Evidence map›Paper›PMID 36203530›Full record

ArticleComputational and mathematical methods in medicine2022

Correlation of Pollen Concentration and Meteorological Factors with Medical Condition of Allergic Rhinitis in Shenyang Area.

Feifei Jiang, Aihui Yan

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Characterizing air pollution exposure methodologies in rhinology: a scoping review.International journal of environmental health research · 2025
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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

2 authors.

Feifei JiangDepartment of Otorhinolaryngology, The First Hospital of China Medical University, Shenyang, 110001 Liaoning, China.ORCID https://orcid.org/0000-0002-0135-8640
Aihui YanDepartment of Otorhinolaryngology, The First Hospital of China Medical University, Shenyang, 110001 Liaoning, China.ORCID https://orcid.org/0000-0003-0474-515X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The pathogenesis of allergic rhinitis (AR) was affected by meteorological and environmental factors. This study investigated the association between clinical symptoms of AR patients with pollen dispersal and meteorological conditions. Methods: The clinical features of 10,838 AR patients who were treated in the Department of Otorhinolaryngology, The First Hospital of China Medical University, Shenyang, from March 2021 to October 2021 were retrospectively analyzed. We collected pollen by a pollen collector, read and counted it under a microscope, identified the species of the pollen particles, and recorded meteorological data (average daily temperature, maximum and minimum temperature, average daily wind, average daily precipitation, average daily humidity, average pressure, air quality index, PM2.5, PM10, SO Results: Among the AR visits, patients >41 years old accounted for the highest proportion (64.15%). 43.67% of the patients were complicated with bronchial asthma, and the disease incidence peaked in September. During the period of the study, a total of 27,512 pollen grains were collected, and 17 species were identified. The pollens of Compositae and Moraceae were the main allergenic sources leading to the increase in AR visits from August to September. The peak of pollen dispersal was in spring, summer, and autumn. The total amount of pollen was not only related to the average daily minimum temperature, average daily precipitation, and average daily humidity but also had a significant correlation with air quality index and air pollutants (PM2.5 and PM10, SO Conclusion: The peak seasons of pollen dispersal in Shenyang were in spring, summer, and autumn, and the allergenic pollens were mainly Compositae and Moraceae. In addition, AR was substantially correlated with pollen concentration and meteorological factors. This study may help provide early warning information and prevention for AR patients.

Indexed as

Air PollutantsRhinitis, AllergicAdultAllergensHumansMeteorological ConceptsNitrogen DioxideParticulate MatterPollenRetrospective StudiesSeasonsAir PollutantsAllergensNitrogen DioxideParticulate Matter

Identifiers

PMID36203530
PMCPMC9532155

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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.