Skip to main content
NCBI home page
ACR Open Rheumatology logoLink to ACR Open Rheumatology
. 2019 Apr 6;1(2):104–112. doi: 10.1002/acr2.1013

Association between Pre‐intervention Physical Activity Level and Treatment Response to Exercise Therapy in Persons with Knee Osteoarthritis—An Exploratory Study

Alison H Chang 1, Jungwha Lee 1, Jing Song 1, Lori Lyn Price 2, Augustine C Lee 3, Kieran F Reid 4, Roger A Fielding 4, Jeffrey B Driban 3, William C Harvey 3, Chenchen Wang 3
PMCID: PMC6857980  NIHMSID: NIHMS1016783  PMID: 31763622

Abstract

Objective

Examine whether pre‐intervention physical activity (PA) level is associated with achieving a positive treatment response of pain and/or function improvement after a 12‐week exercise intervention in participants with knee osteoarthritis (OA).

Methods

We performed a secondary analysis of a randomized, single‐blind comparative effectiveness trial showing similar treatment effects between Tai Chi mind‐body exercise and standard physical therapy intervention for knee OA. Baseline PA was assessed by a Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire and, in a subsample, by tri‐axial accelerometers. The Outcome Measures in Rheumatoid Arthritis Clinical Trials–Osteoarthritis Research Society International (OMERACT‐OARSI) dichotomous responder criteria was used for clinically meaningful improvement at follow‐up. Associations between baseline self‐reported PA by the CHAMPS questionnaire and outcomes of responders vs. nonresponders (reference group) were assessed using logistic regressions, adjusting for demographic covariates. We compared objectively measured PA by accelerometry between responders vs. nonresponders using Wilcoxon tests.

Results

Our sample consisted of 166 participants with knee OA who completed both baseline and 12‐week postintervention evaluations: mean age 60.7 year (SD 10.5), body mass index 32.4 kg/m2 (6.9), 119 (72%) women, and 138 (83%) OMERACT‐OARSI responders. Neither time spent in total PA [odds ratio (OR) 1.00; 95% confidence interval (CI) 0.96, 1.03] nor time in moderate‐to‐vigorous PA (OR 1.01; 95% CI 0.93, 1.09) at pre‐intervention were associated with being a responder. Similar findings were observed in 42 accelerometry sub‐cohort participants.

Conclusion

Pre‐intervention PA levels (subjective report or objective measurement) were not associated with individuals achieving favorable treatment outcomes after a 12‐week exercise intervention, which suggests that regardless of pre‐intervention PA level, individuals will likely benefit from structured exercise interventions.

Keywords: exercise, OMERACT, osteoarthritis, physical activity

Introduction

Among Americans 55 years and older, 40% have frequent knee pain or radiographic knee osteoarthritis (OA) 1. Knee OA is one of the leading causes of activity limitation and disability among adults 2, 3. In the elderly, knee OA is responsible for as much chronic disability as cardiovascular disease 4. There is no cure for OA; current nonsurgical management guidelines recommend exercise, weight management, and biomechanical interventions to reduce symptoms and preserve function 5. Although it is well accepted that exercise therapy leads to improvements in pain, physical function, and quality of life, the reported treatment success varies, possibly because of variances in therapy intensity or dosage 6, 7, 8 and substantial heterogeneity in disease severity, age, body mass index (BMI), and pre‐intervention movement mechanics and activity levels 9, 10, 11. Identifying characteristics that enhance or diminish treatment response would facilitate a more tailored approach to exercise intervention and optimize efficacy and minimize adverse events.

Regular physical activity (PA) provides many general health benefits and has been shown to reduce pain and improve physical function for knee OA. Despite the well‐documented benefits, adults with knee OA are largely inactive 12, 13. Efforts have been directed to increase levels of PA in this population through patient education, behavioral intervention, group‐based walking and/or exercise programs, and individual therapy sessions 14, 15, 16, 17. PA monitoring is also advocated for cohort studies and clinical trials in knee OA in order to track mobility and well‐being in the context of meaningful real‐life behaviors outside the clinical or research settings 15, 18, 19, 20.

Exercise is a planned, structured, and purposeful form of PA. PA level prior to exercise intervention may influence responses to treatment. In theory, physically inactive individuals may benefit from engaging in a regular structured exercise regime and thus achieve improvement in pain and physical function. Alternatively, baseline inactivity, which may signal poor general health and a sedentary lifestyle, could temper the benefits of exercise. It is also plausible that being more physically active at baseline may amplify or diminish the effects of exercise on pain and function. Whether pre‐intervention PA level is associated with a favorable treatment response to exercise therapy in persons with knee OA is unknown. Better understanding of the effect of diverging pre‐intervention activity levels on treatment response would inform future exercise trial design in participant selection and treatment stratification, and ultimately prioritize interventions in patients who will benefit most. We tested the hypothesis that pre‐intervention PA level is associated with achieving a positive treatment response after a 12‐week exercise intervention in participants with knee OA.

