategies to reduce the caesarean section rate in a private hospital and their impact. BMJ Open Qual. 2021 Aug 12;10(3):e001215. 9. Bhatia M, Banerjee K, Dixit P, Dwivedi LK. Assessment of Variation in Cesarean Delivery Rates Between Public and Private Health Facilities in India From 2005 to 2016. JAMA Netw Open. 2020 Aug 3;3(8):e2015022. 10. WHO. Appropriate technology for birth. WHO Reproductive Health Library; 2015. 11. Abubeker FA, Gashawbeza B, Gebre TM, et al. Analysis of cesarean section rates using Robson ten group classification system in a tertiary teaching hospital, Addis Ababa, Ethiopia: a cross-sectional study. BMC Pregnancy Childbirth. 2020;20(1):767. 12. Hanahoe M. Midwifery-led care can lower caesarean section rates according to the Robson ten group classification system. Eur J Midwifery. 2020 Mar 31;4:7. 13. Akadri AA, Imaralu JO, Salami OF, Nwankpa CC, Adepoju AA. Robson classification of caesarean births: implications for reducing caesarean section rate in a private tertiary hospital in Nigeria. BMC Pregnancy Childbirth. 2023 Apr 12;23(1):243. 14. Vogel JP, Betrán AP, Vindevoghel N, Souza JP, Torloni MR, Zhang J, et al. Use of the Robson classification to assess caesarean section trends in 21 countries: a secondary analysis of two WHO multicountry surveys. Lancet Glob Health. 2015 May 1;3(5):e260–70. 15. Hanahoe M. Midwifery-led care can lower caesarean section rates according to the Robson ten group classification system. Eur J Midwifery. 2020 Mar 31;4:7. 16. Negrini R, D’Albuquerque IMSC, de Cássia Sanchez e Oliveira R, Ferreira RD da S, De Stefani LFB, Podgaec S. Strategies to reduce the caesarean section rate in a private hospital and their impact. BMJ Open Qual. 2021 Aug 12;10(3):e001215. 17. Moresi EHC, Moreira PP, Ferrer IL, Baptistella MKCS, Bolognani CV. Robson Classification for cesarean section in a Public Hospital in Distrito Federal. Rev Bras Saúde Materno Infant. 2023 Jan 27;22:1035–42. 18. Singh P, Hashmi G, Swain PK. High prevalence of cesarean section births in private sector health facilities—analysis of district level household survey-4 (DLHS-4) of India. BMC Public Health. 2018 May 10;18(1):613. 19. Bhartia A, Sen Gupta Dhar R, Bhartia S. Reducing caesarean section rate in an urban hospital serving women attending privately in India – a quality improvement initiative. BMC Pregnancy Childbirth. 2020 Sep 23;20(1):556. 20. Sengupta A, Sabastin Sagayam M, Reja T. Increasing trend of C-section deliveries in India: A comparative analysis between southern states and rest of India. Sex Reprod Healthc Off J Swed Assoc Midwives. 2021 Jun;28:100608. 21. RStudio Team. RStudio: Integrated Development for R. RStudio, PBC, Boston, MA; 2023. Available from: http://www.rstudio.com/ 22. World Health Organization. Appropriate technology for birth. WHO Reproductive Health Library; 2015. 23. Vogel JP, Betrán AP, Vindevoghel N, Souza JP, Torloni MR, Zhang J, et al. Use of the Robson classification to assess caesarean section trends in 21 countries: a secondary analysis of two WHO multicountry surveys. Lancet Glob Health. 2015;3(5):e260–70. 24. Akadri AA, Imaralu JO, Salami OF, Nwankpa CC, Adepoju AA. Robson classification of caesarean births: implications for reducing caesarean section rate in a private tertiary hospital in Nigeria. BMC Pregnancy Childbirth. 2023;23(1):243. 25. Baser A, Bisht S, Kalra S. Robson’s Ten Group Classification: an analysis of caesarean section rates in a tertiary care hospital. Int J Reprod Contracept Obstet Gynecol. 2021;10(4):1530–5. 26. Bhatia M, Banerjee K, Dixit P, Dwivedi LK. Assessment of variation in cesarean delivery rates between public and private health facilities in India. JAMA Netw Open. 2020;3(8):e2015022. 27. Betrán AP, Vindevoghel N, Souza JP, Gülmezoglu AM, Torloni MR. A systematic review of the Robson classification for caesarean section: what works, doesn’t work and how to improve it. PLoS ONE. 2014;9(6):e97769. 28. Moresi EHC, Moreira PP, Ferrer IL, Baptistella MKCS, Bolognani CV. Robson classification for cesarean section in a public hospital in Distrito Federal. Rev Bras Saúde Materno Infant. 2023;22:1035–42. 29. Negrini R, D’Albuquerque IMSC, de Cássia Sanchez e Oliveira R, Ferreira RD da S, De Stefani LFB, Podgaec S. Strategies to reduce the caesarean section rate in a private hospital and their impact. BMJ Open Qual. 2021;10(3):e001215. 30. Bismeen S, Sultana N, Gupta M. Audit of caesarean deliveries using Robson’s classification. J Clin Diagn Res. 2019;13(12):QC01–4. 31. Tontus HO, Nebioglu S. Improving the caesarean decision by Robson classification: a population-based study. Ann Glob Health. 2018;86(1):101. 32. Sengupta A, Sagayam MS, Reja T. Increasing trend of C-section deliveries in India: a comparative analysis. Sex Reprod Healthc. 2021;28:100608. 33. Hanahoe M. Midwifery-led care can lower caesarean section rates according to the Robson ten group classification system. Eur J Midwifery. 2020;4:7. 34. Bhartia A, Sen Gupta Dhar R, Bhartia S. Reducing caesarean section rate in an urban hospital serving women attending privately in India – a quality improvement initiative. BMC Pregnancy Childbirth. 2020;20(1):556. 35. Negrini R, D’Albuquerque IMSC, de Cássia Sanchez e Oliveira R, Ferreira RD da S, De Stefani LFB, Podgaec S. BMJ Open Qual. 2021;10(3):e001215. 36. WHO. WHO statement on caesarean section rates. Geneva: World Health Organization; 2015.