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OBJECTIVE. To study factors that influence the probability of episiotomy in Dutch gynaecologist-supervised deliveries. SETTING. Obstetric units of Dutch hospitals. DESIGN. Observational study. METHODS. Data of 65,313 gynaecologist-supervised, vaginal deliveries of live-born singletons registered in the Dutch National Obstetric Database of 1990, were used. Firstly, the effect of characteristics of the mother, the child, the pregnancy, and the delivery on the probability of episiotomy were assessed in univariate analyses. Subsequently logistic regression analysis was used to determine the effect of each variable, while adjusting for the other variables. RESULTS. The episiotomy rate in the total group of gynaecologist supervised deliveries was 39%. In the subgroup of vaginal deliveries of live born singletons, the rate was 46%. Besides the well-known risk factors such as parity, instrumental delivery and length of second stage of labour, ethnicity was also found to have an independent effect on the risk of an episiotomy. Mediterranean, Creole and Hindu women had a lower episiotomy risk than Dutch women (OR: 0.47 and 95% CI: 0.44-0.51). Gynaecologists more often performed episiotomy than midwives, after adjusting for possible confounding factors (OR: 1.54; 1.46-1.63). In University hospitals fewer episiotomies were performed than in large non-university hospitals (OR: 0.81; 0.76-0.87. CONCLUSION. The decision to perform episiotomy appears not to depend solely on factors related to perineal rupture or foetal complications. The probability of episiotomy is also influenced by attendant at delivery and type of hospital


Journal article



Publication Date





449 - 452


Academic Medical Centers, Adult, analysis, article, Child, complications, Confidence Intervals, database, Delivery,Obstetric, English Abstract, epidemiology, Episiotomy, Ethnic Groups, Extraction,Obstetrical, female, Gynecology, Humans, Methods, Netherlands, Obstetrics, Odds Ratio, Parity, Pregnancy, Probability, Regression Analysis, Risk, risk factor, Risk Factors, risk-factors, Rupture, statistics & numerical data, Universities