Evidence map›Paper›PMID 40692892›Full record

ArticleFrontiers in public health2025

Most vulnerable diet and health profiles: identifying countries at risk through a three-theme clustering.

Ahmet Murat Günal, Salim Yılmaz, Sedat Arslan

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

3 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

3 authors.

Ahmet Murat GünalDepartment of Nutrition and Dietetics, Faculty of Health Sciences, Haliç University, İstanbul, Türkiye.
Salim YılmazDepartment of Healthcare Management, Faculty of Health Sciences, Acibadem Mehmet Ali Aydinlar University, İstanbul, Türkiye.
Sedat ArslanDepartment of Nutrition and Dietetics, Faculty of Health Sciences, Bandirma Onyedi Eylul University, Balikesir, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Global disparities in dietary habits, healthcare services, and life expectancy continue to affect vulnerable populations, particularly in low-and middle-income countries. Malnutrition, inadequate healthcare infrastructure, and diet-related chronic diseases contribute significantly to these disparities, necessitating targeted public health interventions. Objectives: This study aims to identify the most vulnerable countries in terms of diet, health, and life expectancy using a three-theme clustering approach. The study categorizes countries based on nutrition and diet, health and disease burden, and healthcare access and life expectancy to determine those at the highest risk. Methods: A cross-sectional analysis was conducted using 2019 data from 168 countries. A k-means clustering algorithm was applied to classify countries into three risk-based clusters for each theme. The Jaccard similarity coefficient was used to evaluate cluster overlap, and statistical significance was assessed through robust regression models and the Kruskal-Wallis H test. Data processing and visualization were performed using RStudio. Results: The analysis identified Cluster 3 as the most vulnerable group, comprising 45 countries with high similarity across all three themes. These countries, predominantly in Africa and Asia, exhibited low daily animal protein intake (<20 g/day), high rates of diet-related diseases, and limited access to healthcare. The healthcare coverage index in these countries ranged from 45.33 to 84.48, with life expectancy as low as 63.39 years. The findings highlight critical inequalities in global health, emphasizing the need for targeted interventions. Conclusion: This study underscores the urgent need for improved nutrition policies and healthcare investments in high-risk regions. Addressing malnutrition, enhancing healthcare services, and implementing targeted public health initiatives are crucial for reducing global health disparities and improving outcomes in vulnerable populations.

Indexed as

DietGlobal HealthHealth Status DisparitiesLife ExpectancyVulnerable PopulationsCluster AnalysisCross-Sectional StudiesDeveloping CountriesHealth Services AccessibilityHumansclustering analysisdietary habitsfood insecurityhealthcare serviceshealth outcomeslife expectancy

Identifiers

PMID40692892
PMCPMC12278288

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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.