SEARCH

SEARCH BY CITATION

Keywords:

  • Radiographic;
  • Knee osteoarthritis;
  • Disability;
  • Knee strength

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Objective

To ascertain predictors of decline in physical functioning among older adults reporting knee pain.

Methods

The Observational Arthritis Study in Seniors was a longitudinal study of 480 adults over 65 years of age. Measurements of strength, sociodemographic characteristics, disease burden (including radiographic knee osteoarthritis [OA]), self-reported disability, and functional limitations were obtained on participants at baseline and at 15 and 30 months.

Results

Radiographic evidence of OA at baseline was moderately associated with an increased decline in both transfer (P = 0.06) and ambulatory-based performance tasks (P = 0.04) but not in self-reported disability. This effect disappeared after accounting for baseline levels of knee pain intensity and knee strength.

Conclusion

Knee pain intensity and knee strength may mediate the relationship between radiographic evidence of knee OA and change in performance. Although it is not clear whether joint disease precedes or follows a decline in muscular strength, these results may help to identify subpopulations of older persons with knee OA who may benefit from interventions aimed at slowing the progression of disability related to transfer and ambulatory-based tasks.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Physical disability is an important public health outcome for older adults. Roughly 40% of persons over the age of 65 years report limitations in their ability to perform activities of daily living. This high prevalence has been attributed, in large part, to the onset of various age-associated chronic diseases (1). Osteoarthritis (OA) is the most common rheumatic disease and the most common chronic disease reported by community-dwelling older adults. OA affects an estimated 20 million older adults in the United States (2, 3). The knee is the second most affected joint in OA and is the most common cause of chronic disability among older persons (4, 5). A review by Hurley (6) suggests that pain and quadriceps weakness are more important determinants of disability in knee OA than is radiographic evidence of knee OA. Given the clinical significance of this chronic disease, the objectives of the current study were to describe how chronic knee pain and radiographic knee OA affect the progression of disability as older adults age, and to identify the role that knee strength might play in this relationship.

Data from the first National Health and Nutrition Examination Survey indicate that 43% of persons with radiographic knee OA report pain, a statistic that is similar to prevalence rates from the Framingham cohort (7, 8). Interestingly, asymptomatic persons with radiographic evidence of knee OA report little or no disability (7, 9), whereas individuals with symptomatic knee OA report limitations in instrumental activities of daily living (e.g., walking, carrying and lifting objects, etc.) and various avocations (10, 11). It is also well established that quadriceps strength is compromised early in the development of knee OA (6, 12), and that loss of quadriceps strength is implicated in the progression of disability with the disease (13). Indirect evidence even suggests that deficits in sensorimotor function of the quadriceps muscle may be important to the pathogenesis of knee OA (6).

Other evidence has linked the prevalence or progression of knee OA to body weight, sex, race, and sociodemographic risk factors (4, 14, 15). Risk factors for disability among older adults include sociodemographic factors such as increased age, lower levels of education, being single, being nonwhite (16, 17), and having multiple comorbidities (18). Finally, although radiographic evidence of knee OA has been linked to disability, the real clinical malady with this disease is pain (19).

Despite the relevance of knee OA and physical disability to the public health of older adults, we are unaware of any prospective studies that describe the rate of decline in physical function as older adults with radiographic knee OA age. Moreover, there is limited information concerning factors that may modify the progression of disability with this disease. Using data from 30 months of followup in the Observational Arthritis Study in Seniors (OASIS), this paper will examine the rate of decline in both functional limitations (transfer and ambulatory measures) and self-reported disability among older adults with radiographic knee OA.

Decline in abilities over time that may be related to the aging of the participant can be thought of as the longitudinal effect of aging. The analyses reported in this paper focus on how the longitudinal effect of aging on functioning may be modified by several a priori selected baseline characteristics. First, we investigate how changes in longitudinal measures of transfer and ambulatory-based functional limitations and self-reported disability are related to radiographic knee OA, knee strength, and knee pain intensity at baseline. Second, we determine whether baseline pain and knee strength possibly mediate the relationship between radiographic knee OA and progression of functional limitations and self-reported disability.

SUBJECTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Design

The OASIS study recruited participants with self-reported knee pain using telephone-based interviews of individuals drawn from a commercial list of persons aged 65 or older residing in Winston-Salem, North Carolina, and surrounding counties. Names on the commercial list were randomly selected, and the individuals received a mailed brochure followed by a telephone call. During phone calls, a brief screening questionnaire was administered, and persons who met all inclusion/exclusion criteria (see below) were asked to provide informed written consent. Self-report and measurement data were collected at baseline and at 15- and 30-month visits. Participants refusing to return for followup visits were requested to complete questionnaires in their residence and return the completed questionnaires via mail.

