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Abstract

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

Objective

To examine whether the associations of physical performance with isometric hip and knee extensors strength and passive hip flexion and internal rotation range of motion (ROM) are nonlinear in community-dwelling adults with hip osteoarthritis (OA).

Methods

Participants were 100 adults (mean age 62 years) with radiographically confirmed hip OA. Physical performance measures included gait speed test and timed stair tests. Piecewise regression models of muscle strength and hip ROM on physical performance measures were used to identify possible breakpoints. Receiver operating characteristic (ROC) curve analysis was used to identify participants with functionally inadequate (≤1.0 meters/second) gait speed and optimal cut points were identified.

Results

Muscle strength and hip ROM were nonlinearly associated with stair measures but not with gait speed measures. The optimal breakpoints and ROC-derived cut points were 1.8–2.5Nm/kg for knee extensors, 1.5–2.1Nm/kg for hip extensors, 25–26° for hip internal rotation ROM, and 109–115° for hip flexion ROM. Muscle strength breakpoints increased monotonically with increasing movement demand.

Conclusion

In individuals with hip OA, the associations between physical performance and measures of muscle strength and hip ROM are less straightforward than previously assumed. These breakpoints and ROC-derived cut points may be useful in identifying individuals for whom interventions that improve muscle strength or hip ROM would be most beneficial.


INTRODUCTION

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

Osteoarthritis (OA) of the hip is a major contributor to physical performance limitations in older adults (1). Specifically, hip OA, along with knee OA, affects the ability to walk and climb stairs more than any other diseases (2). Furthermore, compared with individuals with healthy hips, those with hip OA have strength (torque production) impairments of the hip and knee musculature (3, 4) and range of motion (ROM) limitations of the hip joint (5, 6), and these impairments are important correlates of physical performance (5, 7–9). Overwhelmingly, however, these previous studies (5, 7–9) have focused on linear relationships between physical performance and measures of strength and ROM, with minimal or no regard to possible nonlinear associations. The tendency to assume linear associations is so, despite several previous cross-sectional (10–16) studies not limited to individuals with OA that have demonstrated the contrary, i.e., nonlinear relationships may be the norm rather than the exception. Specifically in these previous studies, measures of muscle strength or joint ROM associated nonlinearly with physical performance such that there was a functional threshold below which the strength/ROM measure and performance were closely related, but beyond which the strength/ROM-performance association attenuated substantially.

Understanding whether similar nonlinear associations exist in individuals with hip OA is important. Thus far, current conservative management guidelines have emphasized muscle strengthening for all patients with hip OA (17); however, studies conducted on muscle strengthening exercises in hip OA have reported only modest treatment effects (18–20). Ostensibly, if muscle performance associations were nonlinear, this may, at least in part, account for the modest effects observed. Furthermore, from a public health perspective, knowledge of the functional strength or ROM thresholds would potentially assist clinicians to better identify individuals who are only mildly disabled by hip OA but who are at risk of mobility decline (i.e., preclinical disability). Indeed, to the extent that preventive interventions would be theoretically effective and relatively easy to be implemented in this specific group of individuals, developing a method to identify them is a worthy endeavor.

Based on these considerations, we initiated this cross-sectional study as a first step to examine whether the associations of physical performance with measures of muscle strength and hip joint ROM are nonlinear in individuals with hip OA. Specifically, we quantified 2 muscle-strength measures, knee and hip extensors strength, and 2 hip ROM measures, hip flexion and internal rotation ROM.

PARTICIPANTS AND METHODS

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

Participants.

