This study was conducted in the Madura district, which is found in the Metekle zone, Benishangul Gumuz regional state, North-west Ethiopia. The district is designated at 546 km from Addis Ababa and 338 km from the regional town, Assosa. The district is located is at 10 050” and 110 50” North latitude and 360 10’360 30” east longitude with an elevation of 1050-1400 above sea level which is low land. The annual temperature of Madura oscillates between 18 0c -38.7 0C with annual rainfall lies between 900 - 1200mm. The total population of district Madura projected from 2018 national census projected report was 56,760 for the year 2019. The pyramidal age structure of the population has remained predominately young with 47.4% under the age of 15 years of these children under five years of age accounts 16.18%. The average household size of the district was 4.5. Among the total inhabitants, 87% were Gumuze, Agew (8.9%), Amhara (3.9%), and all other ethnic groups constitute 0.2% of the population.
The main source of income for the inhabitants of the district is mixed agriculture. Out of the total population, about 85% of households are dependent on crop and animal productions. Most income generation activities by local inhabitants in the district are geared towards satisfying daily needs (to supplement food gaps) including wood extraction for charcoal and fuel. The administrative structures of Mandura were 3 urban and 17 rural kebeles. There are twenty-two Health Posts, two Health centers, and no Hospital in the district. Each health post has two Health Extension workers and one clinical nurse that provides service.
Study design and period
Community based descriptive cross-sectional study was conducted from October to November 2019.
All mothers who gave birth in the last year before the time of data collection who were living in Mandura District were the source population.
All mothers who gave birth in the last year before the time of data collection from selected kebeles were the study population.
All mothers who gave birth the last year before data collections in Mandura district were included.
Institutional delivery service utilization
Pre-disposing factors: Maternal age, marital status, occupation, religion, maternal educations, partner educational status, parity, and age at 1st pregnancy.
Enabling factors: Place of residence, knowledge's on danger sign, attitudes of women, the distance of health care, possessing radio/TV, availability & accessibility of service, availability of transportations
Reinforcing and Need factors: Family preference, self-care preference, frequency of antenatal care (ANC) visit, and types of pregnancy.
Operational definition and definition of Terms
Institutional delivery service utilization: Refers to mothers who had delivered their last baby in hospitals, health centers, private clinics, NGO health facilities, or Health Posts by skilled personnel (33).
Skilled attendants: Refer to people with midwifery skills (midwives, doctors, and nurses with additional midwifery training) who have been trained to proficiency in the skills necessary to manage normal deliveries and diagnose, manage or refer obstetric complications’.
Accessibility of institutional delivery service: Availability of heath facility providing delivery service within 2 hours distance by walk or <5 km (33).
Predisposing factors: Are factors that exist prior and make susceptible or inclining to acquire some behavior like the use of skilled birth attendants (30).
Enabling Factors: Are usually thought of as barriers to behavior changes created by societal factors; such as availability of services and their accessibility (both geographic and economic), limited facilities, and lack of income.
Reinforcing factors: Are the influences of people that encourage or discourage behavioral change (30).
ANC visitor: If a woman visited health care facility during pregnancy for getting pregnancy-related service
Close to health facility: If a woman traveled <5 km to reach the health care facility.
Far from health facility: If a woman traveled>5 km to reach health care facility.
Home delivery: When a mother gave birth at her home or others’ home (neighbor, relatives, or family) or when a birth takes place outside of health institution.
Woman’s autonomy: If a woman decided on the place to give birth by herself or with her husband jointly.
Women’s knowledge: A woman would be considered knowledgeable for danger signs of pregnancy if she scores 50% and above for knowledge questions when one is given for correct answer and zero for incorrect answer (33).
Sample size determinations
For the first objective, the sample size was determined by using a single population proportion formula. By considering the assumptions of 95% level of confidence, 5% margin of error, and 18% the prevalence of institutional delivery service utilization which was conducted in the Pastoralist Community of Northeast Ethiopia (43). And also, by considering the design effect of two and 10% non-response rate, the final sample size was found to be 498 participants.
For the second objective, the sample size was calculated using factors significantly associated with institutional delivery service utilization from previously conducted studies. It was calculated using STATA software by considering the assumptions of the 95% level of confidence, 5% margin of error, 1:1 case to control ratio, and 80% power of the study. The factors like place of residence, availability of radio/TV, and Educational status of the mother taken from a study conducted in Checha district, Pawe Dawro Zones with the same topic. The maximum sample size was 248. Considering design effect 2 and the potential non-response rate of 10%; the final sample size was 546. We use this sample size for our study because it is larger than the previous one.
Sampling method and procedure
Multi-stage sampling was employed. First, stratified the study area by urban and rural was done. Second, Random sampling was held from seventeen rural and all three urban kebeles (lowest administrative unit in Ethiopia) to select a total of nine kebeles; three from urban and six from rural. Then Systematic random sampling was used with every Kth (two) cases from each kebele to get representative participants. Proportional sampling was done based on the number of mothers who gave birth in the last year living in the selected kebele using last year's pregnant mothers' registration book as sampling frame in the health post(figure 1).
Data collection instruments and procedures
Pre-tested questionnaires were used for data collection. The questionnaire was translated into the local language, and to check for its consistency, back-translated into English. Data were collected by trained team face to face interview. The questionnaire contains, questions adapted from instruments used in several studies on delivery service utilization and questions developed by student investigators. The main domains of the questionnaire were predisposing factors, enabling factors, reinforcing, and need factor on potential associated factors for institutional delivery service utilization.
Nine health extension workers were recruited as data collectors to conduct the face-to-face interview and two BSC nurses and the Principal Investigator supervised the data collection process. Two days of training was given to the data collectors and supervisors before the actual data collection regarding the aim of the study, data collection tool, and procedures going through the questionnaires question by question.
Data quality assurance
The collected data were checked for completeness and consistency daily by supervisors. Before the actual data collection took place, a pre-test was done on 5% of the participant out of the study area to ensure the validity of data collection tools. Based on the findings of the pre-test, data collection tools were modified. After checking for completeness, the collected data were checked and reorganized to exclude errors before data entry.
Data processing and analysis
Both descriptive and analytical analysis was carried out to describe, to see the crude and adjusted effect of each variable. The binary logistic regression model was fitted to assess the effect of each independent variable towards the acquisition of institutional delivery service utilization. To identify factors associated with delivery service utilization among women in the Mandura district. First, bi-variable logistic regressions were performed for each independent variable with institutional delivery service utilization among Mandura district and crude odds ratio with 95% confidence intervals were obtained. Then, variables observed with P value<0.2 in the bi-variable analysis were subsequently included in the multivariable logistic regression to determine independent predictors, and model fit was checked by the Hosmer–Lemeshow goodness-of-fit and Potential multi-collinearity among the independent variables was also checked of delivery service utilizations among in Mandura district. The findings of the study were presented using text, tables, and graphs.