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. Author manuscript; available in PMC: 2022 Mar 1.
Published in final edited form as: Gait Posture. 2021 Feb 3;85:151–156. doi: 10.1016/j.gaitpost.2021.01.022

Walking energetics and abductor strength are associated with physical activity in older women with hip osteoarthritis

Kharma C Foucher 1,*, Chun-Hao Huang 1, Burcu Aydemir 1
PMCID: PMC8085128  NIHMSID: NIHMS1672397  PMID: 33578307

Abstract

Background:

Osteoarthritis (OA) can hinder physical activity in older adults for reasons that are not fully understood. Functional barriers may exist such as reduced muscle strength around the affected joint, potentially affecting physical activity. Aging-associated declines in energy capacity may also be exacerbated by OA. These factors may work together to influence physical activity in people with OA.

Research Question:

Our objective was to evaluate the combined role of walking energetics and hip abductor strength on physical activity in older women with hip OA.

Methods:

We evaluated 30 women with moderately symptomatic hip OA (61±10 yrs; 30.7±4.9 kg/m2) in this cross-sectional observational study. We measured physical activity using the UCLA activity score and quantified activity frequency and intensity using accelerometers worn for seven days (7±2 days). We used a portable oxygen exchange system to measure energy used during walking at preferred speeds (relative to total energy capacity assessed using a six-minute walk test) and a dynamometer to measure hip abductor strength. We used Pearson correlations and regression analysis to test our hypotheses.

Results:

Greater energy used during walking was associated with lower self-reported physical activity (R=−0.626, p<0.001), more sedentary time (R=0.567, p=0.002), and less light activity time (R=−0.644, p<0.001). Lower hip abductor strength was associated with lower self-reported physical activity (R=0.406, p=0.039). While there was no association between hip abductor strength and energy used during walking, together these variables predicted 55.5% of the variance in self-reported physical activity.

Significance:

Results suggest intervention targets to promote physical activity in this population.

Keywords: osteoarthritis, exercise, muscle strength, energy metabolism, gait

INTRODUCTION

Physical activity is important for maintenance of function in osteoarthritis (OA).[1] Moreover, exercise is as effective as medication in providing pain relief.[2] Unfortunately few people with OA meet physical activity guidelines,[3,4] with obese individuals being at particular risk.[5] Pain and functional impairments are often cited as key barriers to physical activity in people with OA.[6,7] Thus the very factors that limit physical activity are those that could be improved by physical activity. Behavioral interventions to improve physical activity in people with OA have been attempted but have had mixed results.[8,9] In order to improve physical activity in people with OA, a better understanding of potentially modifiable functional limitations that limit physical activity is needed.

It has been proposed that energy limitations associated with aging can limit physical activity in older adults.[10,11] The energetic model of activity limitation posits that people with increased energy cost of walking relative to their total energy capacity, have a smaller energy reserve compared to those with a lower energy cost of walking.[10–12] Lower energy reserve may lead to reduced physical activity as affected individuals consciously or unconsciously seek to conserve energy to stave off fatigue. This model has been evaluated and used to create successful interventions in older adults with nonspecific mobility impairments,[13] but the model has not been evaluated in people with hip OA.

Decreased hip abductor strength relative to control groups have frequently been associated with hip OA.[14–16] This functional impairment may exacerbate physical activity limitations via the energetic model. Decreased abductor function may be associated with energetically costly gait adaptations. Both experimental and simulation studies demonstrate that hip abductor function is critical for frontal plane stability during walking.[17,18] The abductors work to maintain a level pelvis during single-limb stance, which allows the swing limb to clear the ground as it moves forward. If this is not possible, leaning the trunk over the affected hip can be an effective compensation, either by decreasing the moment arm between the ground reaction force and the hip center, which reduces demand on the abductors, or by ensuring swing limb clearance. In several patient populations, it has been shown that increased trunk motion increases the energy cost of walking,[19,20] or decreases walking efficiency.[21] Thus, hip abductor impairment may serve to reduce walking efficiency and lead to excessive energy use during walking.

The purpose of this study was to evaluate the energetic model of activity limitation in people with hip OA, focusing on women as a first step because they are more likely to report lower activity levels.[22,23] We also sought to evaluate a potential mechanism for aberrant walking energetics – lower ipsilateral hip abductor strength. The hypotheses tested were (i) higher relative energy use during walking is associated with lower physical activity in women with hip OA; (ii) lower abductor strength is associated with lower physical activity in women with hip OA; and (iii) lower abductor strength is associated with higher relative energy use during walking in women with hip OA.

