Evidence map›Paper›PMID 39114317›Full record

ArticleChina CDC weekly2024

A New Approach Refined Probabilistic Health Risk Assessment of Shaoguan Smelter Based on Microenvironment - Guangdong Province, China, 2021.

Liangzhong Li, Lei Zhang, Yile Yan, Bingbing Sun, Ruixue Ma, Qiong Wang, Yunjiang Yu, Haoran Yuan, Jing Cao

Abstract read
In one paragraph

Article in China CDC weekly, 2024. 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
–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

0 citing papers in PubMed.

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

9 authors.

Liangzhong LiGuangdong Provincial Key Laboratory of High-Quality Recycling of End-of-Life New Energy Devices, Guangzhou Institute of Energy Research, Chinese Academy of Sciences, Guangzhou City, Guangdong Province, China.
Lei ZhangState Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, Center for Environmental Health Research, South China Institute of Environmental Sciences, The Ministry of Ecological and Environment of China, Guangzhou City, Guangdong Province, China.
Yile YanState Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, Center for Environmental Health Research, South China Institute of Environmental Sciences, The Ministry of Ecological and Environment of China, Guangzhou City, Guangdong Province, China.
Bingbing SunState Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, Center for Environmental Health Research, South China Institute of Environmental Sciences, The Ministry of Ecological and Environment of China, Guangzhou City, Guangdong Province, China.
Ruixue MaState Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, Center for Environmental Health Research, South China Institute of Environmental Sciences, The Ministry of Ecological and Environment of China, Guangzhou City, Guangdong Province, China.
Qiong WangChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention Beijing, China.
Yunjiang YuState Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, Center for Environmental Health Research, South China Institute of Environmental Sciences, The Ministry of Ecological and Environment of China, Guangzhou City, Guangdong Province, China.
Haoran YuanGuangdong Provincial Key Laboratory of High-Quality Recycling of End-of-Life New Energy Devices, Guangzhou Institute of Energy Research, Chinese Academy of Sciences, Guangzhou City, Guangdong Province, China.
Jing CaoDezhou Center for Disease Control and Prevention, Dezhou City, Shandong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study introduces a novel method for developing an advanced exposure conceptual model tailored for health risk assessment, focusing on microenvironments. Methods: The research was conducted at a major smelter in China to assess the health risks associated with trace metals (TMs) pollutants in the facility and the surrounding soil. Results: Deterministic risk assessment indicated that cobalt, cadmium, antimony, manganese, arsenic, plumbum, and mercury (Co, Cd, Sb, Mn, As, Pb, and Hg) necessitated further evaluation through probabilistic risk assessment to assess potential health risks to residents. The 95% quantile concentrations of other TMs were found to be within acceptable health risk limits. For the probabilistic risk assessment, exposure parameters such as body weight, respiration rate, and exposure duration were collected using a questionnaire. This targeted assessment of the residential microenvironment revealed it as the site of the highest carcinogenic (CR) and non-carcinogenic risks (NCR), with values ranging from 2.84×10 Conclusion: The primary contaminants posing the greatest health risks in residential and industrial areas have been identified as As, Pb, and Mn. The probabilistic health risk model, which focuses on microenvironmental factors, yields more precise results and offers a valuable tool for managing soil health risks.

Indexed as

health risk assessmentmicroenvironmentMonte Carlo simulationSensitivity analysis

Identifiers

PMID39114317
PMCPMC11301604

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.