# Association between higher estimated glucose disposal rate and reduced prevalence of hyperuricemia and gout

Researcher: Ge Zhang
Chinese name: 张格
ORCID identity anchor: https://orcid.org/0000-0002-3116-3246
Canonical researcher: https://drgezhang.com/#person

Journal: Frontiers in Nutrition
Year: 2025
Type: Article
DOI: 10.3389/fnut.2025.1658286
Canonical page: https://drgezhang.com/papers/doi-10-3389-fnut-2025-1658286.html
Markdown record: https://drgezhang.com/papers/doi-10-3389-fnut-2025-1658286.md

## Full Authors

1. Pengfei Liu
2. Kaisaierjiang Kadier
3. Xiaoli Wu
4. Xiangyu Sun
5. Ge Zhang
6. Xiaozhu Liu
7. Daqing Song
8. Chunying Cui

<a id="paper-discovery"></a>
## Research & review context

### Research fields

- Metabolic epidemiology
- Population-based gout and hyperuricemia research

### Review topics

- Insulin-resistance proxies and prevalent disease
- Survey-weighted cross-sectional associations

### Scientific role

Observational analysis of eGDR and two prevalent outcomes in one NHANES adult sample.

### Evidence position

Adjusted association, not prospective prediction, disease prevention or treatment efficacy.

### Related concepts

- Estimated glucose disposal rate
- Hyperuricemia
- Gout

### Possible citation contexts

- Population evidence relating an insulin-resistance proxy to prevalent hyperuricemia and gout.
- Evidence review distinguishing continuous associations from nonsignificant category-specific gout estimates.

Possible literature-review contexts, not evidence of existing citations. Read the findings and Evidence Scope before citing the original article.

## Evidence Snapshot

**Estimated glucose disposal rate, hyperuricemia and gout: cross-sectional NHANES associations**

A survey-weighted analysis of 29,340 NHANES participants examined eGDR associations with hyperuricemia and self-reported gout. Fully adjusted continuous associations were inverse, but the 4–6 mg/kg/min gout contrast was not statistically significant. The evidence does not establish prevention or a treatment effect.

| Evidence | Value |
| --- | --- |
| Unique total | n=29,340 |
| NHANES 2007–2018 analytic sample | n=29,340 |

## Research Question

How is estimated glucose disposal rate associated with prevalent hyperuricemia and self-reported gout in NHANES adults after survey weighting and measured-covariate adjustment?

## Author Evidence Summary

The study analyzed adults from six NHANES cycles covering 2007–2018. The exposure eGDR combines waist circumference, hypertension and HbA1c; hyperuricemia was defined from serum uric acid using sex-specific thresholds, while gout relied on self-reported professional diagnosis. In Model 3, each 1 mg/kg/min higher eGDR was associated with lower odds of both outcomes. For gout, the 4–6 mg/kg/min category did not differ significantly from the <4 reference after full adjustment. This exception is explicit in the body and Table 3 and prevents adopting the abstract's universal category-significance claim. The analysis concerns prevalent disease, with residual confounding, self-report and temporal-order limitations.

## Key Findings

<a id="kf1"></a>
### KF1: Both outcome analyses use the same selected cross-sectional NHANES sample.

Context: Participant counts are unweighted observations, not weighted prevalence estimates or incident cases.

| Evidence | Value |
| --- | --- |
| analytic participants | 29,340 |
| NHANES cycles | 6 (2007–2018) |
| hyperuricemia cases | 5,433 |
| self-reported gout cases | 1,346 |

Source locator: Methods §2.1 Study design and population (sec7); §2.3 Diagnosis of HUA and gout (sec9); Tables 2 and 3 (tab2, tab3), Continuous case/participants rows

<a id="kf2"></a>
### KF2: Higher continuous eGDR was associated with lower adjusted odds of hyperuricemia.

Context: Model 3 weighted logistic regression; odds per 1 mg/kg/min higher eGDR. This is not a 17% reduction in incidence or an intervention effect.

| Evidence | Value |
| --- | --- |
| Model 3 odds ratio | 0.83 |
| 95% confidence interval | 0.81–0.85 |
| P value | <0.001 |

Source locator: Methods §2.2 Calculation of eGDR (sec8), §2.5 Statistical analyses (sec11); Results §3.2 (sec14); Table 2 (tab2), Continuous row, Model 3 and covariate footnote

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### KF3: The continuous gout association was inverse, but not every categorical contrast was statistically significant after full adjustment.