METHODS

Subjects

This prospective cross-sectional study was approved by the Institutional Review Board of the University of Illinois at Chicago. We recruited women from local surgical practices, radio and public transport advertising, and an IRB-approved contact list obtained from medical records. The rationale for the enrollment criteria was to identify a heterogeneous, clinically relevant sample to enhance generalizability. Inclusion criteria were doctor-diagnosed hip OA in one or both hips and age over 50 years. Exclusion criteria included other actively symptomatic joints, history of any total joint replacement within 2 years, inability to walk without assistive devices, and any medical condition that interfered with gait or the ability to safely complete the protocol. One hundred nine women were screened and data from the 30 women who satisfied enrollment criteria, provided written informed consent, and completed the protocol were used in this study. Four subjects reported bilateral hip OA. The most symptomatic hip was used in this analysis. Subjects were characterized clinically using the Hip disability and Osteoarthritis Outcome Score (HOOS).[24] Note that the HOOS was not used as part of the enrollment criteria.

Energy used during walking

First total aerobic capacity was assessed by predicting the VO2max from a treadmill-based six-minute walk test using a published regression equation.[25] For this test, subjects were asked to walk for “as far as possible”. They could adjust speed as needed but were encouraged to maximize distance. Heart rate was measured during the test. The regression equation estimates VO2max based on heart rate, body mass, and distance walked and has been shown to be valid and reliable compared to free-walking conditions.[25] Calculated VO2max was then normalized to body mass and reported as ml/min*kg. Next, during a second evaluation, VO2 in ml/min*kg used during treadmill walking at preferred speeds was assessed using a portable gas exchange system (COSMED K5, Concord, CA, USA) that has been shown to be valid and reliable for this use.[26] We measured VO2 during 2.5 minutes of steady state walking after a 3 minute period of familiarization. Energy use during walking was calculated as 100* VO2 during walking at preferred speeds/total aerobic capacity.

Hip abductor strength

Hip abductor strength was measured as peak isometric torque for each hip. Subjects were positioned in a side-lying position on the reclined seat of a dynamometer (Biodex, Shirley, NY, USA) top. Measuring abductor strength in side-lying has been shown to be the most valid and reliable method.[27] The axis of the dynamometer testing arm was aligned with the participant’s greater trochanter and the distal end of the hip attachment was strapped around the femur of the test limb proximal to the lateral femoral condyle. We performed a gravity correction of the test limb prior to testing. Next, a submaximal practice trial was performed to familiarize each participant with the testing procedure. Finally, subjects performed three consecutive maximal voluntary isometric contractions of 5 seconds with a 30 second rest period in between. During the maximal trials, subjects were instructed to push their leg against the distal end of the hip attachment, which provides resistance, with maximal effort for 3–5 seconds. A single tester administered all tests. The average peak torque (Nm) of the three max trials for each hip was extracted using the manufacturer’s software and normalized to body mass (Nm/kg).

Physical activity

Physical activity was our primary outcome measure. Physical activity was characterized in three ways. First, we used the UCLA activity score.[28] This score is widely used in this population and has been validated against pedometers and other survey instruments.[28,29] The UCLA activity score assesses self-reported activity level ranging from a score of 1 – “Wholly inactive; dependent on others; cannot leave residence” to 10 “Regularly participate in impact sports such as jogging, tennis, skiing, acrobatics, ballet, heavy labor, or backpacking.” Next, subjects were provided with an accelerometer-based activity monitor (ActiGraph GT3X-BT, ActiGraph, Pensacola, FL, USA) to be worn on the wrist for 4–7 days after the assessment after recommendations published in a recent review.[30] We used manufacturer-provided software to extract average number of steps per day and counts per day to represent quantity of activity using the Troiano method.[31] We also extracted intensity of activity characterized as percent sedentary time, percent time spent in light, moderate, or vigorous activity based on counts per minute.[31] Time during which counts per minute were less than 100 was classified as sedentary; counts per minute of 101 – 2019 was classified as light activity; counts per minute of 2020 – 5998 were classified as moderate activity; and counts per minute of 5999 or higher were classified as vigorous activity.[30,31]

Statistical analysis

We used SPSS version 27 (IBM Corp, Armonk, PNY,USA) for all analyses. We used G*power [32,33] to determine the magnitude of a correlation that we could detect with our sample size. We determined that a critical correlation coefficient of |0.361| could be detected at the 80% power level with alpha < 0.05. First, descriptive statistics were computed for all variables. Shapiro-Wilk tests were used to determine normality for all variables. Next, because of a potential impact on physical activity,[34] we assessed the effect of age and BMI on all physical activity variables to determine whether or not they should be included in our analyses using bivariate Spearman correlations. (Spearman correlations were used where variables were not normally distributed.) When either age or BMI was significantly associated with an outcome variable, we used multivariable linear regression analysis to determine whether our primary relationship of interest was still statistically significant as described below.

