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Background: Globally, around 4 million babies die within the first month of birth annually with more than 3 million stillbirths. Of them, 99% of newborn deaths and 98% of stillbirths occur in developing countries. Despite giving priority to maternal health services, adverse birth outcomes are still major public health problems in the study area. Hence, a continuum of care (CoC) is a core key strategy to overcome those challenges. The study conducted on the effectiveness of continuum of care in maternal health services was scarce in developing countries and not done in the study area. We aimed to assess the effectiveness of continuum of care and determinants of adverse birth outcomes. Methods: Community and health facility-linked prospective follow-up study designs were employed from March 2020 to January 2021 in Northwestern Ethiopia. A multistage clustered sampling technique was used to recruit 2198 pregnant women. Data were collected by using a semi-structured and pretested questionnaire. Collected data were coded, entered, cleaned, and analyzed by STATA 14. Multilevel logistic regression model was used to identify community and individual-level factors. Finally, propensity score matching was applied to determine the effectiveness of continuum of care. Results: The magnitude of adverse birth outcomes was 12.4% (95% CI 12.2–12.7): stillbirth (2.8%; 95% CI 2.7–3.0), neonatal mortality (3.1%; 95% CI 2.9–3.2), and neonatal morbidity (6.8%; 95% CI 6.6–7.0). Risk factors were poor household wealth (AOR = 3.3; 95% CI 1.07–10.23), pregnant-related maternal complications during pregnancy (AOR = 3.29; 95% CI 1.68–6.46), childbirth (AOR = 6.08; 95% CI 2.36–15.48), after childbirth (AOR = 5.24; 95% CI 2.23–12.33), an offensive odor of amniotic fluid (AOR = 3.04; 95% CI 1.37–6.75) and history of stillbirth (AOR = 4.2; 95% CI 1.78–9.93). Whereas, receiving iron-folic acid (AOR = 0.44; 95% CI 0.14–0.98), initiating breastfeeding within 1 h (AOR = 0.22; 95% CI 0.10–0.50) and immunizing newborn (AOR = 0.33; 95% CI 0.12–0.93) were protective factors. As treatment effect, completion of continuum of care via time dimension (β = − 0.03; 95% CI − 0.05, − 0.01) and space dimension (β = − 0.03; 95% CI − 0.04, − 0.01) were significantly reduce perinatal death. Conclusions: Adverse birth outcomes were high as compared with national targets. Completion of continuum of care is an effective intervention for reducing perinatal death. Efforts should be made to strengthen the continuum of care in maternal health services, iron supplementation, immunizing and early initiation of breastfeeding.
Community and health facility-linked prospective follow-up study was conducted in Benishangul-Gumuz Regional State (BGRS) from March 2020 to January 2021. The region is one of the eleven regional states of Ethiopia. Assosa town is the capital city of the region, located at 670KMs to the Western of Addis Ababa, the capital city of Ethiopia. The region has three zones, three city administration, twenty-one districts/Woredas, one special district/Woreda’s, and 475 Kebele’s (439 rural and 36 urban). The region represents around 4.6% of the total land area of Ethiopia and most of the people in the region are sparsely populated [16]. The total population of the region in 2022 was 1,219,017 and female in reproductive age group was 328,324 [17]. All pregnant women and births that registered as live births, as well as stillbirths at the time of birth within the follow-up period, were considered as source populations. Whereas, the study population were newborns that registered as “live births” or “stillbirths” (which is declared by women, birth attendants, or health workers) at the time of birth and selected by simple random sampling techniques. The sample size for this study was calculated using STATA/MP 13.0 software by considering two population proportion formulas. The outcome variable was the adverse birth outcomes (stillbirth, neonatal death, and any illness within the neonatal period) and completion of the continuum of care in maternal health services was considered as exposure (predictor) variable for the adverse birth outcomes. There is no similar study in Ethiopia that examined the effect of the continuum of care in maternal health services on adverse birth outcomes; a study conducted in Uttar Pradesh, India was used to estimate the minimum required sample size [13]. Accordingly, the proportion of adverse birth outcomes, “neonatal death”, among mothers who use a complete continuum of care in maternal health services is estimated to be 4.29% (P1 = 0.0429), and the proportion of adverse birth outcomes, “neonatal death”, among mothers who never use maternal health services is estimated to be 8.43% (P2 = 0.0843) [13]. A 95% confidence level and 80% power were used to detect a 4.14% difference. In addition, a ratio (r) of 1:1 was considered for the exposed and unexposed groups. Then, the pooled population proportion (P) = P1+P21+r was calculated (P = 0.0636). Finally, a design effect of 2 and a non-response rate of 10% were considered. Based on these assumptions, the final sample size was found to be 2402 pregnant women. Since this research work was carried out at a regional level, the study subjects (pregnant women) were chosen using a multistage clustered sampling technique. The sampling procedure used for this study was as follows: primarily two zones and one town/city administration were chosen by simple random sampling (SRS). Following that, four districts/“woredas” from the Assosa Zone, two districts/“woredas” from the Metekel Zone, and two districts/“woredas” from the Assosa town/city administration were chosen by simple random sampling (SRS) technique. Thirdly, from each selected district/“woreda”, seven kebeles (except Assosa district/“woreda”: 10 kebeles and Assosa town administration: five ketenas) were selected and included in the study. Then, among the selected kebeles/ketenas (7 kebeles from each district/“woreda”, 10 kebeles from Assosa district/“woreda” and five ketenas from each district/“woreda” of town/city administration), pregnant women were enumerated by using house-to-house visit and all obtained and