ClinicalTrials.gov identifier: NCT00248105.
Rheumatoid Arthritis
Public health impact of risk factors for physical inactivity in adults with rheumatoid arthritis†
Article first published online: 27 MAR 2012
DOI: 10.1002/acr.21582
Copyright © 2012 by the American College of Rheumatology
Additional Information
How to Cite
Lee, J., Dunlop, D., Ehrlich-Jones, L., Semanik, P., Song, J., Manheim, L. and Chang, R. W. (2012), Public health impact of risk factors for physical inactivity in adults with rheumatoid arthritis. Arthritis Care Res, 64: 488–493. doi: 10.1002/acr.21582
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Publication History
- Issue published online: 27 MAR 2012
- Article first published online: 27 MAR 2012
- Accepted manuscript online: 25 JAN 2012 10:02PM EST
- Manuscript Accepted: 8 DEC 2011
- Manuscript Received: 1 AUG 2011
Funded by
- National Institute for Arthritis and Musculoskeletal and Skin Diseases. Grant Numbers: R01AR052912, P60AR48098
- Abstract
- Article
- References
- Cited By
Abstract
Objective
To investigate the potential public health impact of modifiable risk factors related to physical inactivity in adults with rheumatoid arthritis (RA).
Methods
A cross-sectional study used baseline data from 176 adults with RA enrolled in a randomized controlled trial assessing the effectiveness of an intervention to promote physical activity. Accelerometer data were assessed for inactivity (i.e., no sustained 10-minute periods of moderate to vigorous intensity physical activity during a week's surveillance). The relationships between modifiable risk factors (motivation for physical activity, beliefs related to physical activity, obesity, pain, and mental health) and inactivity were assessed using odds ratios (ORs) and attributable fractions (AFs), controlling for descriptive factors (age, sex, race, education, disease duration, and comorbidity).
Results
More than 2 in 5 adults (42%) with RA were inactive. Factors most strongly related to inactivity were lack of strong motivation for physical activity (adjusted OR 2.85; 95% confidence interval [95% CI] 1.31, 6.20 and adjusted AF 53.1%; 95% CI 21.7, 74.6) and lack of strong beliefs related to physical activity (OR 2.47; 95% CI 1.10, 5.56 and AF 49.2%; 95% CI 7.0, 76.4). Together, these 2 factors are related to almost 65% excess inactivity in this sample.
Conclusion
These results support the development of interventions that increase motivation for physical activity and that lead to stronger beliefs related to physical activity's benefits, and should be considered in public health initiatives to reduce the prevalence of physical inactivity in adults with RA.
INTRODUCTION
In the US, nearly 1.3 million people have rheumatoid arthritis (RA), a chronic disease characterized by the inflammation of joints causing pain, stiffness, and swelling (1).
Traditional medical management of arthritis through the early 1980s emphasized medication and rest (2). It is now widely recognized that regular moderate physical activity offers a host of benefits to people with arthritis. Physical activity helps to keep joints flexible, improve balance, and reduce pain. It also strengthens muscles to better support and protect joints affected by arthritis (3, 4). Most persons with arthritis can achieve a substantial reduction in pain, an increase in functional status, and an overall improvement in well-being by participating in a regular physical activity program.
Despite the documented benefits of physical activity, persons with RA are generally not physically active, and their physicians often do not encourage them to engage in regular physical activity. An understanding of the risk factors associated with inactivity that are frequently found among adults with RA may promote the design of clinical and community interventions to improve physical activity participation. To date, the literature addressing this problem is sparse. The goal of this study was to 1) assess the frequency of inactivity in adults with RA, 2) identify modifiable risk factors that may increase the prevalence of physical inactivity among adults with RA and that are potentially amenable to interventions or programs targeting their reduction, and 3) calculate the sample attributable fraction (AF), i.e., the proportion of physical inactivity that is associated with each of the modifiable risk factors for inactivity.
Significance & Innovations
We investigated the potential public health impact of modifiable risk factors, including motivation and beliefs related to the benefits of physical activity.
The public health importance of each modifiable risk factor on physical inactivity was estimated using the attributable fraction in the adults with rheumatoid arthritis.
MATERIALS AND METHODS
Population.