To test the first hypothesis, we used bivariate Spearman correlations to test the association between energy use during walking and physical activity measures. By convention,[35] a correlation coefficient greater than or equal to |0.3| was considered moderate and a correlation coefficient greater than or equal to |0.5| was considered large in this and subsequent tests. For physical activity measures that were associated with age or BMI, we then used multivariable linear regression analysis to verify the associations found with bivariate correlations, or to determine whether additional associations emerge after controlling for the potential confounders. Similarly, to test hypothesis ii, we used Spearman correlations to test the association between ipsilateral hip abductor strength and physical activity measures. We followed with multivariable linear regression as described above. Next, to test hypothesis iii, first we used Pearson correlations to test the association between hip abductor strength and energy use during walking. Finally, we used multivariable linear regression analysis to test the combined influence of energy use during walking and ipsilateral hip abductor strength on physical activity measures.

RESULTS

Before assessing the hypotheses, we evaluated the characteristics of the group (Table 1). Of note, on average subjects used nearly half of their total energy capacity for walking (47.5 ± 19.4). Nevertheless, as a group subjects were moderately active with a mean UCLA score of 5.3 ± 1.3 where a score of 5 indicates “sometimes participates in moderate activities...” Also of note, no subjects spent any time in vigorous activity. Age was associated with time spent in moderate activity (rho = −0.409, p = 0.031) and steps per day (rho = −0.466, p = 0.012) and were included in subsequent analyses involving these outcome variables. BMI was not associated with any physical activity outcome variables (rho = |0.025| to |0.353|, p = 0.065 to 0.899). Pain, based on the HOOS subscale, was associated with UCLA scores (rho = 0.376, p = 0.049) and was included in subsequent analyses involving this variable using multivariable linear regression. Symptoms, based on the HOOS subscale, were not associated with any physical activity outcome variables (rho = 0.075 to 0.334, p = 0.089 to 0.645).

Table 1.

Characteristics of the group of 30 women with hip osteoarthritis

Mean ± standard deviation Range
Age (years) 60.8 ± 9.6 50 – 89
BMI (kg/m2) 30.7 ± 4.9 24.6 – 41.0
HOOS Pain Score 53.6 ± 16.7 22.5 – 85
HOOS Symptoms Score 56.2 ± 18.6 5.0 – 90.0
HOOS Function (ADL) Score 57.1 ± 18.2 19.1 – 92.6
HOOS Function (Sport/Rec) Score 47.6 ± 21.8 12.5 – 87.5
HOOS Quality of Life Score 42.2 ± 21.5 0.0 – 87.5
Energy used during walking (% of total energy capacity) 47.5 ± 19.4 17.5 – 85.3
Preferred walking speed (m/s) 0.60 ± 0.23 0.25 – 1.20
Hip abductor strength (Nm/kg) 0.49 ± 0.26 0.09 – 1.12
UCLA Activity Score 5.3 ± 1.3 3 – 8
Average steps/day 9251 ± 3268 4400 – 14985
Percent time spent sedentary 42.8 ± 15.6 11.7 – 76.5
Percent time spent in light activity 44.5 ± 9.7 20.8 – 59.9
Percent time spent in moderate activity 12.7 ± 8.0 2.6 – 30.0
Percent time spent in vigorous activity - -
Average counts per day 2,020,262 ± 740,391 704,728 – 3,302,447
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Hypothesis 1 was mostly supported (Table 2). Energy used during walking was strongly significantly correlated with UCLA scores (Figure 1, top) in bivariate analyses. This association persisted after accounting for pain (R2 = 0.410, p = 0.001) in the multivariable regression. Sedentary time and light activity time were also strongly correlated with energy used during walking (Figure 1, middle, bottom) in bivariate analyses. Counts per day was moderately correlated with energy used during walking (R = −0.440, p = 0.019). Weaker negative correlations were seen for number of steps taken per day, percent of time spent in moderate activity, but these associations were not statistically significant (R = −0.368 to −0.323, p = 0.054 to 0.094).

Table 2.

Associations between accelerometer-based physical activity measures and energy used during walking and hip abductor strength. Note that no subjects spent any time engaged in vigorous activity.

