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.