PLOS ONE RESEARCH ARTICLE Caesarean section trends in Catalonia between 2013 and 2017 based on the Robson classification system: A cross-sectional study Garazi Carrillo-Aguirre ID1,2, Albert Dalmau-Bueno2, Carlos Campillo-Artero3, Anna Garcı́a- Altés ID2,4,5* 1 Master’s Degree Public Health, Pompeu Fabra University (UPF), Barcelona, Spain, 2 Department of Health, Health Evaluation and Quality Agency of Catalonia (AQuAS), Government of Catalonia, Barcelona, Catalonia, Spain, 3 Center for Research in Health and Economics, Pompeu Fabra University, IB-Salut, a1111111111 Barcelona, Spain, 4 Biomedical Research Networking Center for Epidemiology and Public Health a1111111111 (CIBERESP), Madrid, Spain, 5 Sant Pau Biomedical Research Institute (IIB Sant Pau), Barcelona, Spain a1111111111 a1111111111 * agarciaaltes@gencat.cat a1111111111 Abstract OPEN ACCESS Introduction Citation: Carrillo-Aguirre G, Dalmau-Bueno A, Campillo-Artero C, Garcı́a-Altés A (2020) In Catalonia caesarean rates have always been analysed as a single percentage. The Caesarean section trends in Catalonia between objective is to estimate caesarean section rates using the Robson classification in publicly 2013 and 2017 based on the Robson classification funded hospitals in Catalonia between 2013 and 2017, considering sociodemographic, insti- system: A cross-sectional study. PLoS ONE 15(6): tutional and obstetric characteristics. e0234727. https://doi.org/10.1371/journal. pone.0234727 Materials and methods Editor: Calistus Wilunda, African Population and Health Research Center, KENYA Cross-sectional population-based study in Catalonia including all women delivering within Received: January 15, 2020 publicly funded hospitals between 2013–2017 (n = 210 020). The modified Robson classifi- cation distribution was estimated, the caesarean rate and the overall contribution, analysed Accepted: June 1, 2020 for each year, and by confounders, through logistic regression models. Published: June 16, 2020 Peer Review History: PLOS recognizes the Results benefits of transparency in the peer review process; therefore, we enable the publication of CS rates decreased steadily between 2013 and 2017 in Catalonia within publicly funded all of the content of peer review and author hospitals from 24.3% to 22.8% (cOR 0.92, 95% CI; 0.89 to 0.95). Once adjusted for changes responses alongside final, published articles. The in sociodemographic, institutional and obstetric characteristics the observed decline was editorial history of this article is available here: https://doi.org/10.1371/journal.pone.0234727 even more pronounced (aOR 0.87, 95% CI; 0.84 to 0.90). Within the different groups of Rob- son once adjusted for confounders, groups 1+2 (aOR 0.88, 95% CI; 0.83 to 0.93), 3+4 (aOR Copyright: © 2020 Carrillo-Aguirre et al. This is an open access article distributed under the terms of 0.83, 95% CI; 0.78 to 0.89) and 10 (aOR 0.78, 95% CI; 0.68 to 0.90) presented a reduction the Creative Commons Attribution License, which in caesarean section rates, whereas group 5 showed no significant decrease (aOR 0.95, permits unrestricted use, distribution, and 95% CI; 0.87 to 1.03%). reproduction in any medium, provided the original author and source are credited. Conclusions Data Availability Statement: Data cannot be shared publicly because of confidentiality. Data are The decrease in caesarean section rates in Catalonia is more pronounced when adjusted available from the Government of Catalonia for known confounders, suggesting retrospective overutilization of caesarean section and PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 1 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 Institutional Data Access / Ethics Committee for percentages of (in)adequacy in the past. In any case, it remains above the recommended researchers who meet the criteria for access to by experts. Further efforts should be made to achieve optimum rates, including improve- confidential data. The data underlying the results presented in the study are available from the ment on obstetric data collection Government of Catalonia Registries. Plos One can access aggregated data at hospital level and values used to build graphs under request. You can check up-to-date regulations at http://aquas.gencat.cat/ ca/ambits/analitica-dades/padris/ and address any Introduction inquiries to AQuAS director, Dr. Cesar Velasco A Caesarean Section (CS) is a surgical procedure that, when performed for medical reasons, (cesarvelasco@gencat.cat). could save the life of a woman and her baby. However, it carries risks for both of them and Funding: The authors received no specific funding therefore should only be considered when necessary [1,2]. for this work. The increase on the global rates of CS remains a continuing public health concern [3,4]. Competing interests: The authors have declared The World Health Organization (WHO) stated that priority should remain the provision of that no competing interests exist. CS to all women in need, rather than the achievement of an ideal level [5]. In places where CS is universally available though, optimal rates should be expected (i.e. Catalonia). Not excepted of controversy, recent studies suggested rates between 10–20% of all births [6–9]. There are complex reasons behind the significant increase in CS [10], believed, in principle, to correlate with higher risk profiles of pregnant women and their babies [11]. However, Betrán et al. suggested that it responds to a multifactorial phenomenon including healthcare organisations as well as financial aspects among others [12]. During the years, the comparison of national rates has mask inequalities on access and practice. The WHO (2015) proposed the Robson classification as a global standard system for assessing, monitoring and comparing CS rates [5]. This classifies women into ten different groups, all mutually exclusive, and totally inclusive, based on obstetric characteristics [13]. In Catalonia, the CS rate have concerned health authorities for very long time. Monitoring of CS rate started in 1990 and different published National Health Plans have included the objective of CS reduction [14–18]. However, despite having also implemented several proto- cols and guidelines in regards to care during delivery and the publication of official reports comparing CS rates between hospitals [19–24], their impact is unknown due to a lack of exhaustive evaluation assessments. Rates have ranged between 22% and 32%, with consider- able differences between the public and the private sectors, i.e. 22.3% to 35.9% for the year 2017 [25]. Maternal and neonatal mortality ratio has remained very low (MMR: 3.1, 2010– 2014 [26] and NMR: 1.67, 2014–2017 [27]) and public hospitals do not provide CS under maternal request [28]. In this context, this analysis provides an exciting opportunity for a deeper understanding of the CS rate fluctuation. Motivated by the opportunity that the Robson classification provides, this current study analyses CS trends between 2013 and 2017, in order to firstly, identify the groups of women with the highest contribution to CS rates, and secondly, observe changes in the total CS rate by adjusting for sociodemographic, institutional and obstetric characteristics. The results hope to provide valuable information for the establishment of public health benchmarks for maternal and neonatal health programs, as well as the design of policies and guidelines. Material and methods Study design and participants A retrospective