Methods

Study Design and Participants

We conducted a secondary analysis of a randomized 52‐week, single‐blind, comparative effectiveness trial showing similar positive treatment effects between Tai Chi mind‐body exercise and standard physical therapy interventions for knee OA 21. We enrolled participants aged 40 years or older who met all of the following three criteria. First, they met the American College of Rheumatology criteria for symptomatic knee OA 22 (pain occurring on 50% or more of the days of the past month during at least one of the activities of walking, going up/down stairs, standing upright, or lying in bed at night). Second, they had radiographic evidence of tibiofemoral and/or patellofemoral OA (Kellgren/Lawrence grade 2 or greater, ie, definite osteophyte in the tibiofemoral and/or patellofemoral compartment) in at least one knee. Third, all participants reported knee pain that was 40 or greater on at least one of the five questions in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale (each question being scored between 0 and 100, with higher scores indicating worse pain). Participants were excluded if they had prior experience either with Tai Chi and other similar types of complementary and alternative therapy or with physical therapy program for knee OA in the past year; serious medical conditions; any intra‐articular steroid injections or reconstructive surgery in the past 3 months or any intra‐articular hyaluronic acid injections in the past 6 months; cognitive impairment (Mini‐Mental Status Exam score of less than 24); or if they were unable to walk without a cane or other assistive devices for the baseline assessment. Participants were randomized into Tai Chi (two times per week for 12 weeks) or physical therapy (two times per week for 6 weeks, followed by 6 weeks of monitored home exercise) treatment arm. At the 12‐week follow‐up, both groups showed similar improvements in WOMAC pain score, and the benefits maintained up to 52 weeks 22.

Pre‐Intervention PA Levels

Pre‐intervention PA levels were assessed using both the self‐reported Community Healthy Activities Model Program for Seniors (CHAMPS) PA questionnaire and objectively measured tri‐axial accelerometry. CHAMPS 23 is a 41‐item questionnaire measuring weekly PA levels for older adults by computing total hours per week spent on various common activities. It includes activities of all intensity levels typically undertaken by older adults for exercise, recreation, and daily living, such as walking, swimming, attending a movie, playing cards, visiting friends, and going to church or senior centers. Higher scores reflect greater PA. The recall timeframe is “a typical week during the past 4 weeks.” A reliable and valid 24, 25, 26 measure for self‐reported PA, CHAMPS has been widely used in capturing activity levels for seniors in observational and interventional studies. Activities listed in the CHAMPS questionnaire were assigned a metabolic equivalent (MET) value specific for older adults. Among total activities (hr/wk), moderate‐to‐vigorous (MV) intensity activities (hr/wk) are activities requiring 3 or more MET values. The pre‐intervention self‐reported PA levels were assessed as hours per week spent in total PA and in MV intensity PA.

In a subset of participants, objectively measured PA was captured by a tri‐axial accelerometer (ActiGraph GT3X), which was worn superior to the iliac crest in a custom pouch and secured to the waist belt by a Velcro fastener. Participants were instructed to wear the device for a consecutive 7‐day period, except during sleep, showers, bathing, swimming, or other water activities. A participant log was recorded when the GT3X was worn. Providing activity counts as a composite vector magnitude of three orthogonal axes, the GT3X accelerometer has been shown to be a valid and reliable measure for PA when examined against a previous accelerometer model as well as whole‐body indirect calorimetry 27, 28, 29. Analyses were restricted to participants with at least three valid monitoring days (ie, worn at least 10 hr/day) 30, 31. Using modified Freedson 27 vector magnitude counts per minute, light intensity PA cut‐points are 200‐2689, and MV intensity PA cut‐points are 2690 or greater. To account for variability in daily monitoring time, we standardized these PA measures to 16 hours of wear time per day. For individuals with seven valid days of monitoring, weekly activity minutes spent at each intensity level were the sum of the seven standardized daily total minutes for each intensity level; for individuals with less than seven valid days of monitoring, weekly activity minutes spent at each intensity level were estimated by multiplying seven to the average daily activity minutes over the valid days 32. To enable comparisons between self‐reported PA by CHAMPS and objectively measured PA by accelerometry, we converted GT3X weekly activity minutes to hours.

Treatment Response to Exercise Therapy

We used the Outcome Measures in Rheumatoid Arthritis Clinical Trials–Osteoarthritis Research Society International (OMERACT‐OARSI) responder criteria 33 to define clinically meaningful improvement after the 12‐week exercise intervention. Figure 1 shows the algorithm for determining dichotomous response to exercise therapy (responders vs. nonresponders). The WOMAC is a validated, self‐administered, visual analogue scale specifically designed to evaluate pain for knee and hip OA 34. The visual analogue scale version of WOMAC pain subscore has a range of 0 to 500, and the function subscore has a range of 0 to 1700, with higher scores indicating worse status. The Patient Global Assessment of disease activity is a visual analogue scale that measures the level of knee OA severity on a 10‐point scale, where 0 indicates no disease activity and 10 indicates the most extreme severity. In our study, WOMAC pain and function subscores and the Patient Global Assessment score were each assessed as a person‐based measure and converted to a scale of 0 to 100 at baseline and 12‐week follow‐up.

Figure 1.

Figure 1

Open in a new tab

Outcome Measures in Rheumatoid Arthritis Clinical Trials‐Osteoarthritis Research Society International (OMERACT‐OARSI) responder criteria for defining clinically meaningful improvement at the end of exercise intervention (12 weeks).

