Objective: To identify differences in multimorbidity and individual comorbidities among individuals with rheumatoid arthritis (RA), separated by race and ethnicity. Methods: This case–control study within OptumLabs Data Warehouse from 2010 to 2019 matched RA cases (defined by 2 codes plus prescription of an RA drug) to non-RA controls 1:1 on age, sex, race and ethnicity, region, index date of RA, and insurance coverage duration. We defined multimorbidity as the presence of ≥2 or ≥5 validated comorbidities. Logistic regression models calculated adjusted odds of multimorbidity with 95% confidence intervals (95% CIs) within each race and ethnicity. Results: We identified 154,391 RA cases and 154,391 controls (mean age 59.6, 76% female). Black enrollees had the most multimorbidity ≥2/≥5 (73.1%, 34.3%); Asian enrollees had the least (52.4%, 17.3%). Adjusted odds of multimorbidity ≥2 and ≥5 in RA cases versus controls was 2.19 (95% CI 2.16–2.23) and 2.06 (95% CI 2.02–2.09), respectively. This increase was similar across race and ethnicity. However, we observed elevated occurrence of certain comorbidities by race and ethnicity versus controls (P < 0.001), including renal disease in White enrollees (4.7% versus 3.2%) and valvular heart disease in Black and White enrollees (3.2% and 2.8% versus 2.6% and 2.2%). Conclusion: Multimorbidity is a problem for all RA patients. Targeted identification of certain comorbidities by race and ethnicity may be a helpful approach to mitigate multimorbidity.
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