Evidence map›Paper›PMID 41219254›Full record

ArticleScientific reports2025

Estimated glucose disposal rate and risk of incident hyperuricemia: insights from CHARLS.

YuanJian Liao, MingShun Zuo, Te Xu, YongPan Zhu, JiaJia Tang, LongMei Fan, Neng Zhang

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

YuanJian Liao *Department of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, China.
MingShun Zuo *Department of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, China.
Te XuDepartment of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, China.
YongPan ZhuDepartment of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, China.
JiaJia TangDepartment of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, China.
LongMei FanDepartment of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, China.
Neng ZhangDepartment of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, China. energy20170118@hotmail.com.

Funding

National Natural Sciences Foundation of China (Grant No. 81860524)
6 · The paper itself

Abstract

Hyperuricemia (HUA) is a widespread public health problem worldwide, the etiology of HUA is complex, and there is still a lack of accurate indicators to assess HUA when conducting mass epidemiologic screening. Recent studies have shown that insulin resistance (IR) contributes to the development of HUA, and the estimated glucose disposal rate (eGDR) has been recognized as a reliable surrogate for IR. The aim of this study was to investigate the association between eGDR and incident HUA. A total of 9091 participants without HUA at baseline were enrolled in the China Health and Retirement Longitudinal Study. Multivariate logistic regression models were used to analyze the association between eGDR and incident HUA. Restricted cubic spline (RCS) regression modeling was used to examine the dose-response relationship between eGDR and new-onset HUA, and ROC curve analysis was used to test the predictive power of eGDR. Among 9091 participants, 306 new cases of HUA were documented during a median follow-up of 79.4 months. RCS curves showed a significant linear relationship between eGDR and HUA (nonlinear P > 0.05). After full adjustment for covariates (model 3), higher eGDR values were significantly associated with a lower risk of HUA (P < 0.05). The ORs (95% CI) for eGDR Q2-4 were 0.83 (95% CI 0.57-1.19), 0.65 (95% CI 0.45-0.92), and 0.62 (95% CI 0.43-0.89), respectively, for a significantly lower risk of HUA compared with participants with eGDR Q1. When assessed as a continuous variable, each additional standard deviation of eGDR was associated with an 8% reduction in the risk of new-onset HUA (OR 0.92; 95% confidence interval 0.86-0.98; P = 0.006). Higher eGDR was found to be associated with a reduced risk of HUA. This suggests that eGDR may represent one of the promising predictive and intervention targets for HUA.

Indexed as

Blood GlucoseGlucoseHyperuricemiaAgedChinaFemaleHumansIncidenceInsulin ResistanceLongitudinal StudiesMaleMiddle AgedRisk FactorsROC CurveBlood GlucoseGlucoseCHARLSeGDRHUAHyperuricemia

Identifiers

PMID41219254
PMCPMC12606124

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