Arthritis Care & Research
`Vol. 65, No. 5, May 2013, pp 703–711
`DOI 10.1002/acr.21898
`© 2013, American College of Rheumatology
`ORIGINAL ARTICLE
`
`Lifetime Risk and Age at Diagnosis of
`Symptomatic Knee Osteoarthritis in the US
`ELENA LOSINA,1 ALEXANDER M. WEINSTEIN,2 WILLIAM M. REICHMANN,3 SARA A. BURBINE,2
`DANIEL H. SOLOMON,4 MEGHAN E. DAIGLE,2 BENJAMIN N. ROME,2 STEPHANIE P. CHEN,2
`DAVID J. HUNTER,5 LISA G. SUTER,6 JOANNE M. JORDAN,7 AND JEFFREY N. KATZ4
`
`Objective. To estimate the incidence and lifetime risk of diagnosed symptomatic knee osteoarthritis (OA) and the age at
`diagnosis of knee OA based on self-reports in the US population.
`Methods. We estimated the incidence of diagnosed symptomatic knee OA in the US by combining data on age-, sex-, and
`obesity-specific prevalence from the 2007–2008 National Health Interview Survey, with disease duration estimates
`derived from the Osteoarthritis Policy (OAPol) Model, a validated computer simulation model of knee OA. We used the
`OAPol Model to estimate the mean and median ages at diagnosis and lifetime risk.
`Results. The estimated incidence of diagnosed symptomatic knee OA was highest among adults ages 55– 64 years, ranging
`from 0.37% per year for nonobese men to 1.02% per year for obese women. The estimated median age at knee OA
`diagnosis was 55 years. The estimated lifetime risk was 13.83%, ranging from 9.60% for nonobese men to 23.87% in obese
`women. Approximately 9.29% of the US population is diagnosed with symptomatic knee OA by age 60 years.
`Conclusion. The diagnosis of symptomatic knee OA occurs relatively early in life, suggesting that prevention programs
`should be offered relatively early in the life course. Further research is needed to understand the future burden of health
`care utilization resulting from earlier diagnosis of knee OA.
`
`INTRODUCTION
`Knee osteoarthritis (OA) is a painful, disabling condi-
`tion that affects an estimated 9.3 million US adults (1).
`Because no disease-modifying treatments are available,
`treatments for symptomatic knee OA focus on symptom
`relief and functional restoration, including physical ther-
`apy, medications, joint injections, and total knee replace-
`ment (TKR) (2–5).
`For decades, knee OA had been viewed as a disease
`
`Supported by the NIH/National Institute of Arthritis and
`Musculoskeletal and Skin Diseases (grants R01-AR053112,
`K24-AR057827, K23-AR054095, P60-AR47782, and T32-
`AR-055885). Dr. Suter’s work was supported by the VA
`Connecticut Healthcare System and the Centers for Medi-
`care and Medicaid Services, an agency of the US Depart-
`ment of Health and Human Services (grant HHSM-500-
`2008-0025I/HHSM-500-T0001).
`1Elena Losina, PhD: Brigham and Women’s Hospital,
`Harvard University, and Boston University School of Public
`Health, Boston, Massachusetts; 2Alexander M. Weinstein,
`BA, Sara A. Burbine, BA, Meghan E. Daigle, BS, Benjamin N.
`Rome, BA, Stephanie P. Chen, BS: Brigham and Women’s
`Hospital, Boston, Massachusetts; 3William M. Reichmann,
`PhD: Brigham and Women’s Hospital and Boston University
`School of Public Health, Boston, Massachusetts; 4Daniel H.
`Solomon, MD, MPH, Jeffrey N. Katz, MD, MSc: Brigham and
`Women’s Hospital and Harvard University, Boston, Massa-
`chusetts; 5David J. Hunter, MBBS, PhD: University of Syd-
`
`mostly affecting older persons. However, recent evidence
`documents increased incidence of 2 key risk factors for
`knee OA, i.e., traumatic knee injury (6) and obesity (7,8),
`particularly in younger persons (9,10). Evolving data point
`to a high prevalence of posttraumatic knee OA in younger
`persons (11–13). This trend and the increasing prevalence
`of obesity among children are likely to lead to increased
`rates of OA in young adults (14).
