Evidence map›Paper›PMID 41509614›Full record

ArticleEClinicalMedicine2026

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

Bewketu Sendek Aragie, Getaneh Awoke Yismaw, Belayneh Jejaw Abate, Ashenafi Solomon Weldeyohanis, Solomon Gedlu Nigatu

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Article in EClinicalMedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Bewketu Sendek AragieDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Getaneh Awoke YismawDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Belayneh Jejaw AbateUniversity of Gondar Comprehensive Specialized Hospital, Gondar, Ethiopia.
Ashenafi Solomon WeldeyohanisDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Solomon Gedlu NigatuDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 R 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.

Indexed as

Low birth weightMulti-scale geographic weighted regressionSpatial analysisSub-Saharan Africa

Identifiers

PMID41509614
PMCPMC12774685

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