Context: Table 3 Model 3 compares eGDR categories with <4 mg/kg/min. The 4–6 comparison includes the null and is explicitly described as nonsignificant in Results §3.3.

| Evidence | Value |
| --- | --- |
| continuous OR per 1 mg/kg/min | 0.83 (95% CI 0.79–0.87), P<0.001 |
| 4–6 mg/kg/min versus <4 | OR 0.81 (95% CI 0.63–1.04), P=0.093 |
| 6–8 mg/kg/min versus <4 | OR 0.62 (95% CI 0.47–0.82), P=0.001 |
| >8 mg/kg/min versus <4 | OR 0.35 (95% CI 0.25–0.48), P<0.001 |

Source locator: Results §3.3 Association between eGDR and gout (sec15); Table 3 (tab3), Continuous and category rows, Model 3; contrast with Abstract Results category statement

<a id="kf4"></a>
### KF4: The exposure and outcomes were estimated or measured using distinct operational definitions.

Context: The eGDR proxy and observational outcome definitions do not directly measure a treatment response or establish a new clinical diagnostic test.

| Evidence | Value |
| --- | --- |
| eGDR equation (mg/kg/min) | 21.158 − 0.09×waist circumference (cm) − 3.407×hypertension (yes=1/no=0) − 0.551×HbA1c (%) |
| hyperuricemia thresholds | >7.0 mg/dL in males; >6.0 mg/dL in females |
| gout ascertainment | Self-reported professional diagnosis |

Source locator: Methods §2.2 Calculation of eGDR (sec8); §2.3 Diagnosis of HUA and gout (sec9)

## Study Design & Analytical Framework

### Study profile

- Study Design: Secondary cross-sectional analysis of six NHANES survey cycles, 2007–2018
- Evidence Type: Survey-weighted observational association study; no intervention or prospective incidence evaluation
- Unique total: 29,340
- Population: NHANES adults aged at least 20 years, excluding pregnant participants and those missing eGDR, gout or uric-acid information
- Primary Endpoint: Prevalent hyperuricemia: serum uric acid >7.0 mg/dL in males or >6.0 mg/dL in females
- Secondary Endpoint: Self-reported prior diagnosis of gout by a doctor or other healthcare professional
- External validation: No
- Data modalities: NHANES examination and serum biomarker data, Questionnaire-reported diagnoses and lifestyle measures, Survey-design variables and sampling weights

### Cohort hierarchy

| Cohort | Role | n | Relationship |
| --- | --- | ---: | --- |
| NHANES 2007–2018 analytic sample | Single cross-sectional survey sample used for both outcome analyses; not two independent cohorts | 29340 | Independent cohort |

## What This Study Adds

- Places a composite insulin-resistance proxy alongside measured hyperuricemia and self-reported gout in one weighted population survey analysis.
- Separates continuous association from category-specific evidence; Table 3 does not support a universal significant gout-category effect.

## Evidence Scope

### Supports

- Adjusted prevalence-odds associations in the selected NHANES 2007–2018 adult sample.
- The explicit nonsignificant fully adjusted 4–6 mg/kg/min gout contrast.

### Does Not Establish

- That increasing eGDR prevents hyperuricemia or gout, or reduces future disease incidence.
- Causal mediation by insulin resistance or benefit from an eGDR-targeted intervention.
- A statistically significant adjusted gout association for every eGDR category.
- Prospective prediction accuracy or a clinical treatment threshold.

### Limitations

- Known source discrepancy: Abstract Results implies all higher eGDR categories significantly reduce both outcomes. Table 3 and Results §3.3 instead identify the fully adjusted gout 4–6 contrast as nonsignificant (OR 0.81, 95% CI 0.63–1.04, P=0.093). This page follows the mutually consistent body/table contrast and does not claim the abstract has been formally corrected.
- Cross-sectional associations cannot establish causality, incident risk reduction or prevention; odds ratios are not prevalence ratios.
- Gout ascertainment is self-reported; eGDR estimates insulin resistance rather than directly measuring clamp-derived glucose disposal.
- Covariate adjustment and imputation do not exclude residual confounding or selection bias.
- Supplementary subgroup, interaction and sensitivity estimates are not used as independently verified key findings in this bounded evidence page.

