Evidence map›Paper›PMID 41274438›Full record

ArticleEnvironmental research2026

Long-term air pollution exposure and gait speed decline among older Adults: A longitudinal analysis.

Boeun Kim, Anjum Hajat, Amanda J Gassett, Claire E Adam, Joel D Kaufman, Erin O Semmens, Cindy S Leary, Annette L Fitzpatrick

Abstract read
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In one paragraph

Article in Environmental 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
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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

8 authors.

Boeun KimCollege of Nursing, University of Iowa, Iowa City, IA, USA. Electronic address: boeun-kim@uiowa.edu.
Anjum HajatSchool of Public Health, University of Washington, Seattle, WA, USA.
Amanda J GassettSchool of Public Health, University of Washington, Seattle, WA, USA.
Claire E AdamCenter for Population Health Research, School of Public and Community Health Sciences, University of Montana, Missoula, MT, USA.
Joel D KaufmanSchool of Public Health, University of Washington, Seattle, WA, USA; School of Medicine, University of Washington, Seattle, WA, USA.
Erin O SemmensCenter for Population Health Research, School of Public and Community Health Sciences, University of Montana, Missoula, MT, USA.
Cindy S LearyCenter for Population Health Research, School of Public and Community Health Sciences, University of Montana, Missoula, MT, USA.
Annette L FitzpatrickSchool of Public Health, University of Washington, Seattle, WA, USA; School of Medicine, University of Washington, Seattle, WA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLong-term exposure to air pollution may contribute to gait speed decline through mechanisms involving systemic inflammation, oxidative stress, and cardiopulmonary or autonomic dysfunction. This study investigated the association of long-term exposure to fine particulate matter (PM

methodsWe leveraged data from the Ginkgo Evaluation of Memory Study (GEMS), followed participants for up to six years (mean follow-up: 4.1 years, N = 2850). Gait speed was assessed annually at usual and maximum paces using a 15-foot timed walk test (2002-2008). Spatiotemporal prediction models estimated average PM

resultsParticipants' mean age was 78.6 years (SD = 3.3); 54.3 % were male. An interquartile range (IQR, 2.19 μg/m

conclusionThese findings underscore the importance of addressing environmental risk factors to preserve mobility and reduce the risk of adverse health outcomes associated with slower gait speed.

Indexed as

Air PollutantsAir PollutionEnvironmental ExposureNitrogen DioxideParticulate MatterWalking SpeedAgedAged, 80 and overFemaleHumansLongitudinal StudiesMaleAir PollutantsNitrogen DioxideParticulate MatterFine particlesLongitudinal analysisPhysical functionTraffic-related air pollution

Identifiers

PMID41274438
PMCPMC13182624

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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.