UNASSIGNED: Socio-demographic, travel, and obstetric data of pregnant women were extracted from case notes. Travel data was inputted in Google Maps to extract travel time from the pregnant women\' home to the hospital. Univariate, bivariate and multivariable logistic regression analyses were conducted.
UNASSIGNED: Of the 3,134 included pregnant women, 1,923 (61%) delivered via emergency CS. The odds of an emergency CS were significantly higher among women who were booked (OR=1.97, 95%CI 1.64-2.35), presented with obstructed labour (OR=2.59, 95%CI 1.68-3.99), pre-eclampsia/eclampsia (OR=1.67, 95%CI 1.08-2.56), multiple gestations (OR=2.71, 95%CI 1.72-4.28) and travelled from suburban areas (OR=1.43, 95%CI 1.15-1.78). There was an increasing dose-effect response between travel time to the hospital and emergency CS.
UNASSIGNED: Optimisation of CS rates requires a multi-pronged approach during pregnancy and childbirth, with particular emphasis on supporting pregnant women living in the suburbs.
■社会人口统计,旅行,从病例记录中提取孕妇的产科数据。在Google地图中输入了旅行数据,以提取从孕妇家中到医院的旅行时间。单变量,进行了双变量和多变量逻辑回归分析.
■在3134名孕妇中,1,923(61%)通过紧急CS交付。在预订的女性中,急诊CS的几率明显更高(OR=1.97,95CI1.64-2.35),出现难产(OR=2.59,95CI1.68-3.99),先兆子痫/子痫(OR=1.67,95CI1.08-2.56),多胎妊娠(OR=2.71,95CI1.72-4.28)和从郊区旅行(OR=1.43,95CI1.15-1.78)。在前往医院的旅行时间和急诊CS之间,剂量效应反应增加。
■优化CS率需要在怀孕和分娩期间多管齐下的方法,特别强调支持居住在郊区的孕妇。