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## When This Study Is Useful to Cite

### CU1: What population evidence relates eGDR to prevalent hyperuricemia?

The weighted Model 3 association in this NHANES sample is OR 0.83 per 1 mg/kg/min, with CI 0.81–0.85; this is not incidence reduction.

Evidence: [KF1](#kf1), [KF2](#kf2)

### CU2: Does the paper show a significant gout association for all higher eGDR categories?

No. The 4–6 versus <4 contrast is nonsignificant in fully adjusted Model 3; continuous and higher-category associations require their own stated contrasts.

Evidence: [KF3](#kf3)

### CU3: How were the exposure and gout measured?

eGDR was calculated from waist circumference, hypertension and HbA1c; gout was self-reported professional diagnosis.

Evidence: [KF4](#kf4)

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## What This Study Should Not Be Cited to Claim

- That increasing eGDR prevents hyperuricemia or gout, or reduces future disease incidence.
- Causal mediation by insulin resistance or benefit from an eGDR-targeted intervention.
- A statistically significant adjusted gout association for every eGDR category.
- Prospective prediction accuracy or a clinical treatment threshold.

<a id="evidence-matrix"></a>
## Evidence Matrix

<a id="evidence-kf1"></a>
### Both outcome analyses use the same selected cross-sectional NHANES sample.

- Context: Participant counts are unweighted observations, not weighted prevalence estimates or incident cases.
- Finding: analytic participants: 29,340; NHANES cycles: 6 (2007–2018); hyperuricemia cases: 5,433; self-reported gout cases: 1,346
- Evidence Level: Survey-weighted cross-sectional observational analysis
- Scope: Reported prevalence-odds association or study measurement, not incident disease prediction or an intervention effect.
- Source Locator: Methods §2.1 Study design and population (sec7); §2.3 Diagnosis of HUA and gout (sec9); Tables 2 and 3 (tab2, tab3), Continuous case/participants rows
- Evidence refs: [KF1](#kf1)

<a id="evidence-kf2"></a>
### Higher continuous eGDR was associated with lower adjusted odds of hyperuricemia.

- Context: Model 3 weighted logistic regression; odds per 1 mg/kg/min higher eGDR. This is not a 17% reduction in incidence or an intervention effect.
- Finding: Model 3 odds ratio: 0.83; 95% confidence interval: 0.81–0.85; P value: <0.001
- Evidence Level: Survey-weighted cross-sectional observational analysis
- Scope: Reported prevalence-odds association or study measurement, not incident disease prediction or an intervention effect.
- Source Locator: Methods §2.2 Calculation of eGDR (sec8), §2.5 Statistical analyses (sec11); Results §3.2 (sec14); Table 2 (tab2), Continuous row, Model 3 and covariate footnote
- Evidence refs: [KF2](#kf2)

<a id="evidence-kf3"></a>
### The continuous gout association was inverse, but not every categorical contrast was statistically significant after full adjustment.

- Context: Table 3 Model 3 compares eGDR categories with <4 mg/kg/min. The 4–6 comparison includes the null and is explicitly described as nonsignificant in Results §3.3.
- Finding: continuous OR per 1 mg/kg/min: 0.83 (95% CI 0.79–0.87), P<0.001; 4–6 mg/kg/min versus <4: OR 0.81 (95% CI 0.63–1.04), P=0.093; 6–8 mg/kg/min versus <4: OR 0.62 (95% CI 0.47–0.82), P=0.001; >8 mg/kg/min versus <4: OR 0.35 (95% CI 0.25–0.48), P<0.001
- Evidence Level: Survey-weighted cross-sectional observational analysis
- Scope: Reported prevalence-odds association or study measurement, not incident disease prediction or an intervention effect.
- Source Locator: Results §3.3 Association between eGDR and gout (sec15); Table 3 (tab3), Continuous and category rows, Model 3; contrast with Abstract Results category statement
- Evidence refs: [KF3](#kf3)

<a id="evidence-kf4"></a>
### The exposure and outcomes were estimated or measured using distinct operational definitions.

