Background: Rheumatoid arthritis (RA) is a heterogeneous disease with unknown aetiology (1). The reported worldwide RA prevalence varies widely (2, 3), and it is unclear whether this is due to inconsistencies in defining populations or methodologies used to identify RA patients (3, 4). Accurate RA prevalence data are required to plan preventative, diagnostic, and management strategies to address raising health care service demands and costs associated with improved lifespan and level of disability (5, 6).
Objectives: To estimate the prevalence of RA from international population-based studies and investigate the influence of prevalence definition, data sources, classification criteria and geographical area on RA prevalence.
Methods: A systematic review of existing literature was performed using the Joanna Briggs Institute approach for the systematic review and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A search of ProQuest, MEDLINE, Web of Science, and EMBASE was undertaken to include population-based studies investigating RA prevalence between 1980 and 2019.
Results: Sixty published population-based studies met the inclusion criteria over the study period. The mean point-prevalence of RA was 0.56% (range 0.00% to 2.70%) between 1986 and 2014. The period-prevalence was 0.51% (range 0.05% to 1.9%) between 1955 and 2015. RA point- and period-prevalence was higher in urban settings than rural settings, (0.69% vs 0.48%) and (0.54% vs 0.25%), respectively. The mean point- and period-prevalence were 0.56% (SD=0.52) and 0.57% (SD=0.41) and were lower in sampling population studies than in larger population databases studies (0.60% (SD=0.27) and 0.44% (SD= 0.26)). The highest period-prevalence of RA was observed in linked databases (0.80%, SD=0.1) where RA diagnosis was validated by rheumatologists.
Conclusion: The average point- and period-prevalence of RA were 51/10,000 and 56/10,000 respectively. The RA prevalence was higher in urban areas than rural areas, suggesting an impact of environmental differences. Population database studies were more consistent than sampling studies, and linked databases appeared to provide the best estimate of RA period-prevalence when rheumatologists clinically verified RA.
References: Smolen JS, Aletaha D, Barton A, Burmester GR, Emery P, Firestein GS, et al. Rheumatoid arthritis. Nat Rev Dis Primers 2018;4:1-23.
Tobon GJ, Youinou P, Saraux A. The environment, geo-epidemiology, and autoimmune disease: Rheumatoid arthritis. Journal of Autoimmunity 2010;35:10-4.
Shapira Y, Agmon-Levin N, Shoenfeld Y. Geoepidemiology of autoimmune rheumatic diseases. Nature reviews Rheumatology 2010;6:468-76.
Carmona L, Cross M, Williams B, Lassere M, March L. Rheumatoid arthritis. Best Pract Res Clin Rheumatol 2010;24:733-45.
Kvien TK. Epidemiology and burden of illness of rheumatoid arthritis. Pharmacoeconomics 2004;22:1-12.
Uhlig T, Moe RH, Kvien TK. The burden of disease in rheumatoid arthritis. Pharmacoeconomics 2014;32:841-51.
Acknowledgments: Khalid Almutairi was supported by an Australian Government Research Training Program PhD Scholarship at the University of Western Australia (UWA).
We acknowledge senior librarian Samantha Blake (SB) for her help within the scope of UWA library support services for systematic reviewers.
Disclosure of Interests: Khalid Almutairi: None declared, Johannes (“Hans”) Nossent Speakers bureau: Janssen, David Preen: None declared, Helen Keen Speakers bureau: Pfizer Austrlaia, Abbvie Australia, Charles Inderjeeth Grant/research support from: UCB Australia, Speakers bureau: Eli Lilly
Statistics from Altmetric.com
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.