Caesarean section rates in public vs private hospitals in Europe: a systematic review and meta-analysis using the Robson ten group classification system
Notice bibliographique
Résumé
INTRODUCTION: Since the last two decades, there has been a dramatic rise in caesarean sections (CS) throughout the world. This increase has been seen even in Europe, where rates vary significantly from 17% in Northern Europe to 56% in the South. Although, CS can be a lifesaving intervention when medically necessary, non-essential CS are associated with short- and long-term complications for both the mother and newborn. To curb this rising trend, it is important to understand underlying causes behind regional disparities, including differences between public and private hospitals. OBJECTIVE: To investigate variations in CS rates between public and private hospitals across European regions and at a country level using the Robson Ten Group Classification. METHODS: A systemic review of studies published between 1st January 2000 and 12th March 2025 was conducted using MEDLINE/PubMed, CINAHL, EMBASE, Global Index Medicus, Web of Science and Cochrane library, analysing CS rates in 25 European countries. All studies reporting births in Europe, Robson group, written in English or Swedish were included. The developed protocol was prospectively registered in PROSPERO (Registration number 513579). Meta-analysis using absolute numbers and percentages was conducted to compare the birth rates at country and regional levels. To assess the risk of bias, two reviewers independently evaluated the quality of the studies included using a modified Newcastle-Ottawa Scale adapted for cohort studies. RESULTS: Of 1385 articles, 46 were eligible for inclusion in the final analysis. A total of 12 505939 births were analysed, with 8 543803 (68.3%) occurring in public hospitals and 3 962136 (31.7%) in private hospitals. Overall, Southern Europe illustrated the highest CS rate (54.9% of all births) as compared to Northern Europe (16.9%). There was a lack of reporting from private hospitals, with data only for Southern Europe, where CS rates were significantly higher in private (73.1%) as compared to public (40.9%) hospitals. The largest differences were seen for low-risk women Robson Group 1, 2, 3 and 4 (private vs public: 67.8 vs 28%, 67.6 vs 39.7, 26.9 vs 9.1% and 38 vs 18% respectively). CONCLUSION: High CS rates were observed across Europe, with Southern Europe reporting the highest levels. Rates were consistently higher in private compared to public hospitals. In both settings, Group 5 (women with a previous CS) was the largest contributor to the overall CS rate. However, low-risk women in private hospitals (Groups 1 and 2) had twice the CS rates compared with public hospitals. These findings highlight that the excess CS burden in private hospitals is largely driven by unnecessary procedures in low-risk groups. There is an urgent need for interventions that promote evidence-based care and reduce unnecessary CS especially among low-risk women.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,018 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,021 | 0,031 |
| Bibliométrie | 0,016 | 0,018 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».