Prevalence of and socioeconomic gradient in low birth weight in Ethiopia: further analysis of the 2016 demographic and health survey data

Abstract

Background Evidence suggests appearance of socioeconomic gradient in the probability of low birth weight (LBW). Such evidence, however, is scanty in Ethiopia. The study aimed to examine the prevalence of and socioeconomic gradient in LBW in Ethiopia. Method Data for the study were drawn from the Ethiopia Demographic and Health Survey conducted in 2016. The 2016 EDHS is the fourth wave in the series of nationally representative household surveys carried out in the country to deliver up-to-date health and demographic indicators for the Ethiopian population. Women aged 15 to 49 years were the main focus of the survey, with data also gathered from men aged 15 to 59 years and under five children. The study pursued complex sampling strategy to draw samples representative at national as well as at urban and rural levels. The data are available to the public domain and were accessed from the MEASURE DHS following registration. Multivariable logistic regression model and marginal standardization were used to estimate socioeconomic gradient in the probability of LBW. We performed sensitivity analysis to evaluate variation of LBW according to different categories of socioeconomic position. Maternal education and household wealth were used as measures of the socioeconomic position in the study. Results 13.2% (95% confidence interval = 10.73, 15.65) of births were complicated by LBW. The findings showed that socioeconomic gradient was evident between maternal education and LBW; as education increases from no education to secondary education, the probability of occurrence of LBW consistently declined. However, no gradient in LBW was detected for household wealth. Conclusions We have identified education gradient in LBW, with the highest burden of LBW occurring among the non-educated women. To redress the observed education disparity in LBW, targeted interventions need to be implemented with greater emphasis placed on illiterate women.

Influence of gestational weight gain on baby’s birth weight in Addis Ababa, Central Ethiopia: a follow-up study

“…The proportion of babies born with LBW (7.5% (95% CI 4.8% to 11.0%)) was comparable with the findings from the nationwide study using the 2016 Ethiopia Demographic Health Survey data, which was 13.2% (95% CI 10.7% to 15.7%), 38 but lower than a finding from a metaanalysis conducted in 2018 in Ethiopia (pooled LBW data from 1995 to 2017), which was 17.3% (95% CI 14.1% to 20.4%). 39 Studies conducted in different parts of the country reported that maternal education, 38 employment status, income and maternal age 39 are significantly associated with a baby's birth weight. However, these factors were not significantly associated with birth weight in our study.…”

Policy to Decrease Low Birth Weight in Indonesia: Who Should Be the Target?

“…Moreover, this study revealed that women in all wealth status categories, compared to the wealthiest, had a higher probability of giving birth to LBW babies. An earlier study analyzing secondary data from the 2016 Ethiopia Demographic and Health Survey in Ethiopia also reported similar results with the incidence of LBW being dominant among the poor [ 44 ]. Poor households have limitations in providing food for all family members, including pregnant women.…”

Machine learning algorithms for predicting low birth weight in Ethiopia

“…According to previous research [ 1 , 15 , 16 ], Ethiopia is one of the countries with the most significant number of low birth weight babies globally. Furthermore, while the prevalence of low birth weight has decreased in the country from time to time, more work is needed to promote this decline and to limit the detrimental implications of the occurrence [ 1 , 4 , 13 , 25 ]. In this study, the average birth weight was 3268.983 g, with a maximum of 6000 g and a minimum of 500 g, while quartiles one and three were 3000 and 3750 g, respectively.…”

“…As a result, identifying significant features associated with LBW is an essential initial step. An assessment of the literature [4,22] and data availability is used to do this. These 25 features are shown in Table 1 below.…”

“…Understanding the importance of preterm delivery and poor fetal growth as causes of low birth weight is critical for developing effective prevention interventions. Moreover, [ 4 ] revealed education was one of the predictors in LBW modeling.…”