Determinants of Risk Factors Associated with Low Birth Weight in Nigeria

Low birth weight (LBW) remains a significant public health challenge with profound implications for neonatal and child health, particularly in low-income countries. Defined by the World Health Organization as a birth weight of less than 2.5 kilograms, LBW contributes to increased neonatal mortality and long-term developmental issues. This study examines the prevalence and determinants of LBW in Nigeria, leveraging data from the 2018 Nigeria Demographic and Health Survey (NDHS). The study employs a cross-sectional design and a stratified two-stage sampling technique, analyzing 7,728 recorded birth weights. Key findings indicate that maternal age, education, and socio-economic status significantly influence birth weight. Optimal reproductive ages (25-34 years) and higher educational attainment are associated with healthier birth weights, whereas younger (below 20 years) and older mothers (above 40 years), and those with lower education levels, face higher LBW risks. Employment and wealth are positively correlated with better birth outcomes, underscoring the importance of financial stability. Environmental factors such as urban residence, access to improved water sources, and sanitation facilities also play crucial roles in determining birth weight. The study compares frequentist logistic regression and Bayesian structured additive logistic regression models to identify and predict LBW risk factors, highlighting regional disparities within Nigeria. The findings emphasize the need for targeted interventions addressing socio-demographic, socio-economic, and environmental determinants to reduce the prevalence of LBW and improve maternal and child health outcomes. Enhanced understanding of these factors through advanced statistical modeling can inform policy and health interventions, ultimately contributing to achieving global health targets and improving neonatal health in Nigeria.

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Publication Details

Journal
American Journal of Nursing and Health Sciences
Published
2024-08-30
DOI
https://doi.org/10.11648/j.ajnhs.20240503.15
Citations
1
Primary Topic
Child Nutrition and Water Access
Type
article
Field-Weighted Citation Impact
0.31
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article

Determinants of Risk Factors Associated with Low Birth Weight in Nigeria

Celestine Ekwuluo, Michael Tomori, Aisha Salami, Taiwo Popoola et al.
1 citations
American Journal of Nursing and Health Sciences
Child Nutrition and Water Access
0.31
article

Determinants of Risk Factors Associated with Low Birth Weight in Nigeria

Celestine Ekwuluo, Michael Tomori, Aisha Salami, Taiwo Popoola, Aremu Janet, Ahmed Bello, Olukayode Alewi, Michael Avwerhota, Oladayo Avwerhota, Israel Popoola, Ebenezer Daniel, Adebanke Ogun
article en
1 citations

Abstract

Low birth weight (LBW) remains a significant public health challenge with profound implications for neonatal and child health, particularly in low-income countries. Defined by the World Health Organization as a birth weight of less than 2.5 kilograms, LBW contributes to increased neonatal mortality and long-term developmental issues. This study examines the prevalence and determinants of LBW in Nigeria, leveraging data from the 2018 Nigeria Demographic and Health Survey (NDHS). The study employs a cross-sectional design and a stratified two-stage sampling technique, analyzing 7,728 recorded birth weights. Key findings indicate that maternal age, education, and socio-economic status significantly influence birth weight. Optimal reproductive ages (25-34 years) and higher educational attainment are associated with healthier birth weights, whereas younger (below 20 years) and older mothers (above 40 years), and those with lower education levels, face higher LBW risks. Employment and wealth are positively correlated with better birth outcomes, underscoring the importance of financial stability. Environmental factors such as urban residence, access to improved water sources, and sanitation facilities also play crucial roles in determining birth weight. The study compares frequentist logistic regression and Bayesian structured additive logistic regression models to identify and predict LBW risk factors, highlighting regional disparities within Nigeria. The findings emphasize the need for targeted interventions addressing socio-demographic, socio-economic, and environmental determinants to reduce the prevalence of LBW and improve maternal and child health outcomes. Enhanced understanding of these factors through advanced statistical modeling can inform policy and health interventions, ultimately contributing to achieving global health targets and improving neonatal health in Nigeria.

American Journal of Nursing and Health SciencesVol. 5(3)
International Medical Corps (US), Atlantic International University (US), University of Ilorin (NG), University of Ibadan (NG), Texila American University (GY), Swansea University (GB), World Health Organization - Nigeria (NG)
Openalex Percentile: Top 43%
Child Nutrition and Water Access
0.31
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