Haimanot Abebe1, Solomon Shitu2, Haile Workye3, Ayenew Mose2. 1. Department of Public Health, College of Health Sciences and Medicine, Wolkite University, Wolkite, Ethiopia. 2. Department of Midwifery, College of Health Sciences and Medicine, Wolkite University, Wolkite, Ethiopia. 3. Department of Nursing, College of Health Sciences and Medicine, Wolkite University, Wolkite, Ethiopia.
Abstract
BACKGROUND: Although the rate of stillbirth has decreased globally, it remains unacceptably high in low- and middle-income countries. Only ten countries including Ethiopia attribute more than 65% of global burden of still birth. Ethiopia has the 7th highest still birth rate in the world. Identifying the predictors of stillbirth is critical for developing successful interventions and monitoring public health programs. Although certain studies have assessed the predictors of stillbirth, they failed in identify the proximate predictors of stillbirth. In addition, the inconsistent findings in identify the predictors of stillbirth, and the methodological limitations in previously published works are some of the gaps. Therefore, this study aimed to identify the predictors of stillbirth among mothers who gave birth in six referral hospitals in Southern, Ethiopia. METHODS: A hospital-based unmatched case-control study was conducted in six referral hospitals in Southern, Ethiopia from October 2019 to June 2020. Consecutive sampling techniques and simple random techniques were used to recruit cases and controls respectively. A structured standard tool was used to identify the predictors of stillbirth. Data were entered into Epi Info 7 and exported to SPSS 23 for analysis. A multivariable logistic regression model was used to identify the independent predictors of stillbirth. The goodness of fit was tested using the Hosmer and Lemeshow goodness-of-fit. In this study P-value < 0.05 was considered to declare a result as a statistically significant association. RESULTS: In this study 138 stillbirth cases and 269 controls were included. Women with multiple pregnancy [AOR = 2.98, 95%CI: 1.39-6.36], having preterm birth [AOR = 2.83, 95%CI: 1.58-508], having cesarean mode of delivery [AOR = 3.19, 95%CI: 1.87-5.44], having no ANC visit [AOR = 4.17, 95%CI: 2.38-7.33], and being hypertensive during pregnancy [AOR = 3.43, 95%CI: 1.93-6.06] were significantly associated with stillbirth. CONCLUSIONS: The predictors of stillbirth identified are manageable and can be amenable to interventions. Therefore, strengthening maternal antenatal care utilization should be encouraged by providing appropriate information to the mothers. There is a need to identify, screen, and critically follow high-risk mothers: those who have different complications during pregnancy, and those undergoing cesarean section due to different indications.
BACKGROUND: Although the rate of stillbirth has decreased globally, it remains unacceptably high in low- and middle-income countries. Only ten countries including Ethiopia attribute more than 65% of global burden of still birth. Ethiopia has the 7th highest still birth rate in the world. Identifying the predictors of stillbirth is critical for developing successful interventions and monitoring public health programs. Although certain studies have assessed the predictors of stillbirth, they failed in identify the proximate predictors of stillbirth. In addition, the inconsistent findings in identify the predictors of stillbirth, and the methodological limitations in previously published works are some of the gaps. Therefore, this study aimed to identify the predictors of stillbirth among mothers who gave birth in six referral hospitals in Southern, Ethiopia. METHODS: A hospital-based unmatched case-control study was conducted in six referral hospitals in Southern, Ethiopia from October 2019 to June 2020. Consecutive sampling techniques and simple random techniques were used to recruit cases and controls respectively. A structured standard tool was used to identify the predictors of stillbirth. Data were entered into Epi Info 7 and exported to SPSS 23 for analysis. A multivariable logistic regression model was used to identify the independent predictors of stillbirth. The goodness of fit was tested using the Hosmer and Lemeshow goodness-of-fit. In this study P-value < 0.05 was considered to declare a result as a statistically significant association. RESULTS: In this study 138 stillbirth cases and 269 controls were included. Women with multiple pregnancy [AOR = 2.98, 95%CI: 1.39-6.36], having preterm birth [AOR = 2.83, 95%CI: 1.58-508], having cesarean mode of delivery [AOR = 3.19, 95%CI: 1.87-5.44], having no ANC visit [AOR = 4.17, 95%CI: 2.38-7.33], and being hypertensive during pregnancy [AOR = 3.43, 95%CI: 1.93-6.06] were significantly associated with stillbirth. CONCLUSIONS: The predictors of stillbirth identified are manageable and can be amenable to interventions. Therefore, strengthening maternal antenatal care utilization should be encouraged by providing appropriate information to the mothers. There is a need to identify, screen, and critically follow high-risk mothers: those who have different complications during pregnancy, and those undergoing cesarean section due to different indications.