Evidence map›Paper›PMID 42852352›Full record

ArticleEnvironmental health perspectives2026

Associations of Green Space and Air Pollution Mixture with Heterogeneous Biological Aging Patterns.

Guoqiang Ma, Jing Xu, Yishu Li, Yuefei Wu, Qian Li, Xuan Cao, Zitong Zhao, Jingyan Gao, Lijun Gao, Lina Yan and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Environmental health perspectives, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Guoqiang MaHebei Province Key Laboratory of Environment and Human Health, Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China.ORCID https://orcid.org/0009-0005-9698-2241
Jing XuHebei Province Key Laboratory of Environment and Human Health, Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Yishu LiHebei Province Key Laboratory of Environment and Human Health, Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Yuefei WuHebei Province Key Laboratory of Environment and Human Health, Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Qian LiHebei Province Key Laboratory of Environment and Human Health, Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Xuan CaoHebei Province Key Laboratory of Environment and Human Health, Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Zitong ZhaoHebei Province Key Laboratory of Environment and Human Health, Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Jingyan GaoHebei Province Key Laboratory of Environment and Human Health, Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Lijun GaoDepartment of Occupational Medicine, The Eighth Hospital of Hebei Province, Shijiazhuang 050021, China.
Lina YanHebei Province Key Laboratory of Environment and Human Health, Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China.
Xiaolin ZhangHebei Province Key Laboratory of Environment and Human Health, Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 PM

Indexed as

AgingAir PollutantsAir PollutionEnvironmental ExposureChinaCitiesHumansParticulate MatterAir PollutantsParticulate Matter

Identifiers

PMID42852352
PMCPMC13648064

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.