Evidence map›Paper›PMID 39473619›Full record

ArticleEnvironment & health (Washington, D.C.)2023

Multifaceted Insight into Sensitivity Analysis and Environmental Impact on Human Health of Soil Contamination Risk Assessment.

Hao Zhang, Ping Du, Bei Yuan, Yunhui Zhang, Juan Chen, Hupeng Liu, Aiyang Li, Yuquan Wei, Yanna Xiong, Bin Zhao

Abstract read
In one paragraph

Article in Environment & health (Washington, D.C.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

10 authors.

Hao ZhangTechnical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China.ORCID https://orcid.org/0000-0003-2697-7103
Ping DuTechnical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China.
Bei YuanTechnical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China.
Yunhui ZhangTechnical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China.
Juan ChenTechnical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China.
Hupeng LiuChinese Research Academy of Environmental Sciences, Beijing 100012, China.
Aiyang LiChinese Research Academy of Environmental Sciences, Beijing 100012, China.
Yuquan WeiBeijing Key Laboratory of Biodiversity and Organic Farming, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China.ORCID https://orcid.org/0000-0002-1309-5139
Yanna XiongTechnical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China.
Bin ZhaoInstitute of Eco-Environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sensitivity analysis is a valuable method for evaluating the impact of model parameters on health risk characterization, thereby supporting the prediction of critical uncertainty factors. However, limitations arise in terms of cross-disciplinary discussions and in-depth analyses of previous research. To overcome these limitations, a systematic and multifaceted approach was introduced for analyzing the parameter sensitivities in soil contamination risk assessment. This approach specifically targeted the 12 main parameters associated with 65 soil contaminants for health risk assessment, employing detailed authoritative statistics for risk assessment. Screening analysis revealed that identified heavy metals and organics were influenced by key parameters, such as PM

Identifiers

PMID39473619
PMCPMC11504630

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.