MODELLING THE DETERMINANTS AND FORMS OF DOMESTIC VIOLENCE AGAINST PREGNANT WOMEN: A MULTINOMIAL LOGISTIC REGRESSION APPROACH TO CATEGORICAL DATA ANALYSIS - Gongden , M S; Nweze , N O; Bilkisu , M; Abdulahi, Abubakar (Economics and Statistics Research Journal (ESRJ), 2025)
This study applies a Multinomial Logistic Regression (MLR) framework to model unordered categorical outcomes in public health research, to examine forms of domestic violence experienced during pregnancy. MLR was selected for its capacity to estimate the probability of multiple, non-ordinal outcome categories such as emotional, physical, and sexual violence relative to a set of predictor variables (Agresti, 2018; Hosmer, Lemeshow, & Sturdivant, 2013). Using cross-sectional data from 499 pregnant women attending antenatal care, the model assessed the influence of maternal education, employment status, partner substance use, and mental health history on the likelihood of experiencing each form of violence. MLR results revealed that emotional violence was the most prevalent, followed by physical and sexual violence. The study demonstrates the effectiveness of MLR in disentangling complex, non-binary health outcomes and highlights the pressing need for integrated psycho-social screening and context-specific intervention strategies within maternal health programs (World Health Organization [WHO], 2013; Campbell, 2002). It also supports policy development aimed at addressing the socio-behavioral risk factors that heighten women's vulnerability to domestic violence during pregnancy (Barnett et al., 2011; Bandura, 1977).