Ngwenya Solwayo, Nleya Faith, Mwembe Desmond
Mpilo Central Hospital, P.O. Box 2096, Vera Road, Mzilikazi, Bulawayo, Matabeleland, Zimbabwe.
Royal Women's Clinic, 52A Cecil Avenue, Hillside, Bulawayo, Zimbabwe.
BMC Res Notes. 2020 Jan 30;13(1):46. doi: 10.1186/s13104-020-4911-y.
Maternal mortality is an important global subject. This dataset was generated from a retrospective cross-sectional study carried out at Mpilo Central Hospital, covering the period January 1, 2015 to December 31, 2018. The aim of the study was to compare how frequently the exposure to a risk factor was related to maternal death. Maternal deaths that were recorded during the study period were considered as cases. Controls were selected randomly from women of child-bearing age who survived during the study period. Low-resourced countries contribute significantly to global maternal deaths. Understanding risk factors could help reduce maternal mortality.
The dataset contains data of 387 pregnant women who were included in the study. Data were collected as secondary data using a data collection sheet, as recorded by the hospital staff that gave all necessary demographic details in birth and mortality registers. The data collected included socio-demographic and clinical data. The independent variables were maternal age, gravidity, parity, antenatal visits, booking status, marital status, educational status, days spent in hospital, mode of delivery, fetal outcomes, and maternal complications. The dependent variable was maternal mortality. The data can be used to determine the relationship between the independent variables and maternal death.
孕产妇死亡率是一个重要的全球性课题。该数据集源自于在姆皮洛中心医院开展的一项回顾性横断面研究，涵盖2015年1月1日至2018年12月31日这一时间段。该研究的目的是比较接触风险因素的频率与孕产妇死亡之间的关联。研究期间记录的孕产妇死亡被视为病例。对照是从研究期间存活的育龄妇女中随机选取的。资源匮乏国家在全球孕产妇死亡中占很大比例。了解风险因素有助于降低孕产妇死亡率。
该数据集包含纳入研究的387名孕妇的数据。数据作为二手数据通过数据收集表收集，由医院工作人员记录，他们在出生和死亡登记册中提供了所有必要的人口统计学细节。收集的数据包括社会人口学和临床数据。自变量有产妇年龄、孕次、产次、产前检查次数、登记状态、婚姻状况、教育程度、住院天数、分娩方式、胎儿结局和产妇并发症。因变量是孕产妇死亡率。这些数据可用于确定自变量与孕产妇死亡之间的关系。
