Evidence map›Paper›PMID 39259425›Full record

ArticleBiological trace element research2025

Exploring Potential Human Health Risks Linked to Heavy Metal(Loid)s in Dietary Fishes: Utilizing Data-Driven and Computational Modelling Approaches.

Pritom Bhowmik Akash, Sazal Kumar, Md Saikoth Jahan, Muhammad Shafiqur Rahman, Md Assraf Seddiky, Anti Sorker, Rafiquel Islam

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In one paragraph

Article in Biological trace element research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Pritom Bhowmik AkashDepartment of Civil Engineering, Chittagong University of Engineering & Technology, Chatttogram, 4349, Bangladesh.
Sazal KumarSchool of Environmental and Life Sciences, The University of Newcastle (UoN), Callaghan, NSW, 2308, Australia.
Md Saikoth JahanDepartment of Geography and Environment, Islamic University, Kushtia, 7003, Bangladesh.
Muhammad Shafiqur RahmanMaterials and Chemical Processing Laboratory, The University of Adelaide, Adelaide, SA, 5000, Australia.
Md Assraf SeddikyDepartment of Public Administration, Shahjalal University of Science & Technology, Sylhet, 3114, Bangladesh.
Anti SorkerDepartment of Agricultural Economics, Faculty of Agribusiness Management, Sher-E-Bangla Agricultural University, Sher-E-Bangla Nagar, Dhaka, 1207, Bangladesh.
Rafiquel IslamSchool of Environmental and Life Sciences, The University of Newcastle (UoN), Callaghan, NSW, 2308, Australia. rafiquel.islam@newcastle.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are significant concerns about the risks to human health posed by metal(loid) contamination in dietary fishes in Bangladesh. Therefore, this study aimed to evaluate heavy metal(loid) contamination in fish and their associated health risks using published data from 2000 to 2022. Additionally, the safe limit of fish consumption was estimated using the target hazard quotient (THQ) followed by computational modelling and artificial neural networks (ANN). Results showed that freshwater and herbivorous fishes pose the least non-cancer risks, whereas saltwater and carnivorous fishes pose the highest non-cancer risks to Bangladeshi consumers. However, freshwater and omnivorous fish consumption pose the highest cancer risks compared to all studied metal(loid)s. In particular, among the heavy metal(loid)s, As, Cr, Hg, and Ni pose significant cancer and non-cancer risks to Bangladeshi consumers. On the contrary, the ANN and Decision tree regression (DTR) characterized the dataset, simulation model, or data testing condition, reaching 94.7% accuracy and allowing us to measure the safest fish consumption limit. The herbivorous fishes are less contaminated and allow greater consumption (175.09 g day

Indexed as

Computer SimulationFishesFood ContaminationMetals, HeavySeafoodWater Pollutants, ChemicalAnimalsBangladeshHumansNeural Networks, ComputerRisk AssessmentMetals, HeavyWater Pollutants, ChemicalArtificial neural networkBangladeshDietary safe limitFishHeavy metal(loid)Human health risks

Identifiers

PMID39259425
PMCPMC12125157

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.