Evidence map›Paper›PMID 32698889›Full record

ArticleBMC endocrine disorders2020

Association of total bilirubin and indirect bilirubin content with metabolic syndrome among Kazakhs in Xinjiang.

Hao Hao, Heng Guo, Ru-Lin Ma, Yi-Zhong Yan, Yun-Hua Hu, Jiao-Long Ma, Xiang-Hui Zhang, Xin-Ping Wang, Kui Wang, La-Ti Mu and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC endocrine disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 29% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Bilirubin metabolism in relation to cancer.Frontiers in oncology · 2025
    Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

14 authors at 1 institution in 1 country.

Hao HaoDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Heng GuoDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Ru-Lin MaDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Yi-Zhong YanDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Yun-Hua HuDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Jiao-Long MaDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Xiang-Hui ZhangDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Xin-Ping WangDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Kui WangDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
La-Ti MuDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Yan-Peng SongDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Jing-Yu ZhangDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China.
Jia HeDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China. hejia123.shihezi@163.com.
Shu-Xia GuoDepartment of Public Health, Shihezi University School of Medicine, Shihezi, 832000, Xinjiang, China. gsxshzu@sina.com.
Shihezi University · CN

Funding

National Natural Science Foundation of China (CN) 81560551Shihezi University Innovation Outstanding Young Talents Program (Natural Science) CXPY201908
6 · The paper itself

Abstract

backgroundSome studies have shown that a high level of bilirubin is a protective factor against metabolic syndrome (MS), while a high level of transaminase is a risk factor for MS. However, the existing results are inconsistent and few cohort studies have been published.

methodsUsing an ambispective cohort study, 565 Kazakhs from Xinjiang, China were selected as the study subjects. The baseline serum bilirubin and transaminase levels of the subjects were divided into quartiles and the relationship between these values and the incidence of MS was analyzed. The definition of MS was based on the Joint Interim Statement (JIS) diagnostic criteria.

resultsThe average follow-up time for the subjects was 5.72 years. The cumulative incidence of MS was 36.11% (204 of the 565 subjects), and the incidence density was 63.10/1000 person-years. Multivariate Cox regression analysis showed that the levels of total bilirubin (TBIL) and indirect bilirubin (IBIL) were negatively correlated with the occurrence of MS, Compared to the lowest quartile level (Q1), the hazard ratios of MS the TBIL levels at the Q2-Q4 quartiles were: 0.47 (0.31-0.71), 0.53 (0.35-0.79), and 0.48 (0.32-0.72), respectively, while IBIL levels at the Q2-Q4 quartiles showed an MS hazard ratio of 0.48 (0.32-0.72), 0.54(0.36-0.81), and 0.52 (0.35-0.77), respectively, all at a 95% confidence level. However, no relationship was found between transaminase levels and the incidence of MS.

conclusionSerum TBIL and IBIL levels were negatively correlated with the incidence of MS in a Kazakh population in China.

Indexed as

AdultBilirubinBiomarkersChinaCohort StudiesFemaleFollow-Up StudiesHumansIncidenceMaleMetabolic SyndromeMiddle AgedPrognosisRisk FactorsBilirubinBiomarkersBilirubinMetabolic syndromeTransaminase

Identifiers

PMID32698889
PMCPMC7376964
OpenAlexW3045283585

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.