Associations of Green Space and Air Pollution Mixture with Heterogeneous Biological Aging Patterns
Abstract
Abstract Evidence on associations between green space, air pollution mixture, and heterogeneous biological aging patterns remains limited. We investigated the opposing effects of green space and air pollution mixture on biological aging patterns using an accelerated longitudinal design based on repeated-measures data from 11,760 adults (aged 20–65 years) in a high-pollution Chinese city. Biological age acceleration (BAA) was derived via the Klemera-Doubal method. Group-based trajectory modeling identified three stable BAA profiles, labeled as “slow”, “moderate”, and “accelerated” aging, which were primarily distinguished by overall BAA magnitude rather than divergent slopes over age. Multinomial generalized linear mixed models and weighted quantile sum regression were applied to assess environmental associations. Higher green space (500 m normalized difference vegetation index (NDVI)) was associated with lower odds of membership in the “accelerated aging” trajectory (OR: 0.84; 95% CI: 0.75, 0.95). Even under limited exposure contrast in this high-pollution setting, higher exposures to PM2.5, PM10, SO2, and O3 were associated with higher odds of membership in the accelerated aging trajectory. The air pollution mixture showed a consistent positive association (OR: 1.16; 95% CI: 1.08, 1.24), driven primarily by O3 and PM10. Mediation analysis revealed that 25.0% of the protective association of green space was mediated by reduced pollution exposure. These findings highlight green space as a vital resilience resource, supporting synergistic urban greening and pollution control strategies to promote healthy aging.
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Authors: Guoqiang Ma, Jing Xu, Yishu Li, Yuefei Wu, Qian Li, Xuan Cao, Zitong Zhao, Jie Gao, Lijun Gao, Lina Yan, Xiaolin Zhang
Institutions: Hebei Medical University, The Eighth Hospital of Xi'an