Skip to main content
Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

A Systematic Review of the Robson Classification for Caesarean Section: What Works, Doesn't Work and How to Improve It

  • Ana Pilar Betrán ,

    Affiliation UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction, Department of Reproductive Health and Research, World Health Organization, Geneva, Switzerland

  • Nadia Vindevoghel,

    Affiliation Maternal Child Clinic, Calgary, Canada

  • Joao Paulo Souza,

    Affiliation Department of Social Medicine, Ribeirao Preto Medical School, University of São Paulo, Ribeirao Preto, SP, Brazil

  • A. Metin Gülmezoglu,

    Affiliation UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction, Department of Reproductive Health and Research, World Health Organization, Geneva, Switzerland

  • Maria Regina Torloni

    Affiliation Brazilian Cochrane Centre, São Paulo, Brazil, and Department of Internal Medicine, São Paulo Federal University, São Paulo, Brazil



Caesarean sections (CS) rates continue to increase worldwide without a clear understanding of the main drivers and consequences. The lack of a standardized internationally-accepted classification system to monitor and compare CS rates is one of the barriers to a better understanding of this trend. The Robson's 10-group classification is based on simple obstetrical parameters (parity, previous CS, gestational age, onset of labour, fetal presentation and number of fetuses) and does not involve the indication for CS. This classification has become very popular over the last years in many countries. We conducted a systematic review to synthesize the experience of users on the implementation of this classification and proposed adaptations.


Four electronic databases were searched. A three-step thematic synthesis approach and a qualitative metasummary method were used.


232 unique reports were identified, 97 were selected for full-text evaluation and 73 were included. These publications reported on the use of Robson's classification in over 33 million women from 31 countries. According to users, the main strengths of the classification are its simplicity, robustness, reliability and flexibility. However, missing data, misclassification of women and lack of definition or consensus on core variables of the classification are challenges. To improve the classification for local use and to decrease heterogeneity within groups, several subdivisions in each of the 10 groups have been proposed. Group 5 (women with previous CS) received the largest number of suggestions.


The use of the Robson classification is increasing rapidly and spontaneously worldwide. Despite some limitations, this classification is easy to implement and interpret. Several suggested modifications could be useful to help facilities and countries as they work towards its implementation.


In 1985, The World Health Organization (WHO) stated: “There is no justification for any region to have a caesarean section (CS) rate higher than 10–15%” [1]. Despite the lack of scientific evidence indicating any substantial maternal and perinatal benefits from increasing CS rates, and some studies showing that higher rates could be linked to negative consequences in maternal and child health [2][4], CS rates continue to increase worldwide, particularly in middle- and high-income countries, and have become a major and controversial public health concern [5], [6].

The lack of a standardized internationally-accepted classification system to monitor and compare CS rates in a consistent and action-oriented manner is one of the factors preventing a better understanding of this trend and underlying causes [7]. In 2011, a systematic review and critical appraisal of available classifications for CS concluded that women-based classifications in general, and Robson's 10-group classification in particular, would be in the best position to fulfill current international and local needs [8]. The review recommended that efforts to develop an internationally applicable classification should be most appropriately placed in building upon this classification. Robson proposes a system that classifies women into 10 groups based on their obstetric characteristics (parity, previous CS, gestational age, onset of labour, fetal presentation and number of fetuses) without needing the indication for CS [7]. Table 1 shows the definitions of each group. Since this system can be applied prospectively, and its categories are totally inclusive and mutually exclusive, every woman who is admitted for delivery can be immediately classified based on these few basic characteristics which are usually routinely collected by obstetric care providers worldwide. If used on a continuous basis, some studies suggest that this classification system can provide critical assessment of care at delivery and be used to change practice [7], [9].

Table 1. Obstetric characteristics of women included in each of the 10 groups of the classification; subdivisions proposed by the authors of the 73 included studies, and the number of studies proposing each subdivision by group of Robson.

Since 2001, when the Robson classification (also called the 10-group classification) was proposed, many facilities and countries have incorporated it in their routine clinical practice as a tool to monitor CS rates in their population and to evaluate the impact of changes in management that may alter these rates [10][14]. However, to the best of our knowledge, there is no systematic synthesis and assessment of the experiences, opinions and challenges encountered by users in their facility or country. This information could help units as they work towards the implementation of the classification to plan the necessary steps on more realistic grounds, to be aware of the most challenging issues, and to address critical potential pitfalls in their setting.

Against this background, we set out to conduct a systematic review of the literature to gather the experience of users related to the pros and cons of the adoption, implementation and interpretation of the Robson classification, as well as their adaptations, modifications or recommendations on the use of this classification.


This systematic review was conducted following a protocol specifically designed for this purpose and reported according to the recommendations of the PRISMA statement [15] and the Meta-analysis Of Observational Studies in Epidemiology group (MOOSE) [16].

