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Background Maternity waiting home (MWH) is one of the strategies designed for improved access to comprehensive obstetric care for pregnant women living far from health facilities. Hence, it is vital to promote MWHs for pregnant women in Ethiopia, where most people reside in rural settings and have a high mortality rate. Therefore, this study aimed to assess MWHs utilization and associated factors among women who gave birth in the rural settings of Finfinnee special zone, central Ethiopia. Methods A community-based cross-sectional study was conducted from 15th October to 20th November 2019 among women who gave birth in the last six months before data collection. Multistage random sampling was employed among 636 women from six rural kebeles to collect data through a face-to-face interview. Multivariable logistic regression analysis was fitted, and a 95% confidence level with a p-value <0.05 was used to determine the level and significance of the association. Results Overall, MWHs utilization was 34.0% (30.3% – 37.7%). The higher age (AOR: 4.77; 95% CI: 2.76–8.24), career women (AOR: 0.39 95% CI: 0.20–0.74), non-farmer husband (AOR: 0.28; 95% CI: 0.14–0.55), rich women (AOR:1.84; 95% CI: 1.12–3.02), living greater than 60 minutes far from a health facility (AOR: 1.80; 95% CI: 1.16–2.80), and four and more live-births (AOR: 5.72; 95% CI: 1.53–21.35) significantly associated with MWHs utilization. The common services provided were latrine, bedding, and health professional checkups with 98.2%, 96.8%, and 75.4%, respectively. Besides, feeding service was provided by 39.8%. The primary reason not to use MWHs was the absence of enough information on MWHs. Conclusion One-third of the women who delivered within the last six months utilized MWHs in the Finfinnee special zone. Our results support the primary purpose of MWHs, that women far from the health facility are more likely to utilize MWHs, but lack of adequate information is the reason not to use MWHs. Therefore, it is better to promote MWHs to fill the information gap among women with geographical barriers to reach health facilities.
A community-based cross-sectional study design with a quantitative method was conducted from 15th October to 20th November 2019 in the rural settings of the Finfinnee special zone. Finfinnee special zone had a total population of 649,403 in 2019, of whom, 318,207 were women, and 22,534 were pregnant [21]. The Finfinnee special zone has one administrative town, six rural districts, and 153 administrative kebeles (the smallest administrative division in Ethiopia). Based on evidence obtained from the zonal health department, approximately on average 72 childbirths were conducted over the last six months in each kebele. According to Ethiopia’s three-level healthcare delivery structure, the rural population is covered under the primary level health care delivery that includes the primary hospitals, the health centers and the health posts in which essential and non-specialized health services are provided. Out of 27 health centers in the rural kebeles of the zone, 18 of them had MWHs and were delivering free maternal health care, including health professionals’ checkups, bedding, and food services. The pregnant women became aware of the services during the home visits by health extension workers, health development armies, ANC follow-up, women’s conferences, and other social events [8]. In Ethiopia, the MWH service started a four-decade ago with public support. Accordingly, most MWHs services are provided without government funds free of charge [22]. The source population for this study was all women who gave birth in the past six months of the data collection period in the six rural districts of the Finfinnee special zone. The study population was all women who gave birth in the past six months in selected rural kebeles. Those mothers who gave birth in the last six months and lived 9.5 kilometers away from health facilities were included in the study. The distance of the women’s home and birth status was obtained from the health extension workers. However, women who were seriously ill during data collection time and who lived in the selected kebeles for less than six months (informal residents) were excluded from the study. A single population proportion formula was used for sample size calculation based on the assumptions for the proportion of MWHs utilization in Jimma zone of southern Ethiopia 38.7% [13], 95% confidence level, 5% margin of error, 1.5 design effect, and 5% non-response rate. Therefore, the calculated sample size was 574. The sample size for independent variables was calculated with Epi info version 7 software with an assumption of 95% confidence level, 5% margin of error, and power of 80%. In the previous study [20], distance to a health facility was significantly associated with MWHs utilization with an adjusted odds ratio of 2.4. Thus, the estimated sample size was 636. Thus, 636 (the largest) became the final sample size required for this study. A multistage random