Long Fei, Luo Qing, Li Zirui
School of Mathematics and Physics, Wuhan Institute of Technology, Wuhan, China.
Front Public Health. 2025 Mar 27;13:1551287. doi: 10.3389/fpubh.2025.1551287. eCollection 2025.
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.
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.
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.
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.
随着预期寿命的延长和出生率持续低迷,人口老龄化已成为中国的一个紧迫问题。本研究调查并可视化了2010年和2020年中国西北地区陕甘地区人口老龄化的多尺度空间异质性及其影响因素(人口、社会经济、医疗保健和自然环境因素),旨在为制定促进老年友好型社会的地方老龄化政策提供一些见解。
利用县级人口普查数据和夜间灯光数据,应用空间自相关分析和多尺度地理加权回归来探索老龄化的空间模式以及不同因素在不同尺度上的不同影响。
结果揭示了该地区人口老龄化的渐进性以及显著的空间异质性影响。2010年,人口因素具有全局效应,经济因素具有局部效应,环境因素在区域尺度上产生影响。到2020年,医疗保健因素产生全局影响,而其他因素的空间影响在每个类别中各不相同。
陕甘地区经历了加速老龄化,同时老龄化模式存在明显的时空异质性。在研究期间,四类影响因素的影响规模和程度也发生了变化。这些发现凸显了考虑每个地区的具体地方特征来应对老龄化挑战的重要性。