Participants

A total of 480 participants met eligibility criteria and completed baseline evaluations. The eligibility criteria for participation were (a) age 65 years or older, (b) knee pain on most days, and (c) difficulty with at least one of the following due to knee pain: walking a quarter mile; climbing stairs; getting into and out of a car; rising from a chair; lifting and carrying groceries; getting out of bed; getting out of the bathtub; or performing shopping, cleaning, or self-care activities. Potential participants were excluded if they (a) were moving from the area within 3 years, (b) were under hospice care, (c) were receiving active treatment for cancer (other than skin cancer), (d) had shortness of breath or chest pain at rest, (e) had a mini-mental score < 24, as measured by the Mini–Mental State Examination (20), (f) had a history of rheumatoid or psoriatic arthritis, or (g) were currently participating in another study.

Measures.

Ambulatory performance task.

We selected the time needed for the subject to complete a stair climb task as an objective measure of ambulatory functional limitations. At baseline and during each followup visit, the time required for participants to ascend and descend an isolated set of stairs that was equipped with a handrail was recorded. The stairs had 5 steps with a rise of 17.78 cm and a run of 30.48 cm. There was an 83.82-cm × 121.92-cm platform at the top. Participants began the task by standing on a line that was 27.24 cm from the first step, with their hand placed on the handrail. When told to begin (with the instruction “Do this task as quickly as you can”), they climbed to the top of the steps with their left hand on the rail and immediately turned around and climbed down using the same handrail. The task was scored as the total time to go up and down the stairs. As described by Rejeski and colleagues (21), the stair climb task has excellent 2-week test–retest reliability (coefficient of 0.93). Performance on the task correlates in expected directions with knee strength (−0.58), VO2peak (−0.37), and self-reported ambulatory disability (0.38). The task has also been found to be sensitive to change with physical activity interventions (22).

Transfer performance task

To evaluate participants' performance on transfer-related activities, we used a simulated car task. The car used in this test was a mock-up of a 1988 Valiant that was built to specifications by a metal shop. At the command “Go,” participants opened the door, got into a bucket seat, closed the door, reopened the door, and stepped out, immediately moving to an erect position. The task was timed from the command “Go” until the sequence was completed. Rejeski and colleagues have described the validity and reliability of this measure in an older population with knee OA (21). It has a test–retest reliability of 0.82 and has significant correlations with objective measures of physical function, including time on a treadmill (−0.45) and knee strength (−0.46).

Self-reported functional performance

A measure of self-reported physical functioning was obtained from The Functional Performance Inventory (21). This questionnaire consists of items that assess levels of difficulty with activities of daily living (e.g., walking, meal preparation, and dressing). Participants are asked, “How much difficulty, if any, did you have with each of these activities? Think about the past month.” For each activity, responses are measured on a 5-point Likert scale ranging from 1 (no difficulty) to 5 (unable to do). A composite disability score was obtained by averaging the scores on 10 items covering the following activities: doing light housework, preparing meals, participating in community activities, managing money, visiting with relatives or friends, using the telephone, dressing, taking care of a family member, eating, and shopping. Higher scores indicate greater disability. At the baseline exam, these items had a 0.83 Cronbach's alpha coefficient of internal consistency.

Sociodemographic variables

Variables representing sex, age (measured in years), ethnicity, education (measured in years completed), and whether the participant lived alone (yes/no) were constructed from self-reports.

Physical health–related variables

Standard extended bilateral standing anteroposterior knee radiographs were obtained during the baseline visit. The knee radiographs were read for individual features of OA including joint space narrowing, osteophytes, sclerosis, and cysts using the Osteoarthritis Research Society International knee OA atlas. Two expert readers (Drs. Nancy Lane and Charles Peterfy, University of California, San Francisco) scored each film for the individual features of OA on a 0–3 scale. The average scores from the 2 readers were used to determine the presence of radiographic OA based on criteria described by Felson and colleagues (23), where an osteophyte score of 2 or greater was shown to correlate best with clinical OA. Thus a dichotomous variable was generated consisting of no radiographic OA (osteophyte score < 2) in both knees or radiographic evidence of OA in either knee (osteophyte score ≥2). Both inter- and intra-reader reliability was assessed for readings of osteophytes. When averaged across both knees and lateral and medial compartments, the intra-reader reliability, as measured by the intra-class correlation, was greater than 0.70 for each reader. Inter-reader reliability, also averaged across knees and compartments, was 0.75. Small but statistically significant differences in average scores were found between readers.

Body mass index (BMI [kg/m2]) was calculated using values of weight and height obtained during the baseline medical examination. A history of hypertension, diabetes, or chronic obstructive pulmonary disease (COPD) was coded as present or absent based on whether participants reported being told by a doctor that they had these conditions. A history of cardiovascular disease (CVD) was coded as the number of physician-diagnosed symptoms from a list that included any reported heart attack, angina, stroke, other heart problems, or poor circulation (arterial insufficiency).