cross-sectional trend study was conducted in the Spanish region of Catalonia. The population included women delivering between 1st January 2013 and 31st December 2017. From the total 330,851 (100%) deliveries occurred after 22 weeks gestation, only those that occurred at the 44 publicly funded hospitals offering maternity care in Catalonia were PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 2 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 Fig 1. Flowchart of the population included in the study. https://doi.org/10.1371/journal.pone.0234727.g001 included. As a result, 231,020 (69.83%) deliveries met the eligibility criteria for this research. However, information regarding type of delivery, whether it was vaginal or caesarean section, was considered a sine qua non variable for the study. Thus, missing data in 9.1% of the women regarding outcome (vaginal/CS), reduced the potential sample size to 210,241 (Fig 1). Details of ethics approval A governmental structure called PADRIS exists within the Catalan healthcare administration. PADRIS is an analytical data programme for research and innovation in health. The purpose of the structure is to make data available to scientific communities to promote research, inno- vation, and evaluation in health, with the aim of reusing and exchanging the data generated by the health system in accordance with the legal and regulatory framework. The programme PADRIS ensures that all data made available to researchers is fully anonymised. As workers within the Catalan healthcare administration, we are provided data by PADRIS, and therefore are never given access to identifiable information. Thus, the study did not involve any data col- lection, requiring neither human participants nor patient consent. For that reason, and due to the use of existing anonymised data for research, the study was exempt from institutional review committee approval. It is the standard way of proceeding in the healthcare administra- tion to systematically check the quality of the healthcare providers in our context. Data sources Three data sources were employed: (1) Minimum Basic Data Set (Conjunt Mínim Básic de Dades, CMBD); (2) the Central Registry of Insured Persons (Registro Central de personas PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 3 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 Aseguradas, RCA); and (3) the Clinic Station for Primary Care (Estació Clínica d’ Atenció Primària, E-CAP). Individuals on the registries were given a personal anonymised code that allowed linkage between databases. The different databases were then merged using this anonymised code. 1. CMBD is an administrative registry subject to Ministerial regulation containing exhaus- tive data regarding hospital discharges. All hospitals are required to provide information regarding hospital activity and diagnosis (ICD-9-CM at the time of the current study) [29]. This registry allowed access to information regarding type of delivery and the majority of vari- ables required for the Robson classification. 2. RCA collects personal data of all those insured by the CatSalut (Catalan National Health System), including income level and employment status [30], enabling access to socioeco- nomic status. 3. E-CAP is a computerized system used within the primary healthcare facilities. This enabled access to details of Body Mass Index (BMI) and parity [31]. Definition of variables The primary outcome for this study was delivery by CS. The following variables were required to create the variable Robson classification: parity, gestational age, foetal presentation, previous CS, number of foetuses, and onset of labour [32]. The variable foetal presentation was not recorded within the databases, so it had to be created ad hoc, thus considering cephalic presen- tation in the absence of breech or transverse lie. A modified classification was constructed due to onset of labour not being collected in any of the databases. An adapted Robson classification was created formed of eight mutually exclusive categories. This combined groups 1 and 2, and 3 and 4, with the rest remaining unchanged: nulliparous, singleton cephalic pregnancy, � 37 weeks’ gestation (groups 1+2); multiparous without a pre- vious uterine scar, with singleton, cephalic pregnancy, � 37 weeks’ gestation (groups 3+4); previous CS, singleton, cephalic, � 37 weeks’ gestation (Group 5); all nulliparous with a single breech (Group 6); all multiparous with a single breech, including previous CS (Group 7); all multiple pregnancies, including previous CS (Group 8); all women with a single pregnancy in transverse or oblique lie (including those with previous CS (Group 9); all singleton, cephalic, < 37 weeks’ gestation pregnancies, including previous CS (Group 10). The following variables were also included: age at the time of delivery, nationality, socioeco- nomic status, hospital level, BMI and maternal complications. For the variable nationality The World Bank classification was selected [33]. The variable socioeconomic status is a set variable within the database that arises through pharmaceutical co-pay estimations. There are four co- payment groups: 1) those exempt from co-payment, (disadvantaged population; individuals receiving some form of universal pension scheme, those who no longer receive unemployment allowance, or those who no longer receive unemployment benefit and do not qualify for unem- ployment allowance); 2) those with annual earnings of less than 18,000€; 3) those with annual earnings between 18,000€ and 100,000€; and 4) those with annual earnings over 100,000€. This is predetermined by the system and does not allow further disaggregation. The hospital level follows an order of complexity, based on the care that the pregnant woman and her baby might require. Thus, even though all hospitals will be caring for women with low risk pregnan- cies, the more complex the pregnancy becomes the higher the level of the hospital in which she will be cared for. Level IA being the less medicalised hospitals, and IIIB the most, offering med- ical attention from other specialties if required [34]. The variable maternal complication was created ad hoc and included any of the following diagnoses that had to be recorded prior initi- ating the labour process within this pregnancy: uterine rupture, placenta praevia, pre- PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 4 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 eclampsia, gestational diabetes, diabetes mellitus, heart disease, hypertension, hepatic disease, viral disease, anaemia, renal disease and epilepsy. A code recorded at CMBD that includes dif- ferent diagnosis called “disease that complicates the pregnancy” was also included (For further information S1 Table). Data analysis Missing data. Missing data relating to the different variables ranged between 0.2 and 32%, with CS showing an overall level of 6%. Maternal age accounted for 0.2%; nationality 1.2%; socioeconomic status 0.2%; healthcare facility 1.6%; and BMI 32%. To minimize loss of statisti- cal power, BMI was not included in the final model and a separate sensibility analysis was undertaken. An analysis of the missing data concerning type of delivery was also undertaken to determine any bias related to the response rates. Statistical analysis. Characteristics of the women included in the study were reported for each year, along with the proportion of women delivered by CS. The following were analysed for each specific