Average steps/day Percent time spent sedentary Percent time spent in light activity Percent time spent in moderate activity Counts/day
Percent Energy Used during Walking R = −0.368 R = 0.567 R = −0.644 R = −0.323 R = −0.440
p = 0.054 p = 0.002 p < 0.001 p = 0.094 p = 0.019
Hip Abductor Strength R = −0.229 R = 0.054 R = −0.046 R = −0.049 R = −0.295
p = 0.270 p = 0.799 p = 0.827 p = 0.817 p = 0.152
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Figure 1.

Figure 1.

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Energy used during walking was significantly associated with self-reported physical activity via the UCLA activity score (top) as well as percent of time spent sedentary (middle) and light activity time (bottom).

Hypothesis 2 was also partially supported. Ipsilateral hip abductor strength was positively moderately associated with UCLA scores (Figure 2). This association persisted when pain was included in a regression model. Stronger subjects tended to report higher activity levels. No correlations were seen with any accelerometer-based activity measures (Table 2). No additional associations were seen when age or pain were accounted for in regression models. To determine whether the association between hip abductor and activity was due to the particular influence of the ipsilateral abductors vs. general muscle strength, we also determined the correlation between UCLA scores and contralateral abductor strength. This association was small and was not statistically significant (rho = 0.189, p = 0.301).

Figure 2.

Figure 2.

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Hip abductor strength was associated with self-reported physical activity measured by the UCLA activity score. This association persisted once the effect of pain was accounted for. (R2 = 0.276).

Hypothesis 3 was not supported. There was no association between energy used during walking and hip abductor strength (R = 0.073, p = 0.718). We then, however, tested the extent to which energy used during walking and hip abductor strength together predicted UCLA scores. We found that 55% of the variance in UCLA scores was predicted by these two factors (Table 3). When pain was entered into the model, the R2 value increased to 0.590 (adj. R2 = 0.534) but this change was not statistically significant (p = 0.182 for R2 change). As expected, based on the bivariate correlations, energy used during gait was the strongest predictor based on the standardized coefficients.

Table 3.

Hip abductor strength and energy used during walking predict self-reported physical activity measured via the UCLA activity score.

Model Dependent variable R2 p Independent variable B (95% CI) Standardized β p
1 UCLA scores 0.555 <0.001 Peak isometric abductor strength 2.0 (0.6, 3.3) 0.436 0.005
Energy used during walking −0.041 (−0.060, −0.022) −0.625 <0.001
2 UCLA scores 0.555 <0.001 Peak isometric abductor strength 2.0 (0.6, 3.3) 0.436 0.005
Energy used during walking −0.041 (−0.060, −0.022) −0.625 <0.001
Pain 0.014 (−0.007, 0.036) 0.195 0.182
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DISCUSSION

The purpose of this study was to evaluate the energetic model of activity limitation in women with hip OA and to test a potential OA-specific underlying mechanism, i.e. the role of hip abductor strength. We found that using more energy to walk relative to total energy capacity is associated with less self-reported physical activity and with greater sedentary time and less time spent in light activity. Further, while hip abductor strength was associated with self-reported physical activity, there was no association between hip abductor strength and energy used during walking. This was contrary to our hypothesized mechanism. Energy used during walking and hip abductor strength together were associated with self-reported physical activity with an R2 value of 0.555.

There have been several studies linking walking energetics to function or physical activity in older adults with mobility impairments, although OA specifically has rarely been evaluated. For example, energy use during walking has been associated with physical function and gait speed, a key marker of overall function, in older adults.[12,36,37] These findings are relevant to OA because physical function is impaired in OA, and because physical functional impairments pose barriers to physical activity in people with OA.[6] There is evidence that walking energetics are abnormal in people with OA. Holsgaard-Larsen and Roos evaluated caloric expenditure and steps walked in people with severe OA and healthy controls.[38] They found that both groups walked the same number of steps, but that the OA group expended more calories.[38] This implies that there is excessive energy expenditure per step in people with OA. Together with our results, these studies suggest that targeting walking energetics could be a viable method to understand and improve physical activity in people with OA.

There are therapeutic implications to these findings as prior studies have successfully improved physical activity participation by targeting walking energetics. VanSwearingen et al.[13] found that an intervention designed to make walking easier and reduce energy cost of walking improved activity and participation in older adults with mobility impairments. Manipulating gait symmetry is another strategy that has been used in other populations to improve the energy cost of walking using functional electrical stimulation or split-belt treadmill training.[39,40] These types of interventions have not yet been attempted in people with OA to our knowledge.

