Evidence map›Paper›PMID 28233200›Full record

SynthesisEnvironmental science and pollution research international2017

Association of urinary cadmium with risk of diabetes: a meta-analysis.

Yujie Li, Yun Zhang, Weijing Wang, Yili Wu

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Environmental science and pollution research international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 11% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

  1. Pooled it
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  4. Review
  5. Review
  6. Review
  7. Article
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  12. Review
  13. Article
  14. Chronic Kidney Disease and Exposure to Nephrotoxic Metals.International journal of molecular sciences · 2017
    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

4 authors at 1 institution in 1 country.

Yujie LiDepartment of Epidemiology and Health Statistics, Qingdao University Medical College, No. 38 Deng Zhou Road, Qingdao, 266021, China.
Yun ZhangDepartment of Social Medicine and Health Service Management, Affiliated Hospital of Qingdao University, Qingdao, China.
Weijing WangDepartment of Epidemiology and Health Statistics, Qingdao University Medical College, No. 38 Deng Zhou Road, Qingdao, 266021, China.
Yili WuDepartment of Epidemiology and Health Statistics, Qingdao University Medical College, No. 38 Deng Zhou Road, Qingdao, 266021, China. yiliwu79@163.com.ORCID http://orcid.org/0000-0002-5289-2552
Qingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The association between urinary cadmium and diabetes risk remains controversial. PubMed, Web of Science, China National Knowledge Infrastructure, and Wanfang Data updated on 21 June 2016 were searched for eligible publications. Pooled odds ratio (OR) with 95% confidence interval (CI) of diabetes for highest versus lowest level of urinary cadmium was calculated by using fixed-effect model or random-effect model. Dose-response relationship between urinary cadmium and diabetes was estimated by restricted cubic spline. A total of nine studies with 28,691 participants were included in this meta-analysis. The pooled OR of diabetes for the highest versus lowest level of urinary cadmium was 1.02 (95% CI, 1.00, 1.05; I

Indexed as

AsiaCadmiumChinaDiabetes MellitusHumansProspective StudiesRiskUnited StatesCadmiumDiabetesDose-response analysisEpidemiologyHeavy metalMeta-analysisUrinary cadmium

Identifiers

PMID28233200
OpenAlexW2589631934

What OpenQuestion holds

Textmetadata
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.