Knee pain

Knee pain was assessed using the ambulatory and transfer pain intensity subscales from the Knee Pain Scale (KPS) (24). Each subscale has 3 items that are rated on a 6-point Likert-type scale with the following anchors: 1 (no pain), 2 (mild pain), 3 (discomforting pain), 4 (distressing pain), 5 (horrible pain), and 6 (excruciating pain). The ambulatory items include climbing up or down a flight of stairs or walking a short distance (1 block), whereas the transfer items involve getting into or out of a bed, chair, or car. Means are calculated for the 3 items on each subscale and can range from 1 to 6, with higher scores indicating more severe levels of pain. The KPS has good convergent validity, and confirmatory factor analyses have supported the creation of separate scores for ambulation and transfer (24). Cronbach's alpha reliabilities and test–retest reliabilities for the subscales are all in excess of 0.80.

Knee strength

Concentric knee extension strength was assessed using a Kin-Com 125E isokinetic dynamometer (Chattecx, Chattanooga, TN). Prior to testing, a warm-up period was provided to habituate the subjects to the testing equipment. Gravity effect torque was calculated based on the subject's leg weight at a 45-degree angle. An angular velocity of 30 degrees/second was used for all tests. The activation force for each muscle group was set at 50% of maximal voluntary isometric contraction. Setting a relatively high activation force was based on reports that the amount of activation force significantly influences the magnitude of the average force recorded (25, 26). Knee extensors were tested through a joint arc from 90 to 30 degrees (0 degrees = full extension). The first and last 10 degrees were subsequently deleted to account for the acceleration and deceleration of the dynamometer at the ends of the range of motion and also to account for possible inconsistent effort (26). Hence, force was calculated as the average force between joint angles of 40 and 80 degrees. A rest period of 30–60 seconds was used between trials. Subjects were instructed to give a maximal effort. Two maximal reproducible trials were averaged, and the maximum number of trials for each test condition did not exceed 6 (26). The leg that the participant indicated had the most pain was used for each test. If reported pain was equivalent in both knees, then the leg that the participant indicated was dominant was used. Average force exerted (N) was divided by mass (kg) to provide a measure of strength (N/kg).

Statistical analysis

Independent variables used to adjust mean level of functional limitations and disability at each time point included sex; age; ethnicity; education; living alone; history of hypertension, CVD, diabetes, or COPD; BMI; knee pain intensity score; radiographic evidence of OA; and concentric knee extension strength.

Mixed-effects repeated-measures analysis of covariance was used to relate each dependent variable (stair climb time, car time, and self-report functional performance) to the previously mentioned independent variables (27). Our models employed a popular parameterization used for longitudinal, observational studies (28–30). For our longitudinal analyses of functioning, we investigated whether the presence of radiographic evidence of knee OA, knee strength, and knee pain intensity modified the effect that aging had on change in each dependent measure. All other baseline covariates are included in each model to provide adjustments for the means at each time point, because all selected covariates have reported associations with the outcomes, and inclusion of the covariates helps to adjust the means at each time point for potential biases resulting from missing observations being dependent on covariates. Because this paper focuses on how radiographic evidence of knee OA, knee strength, and knee pain intensity relate to change in each outcome, we have not included modeling results for covariates in our tables.

The approach for model development that we used was to initially adjust for all baseline covariates and to subsequently determine whether baseline levels of radiographic evidence of knee OA, knee strength, and knee pain intensity had a modifying effect on the slope relating change in each dependent variable to elapsed followup time. Initially, radiographic evidence of knee OA, knee strength, and knee pain intensity were each evaluated as the only potential modifier of this slope. Subsequently, we entered all of these variables in the model and investigated for 2-way interactions between presence of knee OA, knee strength, and knee pain intensity. Knee pain intensity during transfer was used to predict the car time task, whereas knee pain intensity during ambulation was used to predict the stair climb task. Knee pain intensity during both ambulation and transfer was used to predict the self-report disability score. This measure contains items that involve both transfer and ambulation. For main effects, P values less than 0.05 were considered statistically significant, whereas, because of the low power typically associated with testing interactions, P values less than 0.10 were used to indicate statistically significant interactions. When an interaction was significant in a model, all corresponding main effects were also included in the model.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Descriptive characteristics

Fifty-one percent of the 480 OASIS participants were female, and 82.5% were white. The ethnic background of the remaining participants was 13.1% African American, 0.6% Asian, and 3.8% Native American. Baseline characteristics of these participants are presented in Table 1. Approximately 41% of participants had BMI ≥30 kg/m2, and approximately 40% had a previous diagnosis of hypertension. Although all participants had to report knee pain on most days of the week in order to qualify for OASIS, only 51.6% of participants with x-rays had radiographic evidence of knee OA based on presence of an osteophyte grade of ≥ 2. Baseline x-rays were not obtained for 17 participants.

Table 1. Baseline characteristics of OASIS participants*
VariableMean ± SD%Range
  • *

    OASIS = Observational Arthritis Study in Seniors; CVD = cardiovascular disease; COPD = chronic obstructive pulmonary disease; BMI = body mass index; OA = osteoarthritis.

  • Number in parentheses is the number of participants for whom information on this variable is available.

