Determinants of newborn birth size in Somaliland: an ordinal logistic regression analysis

Understanding the predictors of birth size is essential for designing effective interventions to reduce neonatal morbidity and mortality in Somaliland.

A comprehensive cross-sectional study was conducted using the 2020 Somali Health and Demographic Survey (SHDS). An ordinal logistic regression model, a robust statistical method, was applied to identify determinants of birth size (Low, Normal, High) among 2,137 mother-infant pairs, ensuring a thorough and reliable analysis.

The prevalence of reported small, average, and large birth sizes was 9.0%, 75.0%, and 16.0%, respectively. Our study identified significant predictors of birth size, including household wealth, maternal age, and birth order. The adjusted odds of having a larger baby were significantly higher for infants from the wealthiest households compared to the poorest (AOR = 1.45; 95% CI: 1.12-1.87), for second-order births compared to first-borns (AOR = 1.38; 95% CI: 1.10-1.74), and for infants of mothers aged 30-34 compared to adolescent mothers (AOR = 2.09; 95% CI: 1.25-3.48). These findings provide valuable insights for designing targeted interventions to improve maternal and child health in Somaliland.

Our findings underscore the importance of socioeconomic status and maternal reproductive patterns in determining birth size. We recommend tailored interventions that target the identified risk factors, with a focus on nutritional support for poor households and reproductive health education for young women. Implementing these recommendations has the potential to significantly improve maternal and child health outcomes in Somaliland, offering hope for a healthier future and a brighter outlook for the region's health. However, our findings also suggest that while factors such as antenatal care attendance are important, their impact may be limited without concurrent improvements in service quality and the empowerment of women, underscoring the need for a multifaceted public health strategy.