Type of study designs

Any study that described the experience of using the Robson classification was eligible for inclusion regardless of the objective and design of the study or the context or setting (e.g. nationwide, facility-based) in which it was applied.

Type of participants

Any study presenting the use of the Robson classification in any group of women was eligible for inclusion regardless of the women's obstetric or medical characteristics, level of risk, education or socio-economic status.

Type of implementation of the Robson classification

We included studies presenting the use of the Robson classification involving any number of patients, for any period of time, for any reason (e.g. audit and feedback, monitor trends, document effectiveness of interventions), to assess any outcome (e.g. rates of CS, maternal or perinatal indicators, patient satisfaction, costs). Studies that used variations of the Robson classification (e.g. analyzing only Robson groups 1 and 2 instead of the 10 groups, or splitting or lumping groups) were eligible for inclusion as long as they described the changes in sufficient detail to be replicable.

Exclusion criteria

We excluded studies that were strictly theoretical or described opinions that were not based on actual experiences of the authors related to the use of the classification or if the definitions used to categorize women in the groups were dubious or unclear. There were no language or country restrictions in this review.

Search strategy for the identification of studies

The search strategy was developed with the assistance of a librarian experienced in electronic search strategies for systematic reviews, from the Brazilian Cochrane Center. Four electronic databases were searched: Medline, Embase, CINAHL and LILACS from January 2000 to 18 January 2013 (see complete search strategy in File S1).

The references of all articles selected for full-text evaluation were also checked for additional potentially relevant studies not identified through the electronic search. Authors were contacted through e-mail for additional data, when necessary. Dr Michael Robson, creator of the classification was contacted to inquire about unpublished material from units that had implemented the classification.

Screening, data extraction template

All citations identified from the electronic searches were downloaded into Reference Manager software version 11 and duplicates were deleted. Two investigator (APB, MRT) independently screened the title and abstract to select potentially relevant citations for full-text reading. All selected articles were independently read by two reviewers (APB, MRT) and those fulfilling the aforementioned selection criteria were included in the review. Disagreements in the process of screening and selection of articles were discussed until consensus was reached. In cases of studies with more than one publication, the latest and/or more complete version was used. Data extraction was performed by two reviewers (APB, MRT; independently and in duplicate) using a standardized data-extraction template specially designed for this review. The information was extracted and discussed until full agreement. A final extraction form was filed for each study.

Information captured for each article included: 1) objectives of the study; 2) country, year, setting, type of institution, time period when the classification was used, number of women/deliveries included, completeness, source of data and average CS rate; 3) observations, comments or criticisms to the overall classification or to any of the 10 groups, adaptations or suggestions proposed to improve the classification, facilitators and barriers identified for its use and implementation; and 4) definitions of the variables used in the construction of the groups of the classification.

Data extraction and synthesis

A thematic synthesis approach [17] and a qualitative metasummary method [18] were used. We also followed the principles of the Cochrane Qualitative Research Methods Group [19]. In brief, we followed three steps to systematically extract and synthesize the views from the authors in the original articles: (a) line-by-line coding to extract the key concepts, usually presented in the Results, Discussion or Methods section; (b) organization of these key concepts to construct “descriptive” themes/topics that formed the skeleton of the structure of the analysis; and (c) development of analytical themes based on the synthesis of the experiences and recommendations of authors of the original articles. This process was performed manually, i.e. without the use of a specific software. The detailed description is depicted in File S2. Three investigators (APB, MRT, NV) coded the concepts, developed the descriptive themes and then the analytical themes, with regular discussions and meetings until reaching full agreement. To assess the relative magnitude of each abstracted concepts, we calculated their frequency effect size [18]. For each concept, the effect size was calculated by dividing the number of reports containing the concept (minus any report derived from the same study and therefore representing a duplicate) by the total number of reports (minus any report derived from the same study and therefore representing a duplicate). In our review, there were no duplicate reports.


The electronic search strategy yielded 273 citations that were reduced to 209 after removing 64 duplicates. An additional 23 records were identified through other sources. After screening titles and abstracts, 97 citations were selected for full-text assessment and 73 were included in this review (see flowchart in Fig 1).

Table 2 presents the main characteristics of the 73 included studies, which report on the use of the Robson classification in over 33 million women. Two thirds of the included studies were published in 2010 or after and presented data collected (either retrospectively or prospectively) from 1974 to 2012. The overall CS rate in the 63 articles that reported this figure ranged from 5% (1974) [20] to 53.5% (2010) [21]. Most of the studies were either cross-sectionals (40%) or trend analysis (36%) using the 10 groups over time. Figure 2 shows the geographical distribution of the 73 studies included in this review; almost 70% of them were conducted in developed regions (Europe, North America and Oceania). Over 70% of the studies reported on the use of the classification at hospital-level and hospital records were the main source of data (Table 2).

