Search

Background: Nearly three-fourths of pregnant women in Ethiopia give birth at home. However, the spatial pattern and spatial variables linked to home delivery in developing regions of Ethiopia have not yet been discovered. Thus, this study aimed to explore the geographical variation of home delivery and its determinants among women living in emerging (Afar, Somali, Gambella, and Benishangul-Gumuz) regions of Ethiopia, using geographically weighted regression analysis. Methods: Data were retrieved from the Demographic and Health Survey program's official database (http://dhsprogram.com). In this study, a sample of 441 reproductive-age women in Ethiopia's four emerging regions was used. Global and local statistical analyses and mapping were performed using ArcGIS version 10.6. A Bernoulli model was applied to analyze the purely spatial cluster discovery of home delivery. GWR version 4 was used to model spatial regression analysis. Results: The prevalence of home delivery in the emerging regions of Ethiopia was 76.9% (95% CI: 72.7%, 80.6%) and the spatial distribution of home delivery was clustered with global Moran's I = 0.245. Getis-Ord analysis detected high-home birth practice among women in western parts of the Benishangul Gumz region, the Eastern part of the Gambela region, and the Southern and Central parts of the Afar region. Non-attendance of antenatal care, living in a male-headed household, perception of distance to a health facility as a big problem, residing in a rural area, and having a husband with no education significantly influenced home delivery in geographically weighted regression analysis. Conclusions: More than three-fourths of mothers in the developing regions of Ethiopia gave birth at home, where high-risk locations have been identified and the spatial distribution has been clustered. Thus, strengthening programs targeted to improve antenatal care service utilization and women's empowerment is important in reducing home birth practice in the study area. Besides, supporting the existing health extension programs on community-based health education through home-to-home visits is also crucial in reaching women residing in rural settings. [ABSTRACT FROM AUTHOR]

Background: Understanding the context of a health programme is important in interpreting evaluation findings and in considering the external validity for other settings. Public health researchers can be imprecise and inconsistent in their usage of the word “context” and its application to their work. This paper presents an approach to defining context, to capturing relevant contextual information and to using such information to help interpret findings from the perspective of a research group evaluating the effect of diverse innovations on coverage of evidence-based, life-saving interventions for maternal and newborn health in Ethiopia, Nigeria, and India. Methods: We define “context” as the background environment or setting of any program, and “contextual factors” as those elements of context that could affect implementation of a programme. Through a structured, consultative process, contextual factors were identified while trying to strike a balance between comprehensiveness and feasibility. Thematic areas included demographics and socio-economics, epidemiological profile, health systems and service uptake, infrastructure, education, environment, politics, policy and governance. We outline an approach for capturing and using contextual factors while maximizing use of existing data. Methods include desk reviews, secondary data extraction and key informant interviews. Outputs include databases of contextual factors and summaries of existing maternal and newborn health policies and their implementation. Use of contextual data will be qualitative in nature and may assist in interpreting findings in both quantitative and qualitative aspects of programme evaluation. Discussion: Applying this approach was more resource intensive than expected, in part because routinely available information was not consistently available across settings and more primary data collection was required than anticipated. Data was used only minimally, partly due to a lack of evaluation results that needed further explanation, but also because contextual data was not available for the precise units of analysis or time periods of interest. We would advise others to consider integrating contextual factors within other data collection activities, and to conduct regular reviews of maternal and newborn health policies. This approach and the learnings from its application could help inform the development of guidelines for the collection and use of contextual factors in public health evaluation. [ABSTRACT FROM AUTHOR]