Evidence map›Paper›PMID 36231914›Full record

ArticleInternational journal of environmental research and public health2022

Air Pollution Increased the Demand for Gym Sports under COVID-19: Evidence from Beijing, China.

Xin Dong, Shili Yang, Chunxiao Zhang

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 86% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 2 institutions in 1 country.

Xin DongSchool of Information Engineering, China University of Geosciences, Beijing 100083, China.
Shili YangBeijing Meteorological Observation Centre, Beijing Meteorological Bureau, Beijing 100089, China.
Chunxiao ZhangSchool of Information Engineering, China University of Geosciences, Beijing 100083, China.ORCID 0000-0002-9320-4218
China University of Geosciences (Beijing) · CNBeijing Meteorological Bureau · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Air pollution may change people's gym sports behavior. To test this claim, first, we used big data crawler technology and ordinary least square (OLS) models to investigate the effect of air pollution on people' gym visits in Beijing, China, especially under the COVID-19 pandemic of 2019-2020, and the results showed that a one-standard-deviation increase in PM2.5 concentration (fine particulate matter with diameters equal to or smaller than 2.5 μm) derived from the land use regression model (LUR) was positively associated with a 0.119 and a 0.171 standard-deviation increase in gym visits without or with consideration of the COVID-19 variable, respectively. Second, using spatial autocorrelation analysis and a series of spatial econometric models, we provided consistent evidence that the gym industry of Beijing had a strong spatial dependence, and PM2.5 and its spatial spillover effect had a positive impact on the demand for gym sports. Such a phenomenon offers us a new perspective that gym sports can be developed into an essential activity for the public due to this avoidance behavior regarding COVID-19 virus contact and pollution exposure.

Indexed as

Air PollutantsAir PollutionCOVID-19BeijingChinaEnvironmental MonitoringExerciseHumansPandemicsParticulate MatterAir PollutantsParticulate Matterair pollutionCOVID-19gym sportsPM2.5 concentrationspatial econometric model

Identifiers

PMID36231914
PMCPMC9566646
OpenAlexW4303696589

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.