The study sample comprised 100 consecutive community-dwelling adults who fulfilled the eligibility criteria. All volunteers lived in Victoria, Australia and responded to advertisements in newspapers and local magazines. Participants were recruited if they had hip or groin pain on most days of the past 1 month, and had radiographic hip OA as confirmed by a radiologist (21). Specifically, radiographic disease severity was assessed using the Kellgren/Lawrence scale, in which higher grades indicate greater severity (22, 23). In this study, only participants with a Kellgren/Lawrence score of 2 or higher were considered to have hip OA. Exclusion criteria included significant back or other joint pain; secondary hip OA due to trauma, inflammatory, or metabolic rheumatic diseases; lower extremity joint replacement; inability to understand English; and the presence of neurologic, cardiac, or other medical conditions that would compromise physical function. The recruitment process is summarized in Figure 1. This research was carried out with approval from the Radiation Advisory Committee at the Department of Human Services and the Human Research Ethics Committee at the University of Melbourne.

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Figure 1. Flowchart of participant recruitment. OA = osteoarthritis.

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Study procedure.

All participants attended a test session at our facility following informed consent. Prior to the physical performance assessment, participants' height, waist circumference, and body mass were obtained. Each participant also completed a set of questionnaires pertaining to, among other things, living arrangements (alone or with others), comorbidities, pain level, and physical activity. Specifically, we obtained information about comorbidities using a checklist of 6 common conditions: hypertension, diabetes, coronary vessel disease, ulcer or stomach disease, pulmonary disease, and cancer (prior). Pain and physical activity were measured using the bodily pain subscale of the Medical Outcomes Study Short Form 36 (SF-36) health survey (24) and the Physical Activity Scale for the Elderly (PASE) (25), respectively. For the PASE, previous studies have demonstrated its strong convergent validity and good test–retest reliability in older adults (25). Total PASE scores range from 0 to >400, with higher scores indicating higher activity levels.

Participants had their symptomatic hip, or the more painful hip in the case of bilateral symptoms, tested. For ease of administrating the battery of tests, and to minimize changing of positions, the physical performance tests (PPTs) were applied before the muscle strength and hip ROM tests.

Physical performance tests.

Each participant completed the timed stair test and the gait speed test. For the timed stair test, we assessed the time taken to climb up and down 6 standardized stairs (step height 18 cm, step depth 30 cm) at both self-selected and fast pace. Handrails were on the right side of the stairs, and participants held them loosely for safety if they wished. For the self-paced stair test, participants were instructed to ascend and descend the stairs in their usual manner. No practice trial was given for this test. For the fast paced stair test, participants were instructed to ascend and descend the stairs as quickly as they could without compromising safety. For this test, each participant performed a practice trial followed by a test trial.

For the gait speed test, participants were timed as they walked an 8-meter walkway at their habitual, self-selected pace. Participants were instructed to “walk at a pace that you consider to be normal,” and each participant performed 2 practice trials followed by 3 walking trials. Using an electronic timing system (Jaycar Electronics, Melbourne, Australia), the time taken to cover the walkway's central 4 meters was measured to eliminate the acceleration or deceleration effects from initiating and stopping the walk. Accordingly, gait speed was computed by dividing the distance (4 meters) by the time taken, and recorded in meters/second. The habitual gait speed averaged over 3 trials was used for analysis.

Muscle strength tests.

Each participant completed the knee and hip extensors strength tests. In each test, following a warm-up comprising 1 submaximal and 1 maximal contraction, all participants performed 2 maximal trials for 5 seconds with a 1-minute rest interval. The higher measurement of 2 valid trials was analyzed. For the knee extensors test, isometric quadriceps torque at 60° of knee flexion was obtained on a KinCom 125-AP isokinetic dynamometer (Chattecx, Chattanooga, TN). Before testing the knee extensors, the gravity compensation procedure was performed by measuring the participant's passive extremity weight at 30° of knee flexion. In order to measure torque values, the distance from the dynamometer ankle cuff force transducer to the dynamometer rotation axis was recorded as the lever arm length. The lever arm length (in meters) was multiplied by the highest maximal voluntary contraction force (N) to obtain muscle torque (Nm). In the present study, knee extensors measurements showed excellent test–retest reliability (intraclass correlation coefficient [ICC] 0.93, SEM 8Nm).