Improving hip abductor muscle strength may offer another avenue to improve physical activity in people with hip OA. Muscle strength and physical function have been consistently linked in previous studies in people with OA.[41,42] In a series of studies Pua et al.[43,44] found positive associations between muscle strength and composite measures of function that included self-reported physical activity. These studies, however, focused on hip flexors and extensors. Hip abductors have been less well studied despite their consistent links to hip OA pathology.[14,16,42] In one study, Judd et al.[45] found clinically significant reductions in the strength of several muscle groups, including the hip abductors, as well as reduced UCLA scores compared to healthy controls. In a subsequent study from this group in people who had undergone total hip arthroplasty, the time course of changes in abductor strength was similar to the time course of changes in UCLA scores, but associations between the two were not evaluated in that study.[46] Our finding that hip abductor strength was independently associated with physical activity suggests that more investigation on the specific role of this muscle group in improving physical activity is warranted.

Contrary to our hypothesis concerning our proposed mechanism, hip abductor strength was not associated with energy used during walking. However, we did not directly evaluate the underlying assumption that this hypothesis was based on. We presumed that women with hip OA compensate for abductor weakness with increased frontal plane trunk motion, which studies have shown is energetically costly.[19–21] This gait compensation has been demonstrated in women with total hip replacements,[18] however it has not been directly shown in hip OA. If increased frontal plane trunk motion is present, it is possible that this compensation is more strongly associated with walking energetics than abductor strength. It is also possible that walking energetics were altered by the novelty of the task, treadmill walking, or increased co-activation during the novel task. It is also possible that a third kinematic or kinetic factor beyond trunk motion may influence both strength and walking energetics.

There are a few limitations to this study that should be considered. Most importantly, there was a risk of selection bias as subjects needed to be able to tolerate the evaluations. This may have biased our sample toward higher functioning individuals. However, the range of HOOS ADL and Sport/Rec scores suggests that our sample reflected a wide range of functional ability. In addition, the sample size, was relatively small. This combined with the variability in the accelerometer data means that we may have been underpowered to detect some important associations. Further, the heterogeneity of the sample may have diluted some of our findings, although it bodes well for generalizability. Next, we did not examine the numerous behavioral factors that influence physical activity. Next, we did not measure radiographic severity of OA. This was in part to reduce participant burden. In addition, there is so far no evidence in the literature suggesting that structural severity plays a larger role than pain or function in determining physical activity levels. Next, we limited our subjects to women. We have previously shown that men and women with hip OA modify abductor function in different ways.[47] It is possible that adaptations to abductor weakness may differ in men and women with concomitant differences in the effects on walking energetics. Finally, the cross-sectional precludes causal inferences and prevents us from inferring directionality of the associations. It is likely that certain relationships, such as that between abductor strength and self-reported physical activity are bidirectional.

In conclusion, energy use during walking and hip abductor strength are independently associated with self-reported physical activity. This study suggests that the energetic model of activity limitation, originally developed to understand physical activity restriction in older adults, is a useful framework for understanding physical activity limitation in older adults with hip OA. Using more of the total energy capacity for walking is associated with spending more time sedentary and less time in light activity. In addition, those with stronger hip abductors were more active as well via self-report. These findings are important because increasing physical activity is associated with less pain and better function in OA. Given that walking energetics and strength were both associated with self-reported physical activity, these factors may be viable strategies for improving overall physical activity in older women with OA. Further, targeting walking energetics may be a modifiable strategy to improve objectively-measured physical activity.

Highlights.

  • Relative energy use during gait was associated with physical activity (PA)

  • Women with hip OA who used more energy for walking were less active overall

  • Women with hip OA who used more energy for walking were more sedentary

  • Women with hip OA who had stronger hip abductors were also more active

  • Abductor strength and energy use during gait were associated with PA (R2 = 0.555)

Acknowledgements:

This work was supported by the National Institutes of Health (R21AG052111 to KCF, UL1TR002003). We thank Megan Horras, BS, Anusha Jalasutram BS, and Samuel Chmell, MD for their help in identifying subjects.

Role of the funding source: This work was supported by the National Institutes of Health (R21AG052111 to KCF), with recruitment resources funded by the UIC Center for Clinical and Translational Science (UL1TR002003). The funding sources had no role in the study design, the collection, analysis and interpretation of data, the writing of the manuscript, or in the decision to submit the article for publication.

Footnotes

Conflict of interest statement: The authors deny any financial and personal relationships with other people or organizations that could inappropriately influence this work.

