Evidence map›Paper›PMID 39934145›Full record

ArticleScientific data2025

Global mercury dataset with predicted methylmercury concentrations in seafoods during 1995-2022.

Haifeng Zhou, Yumeng Li, Qiumeng Zhong, Xiaohui Wu, Sai Liang

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

5 authors.

Haifeng ZhouSchool of Environment, Beijing Normal University, Beijing, 100875, P. R. China.ORCID http://orcid.org/0000-0001-7911-3566
Yumeng LiSchool of Environment, Beijing Normal University, Beijing, 100875, P. R. China.
Qiumeng ZhongGuangdong Basic Research Center of Excellence for Ecological Security and Green Development, Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, P. R. China.
Xiaohui WuSchool of Environment, Beijing Normal University, Beijing, 100875, P. R. China.
Sai LiangGuangdong Basic Research Center of Excellence for Ecological Security and Green Development, Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, P. R. China. liangsai@gdut.edu.cn.ORCID http://orcid.org/0000-0002-6306-5800

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52325005National Natural Science Foundation of China (National Science Foundation of China) 52388101National Natural Science Foundation of China (National Science Foundation of China) 72293602
6 · The paper itself

Abstract

Mercury exposure poses significant threats to human health, particularly in its organic form, methylmercury (MeHg). Diet is the main pathway for human MeHg exposure, especially through seafood consumption. In this context, numerous studies have established seafood MeHg concentration datasets to assess MeHg-related health risks from seafood consumption. However, existing datasets are limited to specific regions and short-term observations, making it difficult to support continuous and dynamic assessments of global MeHg-related health risks. This study takes a bottom-up approach to construct a global seafood MeHg concentration dataset during 1995-2022. Firstly, it compiles a long-term time series marine-scale dataset of seafood MeHg concentrations, based on the reported seafood mercury concentrations from existing literature and machine learning methods. Subsequently, this study used the seafood catch volumes of each nation in different marine areas as weights to estimate the national-scale seafood MeHg concentrations. This dataset can provide essential data support for environmental impact assessment of mercury and its compounds as mentioned in Articles 12 and 19 of the Minamata Convention on Mercury.

Indexed as

Food ContaminationMercuryMethylmercury CompoundsSeafoodWater Pollutants, ChemicalEnvironmental MonitoringHumansMachine LearningMercuryMethylmercury CompoundsWater Pollutants, Chemical

Identifiers

PMID39934145
PMCPMC11814070

What OpenQuestion holds

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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.