Evidence map›Paper›PMID 40090381›Full record

ReviewJournal of obesity & metabolic syndrome2025

Long-Term Exposure to Ambient Air Pollution and Metabolic Syndrome and Its Components.

Hyun-Jin Kim, Juyeon Hwang, Jin-Ho Park

Abstract readReview
In one paragraph

Review in Journal of obesity & metabolic syndrome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. The Indoor Microbiome: Sampling, Analysis and Emerging Trends.Environmental microbiology reports · 2026
    Pooled it
  2. Article
  3. Article
  4. Seasonal PMToxics · 2026
    Article
  5. Review
  6. Association between PMFrontiers in public health · 2026
    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

3 authors.

Hyun-Jin KimNational Cancer Control Institute, National Cancer Center, Goyang, Korea.
Juyeon HwangNational Cancer Control Institute, National Cancer Center, Goyang, Korea.
Jin-Ho ParkDepartment of Family Medicine, Seoul National University Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0002-3942-6813

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ambient air pollution is a serious public health issue worldwide. A growing number of studies has highlighted the negative effects of air pollution on metabolic syndrome (MetS) and its components, including abdominal obesity, disorders of lipid metabolism, elevated blood pressure, and impaired fasting blood glucose. This review provides a brief overview of epidemiological and genetic interaction studies of the links between chronic exposure to ambient air pollution and MetS and its components, as well as plausible mechanisms underlying these relationships. The cumulative evidence suggests that long-term exposure to air pollution, especially particulate matter, increases the risk of MetS and its components. These associations can be partly modified by baseline characteristics, lifestyle, and health conditions. Gene-by-air-pollution interaction studies, limited to candidate genes in the past, have recently been conducted at an expanded genome-wide level. However, more such studies are needed to comprehensively understand the genetics involved in the association between air pollution and MetS. Mechanistic evidence suggests potential biological pathways, including inflammation, oxidative stress, and endothelial dysfunction.

Indexed as

Air pollutionAssociationGene-environment interactionInflammationMetabolic syndromeOxidative stress

Identifiers

PMID40090381
PMCPMC12067007

What OpenQuestion 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 OpenQuestion graph.