Sex (% female) (n = 480)51.0
Age (n = 480)71.82 ± 5.0065–88
Race (% white) (n = 480)82.5
Education (% ≥ 12 years) (n = 480)58.0
Live alone (% Yes) (n = 476)27.9
Hypertension (% Yes) (n = 474)38.8
CVD (no. of symptoms) (n = 479)0.64 ± 0.840–4
Diabetes (% Yes) (n = 473)14.4
COPD (% Yes) (n = 461)12.6
BMI (kg/m2) (n = 480)29.6 ± 5.2218.0–62.2
Ambulatory knee pain intensity score (n = 471)2.48 ± 0.701–6
Transfer knee pain intensity score (n = 473)2.38 ± 0.671–6
Presence of radiographic knee OA (% Yes) (n = 463)51.6
Concentric knee extension strength (N/kg) (n = 472)3.43 ± 1.140.32–7.12
Self-report physical function score at baseline (n = 464)1.33 ± 0.391–3.7
Time to complete stair climb task, seconds (n = 473)10.04 ± 4.704.1–40.1
Time to complete car task, seconds (n = 478)11.48 ± 6.024.3–78.6

Sixteen OASIS participants had knee replacement surgery at some point during followup. Followup data obtained postsurgery for these participants were excluded from all analyses. For self-reported functioning, 101 (21.0%) of the initial 480 participants were either too ill or did not return completed questionnaires at month 30. For the stair climb task, 156 (32.5%) of the initial 480 participants were unable or refused to return to the testing site at month 30, whereas 146 (30.4%) did not complete the car time task at month 30. Participants who completed the month 30 self-report physical function questionnaire (mean = 1.32) did not have a significantly higher level of baseline functioning than those who did not complete the questionnaire (mean = 1.38; P = 0.22). In contrast, those who performed the stair climb task at month 30 took less time to complete the task at baseline (mean = 9 seconds) than those who did not perform the task (mean = 12.07 seconds; P < 0.001). Similarly, those completing the month 30 car time task had a smaller baseline car time (mean = 10.7) than those who did not perform the task (mean = 13.2 seconds; P < 0.001).

In Table 2, we report baseline averages and mean changes from baseline in outcome variables for participants completing month 30 visits. These statistics are stratified by presence of radiographic OA. Unadjusted 30-month mean changes in self-reported functioning (P = 0.44) and car time (P = 0.22) were comparable between OA groups. In contrast, for the stair climb task, the unadjusted 30-month mean changes were significantly different between OA groups (P = 0.04), with a greater decline noted in the group with radiographic OA.

Table 2. Average change from baseline for Observational Arthritis Study in Seniors participants with followup visits*
Presence of radiographic knee OAOutcome variableBaseline value (mean ± SD)Change at month 30 (mean ± SD)
  • *

    Participants who had knee replacements during followup or who are missing baseline radiographic measurements or month 30 outcomes are excluded. OA = osteoarthritis.

  • Change significantly different from zero (P < 0.05). Change is calculated as the baseline value minus the followup value. Negative signs indicate a decline in performance because a larger value is associated with a worse performance for each outcome variable.

NoSelf-report function (n = 168)1.31 ± 0.359−0.10 ± 0.364
Stair climb time, seconds (n = 161)8.41 ± 2.865−1.50 ± 2.419
Car time, seconds (n = 166)10.28 ± 4.446−3.12 ± 4.878
YesSelf-report function (n = 176)1.34 ± 0.360−0.13 ± 0.374
Stair climb time, seconds (n = 146)9.71 ± 3.589−2.41 ± 4.709
Car time, seconds (n = 151)11.20 ± 4.368−3.78 ± 4.668

Overall, for self-reported functioning, 44.9% of participants experienced a decline between baseline and month 15, and 53.0% experienced a decline between baseline and month 30. At month 30 the median decline in self-reported functioning was 0.0 (25th percentile = −0.2 unit, 75th percentile = 0.1 unit). For stair climb time, 66.6% of participants experienced a decline between baseline and month 15, and 70.9% experienced a decline between baseline and month 30. The median decline at month 30 was 1 second (25th percentile = −2.5 seconds, 75th percentile = 0.1 second). For the car time task, 79.1% experienced a decline between baseline and month 15, and 85.1% experienced a decline at month 30. At 30 months, the median decline was −2.6 seconds (25th percentile = −5.1 seconds, 75th percentile = −1.1 seconds).

In Table 3, we present Spearman correlation coefficients characterizing the strength of bivariate relationships between knee strength, knee pain intensity, and both (a) the 3 outcome variables at baseline and (b) change in the outcome measures at month 30. Using bivariate analyses, all variables are associated with baseline functioning measures; however, when related to 30-month change, only knee strength and knee pain intensity show significant associations. At baseline, self-reported disability was positively correlated with stair climb time (r = 0.34) and car time (r = 0.35). Stair climb time and car time were positively correlated (r = 0.76).

