Evidence map›Paper›PMID 29770928›Full record

ArticleClinical rheumatology2018

Body adiposity index, lipid accumulation product, and cardiometabolic index reveal the contribution of adiposity phenotypes in the risk of hyperuricemia among Chinese rural population.

Haoyu Wang, Yingxian Sun, Shuze Wang, Hao Qian, Pengyu Jia, Yintao Chen, Zhao Li, Lijun Zhang

Abstract read
PubMed Publisher
In one paragraph

Article in Clinical rheumatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
1.6field-weighted citation impact, top 19% 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

43 citing papers in PubMed, 57 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

8 authors at 2 institutions in 2 countries.

Haoyu WangDepartment of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China.
Yingxian SunDepartment of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China.
Shuze WangDepartment of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI, 48109, USA.
Hao QianDepartment of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China.
Pengyu JiaDepartment of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China.
Yintao ChenDepartment of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China.
Zhao LiDepartment of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China.
Lijun ZhangDepartment of Hematology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China. zljcmu1h@163.com.ORCID http://orcid.org/0000-0003-4091-8943
First Hospital of China Medical University · CNWashtenaw Community College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adiposity phenotypes, estimated by higher body adiposity index (BAI), lipid accumulation product (LAP), and cardiometabolic index (CMI), has conferred increased metabolic risk. The relative contribution of BAI, LAP, and CMI in hyperuricemia, however, is unknown. We hypothesized that these obesity indicators would refine identification of hyperuricemia. Information on serum uric acid (SUA), fasting lipid profiles, and body adiposity measures (BAI, LAP, and CMI) were recorded in a cross-sectional population-based sample of 11,102 participants (≥ 35 years old) from China. BAI, LAP, and CMI were strong independent predictors of SUA in both sexes after correction for potential confounders. In multivariable models, odds ratio (OR) for hyperuricemia for 1 SD increment in BAI, LAP, and CMI were 1.361 (95% CI, 1.224-1.513), 1.393 (95% CI, 1.273-1.525), and 1.332 (95% CI, 1.224-1.448) in females, respectively. For males, these adiposity indices corresponded to an increased hyperuricemia risk of 14, 47, and 33%, respectively. Additionally, compared to the bottom category, females with the top quartile of BAI, LAP, and CMI showed higher adjusted odds of having hyperuricemia, with ORs of 2.064, 7.500, and 4.944, respectively. ORs for hyperuricemia were statistically significant in the fourth quartile of BAI (1.622 [1.258-2.091]), LAP (5.549 [3.907-7.880]), and CMI (3.878 [2.830-5.313]) of male subgroup. Accumulation of ectopic adiposity in general (quantified by increased BAI), and of visceral adipose tissue in particular (reflected by elevated LAP and CMI), provided important insight regarding hyperuricemia risk and might potentially shed further light on our understanding of the metabolic sequelae of obesity.

Indexed as

AdiposityLipid Accumulation ProductAdultBody Mass IndexChinaCross-Sectional StudiesFemaleHealth Status IndicatorsHumansHyperuricemiaLinear ModelsLipidsMaleMiddle AgedMultivariate AnalysisPhenotypeLipidsAdiposityBody adiposity indexCardiometabolic indexEpidemiologyHyperuricemiaLipid accumulation product

Identifiers

PMID29770928
OpenAlexW2805023334

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.