Evidence map›Paper›PMID 42143292›Full record

ArticleBMC public health2026

Modelling factors associated with infant mortality in Northern Region of Ghana: survival analysis approach.

Zafodor Fuseini Abubakari, Alhassan Faisal, Mahama Jato Asuma

Abstract read
In one paragraph

Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Zafodor Fuseini AbubakariDepartment of Statistics, School of Mathematical Sciences, University of Technology and Applied Sciences, Navrongo, Ghana.
Alhassan FaisalDepartment of Statistics, Faculty of Physical Sciences, University for Development Studies, Tamale, Ghana.
Mahama Jato AsumaDepartment of Statistics and Actuarial Science, Faculty of Physical and Computational Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. jatoasuma11@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Infant mortality remains a significant public health concern in Ghana, particularly in the Northern Region. This study investigated factors associated with infant survival using facility-based data from Kpandai Polyclinic and Tamale West Hospital. The Kaplan-Meier estimator showed no statistically significant survival differences across most categorical covariates, including child sex, maternal education, place of residence, marital status, and occupation; however, a significant difference was observed for mode of delivery. The mean gestational age at delivery was 35.6 weeks, which is below the standard full-term threshold, suggesting a relatively high prevalence of preterm births within the cohort. The standard Cox proportional hazards model identified gestational age and mode of delivery as significantly associated with infant mortality. However, the directions of these associations were counterintuitive and should be interpreted with caution. In particular, the association with mode of delivery is likely influenced by confounding by indication, as caesarean sections are typically performed in response to complications or high-risk pregnancies. Similarly, the effect of gestational age may be influenced by measurement limitations and the absence of detailed clinical variables, such as neonatal complications and birth conditions, which may obscure the true relationship between gestational age and survival. The piecewise time-dependent Cox model revealed that only a few variables particularly mode of delivery, gestational age, and place of residence exhibited notable time-varying associations, whereas the majority of demographic and socioeconomic factors remained largely non-predictive. The extended model provided a superior fit to the data compared to the standard Cox model.

Indexed as

Infant MortalityAdultDelivery, ObstetricFemaleGestational AgeGhanaHumansInfantInfant, NewbornMalePregnancyProportional Hazards ModelsRisk FactorsSocioeconomic FactorsSurvival AnalysisFacility-based cohortInfant mortalityKaplan–MeierLog rank testMaternal and child healthRight censoringTime-dependent Cox proportional hazards Model

Identifiers

PMID42143292
PMCPMC13348610

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LicenceCC BY-NC-ND
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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.