ORIGINAL RESEARCH article
Front. Public Health
Sec. Aging and Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1634712
This article is part of the Research TopicIntegrated Strategies for Lifelong Health: Multidimensional Approaches to Aging and Lifestyle InterventionsView all 29 articles
Analysis of the Differences and Influencing Factors of Rural Population Aging in Gansu Province-Based on Panel Data from 2000 to 2022
Provisionally accepted
- 1Gansu University of Chinese Medicine, Lanzhou, China
- 2Lanzhou University, Lanzhou, China
- 3Gansu Provincial Hospital, Lanzhou, China
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【Abstract】 Objective To analyze the spatial dimension differences and influencing factors of rural population aging in Gansu Province over the past 20 years. Methods Data on population, economy, healthcare, and education from Gansu Province and its 14 cities (prefectures) from 2000 to 2022 were collected, with selected indicators quantified. A spatial dynamic panel data model was established to explore regional differences and the impact of influencing factors on population aging. Results The aging of the rural population in Gansu Province continues to intensify, with regional disparities gradually widening. Among these, the central region exhibits the largest disparity and contribution rate, followed by the southeastern region, while the northwestern region shows the smallest. Intra-regional disparities, particularly in the central region, are the primary source of the overall disparities. Among the influencing factors, an increase in population density helps alleviate aging, whereas a rise in the illiteracy rate exacerbates population aging. Other factors, including the natural population growth rate, GDP per capita, and the number of hospital beds per capita, do not have a significant impact on population aging. Conclusion The aging of the rural population in Gansu is intensifying, with regional disparities widening, influenced by multiple factors such as economic development, population growth, education levels, and medical resources.
Keywords: Population aging, panel data model, Regional disparities, Gansu province, Influencing factors
Received: 25 May 2025; Accepted: 09 Jul 2025.
Copyright: © 2025 Liu, Lv, Zhang and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jiancheng Wang, Gansu Provincial Hospital, Lanzhou, China
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