MARATTO

article · Pediatric Health Medicine and Therapeutics

Newborn Birth Weight and Associated Factors Among Mother-Neonate Pairs in Public Hospitals, North Wollo, Ethiopia

202129 citationsOpen accessDebre Berhan University

In plain language

Neonatal birth weight indicates a child's susceptibility to illness, with low birth weight linked to neonatal morbidity, inhibited growth, cognitive issues, and chronic disease. A cross-sectional study in North Wollo, Ethiopia, evaluated 337 mother-neonate pairs in public hospitals between January and June 2020. The average newborn weight recorded was 2.94 kilograms, and low birth weight occurred in 24 percent of cases. Maternal nutritional factors showed correlation with newborn weight. Key statistically significant predictors of birth weight included maternal age, average monthly family income, marital status specifically being single, alcohol consumption, maternal education, female infant sex, lack of prior abortion history, and multigravida status. Targeted attention towards mothers exhibiting these associated factors is recommended to address the high rate of low birth weight.

Key takeaways

  • Low birth weight affected 24 percent of newborns delivered in public hospitals across North Wollo.
  • The mean birth weight observed across the 337 evaluated mother-neonate pairs was 2.94 kilograms.
  • Maternal nutritional factors, age, education, and family income are significant predictors of neonatal birth weight.
  • Being single, alcohol intake, multigravida status, lack of abortion history, and female infant sex also significantly correlate with birth weight.

Why it matters

Low birth weight increases risks of childhood illness, cognitive impairment, and long-term health complications. Identifying socioeconomic and maternal factors, such as maternal nutrition, education, income, and lifestyle habits, helps public health teams pinpoint high-risk pregnancies. This evidence enables healthcare providers in regional hospital settings to direct care and interventions toward vulnerable mothers to improve neonatal outcomes.

Commercialisation angle

The abstract does not indicate an application pathway.

AI-generated from the published abstract. Always read the original work before citing.

Abstract

BACKGROUND: Birth weight or size at birth is an important indicator of the child's vulnerability to the risk of childhood illnesses and diseases. Low birth weight is closely associated with fetal and neonatal morbidity, inhibited growth and cognitive development, and chronic diseases in life. The study was aimed to assess the birth weight of neonates and associated factors among mothers who gave birth at a public hospital in North Wollo, 2020. METHODS: A hospital-based cross-sectional study was conducted among 337 mothers who gave birth in public hospitals of North Wollo, Ethiopia from January 1st to June 30, 2020. A systematic sampling technique was used to reach the study participants. Data were entered using Epi data 3.1 software and analysis will be done using SPSS 20. Adjusted beta coefficient with 95% confidence interval and p-value ≤ 0.05 was used to declare statistical significance. RESULTS: A total of 337 mothers were included with a response rate of 100%. The mean ± SD weight of the child was 2.94 ± 0.65 kilograms. The prevalence of low birth weight was 24% (95% CI= 19.6, 28.8). Maternal nutritional factors correlate with newborn weight. Age of the mother, family average monthly income, being single, alcohol use, education, female sex, had no abortion history and multigravida became statistically significant predictors of birth weight. CONCLUSION: Almost one-fourth of the newborn child had low birth weight. It will be better to give special attention to mothers with associated factors.

Research topics

  • Gestational Diabetes Research and Management
  • Child Nutrition and Water Access
  • Pregnancy and preeclampsia studies

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.2147/phmt.s299202

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.