Evidence map›Paper›PMID 37888666›Full record

ArticleToxics2023

Association of Air Pollution with the Number of Common Respiratory Visits in Children in a Heavily Polluted Central City, China.

Dan Wang, Yanan Wang, Qianqian Liu, Wenxin Sun, Liangkui Wei, Chengxin Ye, Rencheng Zhu

Open access · goldAbstract read
In one paragraph

Article in Toxics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 25% of its field
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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Observational
  3. Time-Series Analysis of Atmospheric Pollution andThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2025
    Article
  4. 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

7 authors at 2 institutions in 1 country.

Dan WangEmergency Department, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou 450014, China.
Yanan WangSchool of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China.
Qianqian LiuEmergency Department, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou 450014, China.
Wenxin SunSchool of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China.
Liangkui WeiEmergency Department, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou 450014, China.
Chengxin YeEmergency Department, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou 450014, China.
Rencheng ZhuSchool of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China.ORCID 0000-0001-5455-1850
Third Affiliated Hospital of Zhengzhou University · CNZhengzhou University · CN

Funding

the National Key R&D Program of China 2017YFC0212400the Natural Science Foundation of Henan Province No. 232300421243the University Key Research Project of Henan Province No. 23A610007the Young Backbone Teacher Training Program of Zhengzhou University null
6 · The paper itself

Abstract

Children's respiratory health is vulnerable to air pollution. Based on data collected from June 2019 to June 2022 at a children's hospital in Zhengzhou, China, this study utilized Spearman correlation analysis and a generalized additive model (GAM) to examine the relationship between daily visits for common respiratory issues in children and air pollutant concentrations. Results show that the number of upper respiratory tract infection (URTI), pneumonia (PNMN), bronchitis (BCT), and bronchiolitis (BCLT) visits in children showed a positive correlation with PM

Indexed as

air pollutantsgeneralized additive modelmeteorological factorsrespiratory diseases

Identifiers

PMID37888666
PMCPMC10610878
OpenAlexW4387140210

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.