Table 3. Spearman correlation coefficients between predictors and outcomes for Observational Arthritis Study in Seniors participants*
 Baseline values30-month change
VariableSelf-report functioningStair climb time (seconds)Car time (seconds)Self-report functioningStair climb time (seconds)Car time (seconds)
  • *

    All correlations > 0.10 or < −0.10 are significant at P < 0.05. Correlations in columns 2–4 represent the relationships between baseline values of predictors and outcomes. Correlations in columns 5–7 represent the relationships between baseline values of predictors and 30-month change in outcomes. Change is calculated as the baseline value minus the followup value. For example, at baseline greater levels of knee strength are associated with smaller times to perform the stair climb task. Likewise, greater levels of baseline knee strength are associated with less decline in time to complete the stair climb task because large negative changes represent greater declines in stair climb than do small negative or positive values (which represent improvement).

Ambulatory knee pain intensity0.380.32−0.15−0.12
Transfer knee pain intensity0.370.29−0.13−0.06
Concentric extension knee strength−0.24−0.63−0.550.170.290.18

Longitudinal modeling analyses

In Table 4, we present parameter estimates from our repeated-measures models that relate between-person differences in baseline levels of radiographic knee OA, knee strength, and knee pain intensity to expected 30-month change. All models are adjusted for the specified covariates. Estimates are first presented for models where each of these variables was the only baseline predictor allowed to modify the slope relating longitudinal change in functioning to elapsed followup time. For these models, baseline knee strength and ambulatory knee pain intensity were consistently significant predictors of change in all outcomes. Additionally, the presence of radiographic knee OA was moderately predictive of change in time to complete the stair climb (P = 0.06) and car time tasks (P = 0.04).

Table 4. Estimated coefficients for prediction of 30-month change in functioning*
 Self-reported disabilityStair climb time taskCar time task
  • *

    Values represent coefficient estimates for 30-month change obtained from repeated-measures models fit to each outcome. For each unit increase in the predictor variable, the coefficient represents the expected 30-month change in the outcome variable after controlling for other factors in the model. Thus, for the final model for change in stair climb time, two people with a 1-unit difference in baseline knee strength are expected to have a 0.93 difference in their 30-month change in the time to complete the stair climb task. Baseline levels of covariates are included in all repeated-measures models. OA = osteoarthritis.

  • 0.10 > P ≥ 0.05.

  • P < 0.05.

  • §

    P < 0.001.

  • P < 0.01.

  • #

    Entered together into model.

Variables entered alone
 Presence of radiographic knee OA−0.035−0.702−1.066
 Knee strength0.0480.932§0.834
 Ambulatory knee pain intensity#−0.084−0.567
 Transfer knee pain intensity#0.016−1.217
Variables entered together
 Presence of radiographic knee OA0.001−0.161−0.465
 Knee strength0.0400.885§−0.706
 Ambulatory knee pain intensity−0.071−0.251
 Transfer knee pain intensity0.021−2.823
 Knee strength × knee pain intensity during transfer0.604
Final model containing significant effects
 Knee strength0.0480.932§−0.655
 Ambulatory pain intensity
 Transfer pain intensity−2.870
 Knee strength × pain intensity during transfer0.603

Estimates are also presented for the models containing all 3 predictor variables. For the car time task, we found a significant interaction between knee strength and knee pain intensity (P = 0.04). This interaction was the only 2-way interaction between these predictors that was significant in any of our longitudinal models. The possible mediating effect of knee strength and knee pain intensity on the relationship between the presence of radiographic knee OA and change in both the stair climb and car time tasks is evidenced by the loss of statistical significance for the knee OA variable when knee strength and knee pain intensity are entered into the model. The sensitivity of these results to the possibility that the relationships between the predictors and decline may be confounded by initial age was investigated by determining whether the estimated effects were attenuated when change was also allowed to depend on baseline age. For these analyses, we found negligible attenuation of significant effects reported in Table 4, with all effects that were initially statistically significant retaining their significance in the presence of baseline age. After removing nonsignificant variables from these multivariable models, the predicted 30-month changes in each outcome, expressed as a function of baseline knee strength and knee pain intensity, are as follows:

Predicted 30-month change in self-reported disability = −0.3088 + (0.048 × knee strength)

Predicted 30-month change in stair climb task = −5.340 + (0.932 × knee strength)

Predicted 30-month change in car time = 0.693 − (0.655 × knee strength) − (2.87 × transfer knee pain intensity) + (0.603 × transfer knee pain intensity × knee strength).

Figure 1 provides a plot of predicted 30-month changes for car time based on the equation above. The points on this plot correspond to the predicted 30-month changes obtained by substituting into the 30-month car time equation the 25th, 50th, and 75th percentiles for strength (2.6, 3.4, and 4.2, respectively) and pain values of 2 and 3. For ambulatory knee pain intensity values of 2 or 3, increased baseline strength is associated with a lower predicted change in 30-month car time. Larger values of knee pain intensity are predictive of greater 30-month change for participants with lower baseline strength values. The effect of baseline pain on 30-month change diminishes at higher strength values.

thumbnail image

Figure 1. Effect of baseline pain and strength on 30-month change in car time task.