year and modified Robson classification: the relative size of the obstetric pop- ulation (% = n of women in the group/total N women delivered x 100), total CS rate (% = n of CS in the group/total N of women in the group x 100) and the absolute contribution to the total CS rate (% = n of CS in the group/total N of women delivered). The crude change between 2013 and 2017 was calculated for each of the above. Two logistic regression models were used for the analysis between the principal variable (CS) and the remainder of the variables. Crude and adjusted odds ratios were estimated with their correspondent 95% confidence intervals (CI) and p-values. Following the same analytical strategy, maintaining the CS as dependent variable, through ten regression logistic models, crude and adjusted odds ratios were also estimated for each year and for each Robson group for each year. Finally, the performance of the logistic models applied to estimate time trends were assessed. On the one hand, the area under the receiver operating curve (ROC) was estimated to determine the discriminatory capacity and on the other hand, the calibration belt p-value for internal validation. This analysis pretended to establish a reliable baseline. The aim of the study was to analyse CS trends and the intention was not to build a predictive model for CS, although the possibility was explored. Stata software version 14 was used to perform the analysis. Results A significant decrease was identified in CS rates between 2013 and 2017, from 24.30% to 22.80% (see Table 1). The majority of the women on the population sample were Spanish (62.43%), with an income of less than 18.000€ (76.15%). Their average age was 30 (SD 5.6), with most having singleton, cephalic births at term. Some characteristics changed slightly over the years, with the proportion of births to women aged thirty-five or over increasing by 5.23% and an overall significant increase of women with a BMI above 30. In addition, the decrease in the proportion of nulliparous women and increase in multiparous women with previous CS were statistically significant. There was also an increase in the number of women presenting a diagnosis potentially complicating the pregnancy. Determinants of caesarean sections During the study period, 50.009 women were delivered by CS. Rates increased in relation to maternal age, women under twenty with a rate of 14.59%, while those over forty 37.18% (S2 Table). Adjusting for sociodemographic, institutional and obstetric factors, the age differences PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 5 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 Table 1. Socio-demographic and obstetric characteristics in the study population for each year, 2013–2017. Year 2013 Year 2014 Year 2015 Year 2016 Year 2017 n = 43145 n = 42397 n = 41825 n = 41275 n = 41599 n % 95% CI n % 95% CI n % 95% CI n % 95% CI n % 95% CI Type of delivery Vaginal 32659 75.7 75.29– 32134 75.79 75.38– 31802 76.04 75.62– 31526 76.37 75.96– 32114 77.2 76.79– 76.10 76.20 76.44 76.78 77.60 CS 10486 24.3 23.90– 10263 24.21 23.80– 10023 23.96 23.56– 9752 23.63 23.22– 9485 22.8 22.40– 24.71 24.62 24.38 24.04 23.21 Parity Nuliparous 16486 38.21 37.75– 15647 36.91 36.45– 14790 35.36 34.90– 14097 34.15 33.69– 14274 34.31 33.86– 38.67 37.37 35.82 34.61 34.77 Multiparous 26659 61.79 61.33– 26750 63.09 62.63– 27035 64.64 64.18– 27181 65.85 65.39– 27325 65.69 65.23– 62.25 63.55 65.10 66.31 66.14 Previous CS No 39054 90.52 90.24– 38266 90.26 89.97– 37496 89.65 89.35– 36889 89.37 89.07– 37116 89.22 88.92– 90.79 90.54 89.94 89.66 89.52 Yes 4091 9.48 9.21–9.76 4131 9.74 9.46– 4329 10.35 10.06– 4389 10.63 10.34– 4483 10.78 10.48– 10.03 10.65 10.93 11.08 Maternal age years <20 1319 3.06 2.90–3.22 1218 2.87 2.72–3.04 1192 2.85 2.69–3.01 1159 2.81 2.65–2.97 1159 2.79 2.63–2.95 20–24.9 5040 11.68 11.38– 4673 11.02 10.73– 4498 10.75 10.46– 4473 10.84 10.54– 4393 10.56 10.27– 11.99 11.32 11.06 11.14 10.86 25–29.9 10590 24.55 24.14– 10370 24.46 24.05– 9940 23.77 23.36– 9600 23.26 22.85– 9470 22.76 22.36– 24.95 24.87 24.18 23.67 23.17 30–34.9 15028 34.83 34.38– 14618 34.48 34.03– 14008 33.49 33.04– 13695 33.18 32.73– 13632 32.77 32.32– 35.28 34.93 33.95 33.64 33.22 35–39.9 9205 21.34 20.95– 9503 22.41 22.02– 9960 23.81 23.41– 9895 23.97 23.56– 10269 24.69 24.27– 21.72 22.81 24.22 24.39 25.10 �40 1963 4.55 4.36–4.75 2015 4.75 4.55–4.96 2227 5.32 5.11–5.54 2453 5.94 5.72–6.18 2676 6.43 6.20–6.67 Nationality Spain 27116 62.85 62.39– 26428 62.33 61.87– 26314 62.91 62.45– 25503 61.78 61.31– 25886 62.23 61.76– 63.30 62.80 63.38 62.25 62.69 Rest of Europe and 2591 6.01 5.78–6.23 2643 6.23 6.01–6.47 2712 6.48 6.25–6.72 2707 6.56 6.32–6.80 2835 6.82 6.57–7.06 Central Asia Middle East and North 5830 13.51 13.19– 5442 12.84 12.52– 5430 12.98 12.66– 5559 13.47 13.14– 5634 13.54 13.22– Africa 13.84 13.16 13.31 13.80 13.88 Latin América and 4368 10.12 9.84– 4555 10.74 10.45– 4246 10.15 9.86– 4302 10.42 10.13– 3889 9.35 9.07–9.63 Caribbean 10.41 11.04 10.45 10.72 East Asia and Pacific 992 2.3 2.16–2.45 1007 2.38 2.23–2.52 802 1.92 1.79–2.05 841 2.04 1.90–2.18 790 1.9 1.77–2.03 Subsaharian Africa 1138 2.64 2.49–2.79 1130 2.67 2.51–2.82 1163 2.78 2.63–2.94 1118 2.71 2.55–2.87 1075 2.58 2.43–2.74 South Asia 1094 2.54 2.39–2.69 1152 2.72 2.56–2.88 1133 2.71 2.56–2.87 1216 2.95 2.78–3.11 1463 3.52 3.34–3.70 North America 16 0.04 0.02–0.06 40 0.09 0.07–0.13 25 0.06 0.04–0.09 32 0.08 0.05–0.11 27 0.06 0.04–0.09 Socioeconomic status Disadvantaged population 2516 5.83 5.61–6.06 2123 5.01 4.80–5.22 2200 5.26 5.05–5.48 2349 5.69 5.47–5.92 2270 5.46 5.24–5.68 Income <18.000 32238 74.72 74.31– 32517 76.7 76.29– 32393 77.45 77.05– 31703 76.8 76.39– 31246 75.11 74.69– 75.13 77.10 77.85 77.21 75.53 Income 18.000–100.000 8369 19.4 19.03– 7740 18.26 17.89– 7208 17.23 16.87– 7202 17.45 17.08– 8057 19.37 18.99– 19.77 18.63 17.60 17.82 19.75 Income >100.000 22 0.05 0.03–0.08 17 0.04 0.02–0.06 24 0.06 0.04–0.09 24 0.06 0.04–0.09 26 0.06 0.04–0.09 Healthcare facility Level IA 13375 31 30.56– 12757 30.09 29.65– 12660 30.27 29.83– 12140 29.41 28.97– 11813 28.4 27.96– 31.44 30.53 30.71 29.85 28.83 (Continued ) PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 6 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 Table 1. (Continued) Year 2013 Year 2014 Year 2015 Year 2016 Year 2017 n = 43145 n = 42397 n = 41825 n = 41275 n = 41599 n % 95% CI n % 95% CI n % 95% CI n % 95% CI n % 95% CI Level IIA 7070 16.39 16.04– 7032 16.59 16.23– 6694 16 15.65– 6356 15.4 15.05– 6406 15.4 15.05– 16.74 16.94 16.36 15.75 15.75 Level IIB 6666 15.45 15.11– 6602 15.57 15.23– 6557 15.68 15.33– 6591 15.97 15.62– 7107 17.08 16.72– 15.79 15.92 16.03 16.32 17.45 Level IIIA 10566 24.49 24.08– 10526 24.83 24.42– 10547 25.22 24.80– 10577 25.62 25.20– 10442 25.1 24.69– 24.90 25.24 25.64 26.05 25.52 Level IIIB 5468 12.67 12.36– 5480 12.93 12.61– 5367 12.83 12.51– 5614 13.6 13.27– 5831 14.02 13.68– 12.99 13.25 13.16 13.93 14.35 Fetal presentation Cephalic 41833 96.96 96.79– 41123 97 96.83– 40503 96.84 96.67– 40040 97 96.83– 40324 96.94 96.76– 97.12 97.16 97.00 97.16 97.10 Breech 1122 2.6 2.45–2.76 1067 2.52 2.37–2.67 1154 2.76 2.60–2.92 1061 2.57 2.42–2.73 1090 2.62 2.47–2.78 Oblique/Transverse 190 0.44 0.38–0.51 207 0.49 0.42–0.56 168 0.4 0.34–0.47 177 0.43 0.37–0.50 185 0.44 0.38–0.51 Gestational age � 37 weeks term 40492 93.85 93.62– 39822 93.93 93.69– 39383 94.16 93.93– 38811 94.02 93.79– 39194 94.22 93.99– 94.08 94.15 94.38 94.25 94.44 <37 weeks preterm 2653 6.15 