ArticleFrontiers in nutrition2024
Effect of caffeine intake on self-reported and genetic prediction of osteoarthritis: an epidemiological study and Mendelian randomization analysis.
Article in Frontiers in nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Pregabalin plus celecoxib for knee osteoarthritis: impact on pain, knee function recovery, and inflammatory biomarkers.American journal of translational research · 2026Article
- ONMR: an orthopedic and nutritional Mendelian randomization database.NPJ science of food · 2025Article
- Association between obesity indices, insulin resistance markers, and osteoarthritis in middle-aged and elderly Chinese adults.Frontiers in nutrition · 2025Article
- Association between body roundness index and risk of osteoarthritis: a cross-sectional study.Lipids in health and disease · 2024Article
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Authors and funding
7 authors.
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Abstract
Background: Osteoarthritis (OA) holds the distinction of being the most widespread musculoskeletal disorder. Any disruptions in the integrity of the articular cartilage can result in joint malfunction, discomfort, and impaired physical functioning. Increasing evidence indicates the negative impacts of caffeine intake on hyaline cartilage. The primary objective of this study was to delve deeper into understanding the potential link between the consumption of caffeine and the risk of developing OA. Methods: In this study, we constructed logistic regression models to evaluate the correlation between caffeine consumption and the risk of osteoarthritis using data from the National Health and Nutrition Examination Survey. Following that, we utilized genome-wide association studies to conduct a Mendelian randomization (MR) analysis investigating the association between coffee consumption and the likelihood of developing knee OA. We employed various statistical methods, including inverse variance weighting (IVW), weighted median, weighted mode, simple mode, and MR-Egger regression, to ensure comprehensive analysis and robust conclusions. To evaluate heterogeneity and the potential impact of pleiotropy, we conducted several statistical tests, including Cochran's Q test, MR-Egger intercept test, MR Pleiotropy RESidual Sum and Outlier test (MR-PRESSO), and MR Steiger test. Results: The weighted multivariate logistic regression analysis showed that the relationship between high caffeine intake (95-206 and ≥206 mg/day) and OA prevalence remained significantly high even after adjusting for covariates using the lowest caffeine intake (< 11 mg/day) as reference: Model 1-OR (95% Cl) = 1.365 (1.18-1.58) and 1.59 (1.38-1.83); Model 2-OR (95% Cl) = 1.21 (1.04-1.42) and 1.44 (1.23-1.68); and Model 3-OR (95% Cl) = 1.19 (1.01-1.40) and 1.30 (1.10-1.52), respectively ( Conclusion: Our study showed a positive correlation between OA prevalence and high caffeine intake (≥95 mg/day).
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