Trends of infant mortality and its determinants in Ethiopia: mixed-effect binary logistic regression and multivariate decomposition analysis

Abstract

Background: Infant mortality remains a serious global public health problem. The global infant mortality rate has decreased significantly over time, but the rate of decline in most African countries, including Ethiopia, is far below the rate expected to meet the SDG targets. Therefore, this study aimed to investigate the trends of infant mortality and its determinants in Ethiopia based on the four consecutive Ethiopian Demographic and Health Surveys (EDHSs).

Methods: This analysis was based on the data from four EDHSs (EDHS 2000, 2005, 2011, and 2016). A total weighted sample of 46,317 live births was included for the final analysis. The logit-based multivariate decomposition analysis was used to identify significantly contributing factors for the decrease in infant mortality in Ethiopia over the last 16 years. To identify determinants, a mixed-effect logistic regression model was fitted. The Intra-class Correlation Coefficient (ICC) and Likelihood Ratio (LR) test were used to assess the presence of a significant clustering effect. Deviance, Akaike Information Criteria (AIC), and Bayesian Information Criteria (BIC) were used for model comparison. Variables with a p-value of less than 0.2 in the bi-variable analysis were considered for the multivariable analysis. In the multivariable analysis, the Adjusted Odds Ratio (AOR) with 95% Confidence Interval (CI) were reported to identify the statistically significant determinants of infant mortality.

Results: Infant mortality rate has decreased from 96.9 per 1000 births in 2000 to 48 per 1000 births in 2016, with an annual rate of reduction of 4.2%. According to the logit based multivariate decomposition analysis, about 18.1% of the overall decrease in infant mortality was due to the difference in composition of the respondents with respect to residence, maternal age, type of birth, and parity across the surveys, while the remaining 81.9% was due to the difference in the effect of residence, parity, type of birth and parity across the surveys. In the mixed-effect binary logistic regression analysis; preceding interval < 24 months (AOR = 1.79, 95% CI; 1.46, 2.19), small size at birth (AOR = 1.55, 95% CI; 1.25, 1.92), large size at birth (AOR = 1.26, 95% CI; 1.01, 1.57), BMI < 18.5 kg/m² (AOR = 1.22, 95% CI; 1.05, 1.50), and twins (AOR = 4.25, 95% CI; 3.01, 6.01), parity> 6 (1.51, 95% CI; 1.01, 2.26), maternal age and male sex (AOR = 1.50, 95% CI: 1.25, 1.79) were significantly associated with increased odds of infant mortality.

Conclusion: This study found that the infant mortality rate has declined over time in Ethiopia since 2000. Preceding birth interval, child-size at birth, BMI, type of birth, parity, maternal age, and sex of child were significant predictors of infant mortality. Public health programs aimed at rural communities, and multiparous mothers through enhancing health facility delivery would help maintain Ethiopia's declining infant mortality rate. Furthermore, improving the use of ANC services and maternal nutrition is crucial to reducing infant mortality and achieving the SDG targets in Ethiopia.

Keywords: Ethiopia; Infant mortality; Mixed effect analysis; Multivariate decomposition analysis.

Fig. 1

The trends of infant mortality rate among live births from reproductive-age women in Ethiopia over time (2000–2016)

Fig. 2

The trends of infant mortality rate across region regions in Ethiopia over time (2000–2016)