@article{10.11648/j.ajnhs.20240503.15,
  author = {Oladayo Olarinre Avwerhota and Michael Avwerhota and Ebenezer Obi Daniel and Taiwo Aderemi Popoola and Israel Olukayode Popoola and Adebanke Adetutu Ogun and Ahmed Mamuda Bello and Michael Olabode Tomori and Aisha Oluwakemi Salami and Celestine Emeka Ekwuluo and Olukayode Oladeji Alewi and Aremu Bukola Janet},
  title = {Determinants of Risk Factors Associated with Low Birth Weight in Nigeria
},
  journal = {American Journal of Nursing and Health Sciences},
  volume = {5},
  number = {3},
  pages = {77-87},
  doi = {10.11648/j.ajnhs.20240503.15},
  url = {https://doi.org/10.11648/j.ajnhs.20240503.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnhs.20240503.15},
  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.
},
 year = {2024}
}

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TY  - JOUR
T1  - Determinants of Risk Factors Associated with Low Birth Weight in Nigeria

AU  - Oladayo Olarinre Avwerhota
AU  - Michael Avwerhota
AU  - Ebenezer Obi Daniel
AU  - Taiwo Aderemi Popoola
AU  - Israel Olukayode Popoola
AU  - Adebanke Adetutu Ogun
AU  - Ahmed Mamuda Bello
AU  - Michael Olabode Tomori
AU  - Aisha Oluwakemi Salami
AU  - Celestine Emeka Ekwuluo
AU  - Olukayode Oladeji Alewi
AU  - Aremu Bukola Janet
Y1  - 2024/08/30
PY  - 2024
N1  - https://doi.org/10.11648/j.ajnhs.20240503.15
DO  - 10.11648/j.ajnhs.20240503.15
T2  - American Journal of Nursing and Health Sciences
JF  - American Journal of Nursing and Health Sciences
JO  - American Journal of Nursing and Health Sciences
SP  - 77
EP  - 87
PB  - Science Publishing Group
SN  - 2994-7227
UR  - https://doi.org/10.11648/j.ajnhs.20240503.15
AB  - 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.

VL  - 5
IS  - 3
ER  - 

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