Figure 2. Distribution of the 73 articles on Robson's classification according to country of origin.

Table 2. Characteristics of 73 studies that reported the use of Robson's classification.

In line with the thematic synthesis approach [17], the findings of this review are presented under three descriptive themes: design/purpose of the classification, implementation of the classification, and interpretation of the information arising from the classification. Design/purpose includes issues related to the principles, notion, idea, structure, and construct of categories or groups of the classification and its purpose or function. Implementation refers to mechanisms and processes related to how the classification is put into use, including how the required information is obtained, who collects this information, definitions of the variables used, quality assurance, and other elements like the use of software versus manual notation. Interpretation refers to issues relevant for the understanding of the information and data that emerges from the classification and its implementation. Table 3 shows the pros and cons of the Robson classification under each of these three themes and the percentage of studies that mentions each concept. The paragraphs below present the most recurrent concepts.

Table 3. Pros and cons of the Robson classification as experienced and reported by the authors and users in 73 articles included in this systematic review, and effect size (the proportion of articles containing each concept).

Pros of the Robson classification as experienced by users

Users praise the simplicity, robustness, reproducibility and flexibility of the classification; and the fact that the classification is clinically relevant and categorizes women prospectively which in turn allows the implementation and evaluation of interventions targeted at specific groups. The classification itself can be used as an intervention to reduce CS rates [22][24] and help to analyze the contribution of inductions to the overall CS rate [9]. An inherent advantage of the classification is that it allows self-validation since some groups can act as controls. For instance, group 9 (women with a fetus in a transverse or oblique lie) is expected to represent less than 1% of all women admitted for delivery and to have a CS rate of close to 100%. Numbers that differ significantly from these values indicate the possibility of problems with data collection [9].

The resources, software and variables needed to implement the classification are considered minimal, making it suitable for low-resource settings. In addition, “not requiring indications for CS” is an advantage [7], [10], [25][27] because of the variability and potential subjectivity when using indications to classify CS, and because these are insufficiently registered in some settings. This classification challenges traditional myths about alleged drivers of increasing CS rates, such as breeches or multiple pregnancies [28][30].

Cons of the Robson classification as experienced by users

Users report that the basic Robson classification identifies the contributors to the CS rate but does not provide insight into the reasons (indications) or explanations for the differences observed. The classification does not take into account other maternal and fetal factors that significantly influence the rate of CS (e.g. maternal age, pre-existing conditions such as BMI or complications) and therefore additional statistical methods (e.g. adjusting) are necessary to account for these factors.

Recommendations by users

Table 4 shows the modifications, adaptations or recommendations suggested by the users of the classification and the percentage of studies that mentions each recommendation. The paragraphs below present the most recurrent modifications.

Table 4. Modifications, adaptations and recommendations for implementing and interpreting the Robson classification according to the authors/users of the 73 articles included in this systematic review, and effect size (the proportion of articles which recommended each of them).

Ten groups constitute the backbone of the Robson classification. However, many authors used or proposed further subclassifications in each group or merging of groups. Among the 58 studies presenting data using the classification, 34 gave data using the original 10 Robson groups with no subgrouping [9][12], [14], [25][28], [31][55], 18 studies presented their data using subgroups or adding new groups [13], [20], [23], [29], [30], [56][68] and seven studies used less than 10 groups either by focusing on only one or two groups or by combining groups [21], [22], [59], [69][72]. One study proposed both merging and splitting of categories [59].

Table 1 shows the number of studies proposing each subdivision for each Robson group. All but one proposed the subdivision originally suggested by Robson for Groups 2 and 4 into induced (2a and 4a) and CS before labour (2b and 4b). The two most popular subdivisions (useful in several Robson groups) were (i) spontaneous labor/induced labour/CS before labor (Groups 5 through 10), and (ii) without previous uterine scar/with previous uterine scar (Groups 7 through 10). Several different subdivision were proposed for Group 5. A detailed list of the articles suggesting each subdivision is provided in File S2.

Merging Robson groups for specific analysis was also proposed. Most frequent were merging groups 1 and 2 to analyze all nulliparous women together [9], [32], [33], [39], [49] or all multiparous women by merging groups 3 and 4 [9]. Users also suggested collecting additional variables (such as indications for induction and CS or epidemiological and demographic variables) for within group analyses (Table 4). For example, indications for CS could be used within each group and in a hierarchical and standardized manner using the Anderson model [73].

Because ensuring continued quality data collection can be challenging, users recommended regular audits [74]. In particular, users reported challenges in extracting data on fetal presentation and position, induction vs. augmentation, and gestational age; they emphasized the need for training, in both developed and developing countries (see Table 4). In addition, although the collection of additional variables was repeatedly proposed, users warned that the collection of these variables (e.g. indication, reasons for induction, obesity, age) may pose challenges due to poor quality of data and non-standardized definitions. Engaging and involving staff may result in more complete and accurate recording on the patient record, timely collection and better quality data [25], [28].

