ArticleFrontiers in public health2025
Spatiotemporal patterns and social determinants of county life expectancy in the Yangtze River Economic Belt.
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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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.
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Who cites it
1 citing paper in PubMed.
- Editorial: Maximizing local government impact on community health initiatives.Frontiers in public health · 2025Article
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Authors and funding
7 authors.
Funding
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Abstract
Background: Revealing the spatiotemporal differentiation characteristics of population life expectancy (LE) and exploring the spatiotemporal heterogeneity in impacts of social determinants of health (SDOH) is a crucial foundation for the scientific allocation of regional public resources and the formulation and implementation of localized public health policies. Materials and methods: The study focused on 1,068 county-level units in the Yangtze River Economic Belt (YREB) of China, utilizing census data from 2000, 2010, and 2020 to uncover the spatiotemporal differentiation patterns of county-level LE. The Geographically and Temporally Weighted Regression (GTWR) model was employed to analyze the spatiotemporal heterogeneity in impacts of various SDOH on LE and the differences in effects among different types of county-level administrative divisions. Results: (1) From 2000 to 2020, the average LE in the counties of the YREB had gradually increased from 72.3 years to 81.3 years, with a spatial pattern of LE showing that the eastern region exceeded the central region, which exceeded the western region. (2) The high-high clusters were primarily concentrated in urban agglomerations, while low-low clusters were predominantly located in the western region of the YREB. (3) Overall, the gender ratio (GR) and family size (FS) negatively impacted LE, while the average years of education (AYE), the logarithm of per capita disposable income [PDI(ln)], per capita housing area (PHA), and healthcare professionals per 1,000 people (PHP) had positive effects. (4) The impact of different SDOH varied across space and time. Furthermore, the effects of different SDOH varied among different types of county-level administrative divisions. Conclusion: These findings encourage local policymakers to focus on socioeconomic development at the county level, rationally allocate public resources, and formulate and implement localized public health policies in a tailored and orderly manner, thereby promoting spatial equity in population health.
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