Prevalence of rheumatoid arthritis in persons 60 years of age and older in the United States: Effect of different methods of case classification

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Abstract
Objective To determine prevalence estimates for rheumatoid arthritis (RA) in noninstitutionalized older adults in the US. Prevalence estimates were compared using 3 different classification methods based on current classification criteria for RA. Methods Data from the Third National Health and Nutrition Examination Survey (NHANES‐III) were used to generate prevalence estimates by 3 classification methods in persons 60 years of age and older (n = 5,302). Method 1 applied the “n of k” rule, such that subjects who met 3 of 6 of the American College of Rheumatology (ACR) 1987 criteria were classified as having RA (data from hand radiographs were not available). In method 2, the ACR classification tree algorithm was applied. For method 3, medication data were used to augment case identification via method 2. Population prevalence estimates and 95% confidence intervals (95% CIs) were determined using the 3 methods on data stratified by sex, race/ethnicity, age, and education. Results Overall prevalence estimates using the 3 classification methods were 2.03% (95% CI 1.30–2.76), 2.15% (95% CI 1.43–2.87), and 2.34% (95% CI 1.66–3.02), respectively. The prevalence of RA was generally greater in the following groups: women, Mexican Americans, respondents with less education, and respondents who were 70 years of age and older. Conclusion The prevalence of RA in persons 60 years of age and older is ∼2%, representing the proportion of the US elderly population who will most likely require medical intervention because of disease activity. Different classification methods yielded similar prevalence estimates, although detection of RA was enhanced by incorporation of data on use of prescription medications, an important consideration in large population surveys.