Hip extensor strength was quantified by a modification of the supine hip extensors test introduced by Perry et al (26). We have previously described the methods of this test (27). Briefly, the participant was positioned supine with the involved lower extremity in 20° of hip flexion and aligned perpendicularly to a force transducer (Nidec-Shimpo America, Itasca, IL) that was suspended from the ceiling (27). Before each measurement, the participant was instructed to completely relax the involved extremity, and the force transducer was then set at zero to account for passive extremity weight. To obtain torque measurements, the lever arm length of the hip extensors (the distance from the most prominent aspect of the greater trochanter to the point of force transducer attachment 5 cm proximal to the lateral malleolus) was multiplied by the highest transducer force reading. In the present study, hip extensors measurements showed excellent test–retest reliability (ICC 0.97, SEM 13Nm) (27).

Hip ROM tests.

The methods for obtaining hip internal rotation and flexion ROM have been previously described (27). For the hip internal rotation ROM test, the participant sat on the chair of an isokinetic dynamometer, and the participant's thigh and trunk were stabilized. Hip internal rotation ROM was measured using an electronic inclinometer that was positioned along the distal fibula (27). Before each measurement, the inclinometer was set at zero with the hip maintained in neutral medial and lateral rotation. In the present study, hip internal rotation ROM measurements showed excellent test–retest reliability (ICC 0.93, SEM 3.4°) (27).

For the hip flexion ROM test, the participant was positioned in the supine position, and a strap was applied firmly across the contralateral distal thigh with the intent to constrain pelvic movements during hip flexion. Hip flexion ROM was measured using the electronic inclinometer, which was attached to a long (55 cm) flat metal strip thereby allowing the metal strip to be aligned directly over the femoral landmarks (27). In the present study, hip flexion ROM measurements showed excellent test–retest reliability (ICC 0.97, SEM 3.5°) (27).

Statistical analyses.

For each PPT, a residualized measure was created by predicting the PPT performance from the study covariates: age, sex, SF-36 bodily pain, and PASE (log transformed) scores. For the timed-based PPTs, positive residualized values indicated slower performance than that predicted from the study covariates, while negative values indicated faster performance than predicted. More important, the residualized measures allowed for the examination of the portion of the PPTs associated with the muscle strength or hip ROM measures apart from that associated with the covariates. Least square linear regression and locally weighted regression smoothing technique (lowess) were applied to the relationship between the residualized PPT and measures of body mass–adjusted strength and hip ROM. We used the nonparametric generalized additive models (PROC GAM; SAS, Cary, NC) to perform the lowess analyses, and we formally assessed the difference between the linear and lowess models via a likelihood ratio test. If a difference was found, piecewise regression was applied to model the nonlinear strength/ROM-PPT associations and to estimate the “breakpoint” at which the slope changes. Specifically, the nonlinear relationship was modeled using the piecewise function

  • equation image

where β0 is the intercept, and the breakpoint indicates where the change in slope optimally occurs. Accordingly, the parameter β1 represents the slope below the breakpoint, whereas β12 represents the slope above the breakpoint. We used maximum likelihood estimation methods in the Statistical Package for the Social Sciences (SPSS, Chicago, IL) to determine parameters β0, β1, and β2, and plausible breakpoints. For all piecewise models, we evaluated goodness of fit by plotting the residuals against the fitted values.

To enhance the clinical relevance of our breakpoints, we dichotomized gait speed at 1.0 meters/second and defined a participant as walking at a functionally inadequate speed when his or her habitual gait speed was at or below 1.0 meters/second. We chose this cut point on the basis of the increased risk for mortality and mobility limitations in previous studies (28), and the ability to better compare our results with those of others who have chosen a higher cut point (i.e., 1.2 meters/second) for maximum gait speed (14, 29). Each value of the strength and hip ROM measures was used as a cut point to calculate its sensitivity and specificity in classifying a participant who walked with a functionally inadequate speed. For each measure, receiver operating characteristic (ROC) curves were constructed to depict the tradeoffs between the sensitivity and false positive (1–specificity) test results associated with the different cut points. The overall performance of each ROC curve was evaluated by calculating the area under the curve (AUC), and the optimal cut point was based on the Youden index, which is the value that maximizes the sum of sensitivity and specificity (30). We determined sensitivity, specificity, and positive likelihood ratio for all chosen cut points. For all analyses, 2-tailed P values less than 0.05 were considered to be significant.

