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Objective To identify individual-, household- and community-level factors associated with maternity waiting home (MWH) use in Ethiopia. Design Cross-sectional analysis of baseline household survey data from an ongoing cluster-randomised controlled trial using multilevel analyses. Setting Twenty-four rural primary care facility catchment areas in Jimma Zone, Ethiopia. Participants 3784 women who had a pregnancy outcome (live birth, stillbirth, spontaneous/induced abortion) 12 months prior to September 2016. Outcome measure The primary outcome was self-reported MWH use for any pregnancy; hypothesised factors associated with MWH use included woman’s education, woman’s occupation, household wealth, involvement in health-related decision-making, companion support, travel time to health facility and community-levels of institutional births. Results Overall, 7% of women reported past MWH use. Housewives (OR: 1.74, 95% CI 1.20 to 2.52), women with companions for facility visits (OR: 2.15, 95% CI 1.44 to 3.23), wealthier households (fourth vs first quintile OR: 3.20, 95% CI 1.93 to 5.33) and those with no health facility nearby or living >30 min from a health facility (OR: 2.37, 95% CI 1.80 to 3.13) had significantly higher odds of MWH use. Education, decision-making autonomy and community-level institutional births were not significantly associated with MWH use. Conclusions Utilisation inequities exist; women with less wealth and companion support experienced more difficulties in accessing MWHs. Short duration of stay and failure to consider MWH as part of birth preparedness planning suggests local referral and promotion practices need investigation to ensure that women who would benefit the most are linked to MWH services.
Data used in this analysis were collected from three districts in Jimma Zone located in the southern part of Ethiopia. Gomma, Seka Chekorsa and Kersa districts are primarily rural and had populations ranging from 180 000 to 270 000 in 2016.23 The districts were purposefully selected from the 21 comprising Jimma Zone as they had the largest available population sizes compared with other districts, had poorly functioning MWHs according to Jimma Zone Health Office (JZHO) data, and did not have ongoing maternal health interventions such as other research or development projects or maternal health campaigns to minimise potential co-interventions and to facilitate a more even distribution of interventions as requested by our JZHO partners. Ethiopia’s three-tiered healthcare system consists of a district hospital and primary healthcare units (PHCUs) – made up of a health centre and community-based health posts – at the bottom. Levels 2 and 3 include general and specialised hospitals respectively.3 In partnership with the District Health Offices, the JZHO oversees service delivery at the 26 health centres present in the study area. All health centres have either temporary spaces or permanent, standalone structures designated to provide MWH services. According to the national guidelines, women who live far away from health centres, are inaccessible by ambulance, are 38 weeks or more pregnant and/or are at risk of experiencing obstetrical complications during delivery are eligible for MWH referral.4 MWHs are typically expected to consist of two rooms each accommodating six women and to have a suitable space equipped with utensils for women to prepare food or offer meals to women who cannot afford to provide for themselves. MWHs should have access to clean water, latrines and a power source.4 Exit surveys conducted nationally in 2016 revealed only 50% of rural MWHs had water available, 65% had an electricity supply and 73% had latrines although most were shared with other patients.24 As part of the country’s strategy to reduce maternal mortality, the MWH policy was drafted in 2013 to standardise the service provision of this joint community-health system, fee-free initiative. MWH operations are mainly sustained through community cash or crop contributions while management is handled by health centre staff. Reliance on community contributions may result in some variation between the districts in the quality and availability of MWH services. Health extension workers (HEWs), based in health posts, link communities to the health system by tracking pregnant women in their catchment areas and referring them for services.25 Additionally, HEWs provide community-based primary healthcare as prescribed in the 16 modules of the HEP; HEWs offer education and counselling, conduct physical exams of pregnant women, make referrals to health facilities among other antenatal services at the health post. They also conduct postnatal home visits to check-up on mothers and babies.3 26 The data source for this analysis was a baseline survey conducted prior to intervention roll-out in an ongoing cluster-randomised controlled trial aiming to evaluate the effectiveness of two safe motherhood interventions in improving institutional births: (i) functional MWHs and (ii) local leader education (ClinicalTrials.gov Identifier: {“type”:”clinical-trial”,”attrs”:{“text”:”NCT03299491″,”term_id”:”NCT03299491″}}NCT03299491). The MWH component focuses on improving amenities and services available at the MWHs to improve uptake. The education component targets village and religious leaders and uses culturally sensitive trainings to highlight the importance of safe motherhood and delivering at health facilities; materials were developed to address the barriers to maternal care identified in the Three Delays