Declarations of interest: none

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REFERENCES

  • [1].Fransen M, McConnell S, Harmer AR, der Esch MV, Simic M, Bennell KL, Exercise for osteoarthritis of the knee: a Cochrane systematic review, British Journal of Sports Medicine. 49 (2015) 1554–1557. 10.1136/bjsports-2015-095424 [doi]. [DOI] [PubMed] [Google Scholar]
  • [2].Skou ST, Roos EM, Physical therapy for patients with knee and hip osteoarthritis: supervised, active treatment is current best practice, Clinical and Experimental Rheumatology. 37 Suppl 120 (2019) 112–117. https://doi.org/14740 [pii]. [PubMed] [Google Scholar]
  • [3].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 and Cartilage. 21 (2013) 1648–1659. [DOI] [PubMed] [Google Scholar]
  • [4].Centers for Disease Control and Prevention, Prevalence of doctor-diagnosed arthritis and arthritis-attributable activity limitation-United States, 2003–2005, MMWR.Morbidity and Mortality Weekly Report. 55 (2006) 1089–1092. https://doi.org/mm5540a2 [pii]. [PubMed] [Google Scholar]
  • [5].Center for Disease Control and Prevention, Arthritis as a potential barrier to physical activity among adults with obesity-United States, 2007 and 2009, MMWR.Morbidity and Mortality Weekly Report. 60 (2011) 614–618. https://doi.org/mm6019a4 [pii]. [PubMed] [Google Scholar]
  • [6].Kanavaki AM, Rushton A, Efstathiou N, Alrushud A, Klocke R, Abhishek A, Duda JL, Barriers and facilitators of physical activity in knee and hip osteoarthritis: a systematic review of qualitative evidence, BMJ Open. 7 (2017) e017042–017042. 10.1136/bmjopen-2017-017042 [doi]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [7].Stone RC, Baker J, Painful Choices: A Qualitative Exploration of Facilitators and Barriers to Active Lifestyles Among Adults With Osteoarthritis, Journal of Applied Gerontology: The Official Journal of the Southern Gerontological Society. 36 (2017) 1091–1116. 10.1177/0733464815602114 [doi], [DOI] [PubMed] [Google Scholar]
  • [8].Williamson W, Kluzek S, Roberts N, Richards J, Arden N, Leeson P, Newton J, Foster C, Behavioural physical activity interventions in participants with lower-limb osteoarthritis: a systematic review with meta-analysis, BMJ Open. 5 (2015) e007642. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [9].Oliveira CB, Franco MR, Maher CG, Lin CWC, Morelhao PK, Araujo AC, Fiho RFN. Pinto RZ, Physical Activity Interventions for Increasing Objectively Measured Physical Activity Levels in Patients With Chronic Musculoskeletal Pain: A Systematic Review, Arthritis Care & Research. 68 (2016) 1832–1842. 10.1002/acr.22919 [doi]. [DOI] [PubMed] [Google Scholar]
  • [10].Schrack JA, Simonsick EM, Ferrucci L, The energetic pathway to mobility loss: an emerging new framework for longitudinal studies on aging, Journal of the American Geriatrics Society. 58 Suppl 2 (2010) 329. 10.1111/j.1532-5415.2010.02913.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [11].Schrager MA, Schrack JA, Simonsick EM, Ferrucci L, Association between energy availability and physical activity in older adults, American Journal of Physical Medicine & Rehabilitation / Association of Academic Physiatrists. 93 (2014) 876–883. 10.1097/PHM.0000000000000108[doi]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [12].Wert DM, Brach JS, Perera S, VanSwearingen J, The association between energy cost of walking and physical function in older adults, Archives of Gerontology and Geriatrics. 57 (2013) 198–203. 10.1016/j.archger.2013.04.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [13].VanSwearingen JM, Perera S, Brach JS, Wert D, Studenski SA, Impact of exercise to improve gait efficiency on activity and participation in older adults with mobility limitations: a randomized controlled trial, Physical Therapy. 91 (2011) 1740–1751. 10.2522/ptj.20100391. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [14].Marshall AR, Noronha MD, Zacharias A, Kapakoulakis T, Green R, Structure and function of the abductors in patients with hip osteoarthritis: Systematic review and meta-analysis, Journal of Back and Musculoskeletal Rehabilitation. 29 (2016) 191–204. 10.3233/BMR-150614. [DOI] [PubMed] [Google Scholar]