5.92–6.38 2575 6.07 5.85–6.31 2442 5.84 5.62–6.07 2467 5.98 5.75–6.21 2405 5.78 5.56–6.01 Pregnancy complication No 28616 66.33 65.88– 27274 64.33 63.87– 27054 64.68 64.22– 26254 63.6 63.14– 26266 63.14 62.68– 66.77 64.79 65.14 64.07 63.60 Yes 14529 33.67 33.23– 15123 35.67 35.21– 14771 35.32 34.86– 15024 36.4 35.93– 15333 36.86 36.40– 34.12 36.13 35.78 36.86 37.32 Number of neonates Singleton 42360 98.18 98.05– 41589 98.09 97.96– 41047 98.14 98.01– 40426 97.94 97.79– 40781 98.03 97.90– 98.30 98.22 98.27 98.07 98.16 Multiple 785 1.82 1.70–1.95 808 1.91 1.78–2.04 778 1.86 1.73–1.99 852 2.06 1.93–2.21 818 1.97 1.84–2.10 Robson classification Group 1+2 14505 33.62 33.17– 13761 32.46 32.01– 12940 30.94 30.50– 12379 29.99 29.55– 12542 30.15 29.71– 34.07 32.91 31.38 30.43 30.59 Group 3+4 20335 47.13 46.66– 20425 48.18 47.70– 20616 49.29 48.81– 20678 50.09 49.61– 20723 49.82 49.33– 47.60 48.65 49.77 50.58 50.30 Group 5 4210 9.76 9.48– 4203 9.91 9.63– 4304 10.29 10.00– 4316 10.46 10.16– 4455 10.71 10.41– 10.04 10.20 10.59 10.76 11.01 Group 6 532 1.23 1.13–1.34 499 1.18 1.08–1.28 526 1.26 1.15–1.37 431 1.04 0.95–1.15 450 1.08 0.98–1.19 Group 7 487 1.13 1.03–1.23 469 1.11 1.01–1.21 525 1.26 1.15–1.37 507 1.23 1.12–1.34 524 1.26 1.15–1.37 Group 8 785 1.82 1.70–1.95 808 1.91 1.78–2.04 778 1.86 1.73–1.99 852 2.06 1.93–2.21 818 1.97 1.84–2.10 Group 9 159 0.37 0.31–0.43 178 0.42 0.36–0.49 145 0.35 0.29–0.41 140 0.34 0.29–0.40 163 0.39 0.33–0.46 Group 10 2132 4.94 4.74–5.15 2054 4.84 4.64–5.05 1991 4.76 4.56–4.97 1975 4.78 4.58–4.99 1924 4.63 4.43–4.83 n = 29804 n = 29602 n = 29257 n = 29272 n = 29338 Body Mass Index BMI <18.5 533 1.79 1.64–1.95 590 1.99 1.84–2.16 586 2 1.85–2.17 580 1.98 1.82–2.15 605 2.06 1.90–2.23 18.5–24.9 13496 45.28 44.72– 13504 45.62 45.05– 13292 45.43 44.86– 13085 44.7 44.13– 12732 43.4 42.83– 45.85 46.19 46.00 45.27 43.97 25–29.9 10100 33.89 33.35– 9894 33.42 32.89– 9753 33.34 32.80– 9669 33.03 32.49– 9847 33.56 33.02– 34.43 33.96 33.88 33.57 34.11 30–34.9 4047 13.58 13.19– 4018 13.57 13.19– 4034 13.79 13.39– 4252 14.53 14.12– 4364 14.87 14.47– 13.97 13.97 14.19 14.93 15.29 35–39.9 1205 4.04 3.82–4.27 1178 3.98 3.76–4.21 1192 4.07 3.85–4.31 1240 4.24 4.01–4.47 1345 4.58 4.35–4.83 �40 423 1.42 1.29–1.56 418 1.41 1.28–1.55 400 1.37 1.24–1.51 446 1.52 1.39–1.67 445 1.52 1.38–1.66 https://doi.org/10.1371/journal.pone.0234727.t001 PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 7 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 remain similar. In particular, women between 35 and 40 presented a 37% higher chance of CS, and women over 40, twice the likelihood of having a CS than women aged between 25 and 30 (Table 2). In comparison to Spanish women (24.45%), higher rates of CS were found in women from sub-Saharan Africa (27.19%), Latin America and the Caribbean (27.27%) and South Asia (27.89%) (S2 Table). These groups remained similar after adjusting for confounders (Table 2). The variable of socioeconomic level revealed that women with an income of over 18.000€ showed less probability of CS. Differences were also noted relating to the complexity level of the hospital, with Level IIIB undertaking the highest number and Level IA the least (Level IIIB compared to Level IA, crude OR 1.37, 95% CI 1.33–1.42). However, these differences can be explained when adjusting for confounders (Level IIIB compared to Level IA OR 1.07, 95% CI 1.03–1.11). Moreover, as expected, women with any diagnosis potentially complicating the pregnancy had a higher probability of CS, even when adjusting for other confounders (OR 1.44, 95% CI 1.41–1.47) (Table 2). Trends over time in caesarean section rates among the modified Robson groups The overall CS rate steadily declined between 2013 and 2017. The following figures show each of the obstetric groups according to the modified Robson classification during the five years of the study period: Fig 2, the CS rate; Fig 3, the relative size of the obstetric population; and Fig 4, the absolute contribution to the overall CS rate. Within the population sample, the majority of women carried single babies at term in cephalic presentation and belonged to groups 1+2 and 3+4 (31.45% and 48.88%, respectively), followed by multiparous women with a uterine scar (10.22%) and women with premature babies (4.79%). The CS rate was lowest for groups 1+2 and 3+4 and highest (i.e. almost 100%) for groups 6, 7 and 9. Group 5 had an average rate of 54.73%; Group 8 63.33% and Group 10 35.34% (see Fig 2). Most groups demonstrated a subtle downwards tendency in CS rates observed in the graph. The major contributors to the absolute CS rates were groups 1+2, 3+4 and 5. The consider- able reduction in group 1+2 was due to the reduced group size and CS rates. By contrast, group 5 showed an increased overall contribution due to the increasement on the size. It has been established that high-risk pregnancies are a risk factor for CS. The initial analy- ses revealed that the probability of CS in 2017 was, in comparison to 2013, reduced by 8% (OR 0.92, 95% CI 0.89–0.95) (Table 3). However, the profile of women described in Table 1 revealed a significant increase in known risk factors for CS (i.e. age or pregnancy complica- tions). Thus, the analysis adjusted by confounders showed that there was even less probability in comparison to 2013 i.e. 13% (OR 0.87, 95% CI 0.84–0.90). The significant reduction in CS rates was already observed in 2015 (OR 0.96, CI 95% 0.92–0.99) and maintained throughout 2016 (OR 0.93, 95% CI 0.90–0.97) (Table 3). Adjusted odds ratios for the different Robson groups were also estimated, apart from groups 6 to 9, which presented very small sample size. Women in groups 1+2 had a 12% (OR 0.88, 95% CI 0.83–0.93) lower chance of having a CS, with women in groups 3+4 experiencing 17% (OR 0.83, 95% CI 0.78–0.89). Women having premature babies (Group 10) presented a 22% lower chance, although wide CI were obtained due to the sample size (OR 0.78, 95% CI 0.68–0.90). Nevertheless, the reduction was not observed in every group, since Group 5 dem- onstrated no significant differences for any of the years (OR 0.95, 95% CI 0.87–1.03, 2017) (Table 3). PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 8 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 Table 2. Association between caesarean section and socio-demographic and obstetric characteristics. Crude odd ratio Adjusted odd ratio OR 95% CI p-value OR 95% CI p-value Maternal age years <20 0.65 0.60–0.70 <0.001 0.64 0.59–0.69 <0.001 20–24.9 0.79 0.76–0.82 <0.001 0.82 0.78–0.86 <0.001 25–29.9 1 1 30–34.9 1.16 1.13–1.20 <0.001 1.1 1.07–1.14 <0.001 35–39.9 1.5 1.46–1.55 <0.001 1.37 1.33–1.42 <0.001 �40 2.25 2.15–2.35 <0.001 2 1.90–2.10 <0.001 Nationality Spain 1 1 Rest of Europe and Central Asia 0.84 0.80–0.88 <0.001 0.86 0.82–0.90 <0.001 Middle East and North Africa 0.71 0.69–0.73 <0.001 0.77 0.74–0.80 <0.001 Latin America and Caribbean 1.16 1.12–1.20 <0.001 1.16 1.12–1.21 <0.001 East Asia and Pacific 0.65 0.60–0.70 <0.001 0.7 0.64–0.76 <0.001 Sub-Saharian Africa 1.15 1.09–1.23 <0.001 1.21 1.12–1.29 <0.001 South Asia 1.19 1.13–1.27 <0.001 1.15 1.07–1.22 <0.001 North America 0.51 0.32–0.83 0.006 0.49 0.29–0.82 0.007 Socioeconomic status Disadvantaged population 0.84 0.81–0.89 <0.001 0.9 0.86–0.96 <0.001 Income <18.000 € 1 1 Income 18.000–100.000 € 1.07 1.04–1.09 <0.001 0.87 0.85–0.90 <0.001 Income >100.000 € 0.73 0.46–1.18 0.002 0.47 0.27–0.80 0.006 Healthcare facility Level IA 1 1 Level IIA 1.03 1.00–1.06 0.065 0.95 0.92–0.99 