Download figure to PowerPoint

Using the fitted equations from the repeated-measures analyses, estimated performance levels and 30-month percentages of change from baseline are presented in Table 5 for each outcome. These estimates were obtained by substituting values representing combinations of the 25th and 75th percentiles of knee pain and knee strength into the fitted equations. Other covariates included in the equations were set to the mean for the sample at baseline. For each outcome, the effect of higher levels of knee pain or knee strength is apparent in both the magnitude of the predicted values at baseline and month 30 and the magnitude of the predicted change. For the car time outcome, a 65-year-old with knee strength measured at the 25th percentile (strength = 2.6), reporting knee pain at the 25th percentile (pain = 2.0), is predicted to take 3.6 seconds longer to complete the task at month 30 (14.3 seconds) than this person took at baseline (10.7 seconds). This represents a 33.8% decline. In contrast, if this 65-year-old reported baseline knee pain at the 75th percentile (pain = 3.0) but still had knee strength measured at the 25th percentile, then the predicted time to complete the car time task at month 30 is 16.3 seconds (a 43% decline from baseline). This 30-month predicted value is almost a full second greater than that predicted for a 70-year-old with knee strength measured at the 75th percentile reporting pain at the 25th percentile (predicted value = 15.4 seconds). Thus, the effect of the greater baseline level of pain on decline indicates that, after 30 months of followup, the 65-year-old with greater pain is predicted to have a slower time to perform the car task than the 70-year-old with less pain, even though the predicted time for the 65-year-old is faster at baseline (11.4 seconds versus 11.8 seconds).

Table 5. Predicted values from repeated-measures analyses
OutcomePain intensity*Knee strengthBaseline age = 65Baseline age = 70
M0M30§Change %M0M30§Change %
  • *

    25th percentile of baseline pain intensity = 2. 75th percentile of baseline pain intensity = 3. Mean baseline pain intensity was used to obtain predicted values for stair climb time and self-reported disability.

  • 25th percentile of knee strength = 2.60. 75th percentile of knee strength = 4.2.

  • Predicted value at baseline visit.

  • §

    Predicted value at month 30 visit.

Car task time24.28.110.8−33.79.212.0−29.5
2.610.714.3−33.811.815.4−30.5
34.28.811.9−34.710.013.0−30.7
2.611.416.3−43.012.617.5−39.0
Stair climb task timeMean4.26.88.3−20.88.49.8−17.1
Mean2.69.011.9−32.510.513.4−27.9
Self-reported disability scoreMean4.21.281.39−8.231.291.40−8.14
Mean2.61.371.55−13.401.381.56−13.3

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

One objective of this investigation was to characterize the 30-month progression of both self-reported and performance-related functioning among older adults reporting knee pain with or without radiographic knee OA. Based on our evaluations of interactions in a multivariate model, there was no evidence that the rate of decline in self-reported disability was any different for individuals who had knee pain only as compared with those who had knee pain and radiographic evidence of knee OA. Such a finding supports the position that knee pain is the real clinical malady with this disease (19).

With respect to decline in functioning, several points deserve emphasis. First, on average, participants in this community sample experienced statistically significant increases in self-reported disability and time to complete a stair climb or car task over 30 months of followup. Although the presence of radiographic OA did not differentially affect the rate of decline for self-reported disability, in bivariate analyses it was significantly associated with faster progression in the time to complete the stair climb and car tasks. Other studies have found symptomatic knee OA to be an important determinant in the prevalence of physical disability in older adults (11, 31, 32). To our knowledge, this study is the first to illustrate that radiographic knee OA is associated with the rate of decline in both ambulatory and transfer-based functional limitations. As explained below, this association is most probably indirect and related to levels of knee strength and knee pain.

Second, we also found that knee strength and knee pain intensity may serve to mediate the effect of knee OA on decline in performance-based functioning. Based on the work of Baron and Kenny (33), evidence of mediation is obtained when a significant relationship between a predictor and an outcome is diminished when a third factor (that is related to the predictor) is entered into the model. For the stair climb time and car time tasks, the coefficient associated with the effect of knee OA is reduced by at least 50% when knee pain and knee strength are entered into each of these models. Although the relationship between the cross-sectional measurements of radiographic knee OA, knee strength, and knee pain collected at baseline do not represent a temporal, causal relationship, it is possible that increased knee pain and decreased knee strength follow the development of knee OA. However, other evidence suggests that decreased functioning of the quadriceps muscle may be related to the development of knee OA (6). The relationship between knee OA, knee pain, and knee strength results in confounding between these 2 factors and knee OA. Additionally, knee strength and knee pain intensity are likely interrelated, because pain has been shown to inhibit muscle contraction (34, 35). These models underscore the potential that may exist for combatting the physical disability that occurs in older adults with knee OA through strength training. Interventions targeted to improve the strength of the knee extensors may also be of benefit for older adults with knee pain (36).