Statistical Analysis

We summarized pre‐intervention baseline characteristics of the entire analysis sample and the responders vs. nonresponders subgroups. Two‐sample Wilcoxon rank sum tests were used to compare PA measures between responders vs. nonresponders. We performed person‐based multiple logistic regressions to assess the associations between baseline self‐reported PA level by CHAMPS and dichotomized outcomes of treatment responders vs. nonresponders, adjusting for age, sex, and BMI 35. The assumption of linearity between predictors and logit of binary outcomes was checked before conducting logistic regressions. Results for each model were summarized as unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs); results were considered to be statistically significant if the 95% CI did not include the value 1. To explore whether treatment arm impacts these relations, we carried out additional sensitivity analyses to evaluate the patterns of associations in the Tai Chi group only and in the physical therapy group only. In a subgroup of participants with accelerometry data, we compared baseline, objectively measured PA levels between treatment responders vs. nonresponders using the two‐sample Wilcoxon rank sum tests. The small sample size precluded multiple logistic regression models in the accelerometry subgroup. We also evaluated whether the self‐reported PA levels by the CHAMPS questionnaire are related to objectively measured levels by accelerometry using Pearson correlations. SAS Version 9.3 was used for all analyses.

Results

Among 204 participants with symptomatic and radiographic tibiofemoral and/or patellofemoral OA, randomized to Tai Chi or physical therapy interventions, 167 (87 in Tai Chi and 80 in Physical Therapy group) completed both baseline and 12‐week postintervention assessments. Reasons for not completing the 12‐week assessments included: lost interest (n = 2); pre‐existing pain in other body regions other than the knee (n = 3); time constraints (n = 4); preferred to be in the other intervention arm (n = 1); lost to follow‐up (n = 24); other reasons (n = 3). One participant had missing CHAMPS data, leaving our final secondary analysis a sample of 166 persons.

Self‐reported PA by CHAMPS

Table 1 summarizes pre‐intervention baseline sample characteristics. Among the 166 participants, 138 (83.1%) were OMERACT‐OARSI responders. The responders did not differ from nonresponders in baseline age, BMI, sex, Kellgren‐Lawrence (K/L) grade (worse between two knees), WOMAC pain and function, chronic pain self‐efficacy, and depression (Table 1). Table 2 shows the medians and interquartile ranges of respective time spent in total PA and in MV intensity PA, quantified by CHAMPS questionnaire, between the responders and nonresponders. In the fully adjusted regression models (Table 2), there was neither association between pre‐intervention total PA and being a responder to exercise therapy (OR 1.00; 95% CI 0.96, 1.03) nor association of MV intensity PA with being a responder (OR 1.01; 95% CI 0.93, 1.09). We alternatively examined whether being in the bottom or middle tertile of PA (reference group: top tertile) was associated with treatment response and found similar null effects (ie, nonsignificant ORs). Intervention group assignment could potentially impact the PA‐treatment response relationship. We repeated these analyses, separately treating PA as a continuous predictor and as a categorical predictor in the Tai Chi group only and in the physical therapy group only; we found similar null effects (ie, nonsignificant ORs) in both groups. Post hoc analyses applying an alternative definition of treatment response (separately by pain improvement only and by function improvement only) minimally changed our findings.

Table 1.

Baseline characteristics of the analysis sample

Entire Sample n = 166 Responders n = 138 Nonresponders n = 28
Number (%) or mean ± SD
Age (years) 60.7 ± 10.5 61.3 ± 10.7 57.6 ± 9.0
BMI (kg/m2) 32.4 ± 6.9 32.1 ± 6.7 34.2 ± 7.8
Female 119 (71.7%) 102 (73.9%) 17 (60.7%)
K/L grade of the worse knee (n = 164, 136 responders)
0a 3 (1.8%) 3 (2.2%) 0 (0%)
1a 8 (4.9%) 6 (4.4%) 2 (7.1%)
2 66 (40.2%) 55 (40.4%) 11 (39.3%)
3 57 (34.8%) 47 (34.6%) 10 (35.7%)
4 30 (18.3%) 25 (18.4%) 5 (17.9%)
WOMAC Pain (0‐500), higher indicates worse pain 253.3 ± 100.7 253.0 ± 96.4 254.9 ± 121.4
WOMAC Physical Function (0‐1700), higher indicates worse function 885.4 ± 367.3 888.5 ± 362.8 870.3 ± 395.4
Chronic Pain Self‐Efficacy (1‐10), higher indicates better status 6.3 ± 2.1 6.5 ± 2.0 5.3 ± 2.3
Beck Depression Inventory‐II (0‐63), higher indicates worse symptoms 7.7 ± 8.6 7.1 ± 8.3 10.6 ± 9.6
CHAMPS – Total activities (hr/wk) 17.5 ± 12.2 17.6 ± 11.6 16.9 ± 14.8
CHAMPS – MV intensity activities (hr/wk) 5.5 ± 6.0 5.7 ± 5.9 4.8 ± 6.6
Open in a new tab

Abbreviation: BMI, body mass index; CHAMPS = Community Health Activities Model Program for Seniors; K/L = Kellgren/Lawrence; MV = moderate‐to‐vigorous; WOMAC = Western Ontario and McMaster Universities Arthritis Index.

a

Knees had definite osteophytes (K/L grade 2) in the patellofemoral compartment, but K/L grades 0 or 1 in the tibiofemoral compartment.

Table 2.

Pre‐intervention baseline self‐reported physical activity level (by CHAMPS questionnaire) and treatment response to exercise therapy (by OMERACT‐OARSI responder criteria) (n = 166)

Total Activities MV Intensity Activities
Median (IQR), hr/wk

Responders

(n = 138, 83%)

 16.0 (14.0) 4.0 (9.0)

Nonresponders

(n = 28, 17%)

 13.0 (19.0) 2.0 (6.5)
P valuea 0.21 0.30
Associations of baseline physical activity (per 1 hr/wk) with responders (reference group: nonresponders) Odds ratiosb (95% CIs), P value for trend
Unadjusted 1.01 (0.97, 1.04), P = 0.76 1.03 (0.96, 1.11), P = 0.46
Adjusted for age, sex, and BMI 1.00 (0.96, 1.03), P = 0.82 1.01 (0.93, 1.09), P = 0.83
Open in a new tab

Abbreviations: CHAMPS, Community Health Activities Model Program for Seniors; CI, confidence interval; IQR, interquartile range; MV, moderate‐to‐vigorous; OMERACT‐OARSI, Clinical Trials Response Criteria and the Outcome Measures in Rheumatology – Osteoarthritis Research Society International.

a

Two‐sample Wilcoxon rank sum test comparing responders with nonresponders.

b

Odds ratio with 95% CI excluding 1 indicates statistical significance.

