Background & Introduction: Arthritis is a highly prevalent condition in the U.S. and a leading cause of disability. The economic burden of arthritis is estimated to be at least $128 billion annually in the U.S. Effective Surveillance of Arthritis on a national scale is challenging and requires a screening strategy that goes beyond recognizing symptoms reported in a clinical setting.
National estimates of arthritis prevalence rely on a single survey question about doctor-diagnosed arthritis without using survey information on joint symptoms, even though some subjects with only the latter have been shown to have arthritis. The sensitivity of the current surveillance definition is only 53% and 69% in subjects aged 45–64 years and 65 years old or older, respectively, resulting in misclassification of nearly one-half and one-third of subjects in those age groups.
In 2015, estimates indicated that 54.4 million adults (22.7%) in the U.S. had doctor-diagnosed arthritis.
Strategies exist to increase the accuracy of surveillance criteria, and this study was undertaken to estimate arthritis prevalence based on an expansive surveillance definition that is adjusted for the measurement errors in the current definition.
Methods: Using the 2015 National Health Interview Survey, these researchers developed a Bayesian multinomial latent class model for arthritis surveillance based on doctor-diagnosed arthritis, joint symptoms and whether symptom duration exceeded three months.
Results: Of 33,672 participants, 19.3% of men and 16.7% of women ages 18–64 years and 15.7% of men and 13.5% of women ages 65 years old and older affirmed joint symptoms without doctor-diagnosed arthritis. The measurement error–adjusted prevalence of arthritis was 29.9% (95% Bayesian probability interval [95% PI] 23.4–42.3) in men aged 18–64 years, 31.2% (95% PI 25.8–44.1) in women aged 18–64 years, 55.8% (95% PI 49.9–70.4) in men ages aged 65 years old and older, and 68.7% (95% PI 62.1–79.9) in women aged 65 years old and older. Arthritis affected 91.2 million adults (of 247.7 million; 36.8%) in the U.S. in 2015, which included 61.1 million people between 18 and 64 years old (of 199.9 million; 30.6%). The new arthritis prevalence estimate was 68% higher than the previously reported national estimate.
Conclusion: Arthritis prevalence in the U.S. population has been substantially underestimated, especially among adults younger than 65. Arthritis has enormous economic and public health implications. Direct healthcare costs and long-term indirect costs resulting from loss of productivity and disability attributable to arthritis need be revised to account for the corrected prevalence of arthritis affecting individuals at younger ages than previously perceived.