Definitions of core variables in the Robson classification.

Although the 10 groups of the Robson classification are constructed by using a few basic core variables collected from every woman admitted for delivery, there was some variation in the definitions of these parameters, as shown in Table 5. While no article presented a definition of spontaneous labour, four defined induced labour [20], [30], [32], [39]. Multiple definitions were used for what is considered a “birth” and therefore which pregnant women can be included in the classification [13], [21], [23], [27], [33], [41], [45], [54], [59] (see Table 5).

Table 5. Definitions proposed by users for variables required in the Robson classification.

Understanding how to interpret the data from the classification is considered critical for the clinicians. From the public health perspective, users suggest that the optimal CS rate should be calculated after analysis of outcomes in each Robson group. Some novel uses of the classification have been proposed (See Table 4) [26], [51], [69], [75].


This review identified 73 manuscripts presenting the experiences of users on the pros and cons of the adoption, implementation and interpretation of the Robson classification for CS. Our findings show that, despite the lack of official endorsement by any international institutions or any formal guidelines, the use of the Robson classification is increasing rapidly and spontaneously worldwide. In this scenario, the experience and views of the users are a rich source of knowledge and guidance.

According to the users, the main strengths of the Robson classification are the simplicity of its design, the validity of its purpose, its ease of implementation and directness of initial interpretation. This classification has the capacity to overcome the main drawbacks of those which are based on the indications for performing a CS with categories that are not mutually exclusive and with low reproducibility for some of the most common conditions that lead to CS, such as fetal distress or dystocia.

The flexibility of the classification allows for the creation of subdivisions in each group that can improve analyses of local clinical practices. These suggestions are a critical contribution of this systematic review, providing clinicians, other health professionals and researchers with additional ideas to tailor the classification to their needs. Subdivisions have been proposed in almost all of the 10 Robson groups but it is clear that group 5 (women with a previous CS) is the group that received the largest number of suggestions (see Table 1). The recommended modifications in group 5 fall into one of two major axis: either the previous obstetric history of the woman (previous vaginal delivery or number of CS) or the onset of labour (spontaneous or other). In the current context of increasing numbers of caesarean deliveries, the contribution of the group of women with a previous CS (Group 5) to the overall rate of CS is critical from a clinical and epidemiological perspective to interpret practices and monitor the effectiveness of interventions. In addition, if users feel that more in depth analysis are needed, they can add the indications for CS, epidemiological information (e.g. BMI, age) and outcome (e.g. morbidity and mortality) within the 10 groups.

Despite its strengths, the Robson classification, users warn that it is not free of challenges and difficulties. The quality of the data and, therefore, the real value of using the classification should not be taken for granted as it is a struggle even in developed countries. Lack of definition or consensus on the core variables is an issue raised by several users. For example, it is necessary to reach an agreement on when labour starts and how to operationalize the difference between augmentation and induction of labor. Misclassification of women is a real threat and users recommend training, educational efforts and audits to avoid both misclassification and missing data. In fact, missing data has led some users to create a category “99” for these women. We believe this suggestion is very relevant and recommend the addition of this group to the Robson classification to make it completely “totally inclusive”. The size of this group “99” can be useful to audit the quality of the data.

The interpretation of the results of the classification is the weakest point of its use. A simple set of rules for interpretation was recently published by Robson [9] to help users explore all the information provided by this classification, especially when using it to compare data between different settings or changes over time. For example, it should be expected that the combination of groups 1 and 2 represents 35–42% of the total women and a high CS rate in group 2 (more than 35%) suggests a high pre-labour CS rate. Similarly, the combination of groups 3 and 4 should usually account for 30–40% of all women while group 9 should represent 0.2–0.6% of the total women and the CS rate in this particular group is expected to be 100%. However, these rules have not been validated and may not be applicable in all circumstances. The next crucial step would be to assess maternal and fetal outcomes vs CS rates in each of the 10 groups to be able to establish an optimal range of CS rate for best outcomes.

Strengths of this review start by its uniqueness. This is the first systematic review that analyses the experience of users related to pros and cons including challenges and recommendations. We developed a broad search strategy, in order to capture the largest possible number of publications on this topic and contacted the author of the classification to obtain unpublished material. We tried to reduce bias by extracting data in duplicate using a structured data-extraction form specifically created for this review, and by performing in triplicate the coding of the concepts, and the development of descriptive and analytical themes.

This systematic review has several limitations. Despite the efforts mentioned above, it is possible that we did not capture the full extent of its use since we are aware of users who are not documenting their experiences (Robson 2013, personal communication). We acknowledge that by trying to summarize studies and points of view from different settings and countries, the findings can be de-contextualized and what is applicable in one setting may not be relevant in others. However, we believe that most of the encountered barriers and proposed improvements would translate well into all contexts. In addition, despite the use of strict methodology at all steps of the systematic review, there is always potential for subjectivity in qualitative reviews of this type.

