Evidence map›Paper›PMID 41128285›Full record

ArticleAmerican journal of epidemiology2026

The association between long-term exposure to PM2.5 constituents and diabetes incidence and blood glucose levels among World Trade Center Health Program general responders.

Helena Krasnov, Pablo Knobel, Hsiao-Hsien Leon Hsu, Susan L Teitelbaum, Mary Ann McLaughlin, Allan C Just, Itai Kloog, Maayan Yitshak-Sade

Abstract read
In one paragraph

Article in American journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Long-term Exposure to PMmedRxiv : the preprint server for health sciences · 2026
    Article
  3. 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

8 authors.

Helena KrasnovDepartment of Environmental Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID 0000-0003-0230-3112
Pablo KnobelDepartment of Environmental Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID 0000-0001-6902-0286
Hsiao-Hsien Leon HsuDepartment of Environmental Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID 0000-0001-8704-197X
Susan L TeitelbaumDepartment of Environmental Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID 0000-0002-2190-1575
Mary Ann McLaughlinDepartment of Cardiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID 0000-0003-2154-0500
Allan C JustDepartment of Epidemiology, Brown University School of Public Health, Providence, RI, United States.ORCID 0000-0003-4312-5957
Itai KloogDepartment of Environmental Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID 0000-0003-1708-7440
Maayan Yitshak-SadeDepartment of Environmental Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID 0000-0003-4453-0401

Funding

The Mount Sinai Transdisciplinary Center on Early Environmental ExposuresP30ES023515 · NIEHS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Robert O Wright · 2014 to 2026
$21.3M
Institutional Career Development CoreKL2TR004421 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Inga Peter · 2022 to 2026
$6.2M
Cardiometabolic diseases in the World Trade Center general responder cohort and the role of subsequent environmental exposuresR01ES034864 · NIEHS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Maayan Yitshak Sade · 2023 to 2026
$1.9M
Centers for Disease Control and Prevention, National Institute for Occupational Safety and HealthNCATS NIH HHS KL2 TR004421NIEHS NIH HHS P30 ES023515NIEHS NIH HHS R01 ES034864NIEHS NIH HHS R01ES034864 and KL2TR004421NIOSH CDC HHS U10 OH008216
6 · The paper itself

Abstract

Exposure to fine particulate matter (PM2.5) is associated with cardiometabolic risk among World Trade Center Health Program general responders, but current studies focus mainly on PM2.5 mass. We studied the associations between annual source-apportioned PM2.5 exposures, and self-reported diabetes or repeated blood glucose measurements among general responders enrolled between 2003 and 2019 (n = 34 764), residing in Tri-state area. We used non-negative matrix factorization to attribute PM2.5 component to sources (ie, biomass burning, oil combustion, metal industry, other industries, and motor vehicles). We used multivariable mixed-effect models to estimate the simultaneous associations of the source-apportioned PM2.5 exposures with the outcomes. We found (% change [95% CIs]) an interquartile range increase in PM2.5 attributed to metal industry sources (0.42 μg/m3) to be associated with an 8.35% (1.39%, 15.79%) higher risk of diabetes and a 1.31% (0.80%, 1.82%) increase in glucose levels. Source-specific associations with glucose were modified by sex, showing larger associations with biomass burning (1.08% [0.32%, 1.85%] per 0.44 μg/m3) and motor vehicle (1.34% [0.76%, 1.93%] per 0.92 μg/m3) pollution among women, and larger associations with oil-combustion (0.68% [0.03%, 1.34%] per 1.74 μg/m3) pollution among men. These findings can inform policies and interventions targeting emissions from these specific sources, particularly for general responders with a history of extreme air pollution exposures.

Indexed as

Air PollutantsAir PollutionBlood GlucoseDiabetes MellitusEnvironmental ExposureParticulate MatterAdultFemaleHumansIncidenceMaleMiddle AgedNew York CitySeptember 11 Terrorist AttacksAir PollutantsBlood GlucoseParticulate MatterdiabetesglucosePM2.5chemical componentsWorld Trade Center

Identifiers

PMID41128285
PMCPMC13352492

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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 Socratic graph.