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Multilevel multinomial regression analysis of factors associated with birth weight in sub-Saharan Africa
Authors: Meklit Melaku Bezie, Getayeneh Antehunegn Tesema and Beminate Lemma Seifu
Source: Scientific Reports, Volume 14; DOI:https://doi.org/10.1038/s41598-024-58517-6
Topic(s): Birth weight
Country: Africa
  Multiple African Countries
Published: APR 2024
Abstract: Birth weight significantly determines newborns immediate and future health. Globally, the incidence of both low birth weight (LBW) and macrosomia have increased dramatically including sub-Saharan African (SSA) countries. However, there is limited study on the magnitude and associated factors of birth weight in SSA. Thus, thus study investigated factors associated factors of birth weight in SSA using multilevel multinomial logistic regression analysis. The latest demographic and health survey (DHS) data of 36 sub-Saharan African (SSA) countries was used for this study. A total of a weighted sample of 207,548 live births for whom birth weight data were available were used. Multilevel multinomial logistic regression model was fitted to identify factors associated with birth weight. Variables with p-value?
Web: https://www.nature.com/articles/s41598-024-58517-6#Abs1