Abstract
Only 14% of births had information on birth weight available at the time of birth in Ethiopia. Hence, previous studies underestimate the magnitude and associated factors of low birth weight (LBW). As a result, the goal of this study is to fill those gaps in the previous studies. An institution-based cross-sectional study was employed. Binary logistic regression was used to identify the associated factors. In this study, the magnitude of LBW was 13.06%. History of chronic medical illness (AOR = 3; 95% CI: (1.02, 9.17)), haemoglobin level during pregnancy (AOR = 0.23; 95% CI: (0.10, 0.50)), iron/folic acid supplementation (AOR = 0.27; 95% CI: (0.10, 0.72)) and extra meal during pregnancy (AOR = 3.2; 95% CI: (1.52, 7.00)) were significantly associated with LBW. The magnitude of LBW in this study was comparable to the Ethiopian Demographic and Health Survey (EDHS) report from 2016. It is better to intervene in those identified factors in order to reduce LBW. Impact Statement What is already known on this subject? Low birth weight (LBW) accounts for 60–80% of all neonatal deaths each year. In developing countries like Ethiopia, LBW is a major public health concern. Almost half of the world's infants are not weighed at birth, a figure that is especially high in sub-Saharan Africa including Ethiopia. What do the results of this study add? Only 14% of births had information on birth weight available at the time of birth in Ethiopia. Hence, previous studies underestimate the magnitude and associated factors of LBW. To meet the Sustainable Development Goals (SDGs)-2030 targets for neonatal and child mortality, sufficient evidence on the magnitude of LBW and associated factors must be important in order to contribute to the development of timely interventions. A history of chronic medical illness, haemoglobin level, iron/folic acid supplementation and extra meal during pregnancy was associated with LBW. What are the implications of these findings for clinical practice and/or further research? The findings of this study will be useful in developing better health policies to prevent LBW as well as interventions that can target the identified factors.
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