`Most population-based data on knee OA prevalence and
`incidence refer to studies conducted in the mid-1990s
`(15–17). In fact, the 2 most recent studies reporting the
`incidence of symptomatic knee OA in the US were pub-
`
`ney and Royal North Shore Hospital, Sydney, New South
`Wales, Australia; 6Lisa G. Suter, MD: Yale University
`School of Medicine and Yale-New Haven Hospital, New
`Haven, and Veterans Affairs Medical Center, West Haven,
`Connecticut; 7Joanne M. Jordan, MD, MPH: Thurston Ar-
`thritis Research Center, University of North Carolina,
`Chapel Hill.
`Dr. Losina has received fees from her role as Deputy
`Editor of The Journal of Bone and Joint Surgery.
`Address correspondence to Elena Losina, PhD, Depart-
`ment of Orthopedic Surgery, Orthopaedic and Arthritis
`Center for Outcomes Research, Brigham and Women’s Hos-
`pital, 75 Francis Street BC-4-016, Boston, MA 02115. E-mail:
`elosina@partners.org.
`Submitted for publication April 17, 2012; accepted in
`revised form October 23, 2012.
`
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`Losina et al
`
`Significance & Innovations
`● We provide estimates of the incidence of diag-
`nosed symptomatic knee osteoarthritis (OA) in the
`US using self-reported population-based national
`data from 2007–2008.
`● The estimated mean age at diagnosis of symptom-
`atic knee OA was 53.5 years and the estimated
`median age at diagnosis was 55 years.
`● With half of the cases of symptomatic knee OA
`diagnosed by age 55 years, the burden of future
`health care utilization for knee OA may be high.
`
`lished 18 years ago in 1995 (15,16). Furthermore, although
`obesity is a known risk factor, no studies have reported
`age- and sex-specific knee OA incidence separately for
`obese and nonobese persons. Determining the age at diag-
`nosis of symptomatic knee OA is critical to understanding
`the trajectory of decrements in quality of life and utiliza-
`tion of health services.
`We sought to use national self-reported data to derive
`current age-, sex-, and obesity-stratified estimates of the
`incidence of diagnosed symptomatic knee OA, to estimate
`the mean and median ages at diagnosis, and to estimate the
`lifetime risk of diagnosis among 25-year-olds representa-
`tive of the US population.
`
`MATERIALS AND METHODS
`
`Analytical overview. The incidence of diagnosed symp-
`tomatic knee OA was derived as a ratio of disease preva-
`lence odds to disease duration (18) (see Technical Appen-
`dix, section 2, for a more detailed explanation of incidence
`calculations, available in the online version of this article
`at http://onlinelibrary.wiley.com/doi/10.1002/acr.21898/
`abstract). We used self-reported data from the 2007–2008
`National Health Interview Survey (NHIS) to estimate the
`prevalence of diagnosed symptomatic knee OA (19). Dis-
`ease duration was derived using the Osteoarthritis Policy
`(OAPol) Model, a published and validated computer sim-
`ulation model of knee OA natural history and management
`(20,21). Incidence was estimated within 10-year age groups
`and was further stratified by sex and obesity status. We
`then used the OAPol Model and our newly derived inci-
`dence estimates to determine the mean and median ages at
`diagnosis of symptomatic knee OA in the US. To model
`disease duration, cohorts were initialized with knee OA,
`and the output of interest was life expectancy. To model
`the age at diagnosis, cohorts were initialized without knee
`OA, and the output of interest was the development of OA,
`or cumulative incidence of OA.
`
`OAPol Model. The OAPol Model is a validated, state
`transition Monte Carlo computer simulation model of the
`natural history of knee OA (20,21). “State transition” im-
`plies that the natural history and clinical management of
`knee OA are characterized as a series of annual transitions
`
`between health states. The health states are characterized
`by age, sex, obesity, comorbidities, and knee OA disease
`severity among those who develop the condition. The
`model uses a set of transition probabilities to determine
`each individual’s sequence of annual transitions among
`different health states, which may include diagnosis of
`symptomatic knee OA. Every subject without knee OA is
`considered to be at risk for knee OA. The risk is governed
`by age, sex, and obesity (defined by body mass index [BMI]
`ⱖ30 kg/m2).
