Evidence map›Paper›PMID 39327579›Full record

ArticleLipids in health and disease2024

Identifying reliable obesity indices for hyperuricemia among middle-aged and elderly populations: a longitudinal study.

Yuntong Liu, Wei Zhao, Xuhan Liu, Haodong Jiang, Yixia Wu, Lan Luo, Zhengnan Gao

Abstract read
In one paragraph

Article in Lipids in health and disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

7 authors.

Yuntong Liu *Dalian municipal Central Hospital, China Medical University, Shenyang, China.
Wei Zhao *Department of Endocrinology, Dalian Municipal Central Hospital, Dalian, China.
Xuhan LiuDepartment of Endocrinology, Dalian Municipal Central Hospital, Dalian, China.
Haodong JiangDepartment of Cardiovascular, the Second Hospital of Jilin University, Changchun, China.
Yixia WuDepartment of Endocrinology, Dalian Municipal Central Hospital, Dalian, China.
Lan LuoDepartment of Endocrinology, Dalian Municipal Central Hospital, Dalian, China. rolland_304224@sohu.com.
Zhengnan GaoDepartment of Endocrinology, Dalian Municipal Central Hospital, Dalian, China. gao2008@dlut.edu.cn.

Funding

the Dalian Science and Technology Bureau project 2022RG11the National Key R&D Program of China 2017YFC1310700
6 · The paper itself

Abstract

backgroundGiven the established link between obesity and hyperuricemia (HUA), the research want to investigate the relationship between different obesity indices and HUA, and further analyze which obesity index can better predict HUA.

methodsThe data were obtained from a longitudinal study involving middle-aged and elderly populations in Dalian, China. The research encompassed individuals who exhibited typical uric acid levels initially and tracked their progress over a three-year period. 8 obesity indices were evaluated retrospectively. Subgroup analyses were conducted to identify susceptible populations. Restricted cubic splines (RCS) were utilized to model the dose-response relationships between obesity indices and HUA. Receiver operating characteristic (ROC) curves were applied to visualize and compare the predictive value of both traditional and new obesity indices for HUA.

resultsAmong 4,112 individuals with normal baseline uric acid levels, 950 developed HUA. Significant associations with HUA were observed for body mass index (BMI), waist circumference (WC), body roundness index (BRI), cardiometabolic index (CMI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), and abdominal volume index (AVI). Subgroup analysis indicated that all obesity indices proved more effective in assessing the onset of HUA in women without Metabolic Syndrome (MetS). Further analysis using RCS revealed non-linear dose-response relationships between LAP, CMI, VAI, and HUA in males, with similar non-linear relationships observed for all indices in females. The results from the ROC curves indicate that LAP may serve as a better predictor of HUA in males, and CVAI may serve as a better predictor in females.

conclusionHUA is closely associated with obesity indices. Among females, CVAI emerges as the preferred predictive index for HUA. In males, LAP emerges as the preferred predictive index for HUA.

Indexed as

Body Mass IndexHyperuricemiaObesityUric AcidWaist CircumferenceAgedChinaFemaleHumansLongitudinal StudiesMaleMetabolic SyndromeMiddle AgedRetrospective StudiesROC CurveUric AcidHyperuricemiaLongitudinal studyMetabolic syndromeObesity indices

Identifiers

PMID39327579
PMCPMC11426091

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.