Objectively measured PA by accelerometry

Next, we examined PA recorded by accelerometry in a subgroup. Table 3 summarizes pre‐intervention baseline sample characteristics of 42 participants in the accelerometry subgroup. The accelerometry subgroup of 42 participants did not differ from the 124 participants without accelerometry data in age, BMI, % female, K/L grade distribution, WOMAC pain and function scores, self‐efficacy, and depression. The small sample size limited our ability to perform logistic regressions and adjust for covariates. Similar to the results characterizing PA by CHAMPS, which were based on two‐sample Wilcoxon rank sum tests, there were no significant differences in the time spent in total, light, and MV‐intensity activity between responders and nonresponders (Table 4). In a sensitivity analysis of the accelerometry data using a widely established cut point, we dichotomized MV intensity activity into meeting (at least 150 unbouted min/wk in MV intensity activity) (n = 25) versus not meeting (n = 17) the recently published PA guideline 36 and found that meeting the guideline was not related to treatment response. Post hoc analyses applying an alternative definition of treatment response (separately by pain improvement only and by function improvement only) minimally changed our findings.

Table 3.

Baseline characteristics of the accelerometry subgroup

Entire Sample n = 42 Responders n = 37 Nonresponders n = 5
Number (%) or median ± IQR
Age (years) 60.5 ± 15.0 61.0 ± 9.0 55.0 ± 18.0
BMI (kg/m2) 30.1 ± 11.1 30.0 ± 11.1 30.3 ± 2.4
Female 30 (71.4%) 28 (75.7%) 2 (40%)
K/L grade of the worse knee
0a 1 (2.4%) 1 (2.7%) 0
1a 2 (4.8%) 2 (5.4%) 0
2 19 (45.2%) 17 (46.0%) 2 (40.0%)
3 11 (26.2%) 10 (27.0%) 1 (20.0%)
4 9 (21.4%) 7 (18.9%) 2 (40.0%)
WOMAC Pain (0‐500), higher indicates worse pain 243.1 ± 141.4 246.0 ± 138.3 240.1 ± 128.6
WOMAC Physical Function (0‐1700), higher indicates worse function 880.8 ± 607.5 843.0 ± 592.5 1069.3 ± 741.2
Chronic Pain Self‐Efficacy (1‐10), higher indicates better status 6.8 ± 3.9 7.1 ± 3.5 4.1 ± 2.8
Beck Depression Inventory‐II (0‐63), higher indicates worse symptoms (n = 40) 6.0 ± 10.5 5.0 ± 9.0 13.0 ± 9.0
CHAMPS – Total activities (hr/wk) 13.5 ± 13.0 13.0 ± 12.0 18.0 ± 17.0
CHAMPS – MV intensity activities (hr/wk) 3.5 ± 7.0 4.0 ± 5.0 0.0 ± 3.0
Accelerometry – Total activities (hr/wk) 41.3 ± 15.0 41.8 ± 12.1 32.6 ± 21.5
Accelerometry – MV intensity activities (hr/wk) 3.8 ± 5.1 3.9 ± 5.2 2.2 ± 0.6
Accelerometry – Light intensity activities (hr/wk) 36.5 ± 13.6 36.5 ± 9.9 30.4 ± 20.8
Open in a new tab

Abbreviation: BMI, body mass index; CHAMPS = Community Health Activities Model Program for Seniors; IQR = interquartile range; K/L = Kellen/Lawrence; MV = moderate‐to‐vigorous; WOMAC = Western Ontario and McMaster Universities Arthritis Index.

a

Knees had definite osteophytes (K/L grade 2) in the patellofemoral compartment, but K/L grades 0 or 1 in the tibiofemoral compartment.

Table 4.

Pre‐intervention baseline objectively measured physical activity level (by accelerometry) and treatment response to exercise therapy (by OMERACT‐OARSI responder criteria) (n = 42)

Total Activities (Light + MV Intensity) Light‐Intensity Activities MV‐Intensity Activities
Median (IQR), hr/wk

Responders

(n = 37, 86%)

 41.8 (12.1) 36.5 (9.9) 3.9 (5.2)

Nonresponders

(n = 5, 14%)

 32.6 (21.5) 30.4 (20.8) 2.2 (0.6)
P valuea 0.32 0.36 0.27
Open in a new tab

Abbreviation: IQR, interquartile range; MV, moderate‐to‐vigorous; OMERACT‐OARSI, Clinical Trials Response Criteria and the Outcome Measures in Rheumatology – Osteoarthritis Research Society International.

a

Two‐sample Wilcoxon rank sum test comparing responders with nonresponders.