sampling technique was employed in the six rural districts. Eighteen out of 153 rural kebeles of the six districts that didn’t have health facilities within a 9.5 km radius were eligible for the sampling. Six rural kebeles out of the 18 rural kebeles were selected with the highest population size in the first stage. In the second sampling stage, after a proportional allocation to the number of households in each kebele, all households within each kebeles were selected by systematic random sampling technique based on the order of the households on the sampling frame obtained from the health extension workers. The total sample of women delivered within the last six months of the selected kebeles was 1,282, and the sampling interval was 2. Hence, every 2nd household was visited until we got 636 selected postpartum women. When more than one eligible respondent was in the household, one respondent was randomly selected by a lottery method. A repeated visit of the women was employed when the women were absent from the home. After the three visits, the home next to the selected household was included in the study. The outcome variable of this study was the utilization of maternity waiting homes defined as staying at maternity waiting homes reported by women for recent delivery/pregnancy (yes or no), which can be antenatal or postnatal. The independent variables of this study were sociodemographic characteristics of the respondents; age, religion, ethnicity, marital status, educational status, husbands’ educational status, occupation, husbands’ occupation, wealth index, access to transportation, and time taken to the nearest health facility. The obstetric related factors were the number of pregnancies, ANC visit for recent birth, number of ANC visits, birth preparedness plan for the recent birth, number of live births, place of the last birth, PNC follow up for recent birth, heard of MWHs, source of information, the reason to use MWHs, waiting time to get MWHs service, satisfaction with MWHs utilization, services received during the stay, reasons not to use MWHs and husband support to use MWHs. In addition, a principal component analysis was employed to create the wealth index of the women based on information on asset ownership, the number of animals owned, electricity supply to the home, health insurance, drinking water source, type of toilet, and type of materials used for construction of floors in the house. Finally, the wealth index was categorized as poor, medium, and rich. The lowest 33% of households according to the economic status variable were classified as poor; the highest 33% as rich, and the rest as average (medium) wealth index. To avoid recall bias, women who gave birth within the last six months were interviewed for their most recent delivery. A face-to-face interview of 30 min was employed to collect data using a pretested and structured questionnaire adapted after reviewing literature with a related topic and conceptualizing the factors significantly associated with MWHs utilization [12–15, 20, 23]. The questions were designed in such a way that the interviewer and the respondents easily understood what was intended to ask. The questionnaire was prepared in English first and then translated into Affan Oromo (the local language in the study area) then back-translated to English by language experts to check its original meaning. It consists of questions related to the sociodemographic characteristics and obstetric characteristics, and factors related to the experience of MWHs in the pregnancy period. The data were collected by six diploma nurses and supervised by three bachelor health officers after the two days of training, mainly on the tools’ contents. In addition, a pretest was conducted on 32 (5%) postpartum women at Akaki district of Finfinnee Special Zone, and necessary corrections were made on language clarity and steps of the questions before the actual data collection was conducted. After data collection was completed, questionnaires were checked for completeness. The completed data was coded and entered into EpiData 4.6 version software. After exporting to Stata version 14.0, incomplete, improperly formatted, duplicated, or irrelevant records were cleaned. The results of the descriptive analysis were tabulated using frequency and percent. Variables with p-value <0.2 under bivariable logistic regression were fitted for multivariable logistic regression. Adjusted odds ratio (AOR) with a 95% confidence level and a p-value less than 0.05 were used to measure the precision of the association estimate and its significance of association, respectively. This study was conducted following the Declaration of Helsinki. Ethical clearance was obtained from the ethical review committee of the Institute of Public Health, the University of Gondar, with the reference number IPH/676/2/2019. A supporting letter was obtained from the Finfinnee special zone health office. The study objective was explained, and both oral and written informed consent was obtained from the household head and the respondent women.
