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Purpose <p>This study utilized NHANES data from 1999 to 2010 to examine the association between the red cell distribution width to albumin (RAR) ratio and rheumatoid arthritis (RA), and also examined whether obesity plays a moderating role in this relationship.</p> Patients and methods <p>We analyzed 27,418 NHANES participants, calculating RAR as red cell distribution width (%) divided by albumin concentration (g/dL). RA diagnoses were based on questionnaire data. Weighted multivariate logistic regression and subgroup analyses were conducted to assess the log2-RAR–RA association, and smoothing curve fitting was used to examine nonlinear relationships. Finally, we conducted subgroup analyses and interaction tests to explore factors that may influence the association between RAR and RA.</p> Results <p>RA was diagnosed in 5.72% of the population. Higher log2-RAR levels were significantly associated with increased RA prevalence (OR = 2.14; 95% CI 1.59–2.89). A nonlinear relationship was observed, with stronger associations at log2-RAR levels below 1.66. Furthermore, interaction analyses indicated that obesity significantly modified the association between log2-RAR and RA.</p> Conclusion <p>In summary, the relationship between log2-RAR and RA is nonlinear, and obesity may alter the strength of the association between log2-RAR and RA.</p>

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Association between erythrocyte distribution width and albumin ratio and rheumatoid arthritis: analyses of NHANES 1999–2010

  • 期刊论文

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  • 发表日期：

    2026年3月18日

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  • Yang Liu,
  • Dongli Huang,
  • Yanhua Huang

摘要

Purpose

This study utilized NHANES data from 1999 to 2010 to examine the association between the red cell distribution width to albumin (RAR) ratio and rheumatoid arthritis (RA), and also examined whether obesity plays a moderating role in this relationship.

Patients and methods

We analyzed 27,418 NHANES participants, calculating RAR as red cell distribution width (%) divided by albumin concentration (g/dL). RA diagnoses were based on questionnaire data. Weighted multivariate logistic regression and subgroup analyses were conducted to assess the log2-RAR–RA association, and smoothing curve fitting was used to examine nonlinear relationships. Finally, we conducted subgroup analyses and interaction tests to explore factors that may influence the association between RAR and RA.

Results

RA was diagnosed in 5.72% of the population. Higher log2-RAR levels were significantly associated with increased RA prevalence (OR = 2.14; 95% CI 1.59–2.89). A nonlinear relationship was observed, with stronger associations at log2-RAR levels below 1.66. Furthermore, interaction analyses indicated that obesity significantly modified the association between log2-RAR and RA.

Conclusion

In summary, the relationship between log2-RAR and RA is nonlinear, and obesity may alter the strength of the association between log2-RAR and RA.