`the
`In addition to capturing the risk of knee OA,
`model tracks chronic comorbidities that increase mortality
`either directly (coronary heart disease, cancers, and obe-
`sity) and/or by increasing the risk of other chronic diseases
`(diabetes mellitus and obesity). Each simulated person is
`followed by the model until death. Death can occur from
`any health state. All-cause mortality rates were obtained
`from Centers for Disease Control and Prevention life tables
`(19,22–24). Rates specifically attributable to chronic co-
`morbidities (coronary heart disease, cancer, and obesity)
`were then removed from the mortality of the life tables
`to estimate the mortality rates for healthy individuals for
`all age and sex strata. The mortality rates attributable to
`specific comorbidities were then separately applied to per-
`sons with the corresponding comorbidities. Further details
`of the OAPol Model structure have been published else-
`where (20,21), and can also be found in Technical Appen-
`dix, section 1 (available in the online version of this article
`at http://onlinelibrary.wiley.com/doi/10.1002/acr.21898/
`abstract).
`
`Estimating current prevalence of diagnosed symptom-
`atic knee OA. We used self-reported data from the 2007–
`2008 NHIS to estimate the prevalence of diagnosed symp-
`tomatic knee OA (19). The NHIS is a cross-sectional survey
`that is representative of the civilian noninstitutionalized
`population residing in the US. The adult sample, which
`was the basis of our analysis, was comprised of persons
`ages ⱖ18 years. For the purposes of our analysis, we in-
`cluded persons that were ages ⱖ25 years.
`Survey participants were considered to have prevalent
`knee OA if they: 1) answered “yes” to the questions “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?” and “During the past 30 days,
`have you had any symptoms of pain, aching, or stiffness in
`or around a joint?”; 2) specified the knee as an affected
`joint; and 3) did not report having rheumatoid arthritis,
`lupus, fibromyalgia, or gout. We then used a logistic regres-
`sion model that accounted for the complex survey design to
`derive age-, sex-, and obesity-stratified population-based
`prevalence estimates of the prevalence of self-reported
`diagnosed symptomatic knee OA. The regression model,
`built using SAS, version 9.2, included age, age2, age3, and
`age4 and the interaction between obesity and sex.
`Similar algorithms for classifying survey respondents as
`having symptomatic knee OA have shown specificity
`greater than 90% (25,26), which indicates that these algo-
`rithms perform well in terms of classifying patients with-
`out symptomatic knee OA. Since self-reported data may
`
`

`

`Incidence and Lifetime Risk of Diagnosed Symptomatic Knee OA
`
`705
`
`Table 1. Baseline demographic and clinical characteristics of US adults ages 25 years*
`
`Female
`
`Prevalence,
`%†
`
`Incidence,
`%†
`
`RR of
`mortality‡
`
`Source
`
`Male
`
`25.0
`
`63.7
`20.9
`15.4
`
`25.0
`
`65.0
`18.8
`16.1
`
`25.0 ⫾ 0.5
`34.5 ⫾ 1.5
`
`25.0 ⫾ 0.5
`34.5 ⫾ 1.5
`
`26.7 ⫾ 6.1
`27.6 ⫾ 6.0
`27.7 ⫾ 6.2
`
`26.8 ⫾ 7.7
`28.0 ⫾ 6.7
`30.2 ⫾ 8.8
`
`0.0–5.7
`0.0–0.3
`1.5–7.0
`
`0.0–6.4
`0.0–4.4
`0.0–5.1
`
`1.0–30.0
`1.0–36.6
`1.0§
`
`Initial age, years
`Race/ethnicity (all cohorts), %
`
`White, non-Hispanic
`Hispanic
`Black, non-Hispanic
`BMI, mean ⫾ SD kg/m2
`Nonobese (maximum 29.9)
`Obese (minimum 30.0)
`Overall US population
`White, non-Hispanic
`Hispanic
`Black, non-Hispanic
`Comorbid condition
`Cancer
`Coronary heart disease
`Diabetes mellitus
`
`2009 US Census population
`estimates (30)
`
`NHANES 2005–2008 (28,29)
`
`NHANES 2005–2008 (28,29)
`
`* RR ⫽ relative risk; BMI ⫽ body mass index; NHANES ⫽ National Health and Nutrition Examination Survey.
`† Prevalence of comorbid conditions is stratified by sex, race/ethnicity, and obesity status. Incidence and RRs of mortality for comorbid conditions are
`stratified by age, sex, race/ethnicity, and obesity status. The ranges of values across these stratifications are shown.