Among 42 participants with both CHAMPS and accelerometry data, there was no significant correlation in total PA between these two measures (r = 0.06, p = 0.70). Participants markedly underestimated their total activity level [median (interquartile range (IQR)): 13.5 (13.0) hr/wk by CHAMPS vs. 41.3 (15.0) hr/wk by accelerometry]. There was no significant correlation in MV intensity activity (r = 0.16, p = 0.29). Nonetheless, the average MV intensity activity level was fairly comparable between CHAMPS and accelerometry [median (IQR): 3.5 (7.0) hr/wk by CHAMPS vs. 3.8 (5.1) hr/wk by accelerometry].

Discussion

Pre‐intervention PA level, quantified by either subjective report by CHAMPS questionnaire or objective measurement by accelerometry, was not significantly associated with whether an individual will achieve favorable treatment outcomes after a 12‐week exercise intervention. To our knowledge, this is the first study exploring the relationship between baseline PA and treatment response to exercise interventions delivered in a randomized controlled trial for persons with symptomatic, radiographic knee OA. These findings suggest that regardless of pre‐intervention PA level, individuals with knee OA will likely benefit from structured exercise interventions.

In our study, the average self‐reported total activities and MV intensity activities by CHAMPS were 17.5 (SD, 12.2) and 5.5 (SD, 6.0) hr/wk, respectively, which are comparable to what have been reported in the literature 37, 38, 39. Among 150 community‐dwelling older adults (65 years or older), the total PA by CHAMPS was 19.9 (SD, 10.1) hr/wk and the MV intensity PA was 5.7 (SD, 5.5) hr/wk 37. Another study of seniors (71‐86 years old) showed 13.7 (SD, 9.0) hr/wk of total PA and 3.0 (SD, 4.0) hr/wk of MV intensity PA by CHAMPS 38. After participating in a PA promotion program, 575 previously underactive individuals (50 years or older) achieved a CHAMPS total PA of 12.1 (SD, 19.7) hr/wk and MV intensity PA of 5.1 (SD, 10.1) hr/wk 39.

The overwhelming benefits of exercise on physical and mental health have been well documented. Our findings support the universal positive impact of exercise therapy for individuals with knee OA, regardless of pre‐participation PA levels. Similarly, a recent report of patients with systolic heart failure found comparable benefits of exercise training on exercise capacity, mortality, and hospitalization across all baseline self‐reported PA tertiles 40. These observations reinforce that exercise training should be an integral part of therapeutic strategies for all older adults with chronic health conditions, even in those who are already physically active prior to participation. It is unknown whether each participant increased, maintained, or decreased their PA levels after exercise intervention. Additional information on posttherapy PA may shed light on plausible mechanisms of why exercise intervention worked for both inactive and active individuals.

Although self‐reported PA provides nuanced information regarding the type of activities one is engaged in, it is subject to reporting biases, such as imprecise recall and influence of social desirability 41, 42. In agreement with previous studies 43, 44, we found weak correlations between self‐reported and objectively measured PA in both total and MV intensity activities. Comparing CHAMPS with accelerometry among seniors (mean age = 75 years), Hekler and colleagues observed a trend of overreporting in both total and MV intensity PA 26. Interestingly, in our younger cohort (mean age = 62 years), we observed underreporting of total PA (median of 13.5 hr/wk by CHAMPS vs. 41.3 hr/wk by accelerometry) and comparable self‐estimation of MV intensity PA (median of 3.5 hr/wk by CHAMPS vs. 3.8 hr/wk by accelerometry).

MV‐intensity PA is quantified by activities requiring 3 or more MET values in both CHAMPS and accelerometry measures. Sharing an established threshold for MV intensity, PA may have contributed to the comparable weekly hours between these two measures. The discrepancy in total PA (sum of time spent in light and MV‐intensity PA) likely resulted from lower CHAMPS‐recorded time in light‐intensity PA. Items in the CHAMPS questionnaire were developed to specifically focus on various types of purposeful activities, such as walking briskly, cycling, swimming, gardening, and heavy or light household chores, rather than assessing all physical movements. It is plausible that numerous nonpurposeful light‐intensity physical movements, such as walking to the kitchen or to the bedroom located on the second floor, were not reflected in the CHAMPS report but recorded by accelerometry. These findings potentially question the common belief that people tend to overestimate their PA when queried by a questionnaire. The relationship between self‐reported versus objectively measured PA may be more nuanced. Future larger‐scale studies may further elucidate these relations.

One of the strengths of our study is applying the OMERACT‐OARSI responder criteria to define a favorable response to 12‐week exercise interventions. Based on multiple domains that represent clinically meaningful improvements after treatment, OMERACT‐OARSI responder criteria were developed and recommended as an optimal, simplified set of responder criteria for OA clinical trials 33. This approach classifies patients as responders vs. nonresponders using a combination of absolute and relative changes in WOMAC pain, WOMAC function, and Patient Global Assessment. Considering the combined effects of three primary patient‐reported outcomes and accounting for the pre‐intervention status by assessing changes, OMERACT‐OARSI responder criteria provides a more comprehensive and meaningful assessment of treatment outcomes than a single outcome alone 45.

