Evidence map›Paper›PMID 41464970›Full record

ArticleFoods (Basel, Switzerland)2025

Spatiotemporal Patterns of Aquatic Product Risks in China Based on Entropy-Weighted TOPSIS.

Guangcan Tao, Guoyan Li, Dingfang Pu, Luolin Bao, Su Xu, Hongbo Yang, Kang Hu

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 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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0citing papers 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

Who cites it

0 citing papers in PubMed.

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

7 authors.

Guangcan TaoSchool of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 561113, China.ORCID 0000-0003-4734-7389
Guoyan LiSchool of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 561113, China.
Dingfang PuSchool of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 561113, China.
Luolin BaoSchool of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 561113, China.
Su XuSchool of Food Science and Engineering, Guiyang University, Guiyang 550005, China.ORCID 0000-0001-7875-3123
Hongbo YangSchool of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 561113, China.ORCID 0000-0002-0377-5528
Kang HuNational Institutes for Food and Drug Control, Beijing 102629, China.ORCID 0000-0002-3809-073X

Funding

the Education Department of Guizhou Province - Natural Science Research Project QJJ [2023] 042the Education Department of Guizhou Province - Youth Science and Technology Talent Development Project QJJ [2024] 193the Guizhou Academy of Agricultural Sciences Talent Special Project grant number (2022-02 and 2023-02)the Guizhou Provincial Science and Technology Project QKHPTRC-CXTD [2022] 002the National Natural Science Foundation of China 32160071
6 · The paper itself

Abstract

This study investigates the risk classification and spatiotemporal evolution patterns of hazardous substances in Chinese aquatic products. The entropy-weighted TOPSIS method was employed to achieve the ranking of hazardous substances and classify their risk levels. A spatial autocorrelation analysis was conducted to explore the spatial distribution patterns of the highest-risk and higher-risk substances in Chinese aquatic products. Risk-adjustment factors were employed to allow us to perform dynamic analyses of the risks in aquatic products across different temporal and spatial contexts. The results indicate that the top three hazardous substances in aquatic products were cadmium, enrofloxacin, and total volatile basic nitrogen; their relative proximity values were 0.707, 0.689, and 0.429, respectively. Cadmium, enrofloxacin, furazolidone metabolites, and chloramphenicol exhibited significant global spatial autocorrelation. The spatiotemporal analysis found that risks in aquatic products were higher during summer and autumn, with the maximum risk value reaching 0.92. The integrated application of the entropy-weighted TOPSIS method, spatial autocorrelation analysis, and risk-adjusted factors provides a novel perspective for risk assessment. The findings support targeted regulation of high-risk substances in Chinese aquatic products and the optimization of seasonal-regional regulatory approaches. It is recommended that regulatory measures and schemes be adjusted in light of the findings, thus providing a scientific foundation for the safety supervision of aquatic products.

Indexed as

hazardous substancesPareto principlerisk classificationspatial autocorrelationspatial–temporal distribution characteristics

Identifiers

PMID41464970
PMCPMC12733135

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