`‡ Prevalence of comorbid conditions is stratified by sex, race/ethnicity, and obesity status. Incidence and RRs of mortality for comorbid conditions are
`stratified by age, sex, race/ethnicity, and obesity status. The ranges of values across these stratifications are shown. For individuals with ⬎1 of the
`comorbid conditions listed here, the model assigns only the maximum of the RRs of mortality associated with those separate conditions (i.e., RRs are
`not cumulative; an individual with an RR of 1.5 for mortality due to coronary heart disease and an RR of 3.5 for mortality due to cancer will experience
`an RR of 3.5 for mortality). The RRs of mortality due to obesity ranged from 1.0 –2.5.
`§ Although diabetes mellitus does not directly increase the risk of mortality in the model, individuals with diabetes mellitus are at increased risk for
`developing coronary heart disease, which can increase the risk of mortality.
`
`likely overstate the true prevalence of diagnosed symp-
`tomatic knee OA, we used published data on the positive
`predictive value (PPV) of self-reported diagnosed symp-
`tomatic knee OA to reduce the prevalence estimates and
`the corresponding 95% confidence intervals (95% CIs).
`Specifically, we assumed that the PPV was lower for those
`ages ⬍60 years (PPV 66.0%) (27) compared with those ages
`ⱖ60 years (PPV 80.7%) (26). For instance, for a nonobese
`man age 44 years with self-reported prevalence of symp-
`tomatic knee OA at 0.0374, the PPV-adjusted prevalence
`was estimated at 0.0247, or 66.0% of the self-reported
`prevalence. On the other hand, for an obese woman age 64
`years, the predicted prevalence would be 80.7% of the
`self-reported prevalence of 0.2864, or 0.2311. These re-
`duced prevalence data and 95% CIs were used as bench-
`marks for the calibration of OA incidence.
`
`Estimating incidence of diagnosed symptomatic knee
`OA. We estimated the incidence rates of diagnosed symp-
`tomatic knee OA as a ratio of the 2007–2008 NHIS, PPV-
`adjusted prevalence estimates to disease duration (18).
`Because there is no permanent cure for knee OA, to derive
`disease duration we used the OAPol Model to simulate
`life expectancy within each decade of age, further strati-
`fied by sex and obesity (for details, see Technical Appen-
`dix, section 3, available in the online version of this article
`at http://onlinelibrary.wiley.com/doi/10.1002/acr.21898/
`abstract). Incidence rates within 10-year age groups be-
`tween 25 and 85 years were then estimated by dividing
`PPV-adjusted prevalence rates by model-derived disease
`durations.
`
`Disease duration was calculated as an average 10-year
`survival of persons affected by OA, diagnosed within each
`year of the decade, assuming constant rates of diagnosis in
`every year of a given decade. The analysis was conducted
`for the cohort with race/sex and obesity distributions of
`persons affected by knee OA in the US as well as sepa-
`rately for each age/sex/race and obesity cohort with knee
`OA.
`The calculated incidence estimates were calibrated to
`generate model-based prevalences that fell within the 95%
`CIs of the prevalence estimates derived from the 2007–
`2008 NHIS (for details, see Technical Appendix, section 4,
`available in the online version of this article at http://
`onlinelibrary.wiley.com/doi/10.1002/acr.21898/abstract).
`The 95% CIs for incidence estimates were calculated em-
`pirically based on model results. Using a normal approx-
`imation of the Poisson distribution, empirical incidence
`rates were calculated as the number of new cases of diag-
`nosed knee OA from model output divided by the time “at
`risk.” Time at risk was defined as the sum of years alive
`without knee OA within each decade.
