Evidence map›Paper›PMID 34537941›Full record

ArticleEnvironmental science and pollution research international2022

Probabilistic health risk assessment of inorganic arsenic and some heavy metals in rice produced from a typical multi-mining county, China.

Huijuan Hao, Dabing Ge, Yulong Wen, Yuntao Lv, Wanming Chen

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.7field-weighted citation impact, top 37% of its field
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

0 citing papers in PubMed, 14 citations in OpenAlex.

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

5 authors at 1 institution in 1 country.

Huijuan HaoCollege of Resources and Environment, Hunan Agricultural University, Changsha, 410128, People's Republic of China.
Dabing GeCollege of Resources and Environment, Hunan Agricultural University, Changsha, 410128, People's Republic of China. haudbge@hotmail.com.ORCID http://orcid.org/0000-0003-0719-6002
Yulong WenCollege of Resources and Environment, Hunan Agricultural University, Changsha, 410128, People's Republic of China.
Yuntao LvRisk assessment Laboratory for Environmental Factors of Agro-product Quality Safety, Ministry of Agriculture and Villages, Changsha, 410005, People's Republic of China.
Wanming ChenRisk assessment Laboratory for Environmental Factors of Agro-product Quality Safety, Ministry of Agriculture and Villages, Changsha, 410005, People's Republic of China.
Hunan Agricultural University · CN

Funding

national agricultural product quality and safety risk assessment project GJFP201801201national agricultural product quality and safety risk assessment project GJFP2019036
6 · The paper itself

Abstract

The potential impact of exposure to toxic elements in rice on human health has become a global public health issue. This study analyzed the pollution characteristics and probabilistic health risks of exposure to iAs, Pb, Cd, Cr, and Hg in rice produced in a typical multi-mining county using Monte Carlo simulation, a geographic information system, and bioavailability analysis. The results showed that the enrichment of As and Cd was prominent in rice, with mean tAs, iAs, and Cd contents of 0.34 ± 0.20, 0.15 ± 0.09, and 0.48 ± 0.50 mg·kg

Indexed as

ArsenicMetals, HeavyOryzaSoil PollutantsAdultChildChinaEnvironmental MonitoringHumansRisk AssessmentRisk FactorsSoilArsenicMetals, HeavySoilSoil PollutantsBioaccessibilityHealth riskHeavy metalInorganic arsenicSensitivitySpatial distribution

Identifiers

PMID34537941
OpenAlexW3200145476

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.