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Background Stillbirth is an unfavorable outcome of pregnancy, which is still prevalent in many countries despite remarkable efforts made to improve the care of pregnant women. While producing estimates consistent with other national reports, all are hindered by limited data and important causes of death are likely to be missed. However; there is a scarcity of data on stillbirth in Ethiopia particularly in the Wolaita zone. Objective To assess the prevalence and associated factors of stillbirth among women giving birth at public hospitals in the Wolaita zone, southern Ethiopia. Methods A facility-based cross-sectional study was conducted in public hospitals in the Wolaita zone. A stratified sampling technique was used to select 737 women. A pre-tested interviewer-administered questionnaire was used for data collection. Data were entered using Epidata version 3.1 and analyzed using SPSS version 20. Bivariate and multiple logistic regression analysis were used and the crude and adjusted odds ratios at a 95% confidence interval with P-value <0.05 were considered to declare the result as statistically significant. Result This study reported an 8.7% [95% CI: 6.5–10.8] prevalence of stillbirth. Women who lived in rural areas, had pregnancy and labor complications, a high number of pregnancies, a prior history of stillbirth, and a complicated delivery were associated with stillbirth. When compared to urban residents, being a rural resident increased the risk of stillbirth by 2.57 fold [adjusted OR = 2.57, 95% CI: 1.23, 5.40]. When compared to their counterparts, women who experienced complications during pregnancy and labor increased 6.23 fold [AOR = 6.23, 95% CI: 2.67–14.58], having a previous history of stillbirth increased 6.89 fold [AOR =
A facility-based cross-sectional study design was conducted in health facilities in the Wolaita zone from August 2019 to September 2019. Wolaita Zone is one of the 14 Zones in southern nations, nationalities, and peoples’ regional(SNNPR) government; at a distance of 380 km from Addis Ababa, the capital city of Ethiopia. This zone consists of 16 Woredas/districts and 6 city administrations. The projected total population was 2,085,727 with (1,022,006) males and (1,063,721) females. There are about 72 health centers, 4 primary hospitals, 2 private general hospitals, and 1 teaching and referral hospital. According to the Wolaita zone health department health management information system (HMIS) report, 2018, stillbirth was 160 per 45582 live births, from which mostly about 95% were reported from public hospitals. All deliveries of women in the public and private health facilities of Wolaita Zone was considered as source population. And all deliveries of women in the selected public and private health facilities were taken as the study population. The sample size is calculated for the 1st objective by using the single population proportion formula taken from the study done on incidence and determinants of stillbirth among women who gave birth in Jimma University specialized hospital, Ethiopia [6] with the prevalence of 8% of stillbirth. Where n = estimated Sample Size Z1-α/2=the standard normal value corresponding to the desired level of confidence 95% corresponds to the value of 1.96. d = margin of sampling error tolerated 5% =0.05 P = is an estimate of the prevalence rate for the population (an assumption that stillbirth deliveries among laboring women in the study area) So by considering a 5% none—response rate, the total sample required was 119. The sample size for the second objective is calculated using OpenEpi statistical software version 3.03 for factors associated with stillbirth among delivered women from previous studies (Table 1). The sample size calculated for the second objective is higher than the sample size calculated for the first objective. Therefore, the largest sample size 737 is used as the final sample size for this study. The stratified sampling technique was used to select the study participants. A simple random sampling method was used to select the required health facilities in the Wolaita zone. From 72 health centers, 4 primary hospitals, 2 private general hospitals, and 1 teaching and referral hospital, two primary hospitals (BALE and BITENA primary hospitals) and one referral hospital (WSU teaching and referral hospital), and seven health centers namely Sodo, Bodit, Badessa, Dimtu, Gununo, Gasuba, and Humbo health centers which provides routine delivery services for laboring women were selected randomly and the required sample size was allocated to selected health facilities proportionally. The structured questionnaire adapted from similar studies was used [11, 12]. It is divided into five parts. The first section inquired about personal data, including age, occupation, ethnicity, religion, and educational level. The second part elicited information about Obstetric and Reproductive history. The third section was Health service access variables. The fourth section inquired about Behavioral history. The fifth part elicited information about Maternal-fetal factors. Eight diploma graduate midwifery nurses as data collectors and 1 BSc midwifery and 1 health officer supervisor who fluently speak Amharic and Wolaita language were recruited. The questionnaire was prepared in English and then translated into Amharic and Wolaita language and back-translated to English by language experts to check its consistency. Two days of in-depth training was given for data collectors on the overview of research ethics, data collecting tools, and how to fill out the questionnaire. The interviews were conducted after childbirth and before discharge from the facility. Data were edited, coded, and entered into Epidata version 3.1 and exported to SPSS 20 statistical software for analysis. After cleaning data for inconsistencies and missing values in SPSS, descriptive statistics were done. Missing data analysis was conducted by assuming data was missing completely at random (MCAR). Bivariate analysis was done to determine the association between each independent variable and the outcome variable. Before building a bivariable binary logistic regression model, variables significant in other studies and having biological plausibility were selected. In bivariable binary logistic regression, all predictor variables with a p-value of less than 0.25 were identified and entered into a multivariable logistic regression model. Then a multivariable logistic regression model using a backward stepwise selection method at P value< 0.05 and AOR with 95% CI were used to measure the degree of association between independent variables and the outcome variable. Finally, the result was presented by texts, tables, charts, and figures. Two days of in-depth training was given to data collectors. Data collection was supervised by supervisors and the principal investigator. A pretest was conducted on 5% of the sample size in Bedessa Health Center, Wolaita zone, southern Ethiopia. Data were cleaned and checked for completeness daily. Ethical clearance was secured from the ethical clearance committee of the Wolaita Sodo University, College of Health Science and Medicine. The concerned officials at all levels were informed to get the assurance of the study. The purpose, objectives, and importance of the study were explained and both written and verbal informed consent was secured from each participant. The participant was reassured about the loss of the baby and further advice was given. They were told that documents will be kept confidential and have the right to refuse participation totally at any time if they were not comfortable.
