ArticleFrontiers in public health2025
Unveiling the obesogenic neighborhood food environment factors and typologies in Tianjin, China: an integrative analysis of perceived and objective measures.
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 1 paper.
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1 citing paper in PubMed.
- Google Places API-Based US Built Environment Retail (UBER) Index and Its Spatial Association With Diabetes Prevalence Across US Counties: Cross-Sectional Ecological Study.Journal of medical Internet research · 2026Article
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5 authors.
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Abstract
Introduction: Assessing and intervening in food environments constitutes a critical strategy for addressing the obesity epidemics. However, existing assessments predominantly focus on either objective or perceived dimensions, with limited attention to developing countries. This study investigates the impact of neighborhood-level food environments on resident obesity in a national central city of China and establishes a typology of obesogenic community profiles. Methods: We developed an integrative tool that harmonizes objective geospatial data with subjective perceptual metrics. Leveraging stratified sampling survey data on neighborhood food environments ( Results: Among 10 principal components derived from PCA, four obesogenic factors were identified, ranked by effect magnitude: FAC_8 (Perceived Community Food Accessibility Index, Discussion: This study revealed that within the context of China's urban built environment, the prevalence of "food deserts" is minimal. Conversely, an augmented proportion of widely recognized healthy food facilities in developed Western countries has been observed to heighten the risk of obesity, including supermarkets and fresh food markets. This phenomenon exhibits a scale-dependence, indicating that its impact increases with the magnitude of the scale. The most salient characteristic of obesogenic neighborhoods in China is their high objective environmental risk. The study examined and identified neighborhood-level obesity factors and provided a generalizable method for identifying obesogenic neighborhood types, thereby providing empirical evidence for obesity research in developing countries.
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