Evidence map›Paper›PMID 41521142›Full record

ArticleThe Journal of international medical research2026

Associations of PM

Shaomin Diao, Xiaoming Shen

Abstract read
In one paragraph

Article in The Journal of international medical research, 2026. 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

2 authors.

Shaomin DiaoThe First Affiliated Hospital of Henan University of Traditional Chinese Medicine, China.
Xiaoming ShenThe First Affiliated Hospital of Henan University of Traditional Chinese Medicine, China.ORCID 0009-0000-2193-031X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ObjectiveThis study aimed to investigate the associations between fine particulate matter and its major chemical components and cognitive function among middle-aged and older adults in China.MethodsWe conducted a nationwide prospective cohort study using data from the China Health and Retirement Longitudinal Study (2011-2018). Cognitive function was repeatedly assessed through standardized tests of memory and mental status. Annual average concentrations of fine particulate matter and its five major components (sulfate, nitrate, ammonium, black carbon, and organic matter) were estimated at the city level. Fixed-effects models and restricted cubic spline analyses were used to evaluate associations, and random forest models were used to rank the relative importance of components.ResultsHigher exposure to fine particulate matter and several of its major components was significantly associated with lower cognitive scores. Among these components, sulfate exhibited the strongest adverse association with cognitive function. The findings were consistent across multiple sensitivity analyses, including those restricted to provincial capitals and those adjusting for potential confounders.ConclusionsExposure to fine particulate matter and its chemical components may contribute to cognitive impairment among middle-aged and older adults in China. Sulfate appears to be particularly detrimental. These results highlight the need for targeted air pollution control policies that address specific fine particulate matter components to mitigate the burden of cognitive impairment.

Indexed as

Air PollutantsAir PollutionCognitionCognitive DysfunctionEnvironmental ExposureParticulate MatterAgedChinaFemaleHumansLongitudinal StudiesMaleMiddle AgedProspective StudiesSulfatesAir PollutantsParticulate MatterSulfateschemical componentsChinaChina Health and Retirement Longitudinal Studycognitive functionFine particulate mattersulfate

Identifiers

PMID41521142
PMCPMC12791219

What OpenQuestion holds

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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.