Background: In spite of the promotion of institutional delivery in Ethiopia, home delivery is still common primarily in hard-to-reach areas. Institutional delivery supported to achieve the goal of reducing maternal and neonatal mortality in Ethiopia. The objective of this study is to assess the determinants of institutional delivery in Ethiopia. Methods: Cross sectional survey was conducted in 11 administrative regions of Ethiopia. The Ethiopian demographic and health survey data collection took place from January 18, 2016, to June 27, 2016. The study subjects were 11,023 women (15-49 years old) who gave birth in the preceding 5 years before 2016 Ethiopian demographic health survey. This representative data was downloaded from Demographic Health Survey after getting permission. The Primary outcome variable was institutional delivery. The data was transferred and analyzed with SPSS Version 20 statistical software package. Results: Of 11,023 mothers, 2892 (26.2%) delivered at a health facility and 8131 (73.8%) at home. Women with secondary education were 4.36 times more likely to have an institutional delivery (OR: 4.36; 95% CI: 3.12-6.09). Institutional delivery was higher among women who were resided in urban areas by three fold (OR: 3.26; 95% CI: 2.19-4.35). Women who visited ANC (Antenatal care) were about two times more likely to choose institutional delivery (OR: 1.81; 95% CI: 1.58-2.07). Respondents who watch television at least once a week was two times more likely to experience institutional delivery than those who did not watch at all (0R: 1.90; 95% CI: 1.35-2.66). The wealthiest women were 2.61 times more likely to deliver in an institution compared with the women in the poorest category (OR: 2.61; 95% CI: 1.95-3.50). Conclusion: Women having higher educational level, being richest, residing in urban area, visiting antenatal care at least once, and frequent exposure to mass media were factors associated with institutional delivery. Improving access to education and health promotion about obstetrics and delivery through mass media will increase the uptake of institutional delivery.
The population of Ethiopia is diverse encompassing 80 different ethnic groups. According to the 2017 estimate, the population of Ethiopia was about 107,406,158. Ethiopian population is equivalent to 1.41% of the total world population, which ranks number 12 from the world. About 20% of Ethiopian population were resided in urban areas [12, 13]. The Ethiopian demographic and health survey data collection took place from January 18, 2016, to June 27, 2016. The data collectors were health professionals recruited from different health facilities throughout the country. Women in reproductive age (15–49) who resides permanently in the selected households or stayed the night before the survey in the household, were entitled to be part of the study subjects. Cross sectional survey was conducted in 11 administrative regions of Ethiopia. The sample was stratified and selected in two stages where each region stratified into urban and rural areas. Samples of enumeration areas (EAs) selected independently in each stratum in two stages. Based on the 2007 population and housing census, in the first stage, 645 EAs of which 202 from urban areas and 443 from rural areas were selected. Household lists helped as a sampling frame for second stage selection of households for the study. Up to 300 households listed in one-enumeration areas. To reduce the task of household listing, each large enumeration areas selected for the survey was segmented. Then household listing was done only in the selected segments. In the second stage of selection, a fixed number of 28 households in each cluster selected with an equal probability of systematic selection from the newly created household listing. The sampling frame of the 2016 Ethiopian demographic health survey was from Ethiopia Population and Housing Census (PHC), conducted by the Ethiopia Central Statistical Agency in 2007 [4]. About 16,583 entitled women identified for individual interviews. Then Interview completed with 15,683 respondents resulting in the response rate of 95% [4]. To assess determinants of institutional delivery, mothers who gave baby within the preceding 5 years extracted from EDHS dataset. Therefore, 11,023 women included in this study. Since there was a non-proportional allocation of the sample to different regions and their urban and rural areas and the possible differences in response rates, a sampling weight used to ensure the actual representative of the survey results at both the national and domain levels. The sample was taken in a two-stage stratified cluster sample. Therefore, the sampling weights are based on sampling probabilities separately for each sampling stage and each cluster [4]. The outcome variable of the study is institutional delivery. Since the study wants to answer the question “what are the determinants of institutional deliveries?” women who deliver at health institutions at least once will be coded as institutional delivery (Yes = 1). The independent variables where socio demographic characteristics (maternal age, marital status place of resident, maternal educational, husband education, wealth index and watching television), pregnancy and health service related factors (Number of Births, antenatal care, told about danger sign during ANC, and health insurance). Data files transferred via internet file streaming system (IFSS) to the CSA central office during data collection. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. Data editing was accomplished using CSPro software. During the duration of fieldwork, tables generated to check various data quality parameters [4] and specific feedback was given to the teams to improve performance. Bivariate logistic regression employed, with the outcome variable of intuitional delivery. First, univariable analyses performed with each of the demographic indicators and other independent variables with the outcome variable. Variables significant at p-value ≤0.2 were included in the multivariable logistic regression models. Variables that did not have a significant regression coefficient removed from the model. Variables that were not significant at the univariate analysis added back to the model and their significance assessed in the presence of other significant variables. Subsequently, the goodness of fit of our final model tested using the Hosmer-Lemeshow test. Data management procedures and statistical analysis done with SPSS software version 20.
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