Evidence map›Paper›PMID 33559782›Full record

ArticleEnvironmental geochemistry and health2021

Particulate matter pollution and emergency room visits for respiratory diseases in a valley Basin city of Northwest China.

Bowen Cheng, Yuxia Ma, Hang Wang, Jiahui Shen, Yifan Zhang, Lingyun Guo, Yongtao Guo, Mingji Li

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental geochemistry and health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

5 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Article
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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 at 3 institutions in 1 country.

Bowen Cheng *College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
Yuxia Ma *College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China. mayuxia07@lzu.edu.cn.
Hang WangCollege of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
Jiahui ShenCollege of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
Yifan ZhangCollege of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
Lingyun GuoThe Second Hospital, Lanzhou University, Lanzhou, 730000, China.
Yongtao GuoCollege of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
Mingji LiResource and Environment Department, Ningxia University, Yinchuan, 750021, China.
Lanzhou University · CNLanzhou University Second Hospital · CNNingxia University · CN

Funding

National Natural Science Foundation of China 41961028National Natural Science Foundation of China 41975141National Science and Technology Planning Project 2016YFA0602004
6 · The paper itself

Abstract

Epidemiological studies have suggested that particulate matter (PM) pollution seriously affects human health, particularly it is closely associated with respiratory diseases. The aim of this study is to quantitatively evaluate the effect of PMs (PM

Indexed as

Air PollutantsAir PollutionAgedChildChinaEmergency Service, HospitalEnvironmental ExposureFemaleHumansMaleParticulate MatterAir PollutantsParticulate MatterGAMParticulate matterRespiratory diseaseSeasonal modification

Identifiers

PMID33559782
OpenAlexW3126305438

What OpenQuestion holds

Textmetadata
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.