ArticleFrontiers in nutrition2025
Association between obesity indices, insulin resistance markers, and osteoarthritis in middle-aged and elderly Chinese adults.
Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Endocrine‑metabolic imbalance drives osteoarthritis: From whole‑joint pathobiology to precision therapy (Review).International journal of molecular medicine · 2026Review
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7 authors.
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Abstract
Background: Previous studies have indicated an association between osteoarthritis (OA), obesity, and insulin resistance (IR). However, current literature lacks sufficient clinical data to fully elucidate the relationship between obesity indices, insulin resistance surrogates (IR surrogates), and OA in China's middle-aged and elderly population. This study aims to investigate the correlation between obesity indices [body fat percentage (BFP), lipid accumulation product (LAP), body mass index (BMI), waist-to-height ratio (WHtR)], IR surrogates [triglyceride-glucose (TyG) index and its derivatives: TyG with waist circumference (TyG-WC), TyG-BMI, TyG-WHtR, and OA risk, and evaluate the diagnostic efficacy of these indices for OA. Methods: This study utilized data from the China Health and Retirement Longitudinal Study (CHARLS). Multivariable logistic regression and Cox proportional hazards models were employed, alongside Receiver Operating Characteristic (ROC) curves, restricted cubic splines, and subgroup analyses, to assess the associations between obesity indicators, IR surrogates, and the risk of OA in middle-aged and older adults. Results: A multivariable logistic regression analysis was conducted using data from 10,457 participants, of whom 3,667 were diagnosed with OA. In fully adjusted models, all indices as continuous variables were positively associated with OA risk (all Conclusion: Obesity-related indicators and IR surrogates are significantly associated with OA risk. Among these, TyG-WHtR demonstrates the strongest predictive performance, suggesting its potential as an early screening tool for OA. This study highlights obesity and IR as modifiable risk factors, providing a basis for the early prevention and control of OA.
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