Binary Logistic Regression Modeling of Factors Affecting Maternal Health Care Utilization in Nigeria

Abstract

Maternal mortality is still far too high worldwide, even with major efforts to improve the use of maternal health care services. Thus, this study aimed at assessing the factors affecting maternal health care utilization in Nigeria using binary logistic regression model. The antenatal Care (ANC) utilization was used as an indicator of maternal health care utilization. The data for the study were extracted from 2018 Nigerian Demographic and Health Survey (NDHS) Data. The data extracted was analyzed using single level binary logistic regression model. The findings of the study revealed that maternal age at birth, maternal educational level, ethnicity, place of residence, religion, wealth index, sex of household head, birth type, insurance cover, maternal employment status, preceding birth intervals, household size, region, birth order and age of household head were the significant factors affecting maternal health care utilization in Nigeria. Based on these findings it was recommended among others that the government should focus on improving economic conditions and educational opportunities for women through formulating policies and initiatives that target women with no education and those in lower income groups must be put into place.