Third, across the 30-month study period, a higher percentage of the study population experienced decline in stair climb performance (∼71%) and car time performance (∼85%) than in self-reported difficulty with activities of daily living (ADLs) (∼53%). One explanation for this pattern in the data is that ADLs do not depend exclusively on lower extremity function, nor do they typically require the demand inherent in a stair climb or car time task. To address this concern, in unreported analyses we refit all models after removing non–mobility-related tasks consisting of items related to managing money, using the telephone, eating, and dressing from the self-report disability measure. Conclusions from these analyses were consistent with those from analyses based on use of all items. Finally, the variability in rate of progression for both performance and self-reported ADL disability underscores the importance of considering potential modifiers of aging as it affects the progression of disability with this disease.

One limitation of our study is the large amount of missing performance outcomes at the 30-month visit (approximately 35%). For this reason, we used maximum likelihood repeated-measures analyses, permitting intermittent missing data, rather than analyzing change scores for individuals with complete data. These techniques help protect against biases due to missing data when the likelihood of an outcome being missing is dependent on previously observed data (29, 30). An alternative approach to handling the missing data would have been to use an imputation technique. However, simply imputing a very large time for those who did not complete the task would most certainly result in an overestimate of the 30-month change in either performance task, whereas imputing the last observed value carried forward would have resulted in a vast underestimate of this change. Our analysis technique probably results in an underestimate of the change that is intermediate between what would have resulted from imputation of a very large value and use of the last observed value. This limitation underscores the need to select performance tests that are related to disability, are sensitive to change in function, and are relatively easy for more disabled adults to complete but do not have “floor” effects.

The lack of radiographic assessment of the patellofemoral joint is another limitation of this study. In a study of community-dwelling subjects who were older than age 55, a little more than half of whom reported knee pain, isolated symptomatic patellofemoral joint OA was noted in 8% of the women and 2% of the men (37). In that study, somewhat higher scores for disability on the Stanford Health Assessment Questionnaire were found in the subjects with patellofemoral joint OA compared with those with medial compartment OA. Therefore, lack of assessment of the patellofemoral joint in the present study may have resulted in an underestimate of radiographic OA and the association between radiographic disease and functional loss.

Levels of pain and strength could be used to screen for older adults with knee pain who are at higher risk for experiencing decline in function over a 30-month period. The next step in our investigation will be to explore whether characteristics identified as associated with those persons who are predicted to experience the most decline may be precursors to changes in other variables that may mediate the observed change in functioning. For instance, higher levels of baseline knee pain may result in reduced levels of physical activity that lead to loss in muscular strength and subsequent decline in function. Through identification of possible mediating factors, interventions can be planned to help slow the decline in functioning among older adults.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