RESULTS

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

The sociodemographic and functional characteristics of the participants are summarized in Table 1. The variance explained by the muscle strength and hip ROM measures along with the respective breakpoints, where applicable, are shown in Table 2. With the exception of hip extensor strength, linear regression revealed no significant associations of residualized gait speed with strength and ROM measures (P ≥ 0.08). For the stair-climb measures, chi-square tests for the difference in deviances between the linear and lowess models were significant (P < 0.01), indicating the possibility of different linear relationships between strength/ROM and stair measures for different ranges of strength/ROM. Accordingly, piecewise regression models were fitted to allow different slopes in 2 different strength/ROM ranges (Figures 2 and 3). Across models, the strength and ROM measures explained approximately 10–20% of unique variance in stair-climb time. With the exception of the association between hip internal rotation ROM and fast paced stair measures, piecewise analyses indicated that all strength/ROM PPT associations were statistically nonsignificant above their respective breakpoints. In contrast, strength/ROM PPT associations were statistically significant below the breakpoints. Finally, all residual plots showed a relatively constant variance of the residuals about the regression lines and, therefore, no visual evidence of heteroscedasticity.

Table 1. Sociodemographic, clinical, and functional characteristics of the study participants (n = 100)*
CharacteristicValueRange
  • *

    Values are the mean ± SD unless otherwise indicated. K/L = Kellgren/Lawerence.

Age, years62 ± 1045–85
Female, no.60 
Height, meters1.65 ± 0.091.48–1.92
Body mass, kg76.2 ± 15.649.5–130.0
Body mass index, kg/m227.7 ± 4.918.8–40.0
Waist circumference, cm93.9 ± 13.868.0–130.0
Living alone, no.26 
Comorbidities, no.  
 062 
 126 
 ≥212 
Disease severity, no.  
 K/L grade 265 
 K/L grade 325 
 K/L grade 410 
Unilateral symptoms, no.74 
Duration of symptoms, median years4.80.5–40
Muscle strength tests (Nm/kg)  
 Knee extensors1.83 ± 0.590.74–3.79
 Hip extensors2.1 ± 0.740.79–4.17
Range of motion tests, degrees  
 Hip flexion112.7 ± 14.770–142
 Hip internal rotation25.1 ± 10.71–51
Gait speed, meters/second1.2 ± 0.160.84–1.60
Timed stair test, seconds (n = 99)  
 Self pace9.7 ± 2.45.9–18.4
 Fast pace6.9 ± 2.43.2–14.9
Table 2. Breakpoint estimates for hip impairment measures for piecewise regression (n = 100)*
 Timed stair test, fast pace (n = 99)Timed stair test, slow pace (n = 99)Gait speed, self pace, r2
r2Breakpoint estimate (95% CI)No. below breakpointr2Breakpoint estimate (95% CI)No. below breakpoint
  • *

    Values are the r2 and breakpoint estimates (95% confidence interval [95% CI]) from the piecewise regression models, and the number of participants whose strength or range of motion measures fell below the breakpoint estimates. The physical performance measures (timed stair test and gait speed) were adjusted for age, sex, physical activity, and Short Form 36 bodily pain scores.

  • Not assessed due to nonsignificant difference between linear and lowess fits based on the Generalized Additive Model (P values ≥0.67).

  • r2 was generated from a linear regression model regressing the residualized gait measures on hip extensors strength, P = 0.01.

  • §

    Not assessed (NA) due to statistically significant associations between the hip range of motion and residualized physical performance measures below the breakpoint.

