ArticleFrontiers in public health2025
Spatial patterns of childhood obesity clusters linked to socioeconomic inequalities.
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. Not yet cited in PubMed.
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Abstract
Introduction: The childhood obesity epidemic continues to be a challenge worldwide despite advances in prevention and treatment. Multifactorial causes are responsible for this epidemiology, and unequivocally, environmental factors play a key role. Studying the connection between socioeconomic factors and prevalence of childhood obesity is key to instituting change on a public health level. Objective: To identify geographical areas (clusters) with high and low prevalence of childhood obesity and examine their spatial association with socio-economic and demographic factors. Methods: Cluster analysis of geographic and population data for localities and regional councils was performed using growth data for children in grade 1. Analysis of childhood obesity prevalence utilized spatial autocorrelation (Moran's I) and Getis-Ord Results: The cluster analysis identified several significant spatial clusters of localities with high and low z-scores from the Getis-Ord Conclusion: The application of geographic techniques enables examination of spatial patterns of childhood obesity. The current analysis is the first study that demonstrate a direct association between cluster areas of childhood obesity prevalence and socio-economic and demographic factors in the Middle East. It highlights that spatial dependence and heterogeneity are key factors in analyzing patterns of childhood obesity. Correlations between sociodemographic parameters are consistent with patterns observed in high-income countries (a negative socioeconomic index association) and in middle-and low-income countries (a positive association with average years of schooling). The results suggest that the immediate geographic environment plays a substantial role in childhood obesity. Therefore, it may reflect different patterns related to macroeconomic factors, such as the country's income level.
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