ArticleMedicine2026
Association between relative fat mass and rheumatoid arthritis: A cross-sectional study.
Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Obesity has been recognized as a significant contributor to the development of rheumatoid arthritis (RA). Relative fat mass (RFM), a newly proposed anthropometric index, offers an alternative method for estimating body fat percentage. This cross-sectional study aims to elucidate the potential association between RFM and RA risk. Data were obtained from the National Health and Nutrition Examination Survey 1999 to 2018. Weighted multivariable logistic regression was used to assess the independent association between RFM and RA, and subgroup interaction analyses were performed to evaluate potential effect modification. Restricted cubic spline (RCS) models were applied to explore potential nonlinear relationships. Receiver operating characteristic (ROC) curve analysis was conducted to compare the discriminatory ability of RFM and body mass index (BMI). This cross-sectional study demonstrates a positive association between RFM and RA. Although RFM offers some improvement over BMI as an obesity-related indicator, its clinical utility for identifying RA risk remains limited. A total of 43,499 participants were included in the analysis, among whom 2557 had RA. Weighted multivariable logistic regression revealed a significant positive association between RFM and RA (odds ratio = 1.048; 95% confidence interval: 1.036-1.060). This association remained consistent when RFM was analyzed in quartiles, with individuals in the highest quartile showing a significantly higher risk of RA compared to the lowest quartile (odds ratio = 2.487; 95% confidence interval: 1.875-3.299). Subgroup interaction analyses revealed that this association was modified by age, educational level and smoking status. RCS analysis demonstrated a linear relationship between RFM and RA. RFM showed slightly better discrimination than BMI in ROC analysis, but the overall discriminatory performance remained modest (area under the curve = 0.614 vs 0.581).
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.