Background/Purpose: Current national estimates of arthritis prevalence in the United States rely on a single survey question about doctor-diagnosed arthritis from the National Health Interview Survey (NHIS) without using survey information on joint symptoms. In a validation study of these NHIS questions, some persons with only joint symptoms were found to have arthritis when examined by trained rheumatology nurses who excluded those with asymptomatic findings. The validation study suggested that the current surveillance definition of doctor-diagnosed arthritis had only 53% sensitivity among adults between 45-64 years of age resulting in missing nearly half of arthritis cases in that age group. The substantial misclassification as a result of the current imperfect surveillance definition would result in a marked underestimation of prevalence. We aimed to estimate arthritis prevalence, using the term ‘true’ to represent estimates that are adjusted for the imperfect sensitivity and specificity of the current surveillance definition, and the term ‘apparent’ to represent ordinary proportion estimates which fail to so adjust.

Methods: Using the 2015 NHIS, we developed a Bayesian multinomial latent class model for arthritis surveillance criteria based on NHIS questions on joint symptoms and whether symptom duration exceeded three months in addition to a question about doctor-diagnosed arthritis. The NHIS questions explicitly ask subjects to exclude back and neck pain from the reports of joint pain or arthritis. Our Bayesian approach accounted for the imperfect (i.e. <100%) sensitivity and specificity of each criterion in addition to accounting for the correlation between chronic joint symptoms and doctor-diagnosed arthritis in the survey.

Results: Of 33,672 participants in the 2015 NHIS, 19.3% (2,242/11,597) of men and 16.7% (2,294/13,697) of women between 18-64 years of age reported joint symptoms without doctor-diagnosed arthritis; estimates were 15.7% (545/3,474) and 13.5% (660/4,904), respectively, for those ≥65 years old. Bayesian posterior estimates and the corresponding 95% probability intervals (PI) for the ‘true’ prevalences in the 4 sub-populations stratified by age and sex are presented in the Table. Based on our estimates of ‘true’ prevalence, arthritis affected 91.2 (of 247.7; 36.8%) million adults in the US in 2015, which included 61.1 (of 199.9; 30.6%) million persons between 18-64 years of age. Our estimate for arthritis prevalence in 2015 is 68% higher than that previously reported based on the doctor-diagnosed arthritis question of 54.4 (22.7%) million adults.

Conclusion: Arthritis prevalence in the US population has been substantially underestimated, especially among adults <65. Our results may partially explain recent surge in arthritis-related healthcare utilizations such as total knee replacement, especially among younger adults.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/novel-approach-to-arthritis-surveillance-suggests-a-much-higher-prevalence-of-arthritis-among-us-adults-than-previous-estimate/