0.001 Level IIB 1.06 1.02–1.09 0.001 0.94 0.90–0.97 <0.001 Level IIIA 1.2 1.17–1.23 <0.001 1.09 1.05–1.12 <0.001 Level IIIB 1.37 1.33–1.42 <0.001 1.07 1.03–1.11 <0.001 Pregnancy complication No 1 1 Yes 1.43 1.41–1.46 <0.001 1.44 1.41–1.47 <0.001 Robson classification Group 1+2 1 1 Group 3+4 0.38 0.37–0.39 <0.001 0.36 0.35–0.37 <0.001 Group 5 3.87 3.75–4.00 <0.001 3.55 3.43–3.67 <0.001 Group 6 141.44 107.94–185.34 <0.001 145.07 110.67–190.16 <0.001 Group 7 78.92 64.44–96.66 <0.001 78.29 63.89–95.94 <0.001 Group 8 5.53 5.18–5.91 <0.001 4.91 4.59–5.26 <0.001 Group 9 86.62 59.38–126.36 <0.001 74.67 51.14–109.03 <0.001 Group 10 1.75 1.67–1.83 <0.001 1.59 1.52–1.66 <0.001 https://doi.org/10.1371/journal.pone.0234727.t002 It was thus established that fewer CS were performed in Catalonia between 2013 and 2017. Within the years that showed the greatest decrease (p-value <0.05) 2015, 2016, 2017 in CS, up to 2.319 CS (95% CI, 1399–3239) were avoided. Model validation showed that the crude analysis which included all women was well cali- brated and had a high grade of discrimination (calibration belt p-value: 0.915, ROC 0.75, 95% 0.74–0.75), however once the model was adjusted the calibration was dramatically affected (p- PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 9 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 Fig 2. Caesarean section rate. https://doi.org/10.1371/journal.pone.0234727.g002 value 0.01) while the discriminant ability remained similar (ROC 0.77, IC 95% 0.76–0.77). The analysis of the different Robson groups showed good calibration but little discriminatory effect. Discussion Main findings This study identified a significant decrease in CS rates in publicly funded hospitals in Catalonia between 2013 and 2017. When adjusted the CS rates for well-known risk factors, the reduction was even more pronounced. Considering that the characteristics of women are evolving into a higher risk profiles, this means that in equal conditions there are now less CS performed. It is important to note that nulliparous (Group 1+2), multiparous (Group 3+4) and multip- arous women with previous CS (Group 5) contributed most to the overall CS rate, suggesting that possibly are the groups that present larger margins for interventions on the aim of reduc- ing final percentages of CS. Strengths The most significant contribution of this study is the analysis of the individual level data from administrative registries. It enabled the analysis of CS rates for each group of Robson, rather Fig 3. Relative size of the obstetric population. https://doi.org/10.1371/journal.pone.0234727.g003 PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 10 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 Fig 4. Absolute contribution to overall caesarean section rates. https://doi.org/10.1371/journal.pone.0234727.g004 than for the population, as simplified to a single number. Also, the large sample provided an important statistical power to the evidence shown and is innovative since includes adjustment variables not yet examined together in this type of research before. A considerable difference in CS rates was identified between public and private settings in Catalonia [25]. The focus on deliveries in publicly funded hospitals excluded CS on demand, thus avoiding any possible bias. To the best of the current researcher’s knowledge, this is the first time the Robson classifica- tion has been implemented at a population level, within the Mediterranean countries, employ- ing real world data and with consideration of so many confounders. The results could potentially be generalized to other Southern European countries with a similar healthcare framework. Limitations The categorisation of the 10 groups of Robson was constrained by not having the variable onset of labour recorded, therefore a modified version of the Robson classification had to be created. Also, the registry does not collect some other variables which they had to be created ad hoc, i.e. foetal presentation, which was considered cephalic in the absence of a diagnosis of breech or transverse lie. When performing the crosscheck analysis with the measures for data collection quality suggested at the Robson Implementation Manual [32], the parameters in general showed consistency with those proposed. However, having to create the variable pre- sentation ad hoc implied that not all of them were actually transverse, because CS for Group 9 did not end up being 100%. Also, creating variables ad hoc implied a lack of unclassified cases, which is considered another parameter to measure data collection quality. The variable BMI had many omissions and therefore could not be included as an adjusting factor. However, the sensibility analysis showed a similar decrease in CS rates (S3 Table). The analysis of the missing data on the primary outcome revealed more nulliparous than multipa- rous women (S4 Table). However, in view of the small percentage (6%) it was believed that it did not imply deliberate avoidance by hospitals of reporting CS. Furthermore, it was consid- ered that due to the large study sample, results would not have changed significantly. As well as the variable of “pregnancy complication” that since relies on the provider’s clinical diagno- sis, could be prone to bias. This study sample tended to under-represent the highest socioeconomic category, due to private care, but in general, found no differences in CS rates between extreme socioeconomic PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 11 / 17 Table 3. Time trends in caesarean section rates in all women and by groups of Robson. PLOS ONE Calibration Area under 2013⌂ 2014 2015 2016 2017 belt p-value� the ROC curve Area CS rate CI95% OR CS rate CI95% OR CI95% CS rate CI95% OR CI95% CS rate CI95% OR CI95% CS rate CI95% OR CI95% CI95% Crude All 0.915 0.75 0.74– 24.3 23.90– 1 24.21 23.80– 0.99 0.96– 23.96 23.56– 0.98 0.95– 23.63 23.22– 0.96 0.93– 22.8 22.40– 0.92 0.89– 0.75 24.71 24.61 1.03 24.37 1.01 24.04 0.99� 23.20 0.95��� Robson 1 1 0.51 0.50– 24.5 23.80– 1 23.98 23.27– 0.97 0.92– 23.77 23.04– 0.96 0.91– 23.7 22.95– 0.96 0.90– 22.86 22.12– 0.91 0.86– +2 0.51 25.20 24.69 1.03 24.50 1.02 24.44 1.01 23.59 0.97��� Robson 3 1 0.51 0.50– 10.94 10.51– 1 11.05 10.62– 1.01 0.95– 10.88 10.45– 0.99 0.93– 10.41 10.00– 0.95 0.89– 9.49 9.09– 0.85 0.80– +4 0.51 11.37 11.48 1.08 11.30 1.06 10.83 1.01 9.89 0.91�� Robson 5 1 0.51 0.50– 54.35 52.84– 1 55.86 54.36– 1.06 0.98– 55.04 53.56– 1.03 0.94– 54.89 53.40– 1.02 0.94– 53.58 52.12– 0.97 0.89– 0.51 55.85 57.37 1.16 56.53 1.12 56.37 1.11 55.04 1.06 Robson 1 0.50 0.50,- 37.2 35.14– 1 35.54 33.47– 0.93 0.82– 33.7 31.63– 0.86 0.76– 36.2 34.08– 0.96 0.84– 33.89 31.77– 0.87 0.76– 10 0.51 39.25 37.61 1.06 35.78 0.98� 38.32 1.09 36.00 0.98� Adjusted PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 All† 0.01 0.77 0.76– 24.56 24.20– 1 24.29 23.93– 0.98 0.95– 23.9 23.54– 0.96 0.92– 23.59 23.22– 0.93 0.90– 22.56 22.20– 0.87 0.84– 0.77 24.92 24.65 1.02 24.26 0.99� 23.95 0.97��� 22.92 0.90��� Robson 1 0.17 0.59 0.59– 24.92 24.23– 1 24 23.29– 0.95 0.90– 23.72 22.99– 0.93 0.88– 23.52 22.78– 0.92 0.87– 22.61 21.89– 0.88 0.83– +2• 0.60 25.62 24.70 1.00 24.44 0.99� 24.26 0.98�� 23.33 0.93��� Robson 3 0.86 0.59 0.58– 11.14 10.70– 1 11.05 10.62– 0.99 0.93– 10.81 10.39– 0.97 0.91– 10.33 9.92– 0.92 0.86– 9.45 9.05– 0.83 0.78– +4• 0.59 11.57 11.48 1.05 11.23 1.03 10.75 0.98�� 9.85 0.89��� Robson 0.74 0.59 0.58– 54.64 53.15– 1 55.97 54.48– 1.06 0.97– 55.15 53.68– 1.02 0.94– 54.69 