framework.27 The survey targeted 3840 women (24 clusters with 160 each); the sample size was determined by the primary outcome (institutional delivery) of the trial.28 This sample size achieves 80% power to detect an absolute difference in the proportions of institutional delivery of 0.17 assuming a control arm proportion of 0.4 and using a two-sided alpha of 0.025 to account for two pairwise comparisons. Women living within catchment areas of trial PHCUs who had a pregnancy outcome (live birth, stillbirth, miscarriage or abortion) up to 1 year prior to the survey were eligible. A two-stage sampling strategy was employed. First, 24 PHCUs were randomly selected for the trial. Then, 160 women per PHCU were randomly selected from community-based lists of pregnant women generated as part of health post records. HEWs and the Women’s Health Development Army (community-based administration) periodically update these lists. During household interviews conducted between October 2016 and January 2017, data were collected on sociodemographic characteristics, reproductive history, utilisation of various maternal healthcare services including MWHs, decision-making and social support. Structured questionnaires were mostly developed by adapting questions from the Demographic and Health Surveys. Questionnaires were piloted in Mana district, located adjacent to the study districts, and refined based on participant and interviewer feedback on question and response acceptability as well as interview duration. Adaptations primarily involved providing response options suited to the study area. Questionnaires were programmed in Open Data Kit on tablet computers in English, Afaan Oromo and Amharic for data collection. Translations were verified by research team members fluent in these languages. Trained research assistants conducted face-to-face interviews with women in a quiet, private space at the women’s homes; interviews took about 1 hour to complete. Husbands were also interviewed using a shorter version of the women’s questionnaire that included information on travel times to health facilities. Data were available for 3784 (98.5%) women recruited; due to lack of time, illness or the need for husband permission, 56 (1%) women refused to take part in the study. Definitions of variables used in this analysis are presented in table 1. The primary outcome was self-reported MWH use for any pregnancy. Candidate explanatory variables, identified from the literature, and hypothesised to be associated with MWH use at the individual level were women’s education and women’s occupation; at the household level, household wealth, women’s involvement in healthcare-related decision-making, having a companion to accompany women for health facility visits during pregnancy and travel time from home to nearest health centre were considered. Definitions of variables used to explore factors associated with women’s use of MWHs in three districts in Jimma Zone, Ethiopia (2016–2017) *Several dimensions of social support including financial or in-kind assistance, emotional support and practical support were assessed in the survey. Companion support was the dimension most relevant for maternity waiting home use. MWH, maternity waiting home; PHCU, primary healthcare unit. The household wealth variable was created using principal components analysis of items listed in table 1; items were selected to minimise clustering and truncation which compromise reliability.29 Briefly, socioeconomic ‘scores’ were generated for each household, which were then grouped into quintiles; the lowest quintile corresponded to the poorest households and the fifth quintile corresponding to the least poor households.29 Several dimensions of social support including financial or in-kind assistance, emotional support and practical support were assessed in the survey. Companion support was the dimension most relevant for maternity waiting home use. To allow us to explore the potential effect of community birthing norms on MWH use, the percentage of women delivering at a health facility was calculated for each PHCU catchment area and the PHCU-level means compared between MWH users versus non-users; the use of similar proxy variables for social norms have been used to explore contextual effects on utilisation of maternal healthcare services in studies conducted in Ethiopia18 and Africa.30 Characteristics of MWH users and non-users were described using frequencies and proportions or means and SD. X2 tests for categorical variables, and t-tests for continuous variables adjusted for clustering were performed using methods of Donner & Klar.31 Frequencies and proportions of community awareness of MWHs, reasons for use among users and services available to users were also reported. To identify variables associated with MWH use, multivariable generalised linear mixed effects regression was used. All candidate explanatory variables (education, occupation, household wealth, decision-making involvement, companion support, travel time and community birthing norms) were entered into the model. District of residence reported by the woman was included as a covariate to adjust for any district-level differences. A logit link function with a binomial distribution was used. To account for clustering, a random intercept was added for the PHCU. P values less than 0.05 were considered to be statistically significant. Analysis was conducted in STATA V.13. Patients/public were not involved in the design or implementation of this research. Results will be disseminated to policy-makers and local-level service implementers.
