An Application of Hierarchical Logistic Modelling to Maternal Health Care Utilization in Nigeria

Abstract

Background: With a maternal mortality rate of 576 deaths per 100,000 live births, Nigeria accounts for about 10% of all maternal deaths,  globally, and has the second highest mortality rate in the world. This high mortality rate makes maternal health a huge public health  problem in the country. This paper, therefore, aimed at investigating socio-demographic factors affecting the utilization of Maternal  Health Care (MHC) in the context of hierarchical modelling.
Methods: Data were extracted from the Nigerian Demographic and Health Survey, 2013. The data have a hierarchical structure, with the  20,116 Ever-Married Women nested within their respective states of residence. Three different hierarchical logistic regression models  were formulated to allow for comparison of outcomes between clusters.
Findings: A proportion of opposed odds ratio of 0.45 indicate that in 45% of pair-wise comparisons between the urban and rural  residence, the odds of MHC utilization was higher at an urban residence than at a rural residence by 1.388 times. The Median Odds Ratio  (MOR) for Model 2 indicated the odds of MHC utilization was less than 2.41 for a woman in a state at higher risk compared to a different woman in a state at lower risk. The intra-class correlation coefficient revealed a 40% (Model 1), 21% (Model 2) and 16% (Model 3) chances  of utilizing MHC, explained by between-states differences, respectively.
Conclusion: In order to close the variation in healthcare delivery in Nigeria, there is a need for government to execute state-specific  interventions that would allow fair distribution and utilization of MHC.