The authors would like to acknowledge the contributions made by Walter H. Ettinger, Jr., in the development and operations of the OASIS study.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  • 1
    Jette AM, Branch LG. Impairment and disability in the aged. J Chronis Dis 1985; 38: 5965.
  • 2
    Lawrence RC, Helmick CG, Arnett FC, Deyo RA, Felson DT, Giannini EH, et al. Estimates of the prevalence of arthritis and selected musculoskeletal disorders in the United States. Arthritis Rheum 1998; 41: 77899.
  • 3
    Creamer P, Hochberg MC. Osteoarthritis. Lancet 1997; 350: 5038.
  • 4
    Davis MA. Epidemiology of osteoarthritis. Clin Geriatr Med 1988; 4: 24155.
  • 5
    Guccione AA, Felson DT, Anderson JJ. Defining arthritis and measuring functional status in elders: methodological issues in the study of disease and physical disability. Am J Public Health 1990; 80: 9459.
  • 6
    Hurley MV. Quadriceps weakness in osteoarthritis. Curr Opin Rheumatol 1998; 10: 24650.
  • 7
    Davis MA, Ettinger WH, Neuhaus JM, Mallon KP. Knee osteoarthritis and physical functioning: evidence from the NHANES I Epidemiologic Followup Study. J Rheumatol 1991; 18: 5918.
  • 8
    Felson DT, Naimark A, Anderson J, Kazis L, Castelli W, Meenan RF. The prevalence of knee osteoarthritis in the elderly: the Framingham Osteoarthritis Study. Arthritis Rheum 1987; 30: 9148.
  • 9
    Guccione AA, Felson DT, Anderson JJ, Anthony JM, Zhang Y, Wilson PW, et al. The effect of specific medical conditions on the functional limitations of elders in the Framingham Study. Am J Public Health 1994; 84: 3518.
  • 10
    Kelsey JL. Prevalence studies of the epidemiology of osteoarthritis. In: LawrenceRC, SaulmanLE, editors. Current topics in rheumatology: epidemiology of the rheumatic diseases. New York: Gower Medical; 1984. p. 2828.
  • 11
    Verbrugge LM, Lepkowski JM, Konkol LL. Levels of disability among US adults with arthritis. J Gerontol 1991; 46: 57183.
  • 12
    Slemenda C, Brandt KD, Heilman DK, Mazzuca S, Braunstein EM, Katz BP, et al. Quadriceps weakness and osteoarthritis of the knee. Ann Intern Med 1997; 127: 97104.
  • 13
    O'Reilly SC, Jones A, Muir KR, Doherty M. Quadriceps weakness in knee osteoarthritis: the effect on pain and disability. Ann Rheum Dis 1998; 57: 58894.
  • 14
    Felson DT, Anderson JJ, Naimark A, Walker AM, Meenan RF. Obesity and knee osteoarthritis. Ann Intern Med 1988; 109: 1824.
  • 15
    Hannan MT, Anderson JJ, Pincus T. Educational attainment and osteoarthritis: differential associations with radiographic changes and symptom reporting. J Clin Epidemiol 1992; 45: 13947.
  • 16
    Forbes WF, Hayward LM, Agwani N. Factors associated with the prevalence of various self-reported impairments among older people residing in the community. Can J Public Health 1991; 82: 2404.
  • 17
    Verbrugge LM, Gates DM, Ike RW. Risk factors for disability among US adults with arthritis. J Clin Epidemiol 1991; 44: 16782.
  • 18
    Verbrugge LM, Lepkowski JM, Imanaka Y. Comorbidity and its impact on disability. Milbank Q 1989; 67: 45084.
  • 19
    Hadler NM. Knee pain is the malady—not osteoarthritis. Ann Intern Med 1992; 116: 5989.
  • 20
    Folstein MF, Folstein SE, McHugh PR. Mini-mental state: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12: 18998.
  • 21
    Rejeski WJ, Ettinger WH, Shumaker S, James P, Burns R, Elam JT. Assessing performance-related disability in patients with knee osteoarthritis. Osteoarthritis Cartilage 1995; 3: 15767.
  • 22
    Ettinger WH, Burns R, Messier SP, Applegate W, Rejeski WJ, Morgan T, et al. The Fitness Arthritis and Seniors Trial: a randomized trial comparing aerobic exercise and resistance exercise to a health education program on physical disability in older people with knee osteoarthritis. JAMA 1997; 277: 2531.
  • 23
    Felson DT, McAlindon TE, Anderson JJ, Naimark A, Weissman BW, Aliabadi P, et al. Defining radiographic osteoarthritis for the whole knee. Osteoarthritis Cartilage 1997; 5: 24150.
  • 24
    Rejeski WJ, Ettinger WH, Shumaker S, Heuser MD, James P, Monu J, et al. The evaluation of pain in patients with knee osteoarthritis: the knee pain scale. J Rheumatol 1995; 22: 11249.
  • 25
    Jensen RC, Warren B, Laursen C, Morrissey MC. Static pre-load effect on knee extensor isokinetic concentric and eccentric performance. Med Sci Sports Exerc 1991; 23: 104.
  • 26
    Kramer JF, Vax MD, Hakansson D. Effect of activation force on knee extensor torques. Med Sci Sports Exerc 1991; 23: 2317.
  • 27
    Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics 1982; 38: 96374.
  • 28
    Ware JH, Dockery D, Louis TA, Xu XP, Ferris BG Jr, Speizer FE. Longitudinal and cross-sectional estimates of pulmonary function decline in never-smoking adults. Am J Epidemiol 1990; 132: 685700.
  • 29
    Laird NM, Donnelly C, Ware JH. Longitudinal studies with continuous responses. Stat Methods Med Res 1992; 1: 22547.
  • 30
    Diggle PJ, Liang K-Y, Zeger SL. Analysis of longitudinal data. Oxford (UK): Clarendon Press; 1994.
  • 31
    Hawley DJ, Wolfe F, Cathey MA, Roberts FK. Marital status in rheumatoid arthritis and other rheumatic disorders: a study of 7,293 patients. J Rheumatol 1991; 18: 65460.
  • 32
    Cunningham LS, Kelsey JL. Epidemiology of musculoskeletal impairments and associated disability. Am J Public Health 1984; 74: 5749.
  • 33
    Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research. J Pers Soc Psychol 1986; 51: 117382.
  • 34
    O'Reilly SC, Jones A, Muir KR, Doherty M. Quadriceps weakness in knee osteoarthritis: the effect on pain and disability. Ann Rheum Dis 1998; 57: 58894.
  • 35
    Stokes M, Young A. The contribution of reflex inhibition to arthrogenous muscle weakness. Clin Sci (Colch) 1984; 67: 714.
  • 36
    Fisher NM, Pendergast DR, Gresham GE, Calkins E. Muscle rehabilitation: its effect on muscular and functional performance of patients with knee osteoarthritis. Arch Phys Med Rehabil 1991; 72: 36774.
  • 37
    McAlindon TE, Snow S, Cooper C, Dieppe PA. Radiographic patterns of osteoarthritis of the knee joint in the community: the importance of the patellofemoral joint. Ann Rheum Dis 1992; 51: 8449.