Beyond the labels: Classifying countries by child health outcomes – A cluster analysis of child mortality and child-health data
Purssell, E., Frood, S. ORCID: 0009-0007-2993-6012 & Sagoo, R. (2025).
Beyond the labels: Classifying countries by child health outcomes – A cluster analysis of child mortality and child-health data.
Global Health Action, 18(1),
article number 2526315.
doi: 10.1080/16549716.2025.2526315
Abstract
Background
Most health service classification systems are based on organisational components such as service provision, financing, and regulation. This study considers health systems using data focusing on child health outcomes, service provision, and selected social characteristics. This more accurately reflects the reality of health service provision for children, young people, and their families.
Objective
To classify health systems based on child health data through cluster analysis and exploratory and descriptive data analysis.
Method
Data were extracted from the current version of the UNICEF (2023) State of the World’s Children full dataset, concentrating on outcomes related to mortality. Cluster analyses were conducted, and a heatmap was produced to identify patterns and groups among countries and child health indicators. Row and column distances were calculated using the Euclidean distance, and clustering was performed using the complete linkage method. Each variable was centred and scaled using the scale command, allowing variables measured on different scales to be compared without those with large values being weighted more heavily. Countries that performed better or were less healthy than expected were identified through linear regression analysis using the ggplot2 package.
Results
Analysis of countries by cluster reveals six main groups, characterised by child and maternal mortality rates, vaccination levels, access to maternal and child healthcare, access to water and sanitation, and population migration levels.
Conclusion
Identifying patterns in outcomes and identifying countries that perform above or below expectations concerning child health can inform a more nuanced approach to improving a country’s child health outcomes.
Publication Type: | Article |
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Additional Information: | © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. |
Publisher Keywords: | Classifying countries, child health outcomes, cluster analysis, child mortality, child health data |
Subjects: | R Medicine > RJ Pediatrics R Medicine > RJ Pediatrics > RJ101 Child Health. Child health services |
Departments: | School of Health & Medical Sciences School of Health & Medical Sciences > Nursing |
SWORD Depositor: |
Available under License Creative Commons Attribution.
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