`
`Estimating lifetime risk of diagnosed symptomatic knee
`OA and average age at diagnosis. Using the OAPol Model
`and our calculated incidence rates, we estimated the life-
`time risk of diagnosed symptomatic knee OA from age 25
`years, defined as the cumulative probability of being diag-
`nosed with symptomatic knee OA over the lifetime for US
`adults in each of the 5 cohorts described below. The life-
`time risk was calculated by dividing the cumulative num-
`ber of incident cases of diagnosed symptomatic knee OA
`
`

`

`706
`
`Losina et al
`
`Table 2. Estimated prevalence and incidence of diagnosed symptomatic knee
`osteoarthritis by age, sex, and obesity status*
`
`Estimated prevalence
`(using 2007–2008 NHIS data),
`% (95% CI)
`
`Estimated incidence
`(annual),
`% (95% CI)
`
`Nonobese
`Men
`Age 25–34 years
`Age 35–44 years
`Age 45–54 years
`Age 55–64 years
`Age 65–74 years
`Age 75–84 years
`Age ⱖ85 years
`Women
`Age 25–34 years
`Age 35–44 years
`Age 45–54 years
`Age 55–64 years
`Age 65–74 years
`Age 75–84 years
`Age ⱖ85 years
`Obese
`Men
`Age 25–34 years
`Age 35–44 years
`Age 45–54 years
`Age 55–64 years
`Age 65–74 years
`Age 75–84 years
`Age ⱖ85 years
`Women
`Age 25–34 years
`Age 35–44 years
`Age 45–54 years
`Age 55–64 years
`Age 65–74 years
`Age 75–84 years
`Age ⱖ85 years
`
`0.74 (0.61–0.89)
`1.74 (1.51–2.00)
`3.61 (3.21–4.06)
`6.70 (6.09–7.37)
`9.83 (9.01–10.71)
`11.64 (10.51–12.88)
`12.94 (10.86–15.34)
`
`0.88 (0.73–1.05)
`2.06 (1.83–2.31)
`4.26 (3.90–4.64)
`7.85 (7.22–8.52)
`11.44 (10.48–12.47)
`13.50 (12.44–14.65)
`14.97 (13.04–17.12)
`
`1.54 (1.26–1.87)
`3.58 (3.12–4.11)
`7.25 (6.49–8.09)
`13.00 (11.76–14.33)
`18.48 (16.71–20.39)
`21.48 (19.33–23.78)
`23.54 (20.24–27.19)
`
`2.41 (2.02–2.88)
`5.53 (4.93–6.21)
`10.93 (10.01–11.92)
`18.94 (17.52–20.44)
`26.20 (24.25–28.23)
`29.94 (27.73–32.23)
`32.45 (28.79–36.31)
`
`0.12 (0.12–0.12)
`0.13 (0.12–0.13)
`0.22 (0.22–0.22)
`0.37 (0.37–0.38)
`0.20 (0.19–0.20)
`0.13 (0.12–0.13)
`0.04 (0.04–0.04)
`
`0.14 (0.14–0.14)
`0.15 (0.14–0.15)
`0.27 (0.27–0.27)
`0.43 (0.43–0.43)
`0.27 (0.27–0.27)
`0.16 (0.16–0.16)
`0.06 (0.06–0.06)
`
`0.25 (0.24–0.25)
`0.24 (0.24–0.24)
`0.44 (0.43–0.44)
`0.64 (0.64–0.65)
`0.32 (0.32–0.33)
`0.17 (0.17–0.18)
`0.05 (0.05–0.05)
`
`0.37 (0.37–0.38)
`0.40 (0.39–0.40)
`0.57 (0.57–0.58)
`1.02 (1.01–1.02)
`0.41 (0.40–0.41)
`0.28 (0.27–0.28)
`0.10 (0.10–0.10)
`
`* NHIS ⫽ National Health Interview Survey; 95% CI ⫽ 95% confidence interval.
`
`within each cohort predicted by the OAPol Model by the
`size of the initial population at risk for the disease reported
`by US Census data. We used the OAPol Model to estimate
`the mean and median ages at symptomatic knee OA diag-
`nosis using the derived incidence rates. Mean age was
`obtained by constructing a distribution by age of all inci-
`dent cases at diagnosed symptomatic knee OA based on
`the OAPol Model and calculating a mean of this distribu-
`tion (for details, see Technical Appendix, section 5, avail-
`able in the online version of this article at http://online
`library.wiley.com/doi/10.1002/acr.21898/abstract). Median
`age represented the age at which 50% of those ultimately
`diagnosed with symptomatic knee OA had been diagnosed
`(i.e., the 50% mark of the cumulative distribution function
`of incident cases). Mean age is reported to one-tenth of a
`year; median age is reported as an integer.
`
`Populations under consideration. Using the OAPol
`Model, we simulated 5 cohorts that were followed from
`age 25 years until death: 1) nonobese women, 2) obese
`
`women, 3) nonobese men, 4) obese men, and 5) the general
`US population. For nonobese cohorts, the mean ⫾ SD BMI
`at age 25 years was 25.0 ⫾ 0.5 kg/m2. For obese cohorts,
`the mean ⫾ SD BMI was 34.5 ⫾ 1.5 kg/m2. For the general
`US population, BMI distributions, stratified by sex and
`race/ethnicity, were derived from the 2005–2008 National
`Health and Nutrition Examination Survey (NHANES) and
`ranged from a mean ⫾ SD BMI of 26.7 ⫾ 6.1 kg/m2 for
`white, non-Hispanic men ages 25 years to a mean ⫾ SD
`BMI of 30.2 ⫾ 8.8 kg/m2 for black, non-Hispanic women
`ages 25 years (28,29) (Table 1). The distributions of sex and
`race/ethnicity within each cohort were derived from 2009
`US Census data (30). Prevalence rates of comorbid condi-
`tions, including cancer, coronary heart disease, and diabe-
`tes mellitus, were stratified by age, sex, and race/ethnicity
`and were derived from the 2005–2008 NHANES (28,29)
`(Table 1). Incidence rates for comorbidities were calcu-
`lated as the ratio of prevalence odds to disease duration.
