Geospatial variations and predictors of low birth weight in Sub-Saharan Africa: a geospatial modeling using evidence from demographic health survey 2015-2024.

Background: Low birth weight, defined as less than 2.5 kg (5.5 lbs) at birth, remains a critical global public health challenge. It significantly increases the risk of neonatal mortality and immediate complications such as sepsis and hypothermia, along with lifelong consequences including childhood disabilities and adult-onset chronic diseases. However, there was a limited study that described the spatial distribution and predictors of low birth weight in sub-Saharan Africa. The study aimed to assess geospatial variations and predictors of low birth weight in sub-Saharan Africa. Methods: A community-based cross-sectional study design based on Demographic and Health Survey (2015-2024) data, comprising a weighted sample of 138,164 women aged 15-49 years with live births among 28 sub-Saharan African countries, was included in the study. Global Moran's I was calculated to determine overall clustering of low birth weight. Statistically significant hot spot and cold spot areas of low birth weight were determined by Getis-Ord G∗ statistics. Ordinary least squares, spatial lag, spatial error, geographically weighted regression, and multiscale geographically weighted regressions were utilized to determine predictors of low birth weight. The best-fitting models were determined by the highest R2 and the lowest corrected Akaike Information Criterion values. Finally, the statistically significant predictors from the final model were displayed on a map. Findings: Low birth weight was clustered (Moran's I 0.23, z-score 50.2, p-value <0.01) in the study area. Significant hotspot areas were depicted in Mauritania, Mali, Senegal, Burkina Faso, Nigeria, Gabon, Angola, Madagascar, South Africa, Lesotho, Malawi, and Ethiopia. Conversely, low-risk cold spots were observed in Uganda, Kenya, Rwanda, Burundi, Tanzania, Zambia, Zimbabwe, Cameroon, and Sierra Leone. Short birth interval, no visit to a health facility in the last year, twin birth, no media exposure, and unemployed women were significant predictors of low birth weight. Interpretation: There is spatial variation of low birth weight across different regions in sub-Saharan Africa. Significant hotspot and cold spot areas along with significant predictors were identified, which is a priority for policy makers. Targeted maternal health interventions, improved healthcare access, health education using mass media, and economic empowerment for women are recommended to reduce low birth weight. Funding: None.