  • [15].Loureiro A, Constantinou M, Diamond LE, Beck B, Barrett R. Individuals with mild-to-moderate hip osteoarthritis have lower limb muscle strength and volume deficits, BMC Musculoskeletal Disorders. 19 (2018) 303–4. 10.1186/s12891-018-2230 [doi]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [16].Loureiro A, Mills PM, Barrett RS, Muscle weakness in hip osteoarthritis: A systematic review, Arthritis Care & Research. 65 (2013) 340–352. [DOI] [PubMed] [Google Scholar]
  • [17].MacKinnon CD, Winter DA, Control of whole body balance in the frontal plane during human walking, Journal of Biomechanics. 26 (1993) 633–644. [DOI] [PubMed] [Google Scholar]
  • [18].Perron M, Malouin F, Moffet H, McFadyen BJ, Three-dimensional gait analysis in women with a total hip arthroplasty, Clinical Biomechanics (Bristol, Avon). 15 (2000) 504–515. [DOI] [PubMed] [Google Scholar]
  • [19].Caldwell LK, Laubach LL, Barrios JA, Effect of specific gait modifications on medial knee loading, metabolic cost and perception of task difficulty, Clinical Biomechanics (Bristol, Avon). 28 (2013) 649–654. 10.1016/j.clinbiomech.2013.05.012. [DOI] [PubMed] [Google Scholar]
  • [20].Takacs J, Kirkham AA, Perry F, Brown J, Marriott E, Monkman D, Havey J, Hung S, Campbell KL, Hunt MA, Lateral trunk lean gait modification increases the energy cost of treadmill walking in those with knee osteoarthritis, Osteoarthritis and Cartilage. 22 (2014) 203–209. [DOI] [PubMed] [Google Scholar]
  • [21].Nankaku M, Tsuboyama T, Kakinoki R, Kawanabe K, Kanzaki H, Mito Y, Nakamura T, Gait analysis of patients in early stages after total hip arthroplasty: effect of lateral trunk displacement on walking efficiency, Journal of Orthopaedic Science. 12 (2007) 550–554. [DOI] [PubMed] [Google Scholar]
  • [22].Lee YS, Gender differences in physical activity and walking among older adults, Journal of Women & Aging. 17 (2005) 55–70. 10.1300/J074v17n01_05 [doi]. [DOI] [PubMed] [Google Scholar]
  • [23].Rosenfeld CS, Sex-dependent differences in voluntary physical activity, Journal of Neuroscience Research. 95 (2017) 279–290. 10.1002/jnr.23896 [doi]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [24].Nilsdotter A, Lohmander LS, Klssbo M, Roos E, Hip disability and osteoarthritis outcome score (HOOS)-validity and responsiveness in total hip replacement., BMC Musculoskeletal Disorders. 4 (2003) 10. 10.1186/1471-2474-4-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [25].Laskin JJ, Bundy S, Marron H, Moore H, Swanson M, Blair M, Humphrey R, Using a treadmill for the 6-minute walk test: reliability and validity, Journal of Cardiopulmonary Rehabilitation and Prevention. 27 (2007) 407–410. 10.1097/01.HCR.0000300270.45881.d0 [doi]. [DOI] [PubMed] [Google Scholar]
  • [26].DeBlois JP, White LE, Barreira TV, Reliability and validity of the COSMED K5 portable metabolic system during walking, Eur J Appl Physiol. (2020). 10.1007/s00421-020-04514-2. [DOI] [PubMed] [Google Scholar]
  • [27].Widler K, Glatthorn J, Bizzini M, Impellizzeri F, Munzinger U, Leonig M, Maffiuletti N, Assessment of hip abductor muscle strength. A validity and reliability study., Journal of Bone and Joint Surgery American Volume. 91 (2009) 2666–2672. [DOI] [PubMed] [Google Scholar]
  • [28].Zahiri CA, Schmalzried TP, Szuszczewicz ES, Amstutz HC, Assessing activity in joint replacement patients, The Journal of Arthroplasty. 13 (1998) 890–895. [DOI] [PubMed] [Google Scholar]
  • [29].Naal FD, Impellizzeri FM, Leunig M, Which is the best activity rating scale for patients undergoing total joint arthroplasty?. Clinical Orthopaedics and Related Research. 467 (2009) 958–965. 10.1007/s11999-008-0358-5 [doi]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [30].Migueles JH, Cadenas-Sanchez C, Ekelund U, Delisle Nystrom C, Mora-Gonzalez J, Lof M, Labayen I, Ruiz JR, Ortega FB, Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations, Sports Med 47 (2017) 1821–1845. 10.1007/s40279-017-0716-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [31].Troiano RP, Berrigan D, Dodd KW, Mâsse LC, Tilert T, Mcdowell M, Physical Activity in the United States Measured by Accelerometer, Medicine & Science in Sports & Exercise. 40 (2008) 181–188. 10.1249/mss.0b013e31815a51b3. [DOI] [PubMed] [Google Scholar]