Recognizing the potential limitation of relying on self‐reported PA as a predictor in our analysis, we performed secondary analysis using objectively measured accelerometry data available in a subset of participants. The results were similar. It should be acknowledged that the small sample size of the accelerometry sub‐cohort is not optimal for adjusting for covariates and may limit the power of detecting significances. The current study has other limitations. Our study sample consisted of individuals with symptomatic, radiographic knee OA, so the findings may not be generalizable to the general population. Aligning with the overwhelming evidence that exercise intervention improves outcomes in the setting of knee OA 46, 47, more than 80% of our study participants had a favorable outcome. Increasing the number of nonresponders may potentially alter the results. However, our findings are consistent with those of a recent noncontrolled exercise intervention study for persons with knee pain, suggesting that similar pain relief was observed regardless of the initial self‐reported PA levels 48. It is important to note that, following the recently published 2018 PA guideline 36, the MV activity minutes we reported here are total MV time, not “bouted” (MV intensity PA accumulated in bouts lasting 10 minutes or more). Several factors could have contributed to the higher weekly MV‐intensity PA hours reported in our study. First, we calculated total “unbouted” MV‐intensity PA minutes, rather than the legacy “bouted” minutes; they are not directly comparable. Second, the composite vector magnitude (tri‐axial) method used in our study could potentially yield higher MV intensity PA than vertical axis data alone 49. Third, our study sample was younger (mean age = 62) than the Women's Health study 49 (mean age = 71) or the Osteoarthritis Initiative study 50 (mean age = 65). Future clinical trials with a larger sample of accelerometry data will further elucidate these relationships. Finally, waist‐mounted tri‐axial accelerometers do not capture water activities and may underestimate vertical acceleration/deceleration activities, such as cycling or weightlifting; however, these particular activities are queried in the CHAMPS questionnaire.

In summary, pre‐intervention PA level, quantified by either subjective report by CHAMPS questionnaire or objective measurement by accelerometry, did not predict whether an individual will achieve favorable treatment outcomes after a 12‐week exercise intervention for persons with knee OA. Our findings suggest that, in the setting of knee OA, structured exercise interventions can be beneficial even for physically active individuals.

Author contributions

Each author participated in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. All authors have access to the data in the study and can take responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design

Chang, J. Lee, and Wang

Acquisition of data

Reid, Fielding, Driban, Harvey, and Wang

Analysis and interpretation of data

Chang, J. Lee, Song, Price, A. Lee, Reid, Fielding, Driban, Harvey, and Wang

Acknowledgments

The authors thank the study participants for their contribution to the study.

Clinicaltrials.gov identifier: NCT01258985.

The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.

Supported by grants from the National Center for Complementary and Integrative Health, National Institute of Health (R01 AT005521 and K24 AT007323) and the National Center for Advancing Translational Sciences (UL1TR001064) at the National Institutes of Health.

1Alison H. Chang, PT, DPT, MS, Jungwha Lee, PhD, MPH, Jing Song, MS: Northwestern University Feinberg School of Medicine, Chicago, Illinois; 2 Lori Lyn Price, MAS, MLA: Tufts Medical Center and Tufts University, Boston, Massachusetts; 3 Augustine C. Lee, MD, Jeffrey B. Driban, PhD, ATC, CSCS, William C. Harvey, MD, MSc, Chenchen Wang, MD, MSc: Tufts Medical Center, Boston, Massachusetts; 4 Kieran F. Reid, PhD, MPH, Roger A. Fielding PhD: Tufts University, Boston, Massachusetts.

The authors have no conflict of interest relevant to the reported work.

