Evidence map›Paper›PMID 31491979›Full record

ArticleInternational journal of environmental research and public health2019

Probabilistic Human Health Risk Assessment of Heavy Metal Intake via Vegetable Consumption around Pb/Zn Smelters in Southwest China.

Guanghui Guo, Degang Zhang, Yuntao Wang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

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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

3 authors.

Guanghui GuoInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China. guogh@igsnrr.ac.cn.
Degang ZhangInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China. zhangdg.17b@igsnrr.ac.cn.
Yuntao WangInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China. wangyt.16b@igsnrr.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vegetable contamination in mining and smelting areas has resulted in high dietary intakes of heavy metals, which pose potential health risks to local residents. In this study, paired soil-vegetable samples were collected around Pb/Zn smelters in Southwest China. Probabilistic risks to local residents via vegetable consumption were evaluated with a Monte Carlo simulation. The mean concentrations of As, Cd, Cu, Pb, and Zn in the soils were 116.76, 3.59, 158.56, 196.96, and 236.74 mg/kg, respectively. About 38.18%, 58.49%, and 52.83% of the vegetable samples exceeded the maximum allowable concentrations for As, Cd, and Pb, respectively. The daily dietary intake of As, Cd, and Pb exceeded the provisional tolerable daily intakes for local residents, with children showing the highest intake via vegetable consumption. The percentages of the target hazard quotients of As, Cd, and Pb for local residents exceeding the safe value of one were about 95%, 50%, and 25%, respectively. The 95th percentiles of the hazard index for children, adolescents, and adults were 15.71, 11.15, and 9.34, respectively, indicating significant risks to local residents, especially children. These results highlight a need to develop effective strategies to reduce heavy metal contamination and exposure to protect human health.

Indexed as

ProbabilityRisk AssessmentAdolescentAdultChildChild, PreschoolChinaHumansLeadMetals, HeavyMiddle AgedMiningSoil PollutantsVegetablesYoung AdultZincLeadMetals, HeavySoil PollutantsZincdietary intakeheavy metalprobabilistic risk assessmentvegetable

Identifiers

PMID31491979
PMCPMC6765770

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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.