  • [32].Faul F, Erdfelder E, Lang AG, Buchner A, G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences, Behavior Research Methods. 39 (2007) 175–191. [DOI] [PubMed] [Google Scholar]
  • [33].Faul F, Erdfelder E, Buchner A, Lang AG, Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses, Behavior Research Methods. 41 (2009) 1149–1160. 10.3758/BRM.41.4.1149. [DOI] [PubMed] [Google Scholar]
  • [34].Veenhof C, Huisman PA, Barten JA, Takken T, Pisters MF, Factors associated with physical activity in patients with osteoarthritis of the hip or knee: a systematic review. Osteoarthritis and Cartilage / OARS, Osteoarthritis Research Society. 20 (2012) 6–12. 10.1016/j.joca.2011.10.006. [DOI] [PubMed] [Google Scholar]
  • [35].Hu Q, Measures of Effect Size, in: Salkind NJ (Ed.), SAGE Publications, Inc., Thousand Oaks, CA, 2010. [Google Scholar]
  • [36].Schrack JA, Zipunnikov V, Simonsick EM, Studenski S, Ferrucci L, Rising Energetic Cost of Walking Predicts Gait Speed Decline With Aging, The Journals of Gerontology.Series A, Biological Sciences and Medical Sciences. 71 (2016) 947–953. 10.1093/gerona/glw002 [doi]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [37].Schrack JA, Simonsick EM, Ferrucci L, The relationship of the energetic cost of slow walking and peak energy expenditure to gait speed in mid-to-late life, American Journal of Physical Medicine & Rehabilitation. 92 (2013) 28–35. 10.1097/PHM.0b013e3182644165 [doi]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [38].Holsgaard-Larsen A, Roos EM, Objectively measured physical activity in patients with end stage knee or hip osteoarthritis, European Journal of Physical and Rehabilitation Medicine. 48(2012)577–585. [PubMed] [Google Scholar]
  • [39].Awad LN, Palmer JA, Pohlig RT, Binder-Macleod SA, Reisman DS, Walking speed and step length asymmetry modify the energy cost of walking after stroke, Neurorehabilitation and Neural Repair. 29 (2015) 416–423. 10.1177/1545968314552528 [doi]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [40].Finley JM, Bastian AJ, Gottschall JS, Learning to be economical: the energy cost of walking tracks motor adaptation, The Journal of Physiology. 591 (2013) 1081–1095. 10.1113/jphysiol.2012.245506. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [41].Holla JF, Sanchez-Ramirez DC, van der Leeden M, Ket JC, Roorda LD, Lems WF, Steultjens MP, Dekker J, The avoidance model in knee and hip osteoarthritis: a systematic review of the evidence, Journal of Behavioral Medicine. 37 (2014) 1226–1241. 10.1007/s10865-014-9571-8 [doi]. [DOI] [PubMed] [Google Scholar]
  • [42].Hall M, Wrigley TV, Kasza J, Dobson F, Pua YH, Metcalf BR, Bennell KL, Cross-sectional association between muscle strength and self-reported physical function in 195 hip osteoarthritis patients. Seminars in Arthritis and Rheumatism. (2016). https://doi.org/S0049-0172(16)30191–3 [pii]. [DOI] [PubMed] [Google Scholar]
  • [43].Pua Y-H, Hip flexion range of motion and physical function in hip osteoarthritis: Mediating effects of hip extensor strength and pain, Arthritis and Rheumatism. 61 (2009) 633–640.. [DOI] [PubMed] [Google Scholar]
  • [44].Pua YH, Wrigley TV, Collins M, Cowan SM, Bennell KL, Association of physical performance with muscle strength and hip range of motion in hip osteoarthritis, Arthritis and Rheumatism. 61 (2009) 442–450. 10.1002/art.24344 [doi]. [DOI] [PubMed] [Google Scholar]
  • [45].Judd DL, Thomas AC, Dayton MR, Stevens-Lapsley JE, Strength and functional deficits in individuals with hip osteoarthritis compared to healthy, older adults, Disability and Rehabilitation. 36 (2014) 307–312. 10.3109/09638288.2013.790491 [doi]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [46].Judd DL, Dennis DA, Thomas AC, Wolfe P, Dayton MR, Stevens-Lapsley JE, Muscle strength and functional recovery during the first year after THA, Clinical Orthopaedics and Related Research. 472 (2014) 654–664. 10.1007/s11999-013-3136-y [doi]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [47].Foucher KC, Sex-specific hip osteoarthritis-associated gait abnormalities: Alterations in dynamic hip abductor function differ in men and women, Clinical Biomechanics (Bristol, Avon) 48 (2017) 24–29. https://doi.org/S0268-0033(17)30139-0 [pii]. [DOI] [PubMed] [Google Scholar]

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