Evidence map›Paper›PMID 40591556›Full record

ArticlePLOS global public health2025

Spatial variations and predictors of neonatal mortality among births to HIV-infected and non-infected mothers in rural Zambia.

Samson Shumba, Deborah Tembo, Miyanda Simwaka, Nedah Chikonde Musonda, Chipo Nkwemu, Sebean Mayimbo

Abstract read
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Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Samson ShumbaDepartment of Epidemiology and Biostatistics, School of Public Health, University of Zambia, Lusaka, Zambia.ORCID https://orcid.org/0000-0002-5473-9332
Deborah TemboDepartment of Emergency Preparedness and Response, Zambia National Public Health Institute, Lusaka, Zambia.ORCID https://orcid.org/0000-0001-8353-9041
Miyanda SimwakaMinistry of Health, Lusaka, Zambia.
Nedah Chikonde MusondaCopper Rose Zambia, Lusaka, Zambia.ORCID https://orcid.org/0000-0003-2616-847X
Chipo NkwemuDepartment of Epidemiology and Biostatistics, School of Public Health, University of Zambia, Lusaka, Zambia.
Sebean MayimboDepartment of Midwifery, Women's and Child Health, School of Nursing Sciences, University of Zambia, Lusaka, Zambia.ORCID https://orcid.org/0000-0002-7676-079X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In Zambia, neonatal mortality still remains a noteworthy public health problem with a current rate of 27 deaths per 1000 and ranking 162 out of 195 countries globally. The study aimed to investigate the spatial variations and predictors of neonatal mortality in rural Zambia among HIV-infected and non-infected mothers using the national-level data from the 2018 Zambia Demographic and Health Survey (ZDHS). Statistical analyses were conducted using the Rao - Scott Chi-square test to assess associations between neonatal mortality and categorical variables. Additionally, a multilevel mixed effect logistic regression model was used to examine predictors of neonatal mortality. Geospatial variations of neonatal mortality across Zambia's ten provinces were mapped using Quantum Geographical Information System (QGIS) version 3.34.1. Data analysis was performed using R and Stata version 14.2. This study examined the spatial variations and predictors of neonatal mortality among HIV-infected and non-infected mothers in rural Zambia using the 2018 Zambia Demographic Health Survey dataset. Key findings include the protective role of maternal education, with those having secondary or higher education showing reduced odds of neonatal mortality. Women aged 20-24 years in the study had higher odds of neonatal death compared to younger mothers, while delivering in public health facilities was associated with increased neonatal mortality. Maternal HIV status had no significant impact on neonatal outcomes. Spatial analysis revealed significant regional disparities, with high mortality rates in Central, Southern, and Eastern provinces, while North Western Province had lower rates. These results emphasize the need for improved healthcare quality, targeted maternal education programs, and region-specific interventions to address neonatal mortality in Zambia.

Identifiers

PMID40591556
PMCPMC12212519

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.