In the current international scenario of increasing rates of CS, the main drivers of this trend are still unclear and controversial. We believe that a CS rate can only be considered appropriate if the information is available to explain and justify it, and in this context, this systematic review provides important information, guidance and suggestions on how to use the Robson classification such as adding subdivisions and defining a new group for women with missing variables. By collecting real and timely data about which specific groups of women are having a CS, this classification can contribute to a better understanding of the drivers of increasing CS rates and to the development of effective interventions to safely curb this trend.

Supporting Information

File S1.

Search strategy for electronic databases.


File S2.

Detailed description of the process to extract the concepts, create the themes and the final result. In addition, for each Robson group, the detailed description of the sub-classifications proposed by authors.



Disclaimer: The views expressed are solely those of the authors and do not necessarily reflect the decisions or stated policy of the World Health Organization.

Author Contributions

Conceived and designed the experiments: APB MRT. Performed the experiments: APB NV MRT. Analyzed the data: APB NV JPS AMG MRT. Wrote the paper: APB NV JPS AMG MRT.


  1. 1. WHO (1985) Appropriate technology for birth. Lancet 2: 436–437.
  2. 2. Villar J, Carroli G, Zavaleta N, Donner A, Wojdyla D, et al. (2007) Maternal and neonatal individual risks and benefits associated with caesarean delivery: multicentre prospective study. BMJ 335: 1025.
  3. 3. Villar J, Valladares E, Wojdyla D, Zavaleta N, Carroli G, et al. (2006) Caesarean delivery rates and pregnancy outcomes: the 2005 WHO global survey on maternal and perinatal health in Latin America. Lancet 367: 1819–1829.
  4. 4. Lumbiganon P, Laopaiboon M, Gulmezoglu AM, Souza JP, Taneepanichskul S, et al. (2010) Method of delivery and pregnancy outcomes in Asia: the WHO global survey on maternal and perinatal health 2007–08. Lancet 375: 490–499.
  5. 5. Betran AP, Merialdi M, Lauer JA, Bing-shun W, Thomas J, et al. (2007) Rates of caesarean section: analysis of global, regional and national estimates. Paediatric and Perinatal Epidemiology 21: 98–113.
  6. 6. Gibbons L, Belizan JM, Lauer J, Betran AP, Merialdi M, et al. (2010) The global numbers and costs of additionally needed and unnecessary caesarean sections performed per year: overuse as a barrier to universal coverage. World Health Report. Geneva, Switzerland: World Health Organization.
  7. 7. Robson MS (2001) Classification of caesarean sections. Fetal and Maternal Medicine Review 12: 23–39.
  8. 8. Torloni MR, Betran AP, Souza JP, Widmer M, Allen T, et al. (2011) Classifications for cesarean section: a systematic review. PLoS ONE 6: e14566.
  9. 9. Robson M, Hartigan L, Murphy M (2013) Methods of achieving and maintaining an appropriate caesarean section rate. Best Pract Res Clin Obstet Gynaecol 27: 297–308.
  10. 10. Cabeza Vengoechea PJ, Calvo Pérez A, Betrán AP, Mas Morey MM, Febles Borges MM, et al. (2010) Clasificación de cesáreas por Grupos de Robson en dos periodos comparativos en el Hospital de Manacor. Progresos en Obstetricia y Ginecología 53: 385–390.
  11. 11. Kazmi T, Saiseema S, Khan S (2012) Analysis of Cesarean Section Rate - According to Robson's 10-group Classification. Oman Med J 27: 415–417.
  12. 12. Betran AP, Gulmezoglu AM, Robson M, Merialdi M, Souza JP, et al. (2009) WHO global survey on maternal and perinatal health in Latin America: classifying caesarean sections. Reprod Health 6: 18.
  13. 13. Kelly S, Sprague A, Fell D, Murphy P, Aelicks N, et al. (2013) Examining Caesarean Section Rates in Canada Using the Robson Classification System. J Obstet Gynaecol Can.
  14. 14. Costa ML, Cecatti JG, Souza JP, Milanez HM, Gulmezoglu MA (2010) Using a Caesarean Section Classification System based on characteristics of the population as a way of monitoring obstetric practice. Reprod Health 7: 13.
