Perceived Impact of Healthcare Infrastructure, Hospital Personnel and Transportation Accessibility on Maternal Mortality in Oyi Local Government Area, Anambra State Nigeria

Abstract

The study investigated impact of healthcare infrastructure, hospital personnel, and transportation accessibility on maternal mortality in Oyi local government area. Three research questions and three null hypotheses tested at 0.05 level of significance guided the study. The study adopted a descriptive survey design. The population for this study comprises 124,724 women aged 15–49 years, identified as the reproductive age group, residing in Oyi Local Government Area of Anambra State. The sample size is 400 women which was calculated using ‘Taro Yamene’ technique. Four distinct questionnaires were self-created: the Healthcare Infrastructure Assessment Scale (HIAS), the Hospital Personnel Assessment Scale (HPAS), the Transportation Accessibility Scale (TAS), and the Maternal Mortality Scale (MMS). The instruments were trial tested in Awka South Local Government Area, a similar region in Anambra State. The data were collected by the research assistance who were briefed on how to administer and retrieve copies of the instrument. The completed copies of the questionnaire were collected on the spot. Data collected were analyzed using simple regression. The study revealed that improved health infrastructure, competent healthcare personnel, and better transportation accessibility significantly reduced maternal mortality in Oyi LGA. Health infrastructure and personnel availability had strong negative correlations with mortality rates, while transportation showed a moderate yet significant effect, enhancing timely access to emergency obstetric care. The study recommends improved health infrastructure, skilled healthcare personnel, better transportation, and intensified health education to reduce maternal mortality in Oyi LGA. Adequate funding, policy integration, and stakeholder engagement are essential. Limitations include reliance on self-reported data, restricted geographic scope, cross-sectional design, and resource constraints affecting data depth.