The rising role of physical activity in multiscale urban aging

Evidence from spatial MGWR modeling in Hubei

Bibliographic Data

ID22089011
AuthorsJunjun Qiu (0000-0002-2063-2684, Wuhan Sports University, corresponding author), Yuge Zhang (0000-0001-7440-0371, Kookmin University), Binbin Jia (Wuhan Sports University), Danyang Li (0000-0002-4795-5766, Wuhan Sports University, corresponding author)
Year2025
Volume13
Pages1630009-1630009
Publication date2025-07-29
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1630009
PMID40800017
OpenAlexW4412734056
LanguageEN
References cited37

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. Methods We applied Multiscale Geographically Weighted Regression (MGWR) to annual data for 17 cities in Hubei. Explanatory variables encompassed demographic indicators (birth rate, mortality rate), economic affluence (per-capita GDP), healthcare infrastructure indicators (quantity of health institutions and service enterprises), environmental measures (per capita urban park green space, centralized treatment rate of sewage treatment plants), and physical activity prevalence. MGWR’s adaptive bandwidth selection enabled each predictor to operate at its optimal spatial scale, while model fit was assessed via AICc, adjusted R 2 , and residual diagnostics. Results In 2010, spatial variability in aging was dominated by economic (SD≈0.36) and healthcare disparities (SD≈0.31). By 2020, these disparities had largely converged, and demographic divergence—particularly heterogeneous birth-rate effects (SD≈0.42)—became the primary driver. Crucially, physical activity emerged as the most potent local accelerator of aging in 2020 (mean β≈−0.60, SD≈0.25), statistically significant in over half of cities, and operating at a fine spatial scale. Discussion The temporal shift from structural inequality to demographic and lifestyle determinants underscores the evolving landscape of population aging. MGWR’s multi-bandwidth approach revealed that physical-activity interventions must be tailored at the city level, while fertility and economic policies warrant regional coordination. These findings demonstrate MGWR’s advantage over global or single-bandwidth models in capturing layered spatial processes. Future research should employ finer spatial units, longitudinal designs, and integrate psychosocial variables to further elucidate healthy-aging pathways

Data science · Environmental health · Computer Science · Health disparities and outcomes · Medicine · Migration, Aging, and Tourism Studies · Urban Transport and Accessibility