Bayesian modeling of maternal mortality in Ghana

Dioggban Jakperik(1), Saralees Nadarajah(2), Michael J. Adjabui(3),


(1) C. K. Tedam University of Technology and Applied Sciences, Ghana
(2) Howard University, Washington DC, USA
(3) C. K. Tedam University of Technology and Applied Sciences, Ghana
Corresponding Author

Abstract


Maternal mortality is a critical measure for quality of health system in any country and hence many countries have made concerted efforts to check its occurrence. Various stakeholders involved in the management of health system in Ghana have been tasked to ensure women do not die whilst giving birth. This study was conducted on a sample of 1,052 women selected from all the ten administrative regions of Ghana in which 188 maternal deaths occurred. Bayesian logistic modeling was used. Age at death, marital status, age, season, region, place of death, place of residence, religion and ethnicity emerged as the most significant determinants of maternal mortality in Ghana. It was realized that high numbers of maternal deaths were recorded in the least developed regions in the northern region. It is therefore important for stakeholders to devise a road map of getting health workers to accept postings to the rural areas and also provide well resourced health facilities to stem this menace. (Afr J Reprod Health 2023; 27 [2]: 57-66)

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