53.22– 1 0.92– 53.29 51.84– 0.95 0.87– 5• 0.59 56.13 57.46 1.15 56.62 1.11 56.17 1.09 54.74 1.03 Robson 0.76 0.58 0.57– 37.97 36.01– 1 36.12 34.15– 0.91 0.80– 34.11 32.13– 0.83 0.73– 35.47 33.48– 0.89 0.77– 32.9 30.92– 0.78 0.68– 10• 0.58 39.92 38.09 1.05 36.10 0.95�� 37.47 1.01 34.88 0.90��� ⌂Reference group † Adjusted for maternal age, nationality, socioeconomic status, healthcare facility, pregnancy complication, delivery year and modified Robson classification. • Adjusted for maternal age, nationality, socioeconomic status, healthcare facility, pregnancy complication, delivery year and modified Robson classification. �Goodness of fit assuming polynomial relationship � p-value <0.05 �� p-value <0.01 ��� p-value<0.001 https://doi.org/10.1371/journal.pone.0234727.t003 12 / 17 CS trend in Catalonia by Robson classification system 2013-2017 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 levels. The numbers suggested that more Catalan nulliparous women attended the private sec- tor, as this sample was constituted of 35.81% nulliparous and 64.19% multiparous, while national statistics showed about 50% [27]. Regarding the statistical analysis, the purpose of the study hampered the possibility of applying a multi-level approach. Although it is realistic to think that same women could have delivered more than once within the study period, the magnitude of the population sample should still provide relevant and valuable results. Interpretation Following adjustment for individual risk factors, CS rates decreased in Catalonia between 2013 and 2017. However, comparison with other countries and aiming for optimal rates suggests scope for improvement [26,35]. Our study founds similar patterns to that observed in other European countries, groups 1 to 5 are the once contributing the most to the final CS rate [35]. However, attention should be paid to the reduced proportion of nulliparous women in the study sample, since this made the highest contribution to the overall CS rate and would had been higher in the absence of private care. In addition, the evidence suggests that optimising CS rates requires focusing attention on groups 1 to 5. However, the ability to prioritize interventions as a result of our study is com- promised by the inability to determine the onset of labour. CS rates in Group 5 (i.e. women with previous CS) reflected the obstetric practice of previ- ous years. It is particularly linked to CS performed on nulliparous women, and will therefore, if this continues to decrease, be reflected in Group 5. Also suggests that trial of labour following CS (TOLAC) should be prioritized in favour of optimum levels [36]. Rates for women with breech presentations remained the same in our study (groups 6 and 7). Following the Term Breech Trials results, CS for breech rapidly increased worldwide [37]. Spanish guidelines have recently upheld considering vaginal birth acceptable under some cir- cumstances [38,39], with some hospitals in Catalonia now resuming them, although it will take time for numbers to reflect any change. Facilitating the external cephalic version, is in any case the preferred option, also for transverse presentations (group 9) [40–42]. The reason behind the overall decrease remains unclear. The protocol to promote natural birth [43], the adequacy of indications, the creation of an adjusted index for CS [44] or grow- ing evidence of the risks that implies the CS [45] could only be some of the reasons behind. In addition, the fourth-wave of feminism, international organisations on birth-rights together with local organisations or growing eco on the media regarding obstetric violence, could have also influenced this reduction [46,47]. Furthermore, the application of systematic Robson classification has been suggested to con- tribute on the decrease of CS rates. In line with this, interventions and indications should also be audited. CS rates can be safely reduced by applying multifaceted strategies combining audit and feedback, implementing guidelines on mandatory second opinion or educating physicians by local opinion leaders [1,48]. In addition, midwife-led continuity models of care have also proved beneficial, including reducing CS for low risk women [49–51]. In Catalonia, one out of the seven projected midwifery-led units is already functioning. However, midwife ratios in Spain continue to be one of the lowest across European countries [52]. This analysis hopes to provide useful information to the public, public health experts and health professionals, however, does not intend to replace in any case the original Robson clas- sification. It should only be a temporary tool until all needed variables are systematically recorded. PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 13 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 Conclusion This study found a significant decrease in CS rates in Catalonia between 2013–2017. Provides evidence that group 1+2, 3+4 and 10 are the groups that have shown the highest reduction after adjusting for confounders and suggests retrospective overutilization of CS and percent- ages of (in)adequacy in the past. Special attention should be paid to groups 1 to 5 since they imply the biggest contributors to the overall CS rates, and any reduction would imply a consid- erable reduction in the total rate. The reasons behind remains unclear and further efforts should be made as rates remain above optimum levels. Including the Robson classification as a systematic way to analyse CS could be very useful to compare, assess and analyse data and prioritize, however all variables including onset of labour are necessary. Hence, policy makers should give urgent attention to the collection of perinatal data. Supporting information S1 Checklist. STROBE checklist. (DOCX) S1 Table. Diagnostic codes included in the variable pregnancy complication. (DOCX) S2 Table. Bivariate analysis of socio-demographic and obstetric characteristics and type of delivery. (DOCX) S3 Table. Time trends in caesarean section rates including the variable BMI by groups of Robson. (DOCX) S4 Table. Socio-demographic and obstetric characteristics of study population by type of delivery. (DOCX) Acknowledgments The authors thank all the stimulating discussions and guidance from the following: Alba Oli- ver-Parra (UPF), Cristina Colls-Guerra (AQuAS), Cari Almazán-Sáez (AQuAS) and Mercè Armelles-Sebastiá (Maternal and Child Health Services, Catalonian Public Health Agency, Department of Health). Author Contributions Conceptualization: Garazi Carrillo-Aguirre, Albert Dalmau-Bueno. Data curation: Garazi Carrillo-Aguirre, Albert Dalmau-Bueno. Formal analysis: Garazi Carrillo-Aguirre. Methodology: Garazi Carrillo-Aguirre, Albert Dalmau-Bueno, Carlos Campillo-Artero. Project administration: Albert Dalmau-Bueno, Anna Garcı́a-Altés. Writing – original draft: Garazi Carrillo-Aguirre. Writing – review & editing: Garazi Carrillo-Aguirre, Albert Dalmau-Bueno, Carlos Cam- pillo-Artero, Anna Garcı́a-Altés. PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 14 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 References 1. Chen I, Opiyo N, Tavender E, Mortazhejri S, Rader T, Petkovic J, et al. Non-clinical interventions for reducing unnecessary caesarean section. Cochrane Database Syst Rev [Internet]. 2018 Sep 28 [cited 2019 May 2]; 9:CD005528. Available from: http://www.ncbi.nlm.nih.gov/pubmed/30264405 https://doi. org/10.1002/14651858.CD005528.pub3 PMID: 30264405 2. Villar J, Carroli G, Zavaleta N, Donner A, Wojdyla D, Faundes A, et al. Maternal and neonatal individual risks and benefits associated with caesarean delivery: multicentre prospective study. BMJ [Internet]. 