Evidence map›Paper›PMID 41584178›Full record

ArticleFrontiers in public health2025

The association between air pollutants, meteorological factors, and mushroom poisoning cases in Guizhou Province, China: a 5-year time-series study.

Muli Wu, Anzhong Wu, Qingyuan Chen, Sufang Xiong, Yanrong Hu, Shuai Huang, Qing Wang, Jun Li, Hua Guo

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Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Muli Wu *Institute of Public Health Surveillance and Evaluation, Guizhou Center for Disease Control and Prevention, Guiyang, China.
Anzhong Wu *Institute of Public Health Surveillance and Evaluation, Guizhou Center for Disease Control and Prevention, Guiyang, China.
Qingyuan ChenExperimental Center, Guizhou Center for Disease Control and Prevention, Guiyang, China.
Sufang XiongSchool of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China.
Yanrong HuSchool of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China.
Shuai HuangSchool of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China.
Qing WangSchool of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China.
Jun LiSchool of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China.
Hua GuoInstitute of Public Health Surveillance and Evaluation, Guizhou Center for Disease Control and Prevention, Guiyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mushroom poisoning is a major food safety concern in Guizhou Province, where meteorological conditions play an important role in its occurrence. However, the lagged associations and interactions between air pollutants and meteorological factors on poisoning risk remain unclear. This study systematically evaluates the impact of these environmental factors on mushroom poisoning incidence. Methods: We collected daily records of mushroom poisoning cases, air pollutants, and meteorological data in Guizhou Province from 2019 to 2023. A generalized additive model (GAM) was employed to analyze exposure-response relationships and interactions between air pollutants, meteorological factors, and mushroom poisoning cases, while a distributed lag nonlinear model (DLNM) quantified lagged associations. Results: In 2019 and 2023, Guizhou Province reported 5,927 mushroom poisoning cases, with rural areas accounting for 4,306 cases (72.7%) and urban areas for 1,621 (27.3%). Significant nonlinear relationships were observed between the risk of mushroom poisoning and air pollutants [CO, O Conclusion: This study revealed lagged associations and interactions between air pollutants and meteorological factors on mushroom poisoning, providing a scientific basis for precise prevention and control.

Indexed as

Air PollutantsMeteorological ConceptsMushroom PoisoningChinaHumansIncidenceAir Pollutantsair pollutantdistributed lag nonlinear modelmeteorological factormushroom poisoningtime-series study

Identifiers

PMID41584178
PMCPMC12823814

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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.