`We assumed that chronic comorbid conditions were not
`cured in the model, so life expectancies of persons with
`
`

`

`Incidence and Lifetime Risk of Diagnosed Symptomatic Knee OA
`
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`
`Figure 1. Estimated prevalence of diagnosed symptomatic knee osteoarthritis (OA) by age in the US (internal validation of Osteoarthritis
`Policy [OAPol] Model estimates using 2007–2008 National Health Interview Survey [NHIS] data). Broken curves show the prevalence
`among nonobese persons and solid curves show the prevalence among obese persons. Female prevalence is in black; male prevalence is
`in gray. Prevalence from the NHIS is depicted by squares for obese persons and diamonds for nonobese persons and is accompanied by
`95% confidence intervals (95% CIs).
`
`these comorbidities were used as a measure of disease
`duration. Dividing prevalence odds derived from the 2005–
`2008 NHANES data by the estimated disease duration led
`to estimates of the comorbid incidence rates used in the
`model, stratified by age, sex, and race/ethnicity (Table 1).
`
`RESULTS
`
`Estimated prevalence of diagnosed symptomatic knee
`OA. Age-, sex-, and obesity-stratified estimates of the
`prevalence of diagnosed symptomatic knee OA are shown
`in Table 2. For nonobese men, the estimated prevalence
`ranged from 0.74% among those ages 25–34 years to
`12.94% in those ages ⱖ85 years. For nonobese women,
`the estimated prevalence ranged from 0.88% for the
`youngest age group (25–34 years) to 14.97% among those
`ages ⱖ85 years. For obese men, the estimated prevalence
`ranged from 1.54% in the youngest group to 23.54% in the
`oldest group. Obese women had the highest estimated
`prevalence, ranging from 2.41% in the youngest group to
`32.45% in the oldest group.
`
`5.47 years to 3.39 years for the 25–34-year-olds and ⱖ85-
`year-olds, respectively. For nonobese and obese women,
`the estimated disease duration ranged from 5.49 years
`among those ages 25–34 years to 3.89 years among those
`ages ⱖ85 years.
`Estimated annual incidences of diagnosed symptomatic
`knee OA, stratified by age, sex, and obesity, are shown in
`Table 2. Estimated incidence ranged from 0.04% per year
`in nonobese men ages ⱖ85 years to 1.02% per year in
`obese women ages 55– 64 years. For all sex and obesity
`status combinations, the incidence peaked at ages 55– 64
`years and was lowest among those ages ⱖ85 years. For
`nonobese men, the incidence ranged from 0.04% to 0.37%
`per year. For nonobese women, the incidence ranged from
`0.06% to 0.43% per year. Among obese men, the incidence
`ranged from 0.05% to 0.64% per year. For obese women,
`the incidence ranged from 0.10% to 1.02% per year.
`Results of the internal validation analysis using our cur-
`rent incidence estimates are shown in Figure 1. Within
`each 10-year age group, the model-based prevalence esti-
`mates fell within the 95% CI of the NHIS data for each
`cohort, defined by sex and obesity status.
`
`Estimated incidence of diagnosed symptomatic knee
`OA. For nonobese men, the estimated disease duration
`within each decade ranged from 5.48 years for the young-
`est age group to 3.39 years for the age group ⱖ85 years. For
`obese men, the estimated disease duration ranged from
`
`Estimated age at diagnosis of symptomatic knee OA.
