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Infant mortality rate, spatial variation, and it’s time to death determinates in East Africa,Evidence from DHS 2015-2022: Bayesian spatial frailty analysis

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dc.contributor.author Kifle, Tigist
dc.date.accessioned 2025-07-07T13:23:30Z
dc.date.available 2025-07-07T13:23:30Z
dc.date.issued 2025-07-07
dc.identifier.uri http://hdl.handle.net/123456789/9291
dc.description.abstract Introduction: Infant mortality is the death of an infant before his or her first birthday. In 2021, around 3.8 million infants lost their lives, and half of them, approximately 1.9 million were Sub Saharan region. Although the intervention is successful in lowering infant mortality rates worldwide Sub-Saharan Africa, particularly East Africa, continues to struggle with high rates of infant and under-five mortality. Though many studies have been conducted limited literature accounts for the impact of spatial effect. Therefore this study aims to add the spatial random effect to identify factor associated with infant mortality. Objective: This study aims to determine the IMR, spatial variation, and its time to death determinants in East Africa from 2015-2022. Method: This study included a total of 101,532 infants. The IMR was estimated and the spatial pattern was checked by Moran’s I statistics. The Bayesian frailty spatial frailty analysis model with the AFT approach was used to identify the predictor variable. The model was diagnosed through a Cox-Snell plot, and convergence was checked through a trace plot and density plot. Results: The IMR was 39.83 per 1000 live births (95% CI: 35.81, 44.27) in nine East African countries. The spatial distribution of IMR shows a nonrandom pattern and the identified hotspot area was northwestern, northeastern, and eastern Ethiopia, Burundi, western, northern, and southern Malawi, the northeast of Mozambique, southern Tanzania, southwestern Zambia, and northwestern and eastern Zimbabwe. Factor significantly associated with infant survival time from the lognormal AFT model was started breastfeeding after 24 hours (AF = 0.0905, 95%CI: 0.084, 0.106), didn’t have ANC follow-up during her pregnancy (AF = 0.652, 95%CI: 0.535, 0.794) a mother age between 15-24 years (AF = 0.798, 95%CI: 0.709, 0.9), small-sized birth weight (AF = 0.634, 95%CI: 0.565, 0.728), multiple births (AF = 0.25, 95%CI: 0.212, 0.3), Moreover, the Male child's (AF = 0.784 95% CI 0.708, 0.8), parity more than five (AF = 0.79 95%CI: 0.678,0.93), and being unemployed mother (AF = 1.35 95%CI: 1.11, 1.62). Conclusion and Recommendation: The pooled IMR was higher than the global estimate. There was a spatial clustering pattern in infant mortality. Breastfeeding initiation time, number of ANC visits, maternal age, and birth weight, number of pregnancies, infant sex, parity, and unemployment of mother were significantly associated with infant survival time. It is recommended that enhancing ANC service close monitoring of multiple pregnancies, and enhance immediate breastfeeding en_US
dc.description.sponsorship uog en_US
dc.language.iso en en_US
dc.subject Infant mortality rate, East Africa, spatial variation en_US
dc.title Infant mortality rate, spatial variation, and it’s time to death determinates in East Africa,Evidence from DHS 2015-2022: Bayesian spatial frailty analysis en_US
dc.type Thesis en_US


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