References

  • 1. Felson DT, Zhang Y. An update on the epidemiology of knee and hip osteoarthritis with a view to prevention. Arthritis Rheum 1998;41:1343–55. [DOI] [PubMed] [Google Scholar]
  • 2. Cross M, Smith E, Hoy D, Nolte S, Ackerman I, Fransen M, et al. The global burden of hip and knee osteoarthritis: estimates from the Global Burden of Disease 2010 study. Ann Rheum Dis 2014;73:1323–30. [DOI] [PubMed] [Google Scholar]
  • 3. Barbour KE, Helmick CG, Boring M, Brady TJ. Vital signs: prevalence of doctor‐diagnosed arthritis and arthritis‐attributable activity limitation — United States, 2013–2015. MMWR Morb Mortal Wkly Rep 2017;66:246–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Litwic A, Edwards MH, Dennison EM, Cooper C. Epidemiology and Burden of Osteoarthritis. Br Med Bull 2013;105:185–99. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. McAlindon TE, Bannuru RR, Sullivan MC, Arden NK, Berenbaum F, Bierma‐Zeinstra SM, et al. OARSI guidelines for the non‐surgical management of knee osteoarthritis. Osteoarthritis Cartilage 2014;22:363–88. [DOI] [PubMed] [Google Scholar]
  • 6. Juhl C, Christensen R, Roos EM, Zhang W, Lund H. Impact of exercise type and dose on pain and disability in knee osteoarthritis: a systematic review and meta‐regression analysis of randomized controlled trials. Arthritis Rheumatol 2014;66:622–36. [DOI] [PubMed] [Google Scholar]
  • 7. Regnaux JP, Lefevre‐Colau MM, Trinquart L, Nguyen C, Boutron I, Brosseau L, et al. High‐intensity versus low‐intensity physical activity or exercise in people with hip or knee osteoarthritis. Cochrane Database of Systematic Reviews 2015;10:CD010203. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Bennell KL, Hinman RS. A review of the clinical evidence for exercise in osteoarthritis of the hip and knee. J Sci Med Sport 2011;14:4–9. [DOI] [PubMed] [Google Scholar]
  • 9. Lim BW, Hinman RS, Wrigley TV, Sharma L, Bennell KL. Does knee malalignment mediate the effects of quadriceps strengthening on knee adduction moment, pain, and function in medial knee osteoarthritis? A randomized controlled trial. Arthritis Rheum 2008;59:943–51. [DOI] [PubMed] [Google Scholar]
  • 10. Bamman MM, Wick TM, Carmona‐Moran CA, Bridges SL. Exercise medicine for osteoarthritis: research strategies to maximize effectiveness: OA exercise medicine. Arthritis Care Res (Hoboken) 2016;68:288–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Kobsar D, Osis ST, Hettinga BA, Ferber R. Gait biomechanics and patient‐reported function as predictors of response to a hip strengthening exercise intervention in patients with knee osteoarthritis. PLoS One 2015;10:e0139923. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Dunlop DD, Song J, Semanik PA, Chang RW, Sharma L, Bathon JM, et al. Objective physical activity measurement in the osteoarthritis initiative: Are guidelines being met? [Research Support]. Arthritis Rheum 2011;63:3372–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Wallis JA, Webster KE, Levinger P, Taylor NF. What proportion of people with hip and knee osteoarthritis meet physical activity guidelines? A systematic review and meta‐analysis. Osteoarthritis Cartilage 2013;21:1648–59. [DOI] [PubMed] [Google Scholar]
  • 14. Chang RW, Semanik PA, Lee J, Feinglass J, Ehrlich‐Jones L, Dunlop DD. Improving physical activity in arthritis clinical trial (IMPAACT): study design, rationale, recruitment, and baseline data. Contemp Clin Trials 2014;39:224–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Messier SP, Legault C, Mihalko S, Miller GD, Loeser RF, DeVita P, et al. The Intensive Diet and Exercise for Arthritis (IDEA) trial: design and rationale. BMC Musculoskelet Disord 2009;10:93. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Callahan LF, Shreffler JH, Altpeter M, Schoster B, Hootman J, Houenou LO, et al. Evaluation of group and self‐directed formats of the Arthritis Foundation's Walk With Ease Program. Arthritis Care Res (Hoboken) 2011;63:1098–107. [DOI] [PubMed] [Google Scholar]
  • 17. Conn VS, Hafdahl AR, Minor MA, Nielsen PJ. Physical Activity Interventions Among Adults with Arthritis: Meta‐Analysis of Outcomes. Semin Arthritis Rheum 2008;37:307–16. [DOI] [PubMed] [Google Scholar]
  • 18. White DK, Tudor‐Locke C, Felson DT, Gross KD, Niu J, Nevitt M, et al. Walking to meet physical activity guidelines in knee osteoarthritis: is 10,000 steps enough? [Multicenter Study]. Arch Phys Med Rehabil 2013;94:711–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Harding P, Holland AE, Delany C, Hinman RS. Do activity levels increase after total hip and knee arthroplasty? [Clinical Research]. Clin Orthop Relat Res 2014;472:1502–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Fitzgerald GK, Hinman RS, Zeni J Jr, Risberg MA, Snyder‐Mackler L, Bennell KL. OARSI clinical trials recommendations: design and conduct of clinical trials of rehabilitation interventions for osteoarthritis. Osteoarthritis Cartilage 2015;23:803–14. [DOI] [PubMed] [Google Scholar]
  • 21. Wang C, Schmid CH, Iversen MD, Harvey WF, Fielding RA, Driban JB, et al. Comparative effectiveness of Tai Chi versus physical therapy for knee osteoarthritis: a randomized trial. Ann Intern Med 2016;165:77–86. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Altman R, Asch E, Bloch D, Bole G, Borenstein D, Brandt K, et al. Development of criteria for the classification and reporting of osteoarthritis. Classification of osteoarthritis of the knee. Diagnostic and Therapeutic Criteria Committee of the American Rheumatism Association. Arthritis Rheum 1986;29:1039–49. [DOI] [PubMed] [Google Scholar]
  • 23. Stewart AL, Mills KM, King AC, Haskell WL, Gillis D, Ritter PL. CHAMPS physical activity questionnaire for older adults: outcomes for interventions. Med Sci Sports Exerc 2001;33:1126–41. [DOI] [PubMed] [Google Scholar]
  • 24. Harada ND, Chiu V, King AC, Stewart AL. An evaluation of three self‐report physical activity instruments for older adults. Med Sci Sports Exerc 2001;33:962–70. [DOI] [PubMed] [Google Scholar]
  • 25. Cyarto EV, Marshall AL, Dickinson RK, Brown WJ. Measurement properties of the CHAMPS physical activity questionnaire in a sample of older Australians. J Sci Med Sport 2006;9:319–26. [DOI] [PubMed] [Google Scholar]