2007 Nov 17 [cited 2019 Jan 18]; 335(7628):1025. Available from: http://www.ncbi.nlm.nih.gov/ pubmed/17977819 https://doi.org/10.1136/bmj.39363.706956.55 PMID: 17977819 3. Boerma T, Ronsmans C, Melesse DY, Barros AJD, Barros FC, Juan L, et al. Global epidemiology of use of and disparities in caesarean sections. Lancet [Internet]. 2018 Oct [cited 2018 Nov 17]; 392 (10155):1341–8. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0140673618319287 https://doi.org/10.1016/S0140-6736(18)31928-7 PMID: 30322584 4. Betrán AP, Ye J, Moller A-B, Zhang J, Gülmezoglu AM, Torloni MR. The Increasing Trend in Caesarean Section Rates: Global, Regional and National Estimates: 1990–2014. Zeeb H, editor. PLoS One [Inter- net]. 2016 Feb 5 [cited 2019 Apr 22]; 11(2):e0148343. Available from: http://www.ncbi.nlm.nih.gov/ pubmed/26849801 https://doi.org/10.1371/journal.pone.0148343 PMID: 26849801 5. Betran AP, Torloni MR, Zhang JJ, Gülmezoglu AM. WHO statement on caesarean section rates [Inter- net]. Vol. 123, BJOG: An International Journal of Obstetrics and Gynaecology. 2016 [cited 2019 Apr 22]. p. 667–70. Available from: https://apps.who.int/iris/bitstream/handle/10665/161442/WHO_RHR_ 15.02_eng.pdf;jsessionid=05AB78E8403CF090AFCFD9FB79994350?sequence=1 6. Molina G, Weiser TG, Lipsitz SR, Esquivel MM, Uribe-Leitz T, Azad T, et al. Relationship Between Cesarean Delivery Rate and Maternal and Neonatal Mortality. JAMA [Internet]. 2015 Dec 1 [cited 2019 Jan 14]; 314(21):2263. Available from: http://jama.jamanetwork.com/article.aspx?doi=10.1001/jama. 2015.15553 PMID: 26624825 7. Betran AP, Torloni MR, Zhang J, Ye J, Mikolajczyk R, Deneux-Tharaux C, et al. What is the optimal rate of caesarean section at population level? A systematic review of ecologic studies. Reprod Health [Inter- net]. 2015 Dec 21 [cited 2018 Nov 17]; 12(1):57. Available from: http://reproductive-health-journal. biomedcentral.com/articles/10.1186/s12978-015-0043-6 8. Ye J, Zhang J, Mikolajczyk R, Torloni M, Gülmezoglu A, Betran A. Association between rates of caesar- ean section and maternal and neonatal mortality in the 21st century: a worldwide population-based eco- logical study with longitudinal data. BJOG An Int J Obstet Gynaecol [Internet]. 2016 Apr [cited 2018 Nov 17]; 123(5):745–53. Available from: http://doi.wiley.com/10.1111/1471-0528.13592 9. Ye J, Betrán AP, Guerrero Vela M, Souza JP, Zhang J. Searching for the Optimal Rate of Medically Necessary Cesarean Delivery. Birth [Internet]. 2014 Sep [cited 2019 Jan 14]; 41(3):237–44. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24720614 https://doi.org/10.1111/birt.12104 PMID: 24720614 10. Hyde MJ, Modi N. The long-term effects of birth by caesarean section: The case for a randomised con- trolled trial. Early Hum Dev [Internet]. 2012 Dec [cited 2018 Nov 20]; 88(12):943–9. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0378378212002198 https://doi.org/10.1016/j.earlhumdev. 2012.09.006 PMID: 23036493 11. Barber EL, Lundsberg LS, Belanger K, Pettker CM, Funai EF, Illuzzi JL. Contributing Indications to the Rising Cesarean Delivery Rate. Obstet Gynecol [Internet]. 2011 Jul [cited 2019 Jan 18]; 118(1):29–38. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21646928 https://doi.org/10.1097/AOG. 0b013e31821e5f65 PMID: 21646928 12. Betrán AP, Temmerman M, Kingdon C, Mohiddin A, Opiyo N, Torloni MR, et al. Interventions to reduce unnecessary caesarean sections in healthy women and babies. Lancet [Internet]. 2018 Oct [cited 2019 Jan 16]; 392(10155):1358–68. Available from: https://linkinghub.elsevier.com/retrieve/pii/ S0140673618319275 https://doi.org/10.1016/S0140-6736(18)31927-5 PMID: 30322586 13. Souza J, Gülmezoglu A, Lumbiganon P, Laopaiboon M, Carroli G, Fawole B, et al. Caesarean section without medical indications is associated with an increased risk of adverse short-term maternal out- comes: the 2004–2008 WHO Global Survey on Maternal and Perinatal Health. BMC Med [Internet]. 2010 Dec 10 [cited 2018 Nov 17]; 8(1):71. Available from: http://bmcmedicine.biomedcentral.com/ articles/10.1186/1741-7015-8-71 14. Social D de S i S. Pla de salut de Catalunya 1996–1998 [Internet]. 1997. Available from: http://salutweb. gencat.cat/web/.content/_departament/pla-de-salut/Plans-de-salut-anteriors/Pla-de-salut-de- Catalunya-1996-1998/documents/problemes_salutmaternitat98.pdf 15. Generalitat de Catalunya. Departament de Salut. Pla de salut de Catalunya 2002–2005. Departament de Salut [Internet]. [cited 2019 Jun 19]. Available from: http://salutweb.gencat.cat/ca/el_departament/ Pla_salut/plans-de-salut-anteriors/pla-de-salut-de-catalunya-2002-2005/ PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 15 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 16. Servei Català de la Salut. Pla de salut de la Regió Sanitària Barcelona a l ‘ horitzó 2010 Volum II les polı́- tiques de salut [Internet]. 2010 [cited 2019 Jun 19]. Available from: https://catsalut.gencat.cat/web/. content/minisite/catsalut/catsalut_territori/barcelona/coneix_la_regio_sanitaria_barcelona/pla_ territorial_de_salut/pla_de_salut_rsb_vol02.pdf 17. Sanitari De Barcelona C. Pla de salut territorial [Internet]. 2012 [cited 2019 Jun 19]. Available from: http://www.csb.cat/wp-content/uploads/2015/04/Pla-de-salut-CSB-2011-2015.pdf 18. Catalunya G de; D de S. Pla de Salut 2016–2020 [Internet]. Pla de Salut de Catalunya 2016–2020. 2016. 161 p. Available from: http://salutweb.gencat.cat/web/.content/home/el_departament/Pla_salut/ pla_salut_2016_2020/Documents/Pla_salut_Catalunya_2016_2020.pdf 19. Generalitat de Catalunya. Departamento de Salud. Protocolo para la asistencia natural al parto normal Biblioteca de Cataluña. Datos CIP Protocolo para la asistencia natural al parto normal Bibliografı́a [Internet]. 2007 [cited 2019 Jun 18]. Available from: https://www.elpartoesnuestro.es/sites/default/files/ recursos/documents/protocolo_asistencia_parto_normal_cataluna_2007.pdf 20. Cossio MLT, Giesen LF, Araya G, Pérez-Cotapos MLS, Vergara RL, Manca M, et al. Guı́a para embar- azadas. General Catalunya Dep Salut [Internet]. 2009 [cited 2019 Jan 20]; XXXIII(2):81–7. Available from: http://www.anaelbusto.info/guiaembarcataluna.pdf 21. Pública DG de S. Protocol de seguiment de l’embaràs a Catalunya [Internet]. Generalitat de Catalunya. Departament de Salut. Barcelona; 2018 [cited 2019 Jan 20]. Available from: http://salutpublica.gencat. cat/web/.content/minisite/aspcat/promocio_salut/embaras_part_puerperi/protocol_seguiment_ embaras/protocol-seguiment-embaras-2018.pdf 22. Agència de Qualitat i Avaluació Sanitàries de Catalunya. Central de Resultats [Internet]. Barcelona; 2015. Available from: http://observatorisalut.gencat.cat/web/.content/minisite/observatorisalut/ossc_ central_resultats/informes/fitxers_estatics/CdR_Hospitals_dades_2015.pdf 23. Spanish Ministry of Health. Strategy for Assitance at Normal Childbirth in the National Health System 2007. 2008; Available from: http://www.msssi.gob.es/organizacion/sns/planCalidadSNS/pdf/equidad/ estrategiaPartoNormalEnglish.pdf 24. Ministerio de Sanidad y Polı́tica Social. Gobierno de España. Guı́a de práctica clı́nica de atención al parto normal [Internet]. 2010. 