The study participants were 176 adults with RA enrolled in a randomized controlled trial (RCT) assessing the effectiveness of an intervention to promote physical activity (4, 5). Baseline cross-sectional data were used to investigate modifiable risk factors related to physical inactivity. This study received Institutional Review Board approval at Northwestern University, and written informed consent was obtained from each participating subject.
Inclusion criteria for RA participants were 1) age 18 years or older, 2) satisfy American College of Rheumatology criteria for RA (1), 3) able to ambulate at least 50 feet, and 4) English speaking. Exclusion criteria were 1) planned total joint replacement in the subsequent 24 months or lower extremity total joint replacement in the past 12 months, 2) a comorbid condition that limited function more than RA (e.g., peripheral vascular disease, spinal stenosis, residual lower extremity neuromuscular effects of stroke, major signs or symptoms suggestive of pulmonary and cardiovascular disease), 3) body mass index (BMI) >35 kg/m2, 4) inability to perform basic self-care activities, and 5) plans to relocate away from the Chicago area within 24 months.
Study database.
The baseline database of the RCT of a behavior change intervention aimed at increasing the physical activity participation of patients with RA included 1) demographic (age, sex, race), 2) socioeconomic (education), 3) RA disease specific (duration, severity, pain), 4) comorbidity, 5) health behavior (weight), and 6) theoretical behavior change variables (motivation for physical activity, beliefs related to physical activity, mental health). These behavior change variables are based on the Interaction Model of Client Health Behavior (IMCHB) (6), which posits that the changes in a health behavior such as physical activity are related to increases in the motivation for, the positive beliefs about, and the positive affective responses to physical activity in the context of the client's health challenges. The IMCHB shares several concepts in common with other health behavior models, such as the Health Belief Model, Transtheoretical Model, and Social Learning Theory (6). The IMCHB is broader in theoretical scope than Bandura's self-efficacy model because it contains both motivation and affect as constructs separate and distinct from cognitive processing variables. In addition, self-efficacy is only one component of intrinsic motivation; other components that contribute to motivation and that can be targets for intervention include choice, autonomy, and self-determinism. Each of these variables was classified as either a modifiable risk factor or descriptive factor.
Modifiable risk factors.
Modifiable factors were defined as risk factors that may increase the prevalence of physical inactivity and are potentially amenable to interventions or programs targeting their reduction. These included motivation for physical activity, beliefs related to physical activity, obesity, pain, and mental health status. Motivation for increasing physical activity was measured using 6 items regarding the extent of confidence to maintain an active lifestyle on a 4-point scale from “not at all confident (1)” to “completely confident (4).” Higher values represent greater confidence in the ability to maintain a physically active lifestyle. In this RA sample, the motivation items had a Cronbach's alpha of 0.89. The summed scores were divided into tertiles to classify individuals as exhibiting strong motivation (20–24), moderate motivation (16–19), and low motivation (6–15) with respect to physical activity performance. Beliefs related to physical activity were measured using 12 items regarding beliefs about being physically active assessed on a 4-point scale from “does not describe me at all (0)” to “describes me exactly (3).” Higher values represent more positive beliefs about engaging in physical activity. Examples of questions include addressing beliefs related to physical activity and stress or pain management and beliefs about what physical activity helps me to do. In this RA sample, the belief items had a Cronbach's alpha of 0.89. Cronbach's alpha is a measure of internal consistency, i.e., how closely related a set of items are as a group. The summed scores were divided into tertiles to classify individuals as having strong positive beliefs (26–36), moderate beliefs (21–25), and weak beliefs (0–20). Pain measured by the Health Assessment Questionnaire (HAQ) was used to measure arthritis pain severity on a scale between 0 (best; no pain) and 10 (worst) (7). Obesity was defined using BMI calculated from measured height and weight (weight [kg]/height [m2]). Persons were classified as normal weight (BMI 18.5–24.9 kg/m2), overweight (BMI 25.0–29.9 kg/m2), or obese (BMI ≥30 kg/m2). Mental health status was measured by the mental component summary (MCS) score of the Short Form 36 health survey, normalized to a US population-based mean ± SD of 50 ± 10; an MCS score 1 SD below the mean (<40) was deemed poor mental health status (8). For the purpose of analysis, we classified the modifiable risk factors: strong versus moderate/low motivation for physical activity, strong versus moderate/weak beliefs about physical activity, no pain versus some pain, normal weight/overweight versus obese, and not poor versus poor mental health.
