Evidence map›Paper›PMID 33891256›Full record

ArticleEnvironmental geochemistry and health2021

Effects of air pollutant emission on the prevalence of respiratory and circulatory system diseases in Linyi, China.

Xin Wu, Dong Li, Meihui Feng, Houfeng Liu, Hongmei Li, Jing Yang, Pengcheng Wu, Xunjie Lei, Min Wei, Xin Bo

Abstract read
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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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed, 12 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

10 authors at 6 institutions in 1 country.

Xin WuNetwork and Information Department, Linyi People's Hospital, Linyi, 276000, Shandong, China.
Dong LiNetwork and Information Department, Linyi People's Hospital, Linyi, 276000, Shandong, China.
Meihui FengCollege of Geography and Environment, Shandong Normal University, Jinan, 250014, Shandong, China.
Houfeng LiuCollege of Geography and Environment, Shandong Normal University, Jinan, 250014, Shandong, China.
Hongmei LiSchool of Management and Engineering, Capital University of Economics and Business, Beijing, 100070, China.
Jing YangNetwork and Information Department, Linyi People's Hospital, Linyi, 276000, Shandong, China.
Pengcheng WuGuangdong Provincial Academy of Environmental Science, Guangzhou, 510045, Guangdong, China.
Xunjie LeiGuangdong Hydropower Planning and Design Institute, Guangzhou, 510635, Guangdong, China.
Min WeiCollege of Geography and Environment, Shandong Normal University, Jinan, 250014, Shandong, China. minwei@sdnu.edu.cn.
Xin BoAppraisal Center for Environment and Engineering, Ministry of Ecology and Environment, Beijing, 100012, China. boxin@acee.org.cn.
Linyi People's Hospital · CNShandong Normal University · CNCapital University of Economics and Business · CNGuangdong Hydropower Planning & Design Institute · CNGuangdong Provincial Academy of Environmental Science · CNMinistry of Ecology and Environment · CN

Funding

National Natural Science Foundation of China 42075183National Research Program for Key Issues in Air Pollution Control DQGG0209-07National Research Program for Key Issues in Air Pollution Control DQGG0304-07State Key Joint Laboratory of Environmental Simulation and Pollution Control 16K01ESPCT
6 · The paper itself

Abstract

As a typical industrial city, Linyi has suffered severe atmospheric pollution in recent years. Meanwhile, a high incidence of respiratory and circulatory diseases has been observed in Linyi. The relationship between air pollutants and the prevalence of respiratory and circulatory system diseases in Linyi is still unclear, and therefore, there is an urgent need to assess the human health risks associated with air pollutants. In this study, the number of outpatient visits and spatial distribution of respiratory and circulatory diseases were first investigated. To clarify the correlation between diseases and air pollutant emissions, the residential intake fraction (IF) of air pollutants was calculated. The results showed that circulatory and respiratory diseases accounted for 62.32% of the total causes of death in 2015. The incidence of respiratory diseases was high in the winter, and outpatient visits were observed for more males (60.9%) than females (39.1%). The spatial distribution suggested that outpatient visits for respiratory and circulatory diseases were concentrated in the main urban area of Linyi, including the Hedong District, Lanshan District, and Luozhuang District, and especially at the junction of these three areas. After calculating the IF combined with the characteristics of pollution sources, meteorological conditions, and population data, a high IF value was concentrated in urban and suburban areas, which was consistent with the high incidence of diseases. Moreover, high R values and a significant correlation (R > 0.6, p < 0.05) between outpatient visits and residential IF of air pollutants imply similar spatial distributions of outpatient visits and IF value of residents. The spatial similarity of air pollution and outpatient visits suggested that future air pollution control policies should better reflect the health risks of spatial hotspots. This study can provide a potentially important reference for environmental management and air pollution-related health interventions.

Indexed as

Air PollutantsAir PollutionChinaCitiesFemaleHumansMaleParticulate MatterPrevalenceAir PollutantsParticulate MatterAir qualityCirculatory systemIntake fraction (IF)Pollutants emissionRespiratory diseases

Identifiers

PMID33891256
OpenAlexW3153752406

What OpenQuestion holds

Textmetadata
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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.