Introduction: To characterise the detailed phenotypic and comorbid characteristics of participants with rheumatoid arthritis (RA) in the large population-based UK Biobank, thereby enabling future longitudinal analyses.
Methods: We undertook a cross-sectional study using baseline data from the unique UK Biobank resource (n=502 649). RA was based on self-report, and type of medication was used as a proxy measure of valid diagnosis. Participants with and without RA were compared in terms of sociodemographic, lifestyle and other disease-related risk factors. Logistic regression models were used to determine whether participants with RA were more likely to report comorbid conditions, and whether this varied by RA severity. The models were adjusted for potential confounders and lifestyle risk factors.
Results: At baseline, 5657 (1.13%) eligible UK Biobank participants reported RA of whom 2849 (0.57%) had medically treated RA (median duration=10 years). Prevalence was significantly higher among female, South Asian and socioeconomically deprived participants. Participants with RA were significantly more likely to report diabetes (covariate-adjusted OR 1.18, 95% CI 1.06 to 1.32, p<0.01), hypertension (OR 1.19, 95% CI 1.21 to 1.27, p<0.001) and cardiovascular disease (OR 1.52, 95% CI 1.39 to 1.67, p<0.001).
Conclusions: UK Biobank provides extensive data concerning RA population-level comorbidity and risk factors. The frequency, distribution and characteristics of participants reporting RA in UK Biobank are largely consistent with other studies. It provides a unique opportunity to interrogate biomarkers, genetic data, detailed imaging and linkage to clinical records at the population level across primary and secondary care.
Keywords: DMARDs (biologic); DMARDs (synthetic); Epidemiology; Rheumatoid Arthritis.