BACKGROUND Previous epidemiologic studies of autoimmune diseases in the US have included a limited number of diseases or used metaanalyses that rely on different data collection methods and analyses for each disease.METHODS To estimate the prevalence of autoimmune diseases in the US, we used electronic health record data from 6 large medical systems in the US. We developed a software program using common methodology to compute the estimated prevalence of autoimmune diseases alone and in aggregate that can be readily used by other investigators to replicate or modify the analysis over time.RESULTS Our findings indicate that over 15 million people, or 4.6% of the US population, have been diagnosed with at least 1 autoimmune disease from January 1, 2011, to June 1, 2022, and 34% of those are diagnosed with more than 1 autoimmune disease. As expected, females (63% of those with autoimmune disease) were almost twice as likely as males to be diagnosed with an autoimmune disease. We identified the top 20 autoimmune diseases based on prevalence and according to sex and age.CONCLUSION Here, we provide, for what we believe to be the first time, a large-scale prevalence estimate of autoimmune disease in the US by sex and age.FUNDING Autoimmune Registry Inc., the National Heart Lung and Blood Institute, the National Center for Advancing Translational Sciences, the Intramural Research Program of the National Institute of Environmental Health Sciences.
Aaron H. Abend, Ingrid He, Neil Bahroos, Stratos Christianakis, Ashley B. Crew, Leanna M. Wise, Gloria P. Lipori, Xing He, Shawn N. Murphy, Christopher D. Herrick, Jagannadha Avasarala, Mark G. Weiner, Jacob S. Zelko, Erica Matute-Arcos, Mark Abajian, Philip R.O. Payne, Albert M. Lai, Heath A. Davis, Asher A. Hoberg, Chris E. Ortman, Amit D. Gode, Bradley W. Taylor, Kristen I. Osinski, Damian N. Di Florio, Noel R. Rose, Frederick W. Miller, George C. Tsokos, DeLisa Fairweather
Usage data is cumulative from December 2024 through March 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 7,032 | 0 |
1,444 | 0 | |
Figure | 68 | 0 |
Table | 317 | 0 |
Supplemental data | 587 | 0 |
Citation downloads | 126 | 0 |
Totals | 9,574 | 0 |
Total Views | 9,574 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.