Evidence map›Paper›PMID 40079333›Full record

ArticleJournal of the American Heart Association2025

Hypothetical Behavioral Interventions for Mitigating the Cardiovascular Effects of Long-Term Fine Particulate Matter Exposure: Analyses From 2 Prospective Cohorts.

Jialong Wu, Liang Wang, Xu Han, Linya Huang, Qiong Meng, Tingting Yang, Quzong Deji, Zihao Wang, Bing Guo, Xing Zhao

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Jialong WuWest China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China.
Liang WangChengdu Center for Disease Control &Prevention Chengdu Sichuan China.
Xu HanHealth Information Center of Sichuan Province Chengdu Sichuan China.
Linya HuangHealth Information Center of Sichuan Province Chengdu Sichuan China.
Qiong MengDepartment of Epidemiology and Health Statistics, School of Public Health Kunming Medical University Kunming Yunnan China.ORCID 0000-0002-2498-9816
Tingting YangSchool of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education Guizhou Medical University Guiyang China.ORCID 0000-0001-8864-828X
Quzong DejiTibet University Lhasa Tibet China.
Zihao WangChongqing Municipal Center for Disease Control and Prevention Chongqing China.
Bing GuoWest China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China.ORCID 0000-0002-4598-3157
Xing ZhaoWest China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China.ORCID 0000-0001-5713-3603

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhether healthy behaviors can attenuate the adverse association between ambient fine particulate matter (PM METHODS AND

resultsThe parametric g-formula was used to quantify the potential reduction in PM

conclusionsHealthier behaviors could serve as individual-level complementary strategies to emission control for minimizing the health impact of PM

Indexed as

Air PollutantsAir PollutionCardiovascular DiseasesEnvironmental ExposureHealth BehaviorParticulate MatterRisk Reduction BehaviorAdultAgedBody Mass IndexChinaExerciseFemaleHumansIncidenceMaleAir PollutantsParticulate Mattercardiovascular diseasesfine particulate matterg‐formulalifestyle

Identifiers

PMID40079333
PMCPMC12132628

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.