Muscle strength tests, Nm/kg       
 Knee extensors0.182.5 (1.8–3.3)880.122.0 (1.3–2.7)650.02
 Hip extensors0.162.1 (1.1–3.1)560.142.1 (1.4–2.9)560.06
Range of motion tests, degrees       
 Hip flexion0.20111 (94–130)410.15109 (96–121)360.03
 Hip internal rotation0.10NA§NA§0.1026 (8–47)510.00
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Figure 2. Relationship between muscle strength and residualized stair climb performance (positive and negative residualized values represented the extent to which the actual stair time exceeded or fell below what would be predicted from age, sex, pain, and physical activity level, respectively.) A, knee extensors and residualized fast paced timed stair test, B, knee extensors and residualized self paced timed stair test, C, hip extensors and residualized fast paced timed stair test, D, hip extensors and residualized self paced timed stair test.

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Figure 3. Relationship between hip range of motion (ROM) measures and residualized stair climb performance (positive and negative residualized values represented the extent to which the actual stair time exceeded or fell below what would be predicted from age, sex, pain, and physical activity level, respectively.) A, hip flexion ROM and residualized fast paced timed stair test, B, hip flexion ROM and residualized self paced timed stair test, C, hip internal rotation ROM and residualized fast paced timed stair test, D, hip internal rotation ROM and residualized self paced timed stair test.

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The optimal cut points (using the Youden index) to identify individuals with suboptimal gait speed (≤1.0 meters/second-1) are shown in Table 3. Combining Tables 2 and 3, the piecewise breakpoints and ROC-derived cut points were 1.8–2.5Nm/kg for knee extensors, 1.5–2.1Nm/kg for hip extensors, 25° and 26° for hip internal rotation ROM, and 109° to 115° for hip flexion ROM. Overall, the ROC-derived strength cut points were lower than the breakpoints identified for the residualized stair measures. Table 3 also shows the positive likelihood ratios for the strength and ROM measures, and these estimates ranged from 1.7–4.1. In clinical terms, these ratio values indicate that the odds of suboptimal gait speed increased by 1.5- to 4.1-fold when a given strength/ROM measure falls below the cut point.

Table 3. Optimal cut points for hip measures to identify individuals with functionally inadequate gait speed (≤1.0 meters/second), based on receiver operating characteristic curves (n = 100)*
 Cut point (Youden Index)No. below cut pointArea under ROC (95% CI)Sensitivity, % (95% CI)Specificity, % (95% CI)Positive LR (95% CI)
  • *

    ROC = receiver operating characteristic; 95% CI = 95% confidence interval; LR = likelihood ratio.

  • Number of participants whose strength or range of motion measures fell below the ROC-derived cut point.

Muscle tests, Nm/kg      
 Knee extensors1.8 (0.39)360.71 (0.58–0.83)88 (66–97)51 (40–61)1.8 (1.4–2.4)
 Hip extensors1.5 (0.44)220.76 (0.65–0.88)59 (36–78)86 (76–92)4.1 (2.1–7.9)
Range of motion tests, degrees      
 Hip flexion115 (0.32)500.68 (0.56–0.80)76 (53–90)55 (45–66)1.7 (1.2–2.5)
 Hip internal rotation25 (0.31)480.62 (0.47–0.77)77 (53–90)54 (44–64)1.7 (1.2–2.4)

DISCUSSION

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

Our goal was to examine whether the associations between physical performance and measures of muscle strength and hip ROM departed from linearity in individuals with hip OA. The principal finding was that measures of muscle strength and hip ROM were nonlinearly associated with the residualized stair measures but not with the residualized gait speed measures (Table 3). To our knowledge, these findings have not been previously described in individuals with hip OA.

