Evidence map›Paper›PMID 34534520›Full record

SynthesisEnvironmental research2022

Ambient air pollution and COVID-19 risk: Evidence from 35 observational studies.

Si-Tian Zang, Jie Luan, Ling Li, Hui-Xin Yu, Qi-Jun Wu, Qing Chang, Yu-Hong Zhao

Abstract readMeta-Analysis
In one paragraph

Synthesis in Environmental research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 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

31 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  13. Occurrence of COVID-19 and serumGlobal epidemiology · 2024
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  18. Discussion about the Latest Findings on the Possible Relation between Air Particulate Matter and COVID-19.International journal of environmental research and public health · 2023
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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

7 authors.

Si-Tian ZangDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China; Clinical Research Center, Shengjing Hospital of China Medical University, No. 39 Huaxiang Road, Tiexi District, Shenyang, Liaoning, 110022, China. Electronic address: stzang@cmu.edu.cn.
Jie LuanDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China; Clinical Research Center, Shengjing Hospital of China Medical University, No. 39 Huaxiang Road, Tiexi District, Shenyang, Liaoning, 110022, China. Electronic address: jluan@cmu.edu.cn.
Ling LiCenter for Precision Medicine Research and Training, University of Macau, Avenida da Universidade Taipa, Macau, 999078, China. Electronic address: yc07610@connect.um.edu.mo.
Hui-Xin YuDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China; Clinical Research Center, Shengjing Hospital of China Medical University, No. 39 Huaxiang Road, Tiexi District, Shenyang, Liaoning, 110022, China. Electronic address: hxyu@cmu.edu.cn.
Qi-Jun WuDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China; Clinical Research Center, Shengjing Hospital of China Medical University, No. 39 Huaxiang Road, Tiexi District, Shenyang, Liaoning, 110022, China. Electronic address: wuqj@sj-hospital.org.
Qing ChangDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China; Clinical Research Center, Shengjing Hospital of China Medical University, No. 39 Huaxiang Road, Tiexi District, Shenyang, Liaoning, 110022, China. Electronic address: changq@sj-hospital.org.
Yu-Hong ZhaoDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China. Electronic address: zhaoyuhong@sj-hospital.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsThe coronavirus disease 2019 (COVID-19) pandemic is severely threatening and challenging public health worldwide. Epidemiological studies focused on the influence of outdoor air pollution (AP) on COVID-19 risk have produced inconsistent conclusions. We aimed to quantitatively explore this association using a meta-analysis.

methodsWe searched for studies related to outdoor AP and COVID-19 risk in the Embase, PubMed, and Web of Science databases. No language restriction was utilized. The search date entries were up to August 13, 2021. Pooled estimates and 95% confidence intervals (CIs) were obtained with random-/fixed-effects models. PROSPERO registration number: CRD42021244656.

resultsA total of 35 articles were eligible for the meta-analysis. For long-term exposure to AP, COVID-19 incidence was positively associated with 1 μg/m

conclusionsOutdoor air pollutants are detrimental factors to COVID-19 outcomes. Measurements beneficial to reducing pollutant levels might also reduce the burden of the pandemic.

Indexed as

Air PollutionCOVID-19Environmental ExposureHumansParticulate MatterSARS-CoV-2Particulate MatterAir pollutionCOVID-19 incidenceCOVID-19 mortalityMeta-analysisObservational study

Identifiers

PMID34534520
PMCPMC8440008

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.