  15. 15. Moher D, Liberati A, Tetzlaff J, Altman DG (2009) Group TP (2009) Preferred Reporting Items for Systematic Reviews and Meta-analyses: The PRISMA Statement. P Ann Intern Med 151: 264–269.
  16. 16. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, et al. (2000) Meta-analysis of observational studies in epidemiology. A proposal for reporting. JAMA 283: 2008–2012.
  17. 17. Thomas J, Harden A (2008) Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Medical Research Methodology 8.
  18. 18. Sandelowski M, Barroso J, Voils CI (2007) Using Quantitative Metasummary to Synthesize Qualitative and Quantitative Descriptive Findings. Res Nurs Health 30: 99–111.
  19. 19. Noyes J, Popay J, Pearson A, Hannes K, Booth A (2008) Chapter 20: Qualitative research and Cochrane reviews. In: Higgins JPT, Green S, editors. Cochrane Handbook for Systematic Reviews of Interventions Version 501 [Update March 2011]: The Cochrane Collaboration. Available:
  20. 20. Brennan DJ, Murphy M, Robson MS, O'Herlihy C (2011) The Singleton, Cephalic, Nulliparous Woman After 36 Weeks of Gestation. Obstet Gynecol 117: 273–279.
  21. 21. Paleari L, Gibbons L, Chacon S, Ramil V, Belizan JM (2012) Tasa de cesareas en dos hospitales privados con normativas diferentes: abierto y cerrado. Ginecol Obstet Mex 80: 263–269.
  22. 22. Salinas HP, Carmona SG, Albornoz JV, Veloz PR, Terra RV, et al. (2004) ¿Se Puede Reducir El Indice de Cesarea? Experiencia del Hospital Clinico de la Universidad de Chile. Revista Chilena de Obstetricia y Ginecología 69: 8–13.
  23. 23. Scarella A, Chamy V, Sepulveda M, Belizan JM (2011) Medical audit using the Ten Group Classification System and its impact on the cesarean section rate. Eur J Obstet Gynecol Reprod Biol 154: 136–140.
  24. 24. Bjarnadottir R, Smarason A (2012) Trends in Caesarean section rates in Iceland. Acta Obstet Gynecol Scand 91 SUPPL.: 70
  25. 25. Litorp H, Kidanto HL, Nystrom L, Darj E, Essen B (2013) Increasing caesarean section rates among low-risk groups: a panel study classifying deliveries according to Robson at a University hospital in Tanzania. BMC Pregnancy Childbirth 13.
  26. 26. Homer CS, Kurinczuk JJ, Spark P, Brocklehurst P, Knight M (2010) A novel use of a classification system to audit severe maternal morbidity. Midwifery 26: 532–536.
  27. 27. Howell S, Johnston T, Macleod SL (2009) Trends and determinants of caesarean sections births in Queensland, 1997–2006. Australian and New Zealand Journal of Obstetrics and Gynaecology 49: 606–611.
  28. 28. McCarthy FP, Rigg L, Cady L, Cullinane F (2007) A new way of looking at Caesarean section births. Aust N Z J Obstet Gynaecol 47: 316–320.
  29. 29. Vera C, Correa R, Neira J, Rioseco A, Poblete A (2004) Utilidad de la evaluaci¢n de 10 grupos cl¡nicos obst‚tricos para la reducci¢n de la tasa de ces rea en un hospital docente. Revista Chilena de Obstetricia y Ginecología 69: 219–226.
  30. 30. Maneschi F, Sarno M, Vicaro V, Pane C, Ceccacci I, et al. (2009) Analisi Della Frequenza Di Taglio Cesareo Secondo Le Classi Di Rischio Clinico. Riv It Ost Gin 21: 13–18.
  31. 31. Robson MS (2001) Can we reduce the caesarean section rate? Best Pract Res Clin Obstet Gynaecol 15: 179–194.
  32. 32. Brennan DJ, Robson MS, Murphy M, O'Herlihy C (2009) Comparative analysis of international cesarean delivery rates using 10-group classification identifies significant variation in spontaneous labor. Am J Obstet Gynecol 201: 308–308.
  33. 33. Sorbye IK, Vangen S, Oneko O, Sundby J, Bergsjo P (2011) Caesarean section among referred and self-referred birthing women: a cohort study from a tertiary hospital, northeastern Tanzania. BMC Pregnancy Childbirth 11: 55.
  34. 34. Abha S, Reema C (2009) A recent way of evaluating cesarean birth. J Obstet Gynecol India 59: 547–551.
  35. 35. Pot M, Sadler L, McDougall J, Harilall M, Battin M (2009) National Women's Annual Clinical Report 2009. 74–87 p.
  36. 36. Barcaite E, Bartusevicius A, Railaite DR, Butkute I, Draksaite-Zelbiene E (2012) Robsono 10 grupiu cezario pjuvio operaciju klasifikacija. Analizes ir vertinimo rekomendacijos. Lietuvos akuserija ir ginekologija 15: 222–225.
  37. 37. Burke G, Mak CH, Ronan E, Skehan M (2006) The Robson Ten Group Classification of Cesarean Section in a Unit with an Apparent Culture of Liberal Cesarean Section. Am J Obstet Gynecol 10: 307.
