Prevalence of Doctor-Diagnosed Arthritis at State and County Levels — United States, 2014

Doctor-diagnosed arthritis is a common chronic condition that affects approximately 52.5 million (22.7%) adults in the United States and is a leading cause of disability (1,2). The prevalence of doctor-diagnosed arthritis has been well documented at the national level (1), but little has been published at the state level and the county level, where interventions are carried out and can have their greatest effect. To estimate the prevalence of doctor-diagnosed arthritis among adults at the state and county levels, CDC analyzed data from the 2014 Behavioral Risk Factor Surveillance System (BRFSS). This report summarizes the results of that analysis, which found that, for all 50 states and the District of Columbia (DC) overall, the age-standardized median prevalence of doctor-diagnosed arthritis was 24% (range = 18.8%–35.5%). The age-standardized model-predicted prevalence of doctor-diagnosed arthritis varied substantially by county, with estimates ranging from 15.8% to 38.6%. The high prevalence of arthritis in all counties, and the high frequency of arthritis-attributable limitations (1) among adults with arthritis, suggests that states and counties might benefit from expanding underused, evidence-based interventions for arthritis that can reduce arthritis symptoms and improve self-management.

BRFSS is an annual, random-digit–dialed landline and cellphone survey representative of the noninstitutionalized adult population aged ≥18 years of the 50 states, DC, and the U.S. territories.* In 2014, a total of 464,664 interviews among adults were completed, and data from 50 states, DC, Puerto Rico, and Guam are included in this report. Response rates ranged from 25.1% to 60.1%, with a median of 47.0%.^† Respondents were classified as having doctor-diagnosed arthritis if they answered “yes” to the question, “Have you ever been told by a doctor or other health professional that you have some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia?”

All analyses used sampling weights to account for the complex sample design, nonresponse, noncoverage, and cellphone-only households. Data were weighted using an iterative proportional weighting (raking) procedure.^§ For the combined sample of 50 states and DC, unadjusted and age-standardized weighted prevalences with 95% confidence intervals (CIs) for doctor-diagnosed arthritis were estimated by age group (18–44, 45–64, and ≥65 years), sex, race (non-Hispanic white, non-Hispanic black, Hispanic, American Indian/Alaska Native, Asian, Native Hawaiian/Pacific Islander, two or more races, and other non-Hispanic), and education level (less than high school, high school graduate or equivalent, more than high school). Estimates were age-standardized to the projected year 2000 U.S. standard population using three age-groups (18–44, 45–64, and ≥65 years) (3). For states and territories, unadjusted and age-standardized weighted prevalence with CIs for doctor-diagnosed arthritis were estimated, with medians and ranges based on all 50 states and DC; differences were considered statistically significant if the CIs of the age-standardized estimates did not overlap.

A multilevel regression and poststratification approach (4,5) was used to estimate model-predicted arthritis prevalence for counties in all 50 states and DC (3,142 counties). The multilevel regression model included 2014 BRFSS individual-level data on age group, sex, and race/ethnicity, and county-level poverty (percentage under 150% poverty level) from the American Community Survey 5-year estimates, and county-level and state-level random effects. Census Vintage 2014 county population estimates (http://www.census.gov/popest/data/counties/asrh/2014/index.html) were then used to generate final predicted county-level estimates of arthritis prevalence. These estimates were age-standardized to the projected 2000 U.S. standard population using 13 age groups for the population aged ≥18 years (3), and reported in quintiles based on data from all 3,142 counties in the 50 states and DC.

For the combined sample of the 50 states and DC, the prevalence of arthritis ranged from 8.8% among those aged 18–44 years to 53.3 percent among those aged ≥65 years (Table 1). Age-standardized prevalences were higher for women than men and among persons with less compared with more education. Compared with white or black non-Hispanics, those who were American Indian/Alaska Native or identifying as multiracial had higher prevalences, and Hispanics and Asians had lower prevalences of doctor-diagnosed arthritis.

The estimated age-standardized prevalences of arthritis varied among states and counties. For states and territories, doctor-diagnosed arthritis ranged from 18.8% in Hawaii to 35.5% in West Virginia (median = 24.0%) (Table 2). In 2014, 47 states, DC, and Guam had an age-standardized prevalence of doctor-diagnosed arthritis of ≥20%, and four states had an age-standardized prevalence of arthritis of ≥30% (Table 2).

At the county level (Figure), counties along the Appalachian Mountains, the Mississippi River, and the Ohio River tended to be in the highest quintiles of age-standardized model-predicted arthritis prevalence. The majority of counties in Alabama, Kentucky, Michigan, Tennessee, and West Virginia also were in the highest quintile.

Corresponding author: Kamil E. Barbour, kbarbour@cdc.gov, 770-488-5148.

¹Division of Population Health, National Center for Chronic Disease Prevention and Health Promotion, CDC.

References

1. CDC. Prevalence of doctor-diagnosed arthritis and arthritis-attributable activity limitation—United States, 2010–2012. MMWR Morb Mortal Wkly Rep 2013;62:869–73. PubMed
2. CDC. Prevalence and most common causes of disability among adults—United States, 2005. MMWR Morb Mortal Wkly Rep 2009;58:421–6. PubMed
3. Klein RJ, Schoenborn CA. Age adjustment using the 2000 projected U.S. population. Healthy people statistical notes, no. 20. Hyattsville, Maryland: US Department of Health and Human Services, CDC, National Center for Health Statistics; 2001.
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TABLE 1. Weighted prevalence of doctor-diagnosed arthritis* among adults aged ≥18 years, by selected characteristics — 2014 Behavioral Risk Factor Surveillance System, 50 states and the District of Columbia

Abbreviation: CI = confidence interval.
* Doctor-diagnosed arthritis was defined as an affirmative response to the question, “Have you ever been told by a doctor or other health professional that you have some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia?”
^† Weighted number of adults in the population with doctor-diagnosed arthritis.
^§ Doctor-diagnosed arthritis prevalence estimates were adjusted to the projected 2000 U.S. standard population.

TABLE 2. Weighted unadjusted and age-standardized prevalence of doctor-diagnosed arthritis* among adults aged ≥18 years, by state/area — Behavioral Risk Factor Surveillance System, United States,^† 2014

Abbreviation: CI = confidence interval; DC = District of Columbia.
* Doctor-diagnosed arthritis was defined as an affirmative response to the question, “Have you ever been told by a doctor or other health professional that you have some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia?”
^† Includes all 50 states, DC, Puerto Rico, and Guam.
^§ Weighted number of adults in the population with doctor-diagnosed arthritis.
^¶ Doctor-diagnosed arthritis prevalence estimates were adjusted to the projected 2000 U.S. standard population.
** For all 50 states and DC, age-standardized arthritis prevalence estimates in the lowest quartile were considered “low.” Estimates in the two middle quartiles were considered “intermediate,” and estimates in the top quartile were considered “high.”
^†† Median calculation was based on all 50 states and DC.

FIGURE. Age-standardized, model-predicted estimates of the percentage of adults with doctor-diagnosed arthritis, by county — United States, 2014

Sources: CDC. Behavioral Risk Factor Surveillance System, 2014. Census county characteristics: vintage 2014 population estimates. American Community Survey, 2010–2014.
Zhang X, Holt JB, Lu H, et al. Multilevel regression and poststratification for small-area estimation of population health outcomes: a case study of chronic obstructive pulmonary disease prevalence using the Behavioral Risk Factor Surveillance System. Am J Epidemiol 2014;179:1025–33.