Evidence map›Paper›PMID 39493623›Full record

ArticleGeoHealth2024

Association Between Short-Term Exposure to Air Pollutants and Emergency Attendance for Upper Gastrointestinal Bleeding in Hong Kong: A Time-Series Study.

Yun Hao Li, Jing Tong Tan, Poh Hwa Ooi, Fang Jiang, Haidong Kan, Wai K Leung

Abstract read
In one paragraph

Article in GeoHealth, 2024. 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. Review
  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

6 authors.

Yun Hao LiDepartment of Medicine School of Clinical Medicine Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong China.
Jing Tong TanDepartment of Medicine School of Clinical Medicine Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong China.
Poh Hwa OoiDepartment of Medicine School of Clinical Medicine Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong China.
Fang JiangDepartment of Medicine School of Clinical Medicine Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong China.
Haidong KanSchool of Public Health Key Lab of Public Health Safety of the Ministry of Education NHC Key Lab of Health Technology Assessment IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health Fudan University Shanghai China.
Wai K LeungDepartment of Medicine School of Clinical Medicine Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong China.ORCID https://orcid.org/0000-0002-5993-1059

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The relationship between exposure to ambient air pollutants and emergency attendance for upper gastrointestinal bleeding (UGIB) remains inconclusive. This study examines the association between short-term exposure to various ambient pollutants and the risk of UGIB emergency attendance. Data on daily UGIB emergency attendance, ambient pollutants, and meteorological conditions in Hong Kong were collected from 2017 to 2022. A time-series study using a distributed lag non-linear model to analyze the data, considering lag days. Stratified analysis was performed based on sex, seasons, and the COVID-19 pandemic period. The burden was quantified using attributable fraction (AF) and number (AN). The study included 31,577 UGIB emergency records. Exposure to high levels of PM

Indexed as

ambient air pollutionnitrogen dioxideparticulate mattertime‐series studyupper gastrointestinal bleeding

Identifiers

PMID39493623
PMCPMC11528714

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.