Within the range of habitual gait speed observed in our study, not only did we fail to observe a nonlinear association between gait speed and measures of strength and ROM, but a linear association was observed only for the hip extensors. Specific to the knee extensors, our results were inconsistent with those of many (11, 14, 31–33), although not all (34, 35) prior studies. However, this disparity in results is probably explained by the difference in performance on the gait speed test. Specifically, the mean habitual gait speed of our participants was 1.2 meters/second, which is the minimum speed required to cross an intersection (36), and therefore was indicative of a generally high functioning sample. Indeed, only 17 participants walked at a suboptimal speed (≤1.0 meters/second), and gait speed varied approximately 2-fold (from 0.84 to 1.60 meters/second) (Table 1). Interestingly, in studies that have observed an association between knee extensors strength and gait measures (11, 14, 31–33), gait speed varied by at least 5-fold; in studies that have found nonsignificant associations (34, 35), gait speed varied by less than 3-fold. Taken together, perhaps our nonsignificant results are a consequence of limited interindividual variation and a corollary to the postulate by Buchner and de Lateur (12); in a relatively high functioning sample such as ours, the association between strength/ROM and gait performance is likely to be attenuated.

Because our range of gait speed was compressed, the fitting of nonlinear functions was not particularly helpful. Consequently, we used ROC analyses to determine cut points that discriminate participants with and without functionally inadequate gait speed. Although only 17 participants walked at a suboptimal speed, the 95% confidence interval (CI) for the AUCs, with the exception of hip internal rotation ROM, exceeded 0.50, indicating that our measures predict significantly better than random. Reviewing the literature, direct comparisons of our cut points cannot be made with previous data because few studies specifically included individuals with OA (13, 29). Still fewer studies examined hip ROM measures (13), and no studies have examined cut points for hip extensors strength or hip internal rotation ROM. Although not directly comparable, our hip flexion ROM cut point is remarkably concordant with the findings of Escalante et al (13), who demonstrated a J-shape association between hip flexion ROM (measured in quartiles) and the odds of walking at a slow speed, in the San Antonio Longitudinal Study of Aging. Specifically, the authors found that the odds increased sharply by 5-fold for persons in the last ROM quartile, and the corresponding quartile cut point was approximately 114°.

Limiting our comparisons to isometric knee extensors measures, our ROC-derived cut point is lower than that of Ploutz-Snyder et al (29), who reported a cut point of 3.0Nm/kg in 103 community-dwelling older adults, and that of Rantanen et al (14), who reported a cut point of 2.3Nm/kg in 773 older adults who had difficulty with activities of daily living. Because Rantanen et al (14) combined strength measures from both extremities, it may be speculated that their cut point was at least indirectly in agreement with ours. With reference to the study by Ploutz-Snyder et al (29), we could not satisfactorily resolve the discordant results. However, using their cut point (3.0Nm/kg) and assuming an average body mass of 70 kg, the average cut point in absolute strength would be 210Nm, a value that exceeds the average strength reported in healthy older adults (37–42). For this reason, the cut point by Ploutz-Snyder and associates (29) appears implausibly high and should, therefore, be interpreted cautiously.

For the residualized stair-climb measures, because the initial exploratory view of the data using lowess smoothers suggested potential nonlinearity, piecewise regression models were constructed accordingly. Before discussing our findings in detail, we should clearly address the key issue relating to our use of piecewise models. Specifically, the piecewise model chosen in this study assumes a sharp transition at the breakpoint. Given the large 95% CIs of the breakpoints (Table 2), it may be argued that strict breakpoints do not exist, and that the transition between the slopes should be gradual. Moreover, it is probable for other factors, e.g., cardiorespiratory fitness (43), standing balance (44), or lumbopelvic (core) control, to modify the strength/ROM-PPT associations, leading to the wide 95% CIs observed. Indeed, as pointed out by the reviewers, physical performance is the result of complex interdependent neuromuscular and physiologic processes, and it is possible for one physiologic system to compensate for another (44). Ostensibly, if impairments in one determinant can be compensated for by other (nonmeasured) determinants of physical performance, the threshold at which muscle strength or hip ROM begins to affect performance will vary across individuals. Thus, it is important to stress that our breakpoints should be interpreted critically and more broadly as the general range of muscle strength or hip ROM values after which the initial linear regression model may not fit the data optimally.

