Multilevel multinomial regression analysis of factors associated with birth weight in sub-Saharan Africa
Meklit Melaku Bezie1, Getayeneh Antehunegn Tesema2, Beminate Lemma Seifu3
1Department of Public Health, Institute of Public Health, College of Medicine and Health Sciences and Comprehensive Specialized Hospital, University of Gondar, Gondar, Ethiopia. mesiyemaki@gmail.com.
Insights
Low birth weight and macrosomia are significant public health issues in Sub-Saharan Africa. Maternal education, wealth, age, and healthcare access are key factors influencing these birth weight extremes.
Area of Science:
- Public Health
- Epidemiology
- Maternal and Child Health
Background:
- Birth weight is a critical determinant of neonatal and long-term infant health.
- Sub-Saharan Africa (SSA) faces a growing dual burden of low birth weight (LBW) and macrosomia.
- Limited research exists on the prevalence and associated factors of birth weight variations in SSA.
Purpose of the Study:
- To investigate the magnitude of LBW and macrosomia in SSA.
- To identify individual and community-level factors associated with LBW and macrosomia in SSA.
Main Methods:
- Utilized data from the Demographic and Health Survey (DHS) of 36 SSA countries.
- Employed a multilevel multinomial logistic regression analysis on a weighted sample of 207,548 live births.
- Identified significant factors using adjusted Relative Risk Ratios (aRRR) and 95% Confidence Intervals (CI).
Main Results:
- Prevalence of LBW was 10.44% and macrosomia was 8.33% in the study population.
- Individual factors associated with both LBW and macrosomia included maternal education, wealth, age, and number of pregnancies.
- Community-level factors included place of residence and SSA region; LBW was linked to distance to health facilities, while macrosomia was associated with parity, marital status, and desired pregnancy.
Conclusions:
- LBW and macrosomia represent significant public health challenges in SSA.
- Maternal socioeconomic status, education, healthcare access, and demographic factors are crucial determinants.
- Interventions should focus on improving maternal socioeconomic conditions and healthcare accessibility to mitigate the double burden of abnormal birth weights.
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 < 0.2 in the bivariable analysis were considered for the multivariable analysis. In the multivariable multilevel multinomial logistic regression analysis, the adjusted Relative Risk Ratio (aRRR) with the 95% confidence interval (CI) was reported to declare the statistical significance and strength of association. The prevalence of LBW and macrosomia in SSA were 10.44% (95% CI 10.31%, 10.57%) and 8.33% (95% CI 8.21%, 8.45%), respectively. Maternal education level, household wealth status, age, and the number of pregnancies were among the individual-level variables associated with both LBW and macrosomia in the final multilevel multinomial logistic regression analysis. The community-level factors that had a significant association with both macrosomia and LBW were the place of residence and the sub-Saharan African region. The study found a significant association between LBW and distance to the health facility, while macrosomia had a significant association with parity, marital status, and desired pregnancy. In SSA, macrosomia and LBW were found to be major public health issues. Maternal education, household wealth status, age, place of residence, number of pregnancies, distance to the health facility, and parity were found to be significant factors of LBW and macrosomia in this study. Reducing the double burden (low birth weight and macrosomia) and its related short- and long-term effects, therefore, calls for improving mothers' socioeconomic status and expanding access to and availability of health care.
Related Concept Videos
Factorial Design
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Regression Toward the Mean
Two-Way ANOVA
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
One-Way ANOVA: Unequal Sample Sizes


