Evidence map›Paper›PMID 27537182›Full record

ArticlePloS one2016

Application of the Benchmark Dose (BMD) Method to Identify Thresholds of Cadmium-Induced Renal Effects in Non-Polluted Areas in China.

Xiaofeng Wang, Yu Wang, Lingfang Feng, Yan Tong, Zhijian Chen, Shibo Ying, Tianhui Chen, Tao Li, Hailing Xia, Zhaoqiang Jiang and 3 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

7 citing papers in PubMed, 28 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. The Validity of Benchmark Dose Limit Analysis for Estimating Permissible Accumulation of Cadmium.International journal of environmental research and public health · 2022
    Article
  6. Article
  7. Article
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

13 authors at 3 institutions in 1 country.

Xiaofeng WangDepartment of Environmental and Occupational Health, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, Zhejiang, P.R. China.
Yu WangInstitute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, Zhejiang, P.R. China.
Lingfang FengInstitute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, Zhejiang, P.R. China.
Yan TongInstitute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, Zhejiang, P.R. China.
Zhijian ChenInstitute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, Zhejiang, P.R. China.
Shibo YingInstitute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, Zhejiang, P.R. China.
Tianhui ChenInstitute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, Zhejiang, P.R. China.
Tao LiInstitute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, Zhejiang, P.R. China.
Hailing XiaInstitute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, Zhejiang, P.R. China.
Zhaoqiang JiangInstitute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, Zhejiang, P.R. China.
Qi ShangInstitute for Environmental Health and Related Product Safety, Chinese Center for Disease Control and Prevention, Beijing 100050, P.R. China.
Xiaoming LouDepartment of Environmental and Occupational Health, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, Zhejiang, P.R. China.
Jianlin LouInstitute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, Zhejiang, P.R. China.
Zhejiang Academy of Medical Sciences · CNZhejiang Center for Disease Control and Prevention · CNChinese Center For Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The benchmark dose (BMD) method has been increasingly used to assess the health risks of cadmium (Cd) in epidemiological studies. The aim of our study was to estimate the threshold levels of urinary Cd (UCd) using the BMD method in a general population of Jiangshan City, Zhejiang Province of China. In our study, a total of 934 people (469 men, 465 women) were recruited and morning urine samples were collected from all the participants. Levels of Cd, creatinine, and renal dysfunction indicators such as retinol binding protein (RBP), β2-microglobulin (β2-MG), and N-acetyl-b-glucosaminidase (NAG) in urine were detected for analysis of BMD and BMD low (BMDL) of UCd. RBP, β2-MG, and NAG in urine all correlated significantly (P < 0.001) with UCd except of age (P = 0.767). When the benchmark response (BMR) was 5%, the BMD/BMDL of UCd for RBP, β2-MG, and NAG was 1.69/ 0.89, 1.24/0.62, 0.85/0.49 μg/g Cr in men and 1.70/0.76, 1.35/0.64, 1.36/0.65 μg/g Cr in women, respectively. If the BMR was set at 10%, the BMD/BMDL of UCd for RBP, β2-MG, and NAG was 2.44/1.59, 2.09/1.30, 1.80/1.04 μg/g Cr in men and 2.43/1.53, 2.10/1.34, 2.31/1.37 μg/g Cr in women, respectively. Our results provided evidence for Cd-induced tubular effects in cadmium non-polluted areas in China. Both β2-MG and NAG were more sensitive than RBP in response to Cd exposure. But β2-MG was the most sensitive indicator in women, and NAG was the most sensitive one in men.

Indexed as

AcetylglucosaminidaseAdolescentAdultAgedbeta 2-MicroglobulinCadmiumChildChinaCreatinineEnvironmental ExposureFemaleHumansKidneyKidney DiseasesMaleMiddle AgedAcetylglucosaminidasebeta 2-MicroglobulinCadmiumCreatinineRetinol-Binding Proteins

Identifiers

PMID27537182
PMCPMC4990304
OpenAlexW2517192199

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.