Evidence map›Paper›PMID 40796854›Full record

ArticleBMC medicine2025

Global burden of early-onset cardiovascular disease attributable to fine particulate matter pollution from 1990 to 2021: a systematic analysis for the global burden of disease study 2021.

Yixuan Jiang, Huihuan Luo, Guangguo Fu, Jinmiao Chen, Haidong Kan, Renjie Chen

Abstract read
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

6 authors.

Yixuan JiangSchool of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China.
Huihuan LuoSchool of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China.
Guangguo FuDepartment of Cardiovascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Jinmiao ChenDepartment of Cardiovascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Haidong KanSchool of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China. kanh@fudan.edu.cn.
Renjie ChenSchool of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China. chenrenjie@fudan.edu.cn.

Funding

Collaborating Program of Fudan-Minhang Academic Health System 2023FM11National Key Research and Development Program of China 2022YFC3702701National Natural Science Foundation of China 82030103Shanghai Sailing Program 24YF2706700
6 · The paper itself

Abstract

backgroundFine particulate matter (PM

methodsWe calculated the number, age-standardized rate, and percentage of CVD deaths and disability-adjusted life-years (DALYs) attributable to PM

resultsIn 2021, the age-standardized death and DALY rates (per 100,000) of early-onset CVD attributable to total PM

conclusionsDespite significant reduction in early-onset CVD burden attributable to total and household PM

Indexed as

Air PollutionCardiovascular DiseasesEnvironmental ExposureGlobal Burden of DiseaseParticulate MatterAdultDisability-Adjusted Life YearsFemaleGlobal HealthHumansMaleMiddle AgedParticulate MatterCardiovascular diseaseEarly-onsetFine particulate matterGlobal Burden of Disease Study 2021Risk factor

Identifiers

PMID40796854
PMCPMC12344906

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LicenceCC BY-NC-ND
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Registered trials

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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.