Abstract
ObjectivesOptimal antenatal care (ANC) services are the main strategy to reduce maternal and newborn mortality. Understanding the geographic variation of ANC service utilisation is essential for regional- and local-level interventions. However, data on spatial variation of optimal ANC service utilisation are limited. Hence, this study aimed to investigate the spatial variations and determinants of optimal ANC service utilisation in Ethiopia. Study designThis was a spatial and survey regression analysis. MethodsThe secondary analysis of the Ethiopian Demographic and Health Survey 2019 was performed to investigate the spatial variation and determinants of optimal ANC service utilisation among women who were pregnant in the 5 years preceding the survey. Spatial dependency, clustering and prediction were conducted using Global Moran's I statistics, Getis-Ord Gi∗ and Kriging interpolation, respectively, using ArcGIS version 10.8. A survey binary logistic regression model was fitted to identify determinants of optimal ANC service utilisation. ResultsOf 3979 pregnant women, 1656 (41.62%) had optimal ANC visits in Ethiopia. Optimal ANC utilisation was shown more prevalent in Northern, Eastern, Central and Northwestern regions of Ethiopia. The results also identified low levels of optimum ANC utilisation in Northeastern, Southeastern, Southern and Western regions of Ethiopia. Wealth index, timing of initial ANC visit and region were significantly associated with optimal ANC service utilisation in Ethiopia. ConclusionsOptimal ANC service utilisation showed significant spatial dependency in Ethiopia, with spatial clustering in the Northern and Northwestern regions of the country. In addition, the results from this study suggest that financial support should be considered for women living in households in the poorest wealth index and ANC initiation should begin within the first trimester. It is recommended that targeted policies and strategies are introduced to regions with low levels of optimal ANC service utilisation.
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