  • 26. Hekler EB, Buman MP, Haskell WL, Conway TL, Cain KL, Sallis JF, et al. Reliability and validity of CHAMPS self‐reported sedentary‐to‐vigorous intensity physical activity in older adults. J Phys Act Health 2012;9:225–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Sasaki JE, John D, Freedson PS. Validation and comparison of ActiGraph activity monitors. J Sci Med Sport 2011;14:411–6. [DOI] [PubMed] [Google Scholar]
  • 28. Santos‐Lozano A, Santín‐Medeiros F, Cardon G, Torres‐Luque G, Bailón R, Bergmeir C, et al. Actigraph GT3X: validation and determination of physical activity intensity cut points. Int J Sports Med 2013;34:975–82. [DOI] [PubMed] [Google Scholar]
  • 29. Kelly LA, McMillan DG, Anderson A, Fippinger M, Fillerup G, Rider J. Validity of actigraphs uniaxial and triaxial accelerometers for assessment of physical activity in adults in laboratory conditions. BMC Med Phys 2013;13:5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Reid KF, Laussen J, Bhatia K, Englund D, Kirn DR, Price LL, et al. Translating the lifestyle interventions and independence for elders clinical trial to older adults in a real‐world community‐based setting. J Gerontol A Biol Sci Med Sci 2018. E‐pub ahead of print. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Wanigatunga AA, Tudor‐Locke C, Axtell RS, Glynn NW, King AC, McDermott MM, et al. Effects of a long‐term physical activity program on activity patterns in older adults. Med Sci Sports Exerc 2017;49:2167–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Song J, Chang AH, Chang RW, Lee J, Pinto D, Hawker G, et al. Relationship of knee pain to time in moderate and light physical activities: data from osteoarthritis initiative. Semin Arthritis Rheum 2018;47:683–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Pham T, Van Der Heijde D, Lassere M, Altman RD, Anderson JJ, Bellamy N, et al. Outcome variables for osteoarthritis clinical trials: The OMERACT‐OARSI set of responder criteria. J Rheumatol 2003;30:1648–54. [PubMed] [Google Scholar]
  • 34. Bellamy N, Buchanan WW, Goldsmith CH, Campbell J, Stitt LW. Validation study of WOMAC: a health status instrument for measuring clinically important patient relevant outcomes to antirheumatic drug therapy in patients with osteoarthritis of the hip or knee. J Rheumatol 1988;15:1833–40. [PubMed] [Google Scholar]
  • 35. Moons KG, Altman DG, Reitsma JB, Ioannidis JP, Macaskill P, Steyerberg EW, et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med 2015;162:W1–73. [DOI] [PubMed] [Google Scholar]
  • 36. US Department of Health and Human Services . 2008 Physical Activity Guidelines for Americans. URL: https://health.gov/paguidelines/guidelines/.
  • 37. Resnick B, King A, Riebe D, Ory M. Measuring physical activity in older adults: use of the Community Health Activities Model Program for Seniors Physical Activity Questionnaire and the Yale Physical Activity Survey in three behavior change consortium studies. West J Nurs Res 2008;30:673–89. [DOI] [PubMed] [Google Scholar]
  • 38. Pruitt LA, Glynn NW, King AC, Guralnik JM, Aiken EK, Miller G, et al. Use of accelerometry to measure physical activity in older adults at risk for mobility disability. J Aging Phys Act 2008;16:416–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Wilcox S, Dowda M, Griffin SF, Rheaume C, Ory MG, Leviton L, et al. Results of the first year of active for life: translation of 2 evidence‐based physical activity programs for older adults into community settings. Am J Public Health 2006;96:1201–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Mediano MFF, Leifer ES, Cooper LS, Keteyian SJ, Kraus WE, Mentz RJ, et al. Influence of Baseline Physical Activity Level on Exercise Training Response and Clinical Outcomes in Heart Failure: The HF‐ACTION Trial. JACC Heart Fail 2018;6:1011–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Loney T, Standage M, Thompson D, Sebire SJ, Cumming S. Self‐report vs. objectively assessed physical activity: which is right for public health? [Comparative study]. J Phys Act Health 2011;8:62–70. [DOI] [PubMed] [Google Scholar]
  • 42. Dyrstad SM, Hansen BH, Holme IM, Anderssen SA. Comparison of self‐reported versus accelerometer‐measured physical activity. Med Sci Sports Exerc 2014;46:99–106. [DOI] [PubMed] [Google Scholar]
  • 43. Helmerhorst HJ, Brage S, Warren J, Besson H, Ekelund U. A systematic review of reliability and objective criterion‐related validity of physical activity questionnaires. Int J Behav Nutr Phys Act 2012;9:103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Skender S, Ose J, Chang‐Claude J, Paskow M, Brühmann B, Siegel EM, et al. Accelerometry and physical activity questionnaires ‐ a systematic review. BMC Public Health 2016;16:515. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Escobar A, Gonzalez M, Quintana JM, Vrotsou K, Bilbao A, Herrera‐Espiñeira C, et al. Patient acceptable symptom state and OMERACT‐OARSI set of responder criteria in joint replacement. Identification of cut‐off values. Osteoarthritis Cartilage 2012;20:87–92. [DOI] [PubMed] [Google Scholar]
  • 46. Uthman OA, van der Windt DA, Jordan JL, Dziedzic KS, Healey EL, Peat GM, et al. Exercise for lower limb osteoarthritis: systematic review incorporating trial sequential analysis and network meta‐analysis. BMJ 2013;347:f5555. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Skou ST, Pedersen BK, Abbott JH, Patterson B, Barton C. Physical activity and exercise therapy benefit more than just symptoms and impairments in people with hip and knee osteoarthritis. J Orthop Sports Phys Ther 2018;48:439–47. [DOI] [PubMed] [Google Scholar]
  • 48. Skou ST, Bricca A, Roos EM. The impact of physical activity level on the short‐ and long‐term pain relief from supervised exercise therapy and education: a study of 12,796 Danish patients with knee osteoarthritis. Osteoarthritis Cartilage 2018;26:1474–8. [DOI] [PubMed] [Google Scholar]
  • 49. Keadle SK, Shiroma EJ, Freedson PS, Lee IM. Impact of accelerometer data processing decisions on the sample size, wear time and physical activity level of a large cohort study. BMC Public Health 2014;14:1210. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Dunlop DD, Song J, Lee J, Gilbert AL, Semanik PA, Ehrlich‐Jones L, et al. Physical activity minimum threshold predicting improved function in adults with lower‐extremity symptoms. Arthritis Care Res (Hoboken) 2017;69:475–83. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Acr Open Rheumatology are provided here courtesy of Wiley

RESOURCES