Evidence map›Paper›PMID 39007064›Full record

ArticleEClinicalMedicine2024

Population modifiable risk factors associated with neonatal mortality in 35 sub-Saharan Africa countries: analysis of data from demographic and health surveys.

Kedir Y Ahmed, Subash Thapa, Tahir A Hassen, Teketo Kassaw Tegegne, Abel F Dadi, Daniel Bogale Odo, Habtamu Mellie Bizuayehu, Desalegn Markos Shifti, Sewunet Admasu Belachew, Getiye Dejenu Kibret and 11 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in EClinicalMedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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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

21 authors.

Kedir Y AhmedRural Health Research Institute, Charles Sturt University, Orange, NSW 2800, Australia.
Subash ThapaRural Health Research Institute, Charles Sturt University, Orange, NSW 2800, Australia.
Tahir A HassenCenter for Women's Health Research, College of Health, Medicine and Wellbeing, The University of Newcastle, NSW, Australia.
Teketo Kassaw TegegneInstitute for Physical Activity and Nutrition, Deakin University, Geelong, VIC, Australia.
Abel F DadiMenzies School of Health Research, Charles Darwin University, Australia.
Daniel Bogale OdoNational Centre for Aboriginal and Torres Strait Islander Wellbeing Research, National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT, Australia.
Habtamu Mellie BizuayehuFirst Nations Cancer and Wellbeing (FNCW) Research Program, School of Public Health, The University of Queensland, Qld, Australia.
Desalegn Markos ShiftiChild Health Research Centre, The University of Queensland, Qld, Australia.
Sewunet Admasu BelachewFirst Nations Cancer and Wellbeing (FNCW) Research Program, School of Public Health, The University of Queensland, Qld, Australia.
Getiye Dejenu KibretFaculty of Medicine, Health and Human Sciences, Macquarie University, Australia.
Daniel Bekele KetemaThe George Institute for Global Health, University of New South Wales (UNSW), Sydney, Australia.
Zemenu Yohannes KassaCollege of Medicine and Health Sciences, Hawassa University, Hawassa, Ethiopia.
Erkihun AmsaluSydney Medical School, Faculty of Medicine and Health, University of Sydney, Australia.
Meless G BoreSchool of Nursing and Midwifery, University of Technology Sydney, Sydney, Australia.
Abdulbasit SeidAustralian Living Evidence Collaborations, School of Public Health and Prevention Medicine, Monash University, Australia.
Yonatan M MesfinSAEFVIC, Infection and Immunity, Murdoch Children's Research Institute, 50 Flemington Road, Parkville, VIC, Australia.
Kelemu Tilahun KibretGlobal Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Geelong, VIC, Australia.
M Mamun HudaRural Health Research Institute, Charles Sturt University, Orange, NSW 2800, Australia.
Shakeel MahmoodRural Health Research Institute, Charles Sturt University, Orange, NSW 2800, Australia.
Anayochukwu E AnyasodorRural Health Research Institute, Charles Sturt University, Orange, NSW 2800, Australia.
Allen G RossRural Health Research Institute, Charles Sturt University, Orange, NSW 2800, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sub-Saharan Africa (SSA) has the highest burden of neonatal mortality in the world. Identifying the most critical modifiable risk factors is imperative for reducing neonatal mortality rates. This study is the first to calculate population-attributable fractions (PAFs) for modifiable risk factors of neonatal mortality in SSA. Methods: We analysed the most recent Demographic and Health Surveys data sets from 35 SSA countries conducted between 2010 and 2022. Generalized linear latent and mixed models were used to estimate odds ratios (ORs) along with 95% confidence intervals (CIs). PAFs adjusted for communality were calculated using ORs and prevalence estimates for key modifiable risk factors. Subregional analyses were conducted to examine variations in modifiable risk factors for neonatal mortality across Central, Eastern, Southern, and Western SSA regions. Findings: In this study, we included 255,891 live births in the five years before the survey. The highest PAFs of neonatal mortality among singleton children were attributed to delayed initiation of breastfeeding (>1 h after birth: PAF = 23.88%; 95% CI: 15.91, 24.86), uncleaned cooking fuel (PAF = 5.27%; 95% CI: 1.41, 8.73), mother's lacking formal education (PAF = 4.34%; 95% CI: 1.15, 6.31), mother's lacking tetanus vaccination (PAF = 3.54%; 95% CI: 1.55, 4.92), and infrequent antenatal care (ANC) visits (PAF = 2.45; 95% CI: 0.76, 3.63). Together, these five modifiable risk factors were associated with 39.49% (95% CI: 21.13, 48.44) of neonatal deaths among singleton children in SSA. Our subregional analyses revealed some variations in modifiable risk factors for neonatal mortality. Notably, delayed initiation of breastfeeding consistently contributed to the highest PAFs of neonatal mortality across all four regions of SSA: Central, Eastern, Southern, and Western SSA. Interpretation: The PAF estimates in the present study indicate that a considerable proportion of neonatal deaths in SSA are preventable. We identified five modifiable risk factors that accounted for approximately 40% of neonatal deaths in SSA. The findings have policy implications. Funding: None.

Indexed as

Neonatal mortalityPopulation attributable fractionsSub-Saharan AfricaSustainable development goals (SDGs)

Identifiers

PMID39007064
PMCPMC11245992

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.