  38. 38. Chong C, Su LL, Biswas A (2012) Changing trends of cesarean section births by the Robson Ten Group Classification in a tertiary teaching hospital. Acta Obstet Gynecol Scand 91: 1422–1427.
  39. 39. Ciriello E, Locatelli A, Incerti M, Ghidini A, Andreani M, et al. (2012) Comparative analysis of cesarean delivery rates over a 10-year period in a single Institution using 10-class classification. J Matern Fetal Neonatal Med 25: 2717–2720.
  40. 40. Reti L (2007) Can we reduce the Royal Women's Hospital Caesarean section rate? Clinical Practice Review.
  41. 41. Delbaere I, Cammu H, Martens E, Tency I, Martens G, et al. (2012) Limiting the caesarean section rate in low risk pregnancies is key to lowering the trend of increased abdominal deliveries: an observational study. BMC Pregnancy Childbirth 12: 3.
  42. 42. Florica M, Stephansson O, Nordstrom L (2006) Indications associated with increased cesarean section rates in a Swedish hospital. International Journal of Gynaecology and Obstetrics 92: 181–185.
  43. 43. Kraulaidyte V, Puskova I, Zakareviciene J, Jursenas R, Lauzikiene D, et al. (2011) Vilniaus miesto universitetines ligonines Akuserijos ir ginekologijos klinikoje atliktu cezario pjuvio operaciju analize pagal M. Robsono klasifikacija. Lietuvos akuserija ir ginekologija 14: 114–121.
  44. 44. Meloni A, Loddo A, Martsidis K, Deiana SA, Porru D, et al. (2012) The role of caesarean section in modern obstetrics. J Pediatr Neonat Individualized Med 1: 53–58.
  45. 45. Minsart AF, De SM, Englert Y, Buekens P (2013) Classification of cesarean sections among immigrants in Belgium. Acta Obstet Gynecol Scand 92: 204–209.
  46. 46. Program PEIRC (2011) Perinatal Database Report 2008.
  47. 47. Rasmussen OB, Pedersen BL, Wilken-Jensen C, Vejerslev LO (2000) Stratified rates of cesarean sections and spontaneous vaginal deliveries. Data from five labor wards in Denmark—1996. Acta Obstet Gynecol Scand 79: 227–231.
  48. 48. Suliman S, Soma-Pillay P, Pattinson RC, Macdonald AP (2010) Factors Associated with Caesarean Section using the Robson Ten Group Classfication System.
  49. 49. Teguete I, Traore M, Sissoko A, Djire MY, Thera A, et al. (2012) Determining Factors of Cesarean Delivery Trends in Developing Countries: Lessons from Point G National Hospital (Bamako-Mali). In: Salim R, editor. Cesarean Delivery: InTech.
  50. 50. Thaens AA, Bonnaerens G, Martens G, Mesens T, Van Holsbeke C, et al. (2011) Understanding rising caesarean section trends: relevance of inductions and prelabour obstetric interventions at term. F, V & V IN OBGYN 3: 286–291.
  51. 51. Torloni MR, Caetano ACR, Zamarian ACP, Lopes CD, Puccini R, et al. (2009) Why are Cesarean section rates so high in diabetics? FIGO.
  52. 52. Services DoCaFH (2004) Trends in Cesarean Births in Utah, 1999–2002. Salt Lake City, UT: Utah Department of Health.
  53. 53. Maneschi F, Sarno M, La Rocca A, Ceccacci I, Algieri M, et al. (2011) Riflessioni sul tasso globale di taglio cesareo. Epidemiologia NOG. pp. 4–9.
  54. 54. Stavrou EP, Ford JB, Shand AW, Morris JM, Roberts CL (2011) Epidemiology and trends for Caesarean section births in New South Wales, Australia: a population-based study. BMC Pregnancy Childbirth 11: 8.
  55. 55. Gonzales Rengifo G, Fort A, Tapia Aguirre V, Betran AP (2013) Tendencias y determinantes de cesareas en el Peru.
  56. 56. BC PS (2011) Examining cesarean delivery rates in British Columbia using the Robson Ten Classification. Part 1. Understanding the 10 groups. Vancouver, BC.
  57. 57. Fell D, Prince M, Sprague A, Walker M, Darling L, et al. (2011) Better outcomes registry and network (BORN) Ontario Perinatal Health Report 2009–2011, Greater Toronto Area LHINs 5 to 9.
  58. 58. Program BCPH (2009) Caesarean Birth Task Force Report 2008. Vancouver, BC, Canada.
  59. 59. Zhang J, Troendle J, Reddy UM, Laughon SK, Branch DW, et al. (2010) Contemporary cesarean delivery practice in the United States. Am J Obstet Gynecol 203: e1–e10.
  60. 60. Goonewardene M, Kumara DMA, Arachchi DRJ, Vithanage R, Wijeweera R (2012) The rising trend in caesarean section rates: should we and can we reduce it? Sri Lanka Journal of Obstetrics and Gynaecology 34: 11–18.