- Context: The eGDR proxy and observational outcome definitions do not directly measure a treatment response or establish a new clinical diagnostic test.
- Finding: eGDR equation (mg/kg/min): 21.158 − 0.09×waist circumference (cm) − 3.407×hypertension (yes=1/no=0) − 0.551×HbA1c (%); hyperuricemia thresholds: >7.0 mg/dL in males; >6.0 mg/dL in females; gout ascertainment: Self-reported professional diagnosis
- Evidence Level: Survey-weighted cross-sectional observational analysis
- Scope: Reported prevalence-odds association or study measurement, not incident disease prediction or an intervention effect.
- Source Locator: Methods §2.2 Calculation of eGDR (sec8); §2.3 Diagnosis of HUA and gout (sec9)
- Evidence refs: [KF4](#kf4)

## Q&A

### How many participants and which outcomes were analyzed?

One analytic sample of 29,340 adults was used for both outcomes; Tables 2 and 3 list 5,433 hyperuricemia and 1,346 self-reported gout cases. These case counts must not be substituted for survey-weighted prevalence.

Evidence: KF1

### Was every higher eGDR category significantly associated with less gout?

No. Table 3 Model 3 gives OR 0.81, 95% CI 0.63–1.04 and P=0.093 for 4–6 versus <4 mg/kg/min. Results §3.3 states this loss of significance. The abstract's broader all-category statement is not adopted.

Evidence: KF3

### What did the continuous adjusted analyses report?

Per 1 mg/kg/min higher eGDR, Model 3 reports OR 0.83 (95% CI 0.81–0.85) for hyperuricemia and OR 0.83 (0.79–0.87) for gout. These are prevalence-odds associations.

Evidence: KF2, KF3

### Does this demonstrate that raising eGDR will prevent disease?

No. The cross-sectional design cannot establish temporal order or a preventive intervention effect. Gout is self-reported and eGDR is a calculated proxy.

Evidence: KF1, KF4

## Concepts & Entities

### Conditions

hyperuricemia, gout

### Populations

US NHANES adults aged at least 20 years

### Outcomes

prevalent hyperuricemia, self-reported gout

### Methods

survey-weighted logistic regression, cross-sectional analysis, estimated glucose disposal rate

### Data Types

survey questionnaires, serum uric acid, HbA1c, waist circumference

### Models & Tools

eGDR

### Datasets & Cohorts

NHANES 2007–2018

## Related Research

- [Associations Between Cardiovascular Health (Life's Essential 8) and Mental Disorders](https://drgezhang.com/papers/doi-10-1002-clc-70019.html) — Another cross-sectional NHANES analysis illustrating survey-weighted prevalence associations; not independent confirmation of the eGDR findings. (DOI: 10.1002/clc.70019)

## Publication & Provenance

- DOI: https://doi.org/10.3389/fnut.2025.1658286
- Publisher: https://doi.org/10.3389/fnut.2025.1658286
- Pmc Url: https://pmc.ncbi.nlm.nih.gov/articles/PMC12501789/
- PubMed: https://pubmed.ncbi.nlm.nih.gov/41064288/
- PMCID: PMC12501789
- Pmid: 41064288
- Version: Formal published article archived as PMC12501789.1; no scientific correction relation returned by the targeted Crossref metadata check on 2026-10-26. This is not an exhaustive absence-of-correction claim.
- Evidence Basis: Methods §§2.1–2.5 and Results §§3.2–3.3, including text-encoded Tables 2–3. The contradictory universal category claim in Abstract Results is explicitly excluded.
- Source Verification Scope: Formal Methods, Results and text-encoded tables were checked directly. No original statistical reanalysis and no source figures reproduced.
- License: CC BY 4.0, as stated in article-level permissions.
- Source Sha256: 42d4736dac32237e52512f05e654c5d4c78deff3c9c327db465b9212c2d24ca2

## Evidence-page notice

Author-controlled evidence page for this publication. This page provides an evidence-oriented summary and does not replace the publisher's version of record. The explicitly disclosed inconsistent findings are excluded from the supported evidence scope.

## Links

- DOI: https://doi.org/10.3389/fnut.2025.1658286
- HTML page: https://drgezhang.com/papers/doi-10-3389-fnut-2025-1658286.html
- Google Scholar query: https://scholar.google.com/scholar?q=%22Association%20between%20higher%20estimated%20glucose%20disposal%20rate%20and%20reduced%20prevalence%20of%20hyperuricemia%20and%20gout%22
- ORCID: https://orcid.org/0000-0002-3116-3246