Socioeconomic factors contributing to exclusion of women from maternal health benefit in Abuja, Nigeria

Author:

Oyewale Tajudeen O.,Mavundla Thandisizwe R.

Abstract

Background: An understanding of the predictive effect of socioeconomic characteristics (SECs) of women on maternal healthcare service utilisation is essential in order to maximise maternal health benefits and outcomes for the newborn.Objectives: To describe how SECs of women contribute to their exclusion from maternal health benefits in Abuja Municipal Areas Council (AMAC) in Abuja, Nigeria.Method: A non-experimental, facility-based cross-sectional survey was done. Data were collected from 384 respondents using a structured interviewer-administered questionnaire. The participants were sampled randomly at antenatal care (ANC) clinics in the five district hospitals in AMAC. Data analysis included descriptive statistics, cross-tabulations and measures of inequality. Logistic regression analysis was used to test the relationship between SECs (predictors) and maternal healthcare service utilisation.Results: There were differentials in the utilisation of maternal healthcare services (ANC, delivery care, post natal care [PNC] and contraceptive services) amongst women withdifferent SECs; and the payment system for maternal healthcare services was regressive. There were inconsistencies in the predictive effect of the SECs of women included in this study (age,education, birth order, location of residence, income group and coverage by health insurance) on maternal healthcare service utilisation when considered independently (bivariate analysis) as opposed to when considered together (logistic regression), with the exception of birth order, which showed consistent effect.Conclusion: SECs of women were predictive factors of utilisation of maternal healthcare services. There is a need for targeted policy measures and programme actions toward multiple SECs of women in their natural co-existing state in order to optimise maternal health benefits.

Publisher

AOSIS

Subject

General Medicine

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