Background Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease of unknown etiology. Numerous studies have investigated the association between body mass index (BMI) and RA risk, but findings have been inconsistent. Objective This study aims to comprehensively evaluate the association between different BMI categories and RA risk using a meta-analytic approach. Methods We systematically searched PubMed, Embase, Web of Science, and the Cochrane Library from inception until September 2025 for observational studies investigating the association between BMI and RA onset. A random-effects model was used to calculate pooled odds ratios (ORs) and 95% confidence intervals (CIs) for the association between different BMI categories and RA risk. The robustness of the findings was evaluated through sensitivity analyses, subgroup analyses, and assessment of publication bias. Results This meta-analysis included 20 observational studies (8 cohort and 12 case-control studies) with a total sample size of 568,889. Our findings indicated no significant association between underweight and RA risk (OR: 0.84, 95% CI: 0.70–1.01, p = 0.058). In contrast, both overweight (OR: 1.13, 95% CI: 1.06–1.19, p 0.001) and obesity (OR: 1.25, 95% CI: 1.14–1.36, p 0.001) were significantly associated with an increased risk of RA, with the association being particularly pronounced in female participants. Conclusion This study demonstrates that overweight and obesity are robustly associated with a significantly increased risk of developing RA, particularly among females. In contrast, the association between underweight and RA risk remains inconclusive and warrants further investigation. Systematic review registration INPLASY (Registration Number: INPLASY2025110039).
Building similarity graph...
Analyzing shared references across papers
Loading...
Fei Cao
Xiaohong Kang
Weizhuo Wang
SHILAP Revista de lepidopterología
Frontiers in Medicine
First Affiliated Hospital of Zhengzhou University
Second Affiliated Hospital of Xi'an Jiaotong University
Pingdingshan University
Building similarity graph...
Analyzing shared references across papers
Loading...
Cao et al. (Tue,) studied this question.
www.synapsesocial.com/papers/6997f941ad1d9b11b345231d — DOI: https://doi.org/10.3389/fmed.2025.1750640