`Using current demographic, obesity, and comorbidity
`profiles representative of the general population in the
`US, the estimated mean ⫾ SD age at symptomatic knee OA
`diagnosis was 53.5 ⫾ 14.4 years. The estimated median
`
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`708
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`Losina et al
`
`'ii 100%
`
`E 90%
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`80%
`
`70%
`
`60%
`
`40%
`
`30%
`
`20%
`
`10%
`
`Median age: 55 years
`
`0% ...... - - - -~ - -~~~ -~ - -....... ~---~~~~-~~~--~~~~
`75
`45
`25
`55
`40
`65
`80
`35
`50
`85
`30
`60
`70
`90
`
`Age
`
`Figure 2. Estimated age at diagnosis among persons with symptomatic knee osteoarthritis (OA). The black curve is the cumulative
`incidence using calculated and calibrated incidence estimates. The vertical broken line denotes the median age at diagnosis (i.e., the age
`by which 50% of cases have been diagnosed).
`
`Lifetime risk
`of knee OA by
`cohort
`
`Female, obese 23.87%
`
`Male, obese 15.70%
`
`Overall 13.83%
`.. .. ·.·.·.·.········--:-·-·.·.·.·.·.· · ·· ··· ·· ·· ··
`.. ·.·.··-·:-:-:-·-<··-·.····
`
`..... _______________ __,:;...._:/~ ... , ~ -----------
`.. ·······················:_::::: =--=~~==
`
`Female, non-obese
`12.22%
`
`Male, non-obese 9.60%
`
`· ·········~ :..---
`
`9.29%
`
`~::=---
`
`30%
`
`25%
`
`20%
`
`15%
`
`10%
`
`5%
`
`0%
`
`Cumulative Incidence of Diagnosed Symptomatic Knee OA
`
`25
`
`30
`
`35
`
`40
`
`45
`
`50
`
`55
`
`60
`
`65
`
`70
`
`75
`
`80
`
`85
`
`90
`
`Age
`
`Figure 3. Estimated cumulative incidence of diagnosed symptomatic knee osteoarthritis (OA) from age 25 years in the US population,
`stratified by sex and obesity status. The patterned gray curve shows the overall cumulative incidence of diagnosed symptomatic knee OA
`from age 25 years. Broken curves show the cumulative incidence among nonobese persons; solid curves show the cumulative incidence
`among obese persons. Female cumulative incidence is in black; male cumulative incidence is in light gray. The cumulative incidence by
`the end of life shows the lifetime risk for each cohort, as denoted in the right margin. The point of intersection of the black horizontal and
`vertical lines emphasizes the cumulative incidence for the general US population by age 60 years.
`
`

`

`Incidence and Lifetime Risk of Diagnosed Symptomatic Knee OA
`
`709
`
`age at diagnosis of symptomatic knee OA was 55 years
`(Figure 2).
`
`Lifetime risk of diagnosed symptomatic knee OA. The
`lifetime risk of diagnosed symptomatic knee OA from age
`25 years in the US population was estimated at 13.83%,
`with a 9.29% risk of having diagnosed symptomatic knee
`OA by age 60 years (Figure 3). In obese persons, the life-
`time risk of diagnosed knee OA was estimated at 19.67%
`compared to 10.85% for nonobese persons. In women, the
`lifetime risk was estimated at 16.34% compared to 11.42%
`in men. In sex- and obesity-stratified cohorts, we estimated
`the lifetime risk to be highest in obese women at 23.87%
`and lowest in nonobese men at 9.60%.
`
`DISCUSSION
`
`We used the OAPol Model, a state transition Monte Carlo
`computer simulation model, combined with national data
`from the 2007–2008 NHIS on the prevalence of diagnosed
`symptomatic knee OA, to estimate the annual incidence of
`diagnosed symptomatic knee OA in the US. We estimated
`that incidence peaked during ages 55– 64 years, was higher
`among obese persons than nonobese persons and, adjust-
`ing for obesity, was higher among women than men. The
`estimated median age at knee OA diagnosis was 55 years.
`Our incidence estimates were derived with an approach
`that relates incidence, prevalence odds, and disease dura-
`tion (prevalence odds/disease duration ⫽ incidence rate).
`Prevalence was obtained from a national population-based
`cross-sectional study. To ensure a “stable population,” we
`considered prevalence to be stable within 10-year age in-
`tervals. This method is widely used when longitudinal
`data are not available (31,32).
`This study adds important insights to research on OA
`incidence. Until now, a report from the mid-1990s pro-
`vided the most recently published estimates of the inci-
`dence of diagnosed symptomatic knee OA (15–17). Our
`contemporary estimates are consistent with prior literature
`in showing a higher incidence of diagnosed knee OA
`among women (16) and among obese individuals (8,33,34).
