| Summary: | The healthcare sector is paying attention to pregnancy and antenatal care (ANC) for mothers. Thus, the presented study aimed at exploring the trend and identifying the barrier for ANC utilization of mothers in Ethiopia. Data mining is a field of big data science used to discover patterns and knowledge from big data. All Ethiopian demographic and health survey datasets from 2000 to 2016 were used for this study. The cross-sectional study was conducted using the knowledge discovery process having steps; selection, cleaning, integration, transformation, and data mining algorithms (classification, clustering, association rules, and attribute ranking with pattern prediction). The proportion of ANC utilization was 27.6%, 28.2%, 34.5%, and 62.9% in 2000, 2005, 2011, and 2016 respectively. The pooled data contained 28,631 mothers, which were included in the study. Of these, 56.09% of them were not utilizing ANC during pregnancy. Pregnancy complication, the educational status of mothers and husbands, mother's residence, economic status, and media exposure had an association with ANC utilization having a confidence level of 95% and above. ANC utilization in Ethiopia increased significantly from 27.6%in 2000 to 62.9% in 2016. Despite this increment, the pooled proportion of ANC utilization is still low. The barriers to this low utilization were; pregnancy complication, poor education of mothers and their husbands, rural residence, poor economic status, and poor media exposure. Finally, this study will recommend that the government of Ethiopia has to expand the media and education coverage related to ANC throughout the country and mothers have to be aware of the importance of ANC during pregnancy. Keywords: Antenatal care, Data mining, EDHS, Ethiopia, KDD
|
|---|
