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Cities play a fundamental role in policy decision-making processes, necessitating the availability of city-level population projections to better understand future population dynamics and facilitate research across various domains, including urban planning, shrinking cities, GHG emission projections, GDP projections, disaster risk mitigation, and public health risk assessment. However, the current absence of city-level population projections for China is a significant gap in knowledge. Moreover, aggregating grid-level projections to the city level introduces substantial errors of approximately 30%, leading to discrepancies with actual population trends. The unique circumstances of China, characterized by comprehensive poverty reduction, compulsory education policies, and carbon neutrality goals, render scenarios like SSP4(Shared Socioeconomic Pathways) and SSP5 less applicable. To address the aforementioned limitations, this study made three key enhancements, which significantly refines and augments our previous investigation. Firstly, we refined the model, incorporating granular demographic data at the city level. Secondly, we redesigned the migration module to consider both regional and city-level population attractiveness. Lastly, we explored diverse fertility and migration scenarios.
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http://dx.doi.org/10.1038/s41597-023-02735-6 | DOI Listing |
PLoS One
September 2025
Spatial Information Research Institute, Korea Land and Geospatial Informatix Corporation, Jeonju, Jeonbuk State, South Korea.
This study introduces an expanded methodology for smart regional planning tailored to improve public service accessibility. We develop a city-level distance-time conversion factor (DCF) that utilizes regional characteristics to offer more intuitive estimates of travel times and distances in public service planning. This approach integrates three key variables: road network distances, Euclidean straight-line distances, and minimum travel times derived from both speed limits and actual traffic speeds.
View Article and Find Full Text PDFFront Public Health
September 2025
School of Economics and Management, Huangshan University, Huangshan, China.
Background: China's persistent fertility decline poses serious long-term demographic and socioeconomic challenges. The COVID-19 pandemic has introduced additional uncertainty, raising questions about how external shocks affect fertility intentions in real time.
Objective: This study examines the causal impact of localized COVID-19 shocks on fertility intentions in China, as measured by high-frequency digital search data that capture real-time behavioral shifts.
JMIR Med Inform
August 2025
Department of Orthopedic Surgery, School of Basic Medical Sciences, Qilu Hospital of Shandong University, No. 107 Wenhua West Road, Jinan, Shandong Province, 250012, China, 86 531-82169562.
Background: Hepatitis C virus (HCV) remains a significant public health concern in China, particularly in Shandong Province, where detailed molecular epidemiological data are limited. HCV exhibits substantial genetic diversity, and understanding its genotype distribution and transmission dynamics is critical for developing effective control strategies.
Objective: This study aimed to investigate the genetic diversity, geographic dissemination, and evolutionary history of HCV genotypes in Shandong Province, China, using molecular techniques and phylogenetic methods.
Introduction: Population aging in China exhibits pronounced spatial heterogeneity, driven by complex interactions among demographic dynamics, economic development, healthcare infrastructure, environmental conditions, and lifestyle factors. Understanding which determinants exert the strongest-and most geographically variable-effects is critical for designing targeted healthy-aging policies. This study investigates the multiscale influences on the city-level aging rate in Hubei Province, comparing patterns in 2010 and 2020.
View Article and Find Full Text PDFJ Photochem Photobiol B
October 2025
Program of Environmental Physical Factors and Health, School of Public Health, China Medical University, No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province 110122, China; Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention, China Medical University, Min
Objective: To investigate the association between long-term exposure to ambient ultraviolet radiation (UVR) and the risk of developing type 2 diabetes (T2D).
Research Design And Methods: This study analyzed data from 14,825 participants enrolled in the 2015 China Health and Retirement Longitudinal Study (CHARLS). Ground-based daily average UVR monitoring data, collected from January 1, 2005, to December 31, 2014, across 724 stations in China, were matched to 125 cities corresponding to participants' residences.