Bayesian spatial analysis of factors influencing neonatal mortality and its geographic variation in Ethiopia

Abstract

Background Ethiopia is a Sub-Saharan country with very high neonatal mortality rates, varying across its regions. The rate of neonatal mortality reduction in Ethiopia is slow, and Ethiopia may not meet the third United Nations sustainable development target by 2030. This study aimed to investigate the spatial variations and contributing factors for neonatal mortality rates in Ethiopia. Methods We analysed data from the 2016 Ethiopian Demographic and Health Survey (EDHS), which used a two-stage cluster sampling technique with a census enumeration area as primary and households as secondary sampling units. A Bayesian spatial logistic regression model using the Stochastic Partial Differential Equation (SPDE) method was fitted accounting for socio-economic, health service-related and geographic factors. Results Higher neonatal mortality rates were observed in eastern, northeastern and southeastern Ethiopia, and the Somali region had higher risks of neonatal mortality. Neonates from frequently drought-affected areas had a higher mortality risk than less drought-affected areas. Application of traditional substances on the cord increased the risk of neonatal mortality (Adjusted Odds Ratio (AOR) = 2.07, 95% Credible Interval (CrI): 1.12 to 4.30) and getting health facility delivery services had a lower odds of neonatal mortality (AOR = 0.60, 95% CrI: 0.37, 0.98). Conclusions Residing in drought-affected areas, applying traditional substances on the umbilical cord and not delivering at health facilities were associated with a higher risk of neonatal mortality. Policy-makers and resource administrators at different administrative levels could leverage the findings to prioritise and target areas identified with higher neonatal mortality rates.

Nomogram to predict risk of neonatal mortality among preterm neonates admitted with sepsis at University of Gondar Comprehensive Specialized Hospital: risk prediction model development and validation

“…It is also found higher than a study conducted among neonates referred to comprehensive and specialized hospitals in Amhara regional state 30.6% [ 6 ] and Tikur Anbesa Specialized Hospital 29.8% [ 27 ]. This higher and lower incidence of neonatal mortality in different settings might be due to geographic variation across the country which resulted from socioeconomic inequalities as established in previous studies [ 50 , 51 ]. In addition, the variation in quality of care across hospitals in Ethiopia might result this difference [ 52 , 53 ].…”

Proximate and distant determinants of maternal and neonatal mortality in the postnatal period: A scoping review of data from low- and middle-income countries

“…Marital status. Of the thirteen studies [25,26,37,45,58,61,65,68,70,81,85,90,93] that examined marital status as a risk factor, three found a decreased risk of neonatal mortality when mothers were married [26,65,93].…”

Predictors of pregnancy loss among urban and rural women aged 15 to 49 years in Pakistan

“…The explanatory variables were selected based on existing literature regarding predictors of pregnancy loss in Pakistan (7-9, 15, 16, 21, 22). This study also adapted the Mosley and Chen framework which is widely used to study child survival in LMIC (17,(23)(24)(25)(26)(27)(28). The framework consists of community level factors, socioeconomic factors, maternal factors, environmental factors, and health services factors as seen in Fig.…”