registered pregnant women were included in the study. BSC Midwifery and Health Extension Workers (HEWs) assessed and diagnosed pregnancy status of the women. All women who claimed 8 weeks or longer pregnancy, as determined by the loss of two consecutive menses and pregnancy screening criteria (S1), were considered for eligibility and joined the study, which was followed for 11 months. Assuming that each household with pregnant women had at least one pregnant woman, households with pregnant women and neonates were selected as the final sampling unit (FSU). Meantime, all health facilities found within the catchment areas were listed and considered as a candidate for the health facility-based survey. Therefore, 46 health facilities (3 hospitals, 12 health centers, and 31 health posts) were found within the catchment areas and included in the health facility-based survey. The inclusion criteria were births that were registered or informed as live births or stillbirth after the expulsion of placenta and whose mother was a permanent resident of the sampled areas. Whereas, pregnant women with hearing or other communication disabilities, severely ill and mentally ill women, pregnant women whose pregnancy is less than 8 weeks, and pregnant women who had completed fourth ANC visit at the time of the baseline survey were excluded. Data collection was conducted using semi-structured questionnaires and registration format adapted from EDHS 2011 [18], National Technical Guidance for Maternal and Perinatal Death Surveillance and Response (MPDSR) 2017 [19], MCH Program Indicator Survey 2013 [20], and survey tools conducted in Jimma Zone, Southwestern Ethiopia [21], Rural Southern Ethiopia [22] and other relevant different kinds of literature. The instrument was prepared in English and translated into the local language (“Amharic”) and then back-translated to English to ensure the validity of the instrument. Following that, training was offered for data collectors and supervisors for 3 days, and also pre-test was carried out on 35 individuals, located outside of the study areas/cluster. During actual data collection, the principal investigator and supervisors were frequently supervising and checking the work of data collectors, and also clarification and direction were forwarded to those who had doubts. Moreover, chronbach alpha at 0.7 cut-off point was used to test inter item consistency of the indicators to measure the composite score of adverse birth outcomes, continuum of care and household wealth index quintile. Adverse birth outcome: pregnant women who experienced a pregnancy termination after 28 weeks of gestational age, categorized as “stillbirth,” or neonates who showed any evidence of life after complete expulsion or extraction from their mother and had any illness within 28 days, categorized as “neonatal morbidity,” or neonates who died before 28 days after delivery, categorized as “neonatal mortality.” Continuum of care in maternal health services: package of interventions consisting of a composite measure of nine variables (1st ANC, 2nd ANC, 3rd ANC, and 4th ANC, Skill delivery care, 1st PNC, 2nd PNC, 3rd PNC and 4th PNC services). Pregnant women who miss at least one or more packages of intervention/s categorized as discontinuation of care, otherwise, receive the entire recommended minimum package of interventions considered as “completing the continuum of care in maternal health services.” Intervention or exposure group: pregnant women who used the entire maternal health services (ANC, SD, and PNC) in a continuous manner were considered as “exposure groups” or “completion of the continuum of care in maternal health services. ” Control or non-exposure group: pregnant women who missed at least one service in maternal health services (ANC, SD, and PNC) were considered as “non-exposure groups” or “discontinuation of care in maternal health services.” Data were coded and entered into Epi. Info version 7.2.2.6 to develop skipping patterns and avoid logical mistakes. Then, data were cleaned, edited, and analyzed using STATA Software version 14. All variables were computed for descriptive statistics. Analysis with only one independent variable was performed; the crude odds ratio and 95% confidence interval were used to select candidate variables for multivariable analysis at p < 0.25. At the level of significance (p < 0.05), a maximum likelihood estimate of the independent effect on the outcome variable was calculated. The household wealth index was calculated and categorized by using Principal Component Analysis (PCA). Before running the full model, effect modification or interaction effect at p 10%) were assessed. All independent variables included had VIF < 10 and the multi-collinearity effects of each variable were p < 0.1. Hence, there was no significant interaction and the multi-collinearity effects were detected. Since the sampling procedure for this study was a multistage clustered sampling procedure; due to cluster variability multilevel logistic regression model was applied to detect determinant factors of adverse birth outcomes (stillbirth, neonatal death, and any neonatal illness). Thus, for this study, ‘Kebeles/Ketenas’ were considered as clusters, and cluster level variables such as place of residence, access to the hospitals, access to the health centers, access to the health posts, and household wealth index were taken as level-2 variables. Women who gave birth during follow study were nested within their household wealth index and the community. As a result, women’s individual-level variables were socio-demographic, obstetric, information, maternal health services, and newborn health services were taken as level-1 variables. Log likelihood ratio (LR) test was performed to confirm the goodness of fit for the multilevel model that was found to be statistically significant indicating that the dataset is a best fit to the model. Finally, the effect of continuum of care in maternal health services on perinatal death was estimated by Propensity Score Matching (PSM). The treatment effects were measured by Average Treatment Effect in Treated (ATT) with β and 95% CI at p < 0.05.
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