Evidence map›Paper›PMID 39967945›Full record

ArticleArchives of medical science : AMS2024

Relationships between blood concentrations of cadmium, lead, mercury, selenium, and manganese and the risk of chronic kidney disease: a cross-sectional study based on NHANES 2011-2018.

Shenghua Yao, Dan Xu

Abstract read
In one paragraph

Article in Archives of medical science : AMS, 2024. 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. 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

2 authors.

Shenghua YaoDepartment of Nephrology, Yuyao People's Hospital, Ningbo, China.
Dan XuDepartment of Geriatrics, Yuyao People's Hospital, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Currently, knowledge on relationships between blood concentrations of cadmium, lead, mercury, selenium, and manganese and the risk of chronic kidney disease (CKD) is lacking. The aim of the study was to ex-plore the relationships between blood concentrations of heavy metals and the occurrence of CKD. Material and methods: Data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 were used to investigate the relationships between blood concentrations of mercury, lead, cadmium, selenium, and manganese and the occurrence of CKD using a weighted logistic recession analysis. Restrictive cubic spline analysis was applied to assess the dose-response relationship. The sample population was divided into four groups based on the quartiles of heavy metal concentrations (Q1: < 25 Results: A total of 15,450 participants were included. With regard to blood lead concentrations, the odds ratio (OR) for CKD in Q4 relative to Q1 was 1.36 (95% confidence interval [CI]: 1.20-1.61), indicating an increased oc-currence of CKD in Q4. With regard to blood cadmium concentrations, the ORs for CKD in Q2, Q3, and Q4 were 1.06 (95% CI: 0.92-1.22), 1.21 (95% CI: 1.05-1.39), and 1.52 (95% CI: 1.31-1.76), respectively. Non-linear dose-response relationships were identified between blood cadmium and lead concentrations and the occurrence of CKD. Further, blood lead and cadmium concentrations showed statistically significant interaction effects with age, hypertension, and obesity on CKD. Conclusions: Higher cadmium and lead concentrations in blood are asso-ciated with increased occurrence of CKD, especially in older adults, people with hypertension, and people with obesity.

Indexed as

diseaseepidemiologymetals

Identifiers

PMID39967945
PMCPMC11831350

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.