`However, the estimated rates of diagnosed knee OA
`incidence differ somewhat from prior studies published
`10 –20 years ago. The study by Oliveria et al, published in
`1995 based on data from the Fallon Community Health
`Plan, used medical records to estimate the annual inci-
`dence of diagnosed knee OA. The authors found that the
`incidence of diagnosed symptomatic knee OA increases
`with increasing age until age 80 years (16). The key dif-
`ference in the estimated incidence between our study
`and the study reported by Oliveria et al in the 1990s lies
`in distributional shift. In our study, diagnosed OA inci-
`dence peaked in an earlier age group (55– 64 years), con-
`sistent with current trends where use of TKRs occurs
`earlier in life, with 40% of TKR recipients being ages ⬍65
`years (35–38).
`Our estimates also provide insight into the differential
`impact of obesity on diagnosed OA incidence across age
`and sex strata. A recent study from the Johnston County
`Osteoarthritis Project in North Carolina found that the
`
`lifetime risk of symptomatic knee OA from age 45 years
`was nearly 45% (39), considerably greater than our esti-
`mate of 14%. Several differences in the study design and
`population may explain this difference. First, the Johnston
`County study utilized radiographs to define symptomatic
`knee OA. Unpublished data from the Johnston County
`Osteoarthritis Project indicate that only approximately
`two-thirds of those identified as having symptomatic knee
`OA reported being diagnosed with OA by a health profes-
`sional. Second, the current study projected lifetime risk
`from an earlier age (25 years), while the Johnston County
`study estimated lifetime risk from age 45 years (39). Third,
`differences between the study populations in Johnston
`County and the NHIS may also account for some of the
`differences in estimated lifetime risk. Indeed, when we ran
`a cohort through the model using the sex, race, and BMI
`distributions, as well as the incidence, prevalence, and
`progression of symptomatic knee OA representative of the
`Johnston County population, the lifetime risk for develop-
`ing knee OA increased from 14% to 38%, similar to the
`45% risk reported in the Johnston County study. The re-
`maining differences may reflect the fact that although the
`Johnston County Study had good followup, not all study
`participants returned for the followup assessment. As in
`many cohorts, those participants who developed OA were
`more likely to return for followup assessments, increasing
`the estimates of OA risk.
`Our estimates suggest that persons ages 55– 64 years
`today are at highest risk for a new diagnosis of symptom-
`atic knee OA, with the incidence of diagnosed disease
`tapering off in older ages. If these differences are indicative
`of secular trends, they may reflect increased likelihood of
`diagnosis earlier in life rather than earlier onset of biologic
`disease. An increase in the rate of diagnosed cases could
`result from increased patient awareness of knee OA, as
`well as a heightened inclination to diagnose knee OA on
`the part of physicians. Because rigorous comparisons be-
`tween our findings and the study by Oliveria and col-
`leagues are limited by methodologic differences and het-
`erogeneity in the study populations, further research is
`needed to understand secular trends in the incidence and
`diagnosis of symptomatic knee OA.
`Our findings have important implications for disease
`prevention and health care utilization. The early median
`age at diagnosis of symptomatic knee OA (55 years) sug-
`gests that public health officials should introduce preven-
`tion strategies relatively early in the life course. Policy-
`makers should implement prevention strategies aimed at
`reducing obesity and the risk of knee injury, 2 major risk
`factors for knee OA. Furthermore, the early age at diag-
`nosis of symptomatic knee OA may yield high levels of
`lifetime health care utilization and costs. In the last de-
`cade, the mean age of persons undergoing TKR has de-
`creased from 69 to 66 years and utilization of TKR has
`tripled among US adults ages 45– 64 years (38). Whether
`health outcomes improve as a result of early diagnosis of
`symptomatic knee OA offers a rich area for future research.
`The results from this study should be viewed within the
`context of certain assumptions and limitations in our ap-
`proach. First, the definition of OA poses challenges (40).
`The incidence estimates reported here depend on the
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`Losina et al
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`method used to define diagnosed symptomatic knee OA.
`To derive population-based national data, we relied on a
`national, self-reported survey (2007–2008 NHIS). Diag-
`nosed symptomatic knee OA was defined based on re-
`sponses to several questions asked in the survey. Certain
`questions pertain more to recent knee pain than to chronic
`knee pain, which would serve as a better indicator of knee
`OA prevalence. However, algorithms similar to the one we
`used have specificity greater than 90% (25,26), and the
`