Evidence map›Paper›PMID 35520285›Full record

ArticleFrontiers in nutrition2022

The Association Between Hyperuricemia and Obesity Metabolic Phenotypes in Chinese General Population: A Retrospective Analysis.

Xiaojing Feng, Yanyi Yang, Huiqi Xie, Siqi Zhuang, Yiyuan Fang, Yufeng Dai, Ping Jiang, Hongzhi Chen, Haoneng Tang, Lingli Tang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

16 citing papers in PubMed, 24 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Xiaojing FengDepartment of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
Yanyi YangHealth Management Center of the Second Xiangya Hospital, Central South University, Changsha, China.
Huiqi XieDepartment of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
Siqi ZhuangDepartment of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
Yiyuan FangDepartment of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
Yufeng DaiDepartment of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
Ping JiangDepartment of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
Hongzhi ChenNational Clinical Research Center for Metabolic Disease, The Second Xiangya Hospital, Central South University, Changsha, China.
Haoneng TangDepartment of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
Lingli TangDepartment of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
Second Xiangya Hospital of Central South University · CNCentral South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Serum uric acid (UA) not only affects the development of obesity but also alters the metabolic status in obese subjects; thus we investigated the relationship between serum UA and the overweight/obese metabolic phenotypes. Methods: The demographic, biochemical, and hematological data were collected for 12,876 patients undergoing routine physical examination, and 6,912 participants were enrolled in our study. Participants were classified into four obesity metabolic phenotypes according to their BMI and the presence of metabolic syndrome: metabolically healthy overweight/obese (MHOO), metabolically healthy and normal weighted (MHNW), metabolically abnormal and overweight/obese (MAOO), and metabolically abnormal but normal weighted (MANW). Univariate and multivariate logistic regression analysis, stratified analysis, and also interaction analysis were conducted to analyze the relationship between serum UA and obesity metabolic phenotypes. Results: Multivariable logistic regression analysis showed that hyperuricemia was positively associated with MHOO, MANW, and MAOO phenotypes relative to MHNW. After adjusting for the confounding factors, the odds ratios (OR) for individuals with hyperuricemia to be MHOO, MANW, and MAOO phenotypes were 1.86 (1.42-2.45), 2.30 (1.44-3.66), and 3.15 (2.34-4.24), respectively. The ORs for having MHOO, MANW, and MAOO increased 6% [OR: 1.06 (1.05-1.07), Conclusion: In our study, we discovered that hyperuricemia was positively associated with MHOO, MANW, and MAOO phenotypes, and this relationship was independent of sex and age.

Indexed as

hyperuricemiametabolic phenotypesobesityoverweighturic acid

Identifiers

PMID35520285
PMCPMC9063096
OpenAlexW4224288886

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.