ArticleFrontiers in public health2025
Multiscale spatial heterogeneity of population aging in relation to its influential factors: a case study in the Shaanxi-Gansu region, China.
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 5 papers.
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Who cites it
5 citing papers in PubMed.
- Spatiotemporal coupling coordination between population aging and healthcare resource capacity in China: a provincial-level analysis, 2000-2023.Frontiers in public health · 2026Article
- Psychological safety and its influencing factors among elderly patients following traumatic fracture surgery: a cross-sectional study.BMC geriatrics · 2025Article
- Analysis of the differences and influencing factors of rural population aging in Gansu Province-based on panel data from 2000 to 2022.Frontiers in public health · 2025Article
- The rising role of physical activity in multiscale urban aging: evidence from spatial MGWR modeling in Hubei.Frontiers in public health · 2025Article
- Spatial disparities of population aging in Shenzhen: from China's Hukou perspective.Frontiers in public health · 2025Article
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3 authors.
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Abstract
Objective: With the extension of life expectancy and persistently low birth rates, population aging has become a pressing issue in China. This study investigates and visualizes the multiscale spatial heterogeneity of population aging and its influential factors (demographic, socioeconomic, healthcare, and natural environmental factors) across the Shaanxi-Gansu region in northwestern China for 2010 and 2020, and aims to offer some insights for designing localized aging policies to promote an older adult-friendly society. Methods: Using county-level census data and nighttime light data, spatial autocorrelation analysis and multiscale geographically weighted regression were applied to explore spatial patterns of aging and the varying impacts of different factors across scales. Results: The results reveal progressive population aging and significant spatial heterogeneous impacts in the region. In 2010, demographic factors had global effects, economic factors had local effects, and environmental factors influenced at regional scales. By 2020, healthcare factors exerted global impacts, while the spatial influence of the other factors varied within each category. Conclusion: The Shaanxi-Gansu region experienced accelerated aging along with distinct spatial-temporal heterogeneity in aging patterns. The scale and magnitude of the impacts from four types of influencing factors also shifted over the study period. These findings highlight the importance of addressing aging challenges by considering the specific local characteristics of each area.
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