Multiscale spatial heterogeneity of population aging in relation to its influential factors: a case study in the Shaanxi-Gansu region, China

ObjectiveWith 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,...

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Bibliographic Details
Main Authors: Fei Long, Qing Luo, Zirui Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Public Health
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Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2025.1551287/full
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Summary:ObjectiveWith 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.MethodsUsing 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.ResultsThe 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.ConclusionThe 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.
ISSN:2296-2565