Returning our attention to the residualized stair measures, Figures 2 and 3 suggest mostly nonlinear relationships. However, 2 details of the 2-slope plots merit specific mention. First, less distinct slope changes were observed for the fast paced measures than for the self-paced measures. In fact, for the association between hip internal rotation ROM and the fast paced stair measure, no breakpoint was identified. Second, the strength breakpoints identified for the residualized stair measures were higher than the ROC-derived cut points identified for suboptimal gait speed (Tables 2 and 3). From a mechanistic viewpoint, the latter findings are not surprising. Specifically, our PPTs represent a gradient of increasing movement demand; self-paced gait test is less demanding than self-paced stair test which, in turn, is less demanding than the fast paced stair test. As movement demand increases, fewer participants would possess strength values that were in excess of what was required for the task; hence, strength breakpoints increase concomitantly.

In contrast, interpreting the ROM breakpoints is somewhat difficult and requires speculation. Although our breakpoints were clearly greater than the hip angles observed during stair climbing in hip-healthy adults (45), they may indicate the general ROM necessary for the muscles to operate at an optimal region of the length-tension curve (46). Also, because participants were not allowed to skip steps during the self-paced and fast paced stair tests, this may have resulted in essentially identical breakpoints, at least for the hip-flexion measures.

Our results have clinical implications. Although causality cannot be inferred from cross-sectional data, it is possible that addressing hip ROM deficits that fall below the breakpoints would improve function, which is reminiscent of the substantial functional improvements associated with hip joint mobilizations demonstrated by Hoeskma et al (18) and Currier et al (47). Interestingly, although Hoeskma et al (48) did not identify patient subgroups for whom mobilizations would be most beneficial, the clinical criteria used to diagnose hip OA in their study included less than 115° and 15° for hip flexion and internal rotation, respectively (49). Because these values fell below our breakpoints, one would expect most, if not all, of their patients to benefit from hip joint mobilizations. Equally, Currier et al (47) found that individuals with symptomatic hip OA and hip internal rotation of less than 17° tended to respond favorably to hip mobilizations. Again, because the ROM was below our breakpoint, their results match our expectations. On the other hand, studies conducted thus far on muscle strengthening exercises in hip OA have reported only modest treatment effects (18–20) and did not identify subgroups for whom exercises would be most beneficial. Our data raise the intriguing possibility that effect sizes and study efficiency could potentially be enhanced had patient subgroups been studied. Future studies should explore this possibility.

Besides the limitations of the piecewise models, our study has other limitations. First, our cross-sectional results may be affected by reverse causation, i.e., physical-function limitations could adversely affect muscle strength and hip ROM, and our inferences about the strength/ROM-PPT associations would be clarified if we had longitudinal data and a study population with more variability in gait speed. Second, this study is limited by the absence of consensus that would enable us to define acceptable levels of stair performance, and, therefore, to compare cut points generated from piecewise and ROC analyses. Third and most important, our sample size was small and to produce more precise breakpoints, larger samples are necessary to examine the complex interaction between the strength/ROM measures and other physiologic systems. Accordingly, our study should best be viewed as a hypothesis generating inquiry intended to motivate a larger research agenda.

At the simplest, we have demonstrated that muscle strength and hip ROM measures are associated with physical performance in individuals with hip OA. However, our results extend previous work by suggesting that these associations may be nonlinear. The ability to identify individuals whose physical performance would decline more sharply with every unit decrease in muscle strength or hip ROM would help health care professionals be more successful in targeting interventions. In that context, although the breakpoints in this study should be considered more speculative than definitive, our approach is, nevertheless, a means by which patient subgroups may be identified, and deserves greater attention in future research.

AUTHOR CONTRIBUTIONS

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

Mr. Pua had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study design. Pua, Wrigley, Cowan, Bennell.

Acquisition of data. Pua, Wrigley.

Analysis and interpretation of data. Pua, Wrigley, Cowan, Bennell.

Manuscript preparation. Pua, Wrigley, Cowan, Bennell.

Statistical analysis. Pua, Collins.

Acknowledgements

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

We would like to thank the anonymous reviewers for their critical and constructive suggestions for improvement of the manuscript. We also thank the participants for donating their time.

REFERENCES

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