  61. 61. Bjarnadottir R, Smarason A (2013) Iceland Report from Birth Registry.
  62. 62. Robson MS (2012) National Maternity Hospital Dublin. Clinical Report for the Year 2008.
  63. 63. Services AH (2009) Caesarean Births In Alberta. Alberta Perinatal Health Provincial Report. pp. 12–24.
  64. 64. Allen VM, Baskett TF, O'Connell CM (2010) Contribution of select maternal groups to temporal trends in rates of caesarean section. J Obstet Gynaecol Can 32: 633–641.
  65. 65. Slavin V, Fenwick J (2012) Use of a Classification Tool to Determine Groups of Women That Contribute to the Cesarean Section Rate: Establishing a Baseline for Clinical Decision Making and Quality Improvement. International Journal of Childbirth 2: 85–94.
  66. 66. Thomas J, Paranjothy S (2001) Royal College of Obstetricians and Gynaecologists Clinical Effectiveness Support Unit. The National Sentinel Caesarean Section Audit Report. London, United Kingdom: RCOG Press.
  67. 67. Chan JCY, Honest H (2010) Implementing the ten-group-classification-system of ceasarean section at Good Hope Hospital (UK) for 2008. Arch Dis Child Fetal Neonatal.
  68. 68. Budhwa T, Holmberg V, Chapman B (2010) The Birthing Review Project.
  69. 69. Watson M, Howell S, Macleod SL, Cornes S (2009) The effect of Body Mass Index on delivery method of low risk pregnancies in public and private patients, Queensland 2008. Health Statistics Centre, Queensland Health.
  70. 70. Flood K, Simpson L, Sela H, Ananth C (2013) CUT study: cesarean deliveries in United States using ten group classification. Am J Obstet Gynecol Supplement to January 2013.
  71. 71. Sudarsan S, Soma S, Rupkamal D, Mayoukh C, Sekhar BH, et al. (2012) A Paradigm Shift to Check the Increasing Trend of Cesarean Delivery is the Need of Hour: But How? The Journal of Obstetrics and Gynecology of India 62: 391–397.
  72. 72. Fischer A, LaCoursiere DY, Barnard P, Bloebaum L, Varner M (2005) Differences between hospitals in cesarean rates for term primigravidas with cephalic presentation. Obstet Gynecol 105: 816–821.
  73. 73. Anderson GM, Lomas J (1984) Determinants of the increasing cesarean birth rate. The New England Journal of Medicine 311: 887–892.
  74. 74. Knight M, Sullivan EA (2010) Variation in caesarean delivery rates. Specific groups should be monitored at a local level. BMJ 341.
  75. 75. Zamarian A, Torloni MR, Caetano A, Lopes C, Fernandes L, et al. (2009) Cesarean section in women with systemic lupus erythematosus experience from a Brazilliam univerisity hospital. Int J Gynaecol Obstet 107S: S451.
  76. 76. Colais P, Fantini MP, Fusco D, Carretta E, Stivanello E, et al. (2012) Risk adjustment models for interhospital comparison of CS rates using Robson's ten group classification system and other socio-demographic and clinical variables. BMC Pregnancy Childbirth 12: 54.
  77. 77. Grunebaum A, Lin S, Greenwood E, Lehman A (2012) The Contribution of Patient Age To The Robson Cesarean Section Classification. AmJ Obstet Gynecol 206: S287–S288.
  78. 78. Allen VM, Scott H, Baskett TF (2012) Classification of Caesarean Sections in Canada: The Modified Robson Criteria. J Obstet Gynaecol Can 34: 1130–1132.
  79. 79. Keane D, Robson M (2000) Analysis of caesarean section rates using the Robson 10-groups. Int J Gynaecol Obstet 70: A19.
  80. 80. Farine D, Shepherd D (2012) Classification of caesarean sections in Canada: the modified robson criteria. J Obstet Gynaecol Can 34: 976–979.
  81. 81. Brennan DJ, Robson MS (2009) Nulliparous term singleton vertex caesarean delivery rates. American Journal of Obstetrics and Gynecology 200: e8.
  82. 82. Betran AP, Vindevoghel N, Souza JP, Gülmezoglu M, Torloni MR (2014) Implementation of the Robson classification for caesarean section: What do users think? A systematic review. PLoS ONE.
  83. 83. Gonzalez R, Merialdi M, Lincetto O, Lauer J, Becerra C, et al. (2006) Reduction in neonatal mortality in Chile between 1990 and 2000. Pediatrics 117: e949–e954.
  84. 84. Gu Y, Rigg L, Cullinane F, Mee J (2011) Second Stage Caesarean Section in Women in Robson Group One. Journal of Paediatrics and Child Health 47 SUPPL: 79