Multilevel Modelling of the Individual and Regional Level Variability in Predictors of Incomplete Antenatal Care Visit among Women of Reproductive Age in Ethiopia: Classical and Bayesian Approaches.

Abstract

Background: Antenatal care is an operational public health intervention to minimize maternal and child morbidity and mortality. However, for varied reasons, many women fail to complete the recommended number of visits. The objective of this study was to assess antenatal care utilization and identify the factors associated with the incomplete antenatal care visit among reproductive age women in Ethiopia. Methods: The 2019 Ethiopian Mini Demographic and Health Survey data were used for this study. Multilevel logistic regression analysis and two level binary logistic regression models were utilized. Results: Around 56.8% of women in Ethiopia did not complete the recommended number of antenatal care visits. Women from rural areas were about 1.622 times more likely to have incomplete antenatal care compared to women from urban areas. Women who had no pregnancy complication signs were about 2.967 times more likely to have incomplete antenatal care compared to women who had pregnancy complication signs. Women who had a slight problem and a big problem with the distance from a health center were about 1.776 and 2.973 times more likely, respectively, to have incomplete antenatal care compared to women whose distance from a health center was not a problem. Furthermore, women who had ever terminated pregnancy were about 10.6% less likely to have incomplete antenatal care compared to women who had never terminated pregnancy. Conclusions: The design and strengthening of existing interventions (e.g., small clinics) should consider identified factors aimed at facilitating antenatal care visits to promote maternal and child health related outcomes. Issues related to urban–rural disparities and noted hotspot areas for incomplete antenatal care visits should be given special attention.