103 p. Available from: http://www.guiasalud.es/GPC/GPC_472_Parto_ Normal_Osteba_compl.pdf%0Ahttp://www.msssi.gob.es/organizacion/sns/planCalidadSNS/pdf/ InformeFinalEAPN_revision8marzo2015.pdf 25. Jané Checa M, Vidal Benedé MJ, Tomás Bonodo Z, Maresma Soler M. Indicadors de salut perinatal a Catalunya. Any 2017 [Internet]. Barcelona; 2018 [cited 2018 Nov 22]. Available from: http://canalsalut. gencat.cat/ca/professionals/vigilancia-epidemiologica/vigilancia-perinatal/ 26. EURO-PERISTAT. European Perinatal Health Report: http://www.europeristat.com. 2015; Available from: www.europeristat.com 27. Generalitat de Catalunya. Idescat. Anuario estadı́stico de Cataluña. Indicadores de natalidad [Internet]. 2019 [cited 2019 Apr 28]. Available from: https://www.idescat.cat/pub/?id=aec&n=287&lang=es 28. Sociedad Española de Ginecologia y Obstetricia (SEGO). documentoconsensoSEGO.pdf—Google Drive [Internet]. [cited 2019 Nov 5]. Available from: https://drive.google.com/file/d/ 0ByuDDZFNh88AZGNjMGY5NDctMDYzNi00OGM5LWJkZjMtZmM3MDc2ZmM2ZWMx/view 29. Ministerio de Sanidad C y BS. Conjunto Mı́nimo Básico de Datos—Hospitalización. 2019 [cited 2019 May 3]; Available from: http://www.iasist.com/es/2181/Conjunto-Minimo-Basico-de-Datos-CMBD 30. Generalitat de Catalunya. Registre central de població del CatSalut. CatSalut. Servei Català de la Salut [Internet]. 2019 [cited 2019 May 3]. Available from: https://catsalut.gencat.cat/ca/proveidors- professionals/registres-catalegs/registres/central-poblacio/ 31. Generalitat de Catalunya. eCAP. Departament de Salut [Internet]. 2018 [cited 2019 May 3]. Available from: http://salutweb.gencat.cat/ca/ambits_actuacio/linies_dactuacio/tecnologies_informacio_i_ comunicacio/ecap/ 32. World Health Organization (WHO). Robson criteria implementation manual. 2017. 33. The World Bank. World Bank Country and Lending Groups–World Bank Data Help Desk. World Bank [Internet]. 2017 [cited 2019 Apr 14];1–8. Available from: https://datahelpdesk.worldbank.org/ knowledgebase/articles/906519-world-bank-country-and-lending-groups 34. Direcció General de Planificació i Avaluació. Pla Estratègic d’Ordenació de l’Atenció Maternoinfantil als Hospitals de la Xarxa Hospitalària d’Utilització Pública a Catalunya. Barcelona; 2008. 35. Pyykönen A, Gissler M, Løkkegaard E, Bergholt T, Rasmussen SC, Smárason A, et al. Cesarean sec- tion trends in the Nordic Countries—a comparative analysis with the Robson classification. Acta Obstet Gynecol Scand [Internet]. 2017 May [cited 2019 Apr 28]; 96(5):607–16. Available from: http://doi.wiley. com/10.1111/aogs.13108 PMID: 28176334 PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 16 / 17 PLOS ONE CS trend in Catalonia by Robson classification system 2013-2017 36. SEGO. Parto vaginal tras cesárea Protocolos Asistenciales en Obstetricia [Internet]. 2010 [cited 2019 May 2]. Available from: https://www.elpartoesnuestro.es/sites/default/files/recursos/documents/sego_ protocolo_pvdc_2010.pdf 37. Hannah ME, Hannah WJ, Hewson SA, Hodnett ED, Saigal S, Willan AR. Planned caesarean section versus planned vaginal birth for breech presentation at term: a randomised multicentre trial. Term Breech Trial Collaborative Group. Lancet (London, England) [Internet]. 2000 Oct 21 [cited 2019 May 2]; 356(9239):1375–83. Available from: http://www.ncbi.nlm.nih.gov/pubmed/11052579 38. Sociedad Española de Obstetricia y Ginecologı́a. External cephalic version. Progresos Obstet y Gine- col [Internet]. 2015 Aug 1 [cited 2019 May 2]; 58(7):337–40. Available from: http://linkinghub.elsevier. com/retrieve/pii/S0304501314002775 39. Azria E, Le Meaux J-P, Khoshnood B, Alexander S, Subtil D, Goffinet F, et al. Factors associated with adverse perinatal outcomes for term breech fetuses with planned vaginal delivery. Am J Obstet Gynecol [Internet]. 2012 Oct [cited 2019 May 2]; 207(4):285.e1–285.e9. Available from: http://www.ncbi.nlm.nih. gov/pubmed/23021690 40. Salzer L, Nagar R, Melamed N, Wiznitzer A, Peled Y, Yogev Y. Predictors of successful external cephalic version and assessment of success for vaginal delivery. J Matern Neonatal Med [Internet]. 2015 Jan 2 [cited 2019 May 2]; 28(1):49–54. Available from: http://www.ncbi.nlm.nih.gov/pubmed/ 24593778 41. Royal College of Obstetricians and Gynaecologists. External Cephalic Version and Reducing the Inci- dence of Term Breech Presentation. BJOG An Int J Obstet Gynaecol [Internet]. 2017 [cited 2019 May 2]; 124(7):e178–92. Available from: https://www.rcog.org.uk/en/guidelines-research-services/ guidelines/gtg20a/ 42. The American College of Obstetrician and Gynaecologists. Practice Bulletin No. 161. Obstet Gynecol [Internet]. 2016 Feb [cited 2019 May 2]; 127(2):e54–61. Available from: http://insights.ovid.com/ crossref?an=00006250-201602000-00051 https://doi.org/10.1097/AOG.0000000000001312 PMID: 26942387 43. Generalitat de Catalunya. Departamento de Salud. Protocolo para la asistencia natural al parto normal Biblioteca de Cataluña. Datos CIP Protocolo para la asistencia natural al parto normal Bibliografı́a. Dirección General de Salud Pública, editor. Barcelona; 2007. 44. Agència de Qualitat i Avaluació Sanitàries de Catalunya. Àmbit Hospitalari. Dades del 2015. 2016; Available from: https://scientiasalut.gencat.cat/bitstream/handle/11351/3165/central_resultats_ambit_ hospitalari_dades_2015.pdf?sequence=1&isAllowed=y 45. Sandall J, Tribe RM, Avery L, Mola G, Visser GH, Homer CS, et al. Short-term and long-term effects of caesarean section on the health of women and children. Lancet [Internet]. 2018 Oct 13 [cited 2019 Jun 20]; 392(10155):1349–57. Available from: http://www.ncbi.nlm.nih.gov/pubmed/30322585 https://doi. org/10.1016/S0140-6736(18)31930-5 PMID: 30322585 46. Birth rights: protecting human rights in childbirth. 2010 [cited 2019 Jun 20];(November):2010. Available from: http://www.birthrights.org.uk/ 47. DONA LLUM–Associació Catalana per un Part Respectat–Treballem per a aconseguir uns parts més respectats i segurs, i uns naixements més feliços. [Internet]. [cited 2019 Jun 20]. Available from: https:// www.donallum.org/ 48. Chaillet N, Dumont A. Evidence-Based Strategies for Reducing Cesarean Section Rates: A Meta-Anal- ysis. Birth [Internet]. 2007 Mar [cited 2019 May 2]; 34(1):53–64. Available from: http://www.ncbi.nlm. nih.gov/pubmed/17324180 https://doi.org/10.1111/j.1523-536X.2006.00146.x PMID: 17324180 49. McLachlan H, Forster D, Davey M-A, Farrell T, Flood M, Shafiei T, et al. The effect of primary midwife- led care on women’s experience of childbirth: results from the COSMOS randomised controlled trial. BJOG An Int J Obstet Gynaecol [Internet]. 2016 Feb [cited 2019 May 2]; 123(3):465–74. Available from: http://doi.wiley.com/10.1111/1471-0528.13713 50. McLachlan H, Forster D, Davey M, Farrell T, Gold L, Biro M, et al. Effects of continuity of care by a pri- mary midwife (caseload midwifery) on caesarean section rates in women of low obstetric risk: the COS- MOS randomised controlled trial. BJOG An Int J Obstet Gynaecol [Internet]. 2012 Nov [cited 2019 May 2]; 119(12):1483–92. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22830446 51. Sandall J, Soltani S, Gates S, Shennan A, Devane D. Midwifeled continuity models versus other models of care for childbearing women (Review). Cochrane database Syst Rev. 2016; 4(10):46–67. 52. Eurostat. File:Practising midwives, 2011 and 2016 (per 100 000 inhabitants) HLTH18.png—Statistics Explained [Internet]. 2018 [cited 2019 May 2]. Available from: https://ec.europa.eu/eurostat/statistics- explained/index.php?title=File:Practising_midwives,_2011_and_2016_(per_100_000_inhabitants) _HLTH18.png PLOS ONE | https://doi.org/10.1371/journal.pone.0234727 June 16, 2020 17 / 17