# Association between insulin resistance-related lipid indices and arthritis: a U. S. cross-sectional study

**Authors:** Ao Wu, Haodong Teng, Xiaoxia Wang, Ketao Shi, Zhi Gao, Honghao Xu, Liang Yue

PMC · DOI: 10.3389/fnut.2025.1583598 · Frontiers in Nutrition · 2025-07-02

## TL;DR

This study finds that lipid-related indicators are linked to arthritis risk, suggesting better glucose and lipid management could reduce arthritis.

## Contribution

The novel contribution is identifying specific lipid indices that are significantly associated with arthritis risk in a large U.S. population.

## Key findings

- Seven lipid-related indicators are positively associated with arthritis risk.
- TyG-WHtR and TyG-BMI show modest accuracy in predicting arthritis with AUC > 0.6.
- Enhanced glucose and lipid management may reduce arthritis risk.

## Abstract

Arthritis is a degenerative disease that causes a huge social burden. Lipid-related molecules participate in the inflammatory response process of arthritis and are closely related to the pathological process of arthritis. Lipid-related indicators are easily available and have great potential in predicting arthritis. This study used cross-sectional data to explore lipid-related indicators and arthritis risk.

18,683 participants were involved in this study, selected from the NHANES database covering the period from 2001 to 2018. The study utilized multivariate regression models to examine the association between various lipid-related parameters (including the TyG index, TyG-WC index, TyG-WHtR index, TyG-BMI index, HOMA-IR index, VAI index, and LAP index) and arthritis.

After taking into account and appropriately addressing potential confounding variables and factors, all seven lipid-related indicators were positively associated with arthritis risk, and there was a significant difference in the highest quartile of seven lipid-related indicators compared with the lowest quartile (P < 0.001). Among them, the area under the ROC curve (AUC) of TyG-WC, TyG-WHtR, TyG-BMI, and LAP was >0.6, indicating they had modest accuracy in predicting arthritis. Logistic regression analysis showed that the best Cut-off values for predicting arthritis for these indicators were as follows: TyG: 8.45 [Odds ratio (95% Cl) = 1.77 (1.62, 1.94)]; TyG-WC: 850.39 [Odds ratio (95% Cl) = 1.36 (1.24, 1.49)]; TyG-WHtR: 4.97 [Odds ratio (95% Cl) = 2.39 (2.17, 2.63)]; TyG-BMI: 255.24 [Odds ratio (95% Cl) = 1.87 (1.71, 2.05)]; HOMA-IR: 2.79 [Odds ratio (95% Cl) = 1.51 (1.39, 1.65)]; VAI: 1.35 [Odds ratio (95% Cl) = 1.60 (1.47, 1.75)]; LAP: 33.46 [Odds ratio (95% Cl) = 1.20 (1.09, 1.31)], both P-values are < 0.001.

The results showed that seven lipid-related markers were positively associated with arthritis risk. Enhancing the management of glucose, lipids, and insulin sensitivity may significantly reduce the risk of arthritis.

## Linked entities

- **Diseases:** arthritis (MONDO:0005578)

## Full-text entities

- **Genes:** INS (insulin) [NCBI Gene 3630] {aka IDDM, IDDM1, IDDM2, ILPR, IRDN, MODY10}
- **Diseases:** Arthritis (MESH:D001168), degenerative disease (MESH:D019636), inflammatory (MESH:D007249), insulin resistance (MESH:D007333)
- **Chemicals:** glucose (MESH:D005947), Lipid (MESH:D008055)

## Full text

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## Figures

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## References

35 references — full list in the complete paper: https://tomesphere.com/paper/PMC12263402/full.md

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Source: https://tomesphere.com/paper/PMC12263402