Descriptive factors.
Descriptive factors included age, sex, race, education, disease duration, and comorbidities. Individuals were classified as white or nonwhite based on self-report. Education was dichotomized as college graduate versus less education. Duration of RA disease activity was reported in years. Comorbidities based on medication profiles were categorized into either “mobility limiting” (e.g., asthma, depression, cardiovascular disease) or “non–mobility limiting” (e.g., hypothyroidism, allergies, urinary frequency).
Outcome: physical activity measures.
Physical activity was objectively measured in the study participants using a GT1M ActiGraph accelerometer, which is a small uniaxial accelerometer that measures vertical acceleration and deceleration (9). The validity and reliability of the ActiGraph accelerometers under field conditions have been established in many populations, including RA (10–13). Accelerometer output is an activity “count,” which is the weighted sum of the number of accelerations measured over a time period (e.g., in this case, 1 minute), where the weights are proportional to the magnitude of measured acceleration.
Trained research personnel initialized each accelerometer and gave instructions at an in-person visit on how to position and wear the accelerometer. Participants were given uniform scripted instructions to wear the unit on a belt at the natural waistline on the right hip in line with the right axilla upon arising in the morning and continuously until retiring at night, except during water activities, for 7 consecutive days. At the end of the 7-day monitoring period, participants returned the accelerometers to the research center; data were downloaded using the manufacturer's software and were checked for valid data recording.
Accelerometer data were analytically filtered using methodology validated in patients with rheumatic disease (14–16). Nonwear periods were defined as ≥90 minutes with zero activity counts (allowing for 2 interrupted minutes with counts <100) (14). A valid day of monitoring was defined as 10 or more wear hours in a 24-hour period (15). We calculated the total daily minutes of moderate to vigorous (MV; counts ≥2,020) physical activity occurring in bouts lasting 10 or more minutes, with allowance for interruptions of 1 or 2 consecutive minutes below the MV threshold, consistent with National Cancer Institute methodology (16). Physical inactivity was defined according to the US Department of Health and Human Services (DHHS) physical activity levels (10): as zero MV activity bouts (lasting at least 10 minutes) per week. For simplicity, the term “active” refers to having at least one 10-minute bout of MV activity during the 7-day monitoring period.
Statistical analysis.
Characteristics of persons who are inactive and active based on descriptive factors and modifiable health factors were summarized by descriptive statistics. Logistic regression was used to identify modifiable factors associated with physical inactivity controlling for descriptive factors; an associated 95% confidence interval (95% CI) that falls above 1 indicates a significant association.
The AF related to inactivity was estimated for each modifiable risk factor using both the risk factor sample proportion and its association with inactivity. In a cross-sectional sample, the AF is the expected proportion by which the outcome frequency (e.g., inactivity prevalence) would be reduced if the risk factor were totally absent (17). The CI of the AF that falls above 0 indicates a significant contribution of the risk factor to the outcome. The AF for a combination of risk factors is the excess proportion of the outcome that can be attributed to any of the combined factors. The term “excess” conceptually refers to the reduction in the outcome that would occur if the risk factor were removed from the population (e.g., all individuals with pain reduced pain to be classified as no pain). In the present study, the AF of modifiable factors was estimated using relative risk estimates from Poisson regression with robust error variance and the sample prevalence of the modifiable risk factors. SAS, version 9.2, with a modified SAS macro (18, 19) was used to calculate point estimates and 95% CIs of the AFs for modifiable risk factors: motivation for physical activity, beliefs related to physical activity, obesity, pain, and mental health status.
RESULTS
A total of 176 persons ages 23–86 years with RA participated in physical activity measurement using accelerometers at the baseline visit. Participants had a mean age of 55 years; were primarily women (82%), white (75%), and college educated (85%); and had a mean ± SD RA disease duration of 13.5 ± 10 years (Table 1). More than 2 in 5 adults (42%) with RA were classified as inactive, demonstrating no 10-minute bouts of MV activity during the week of monitoring. The mean ± SD light activity was 478 ± 103 minutes per day and the mean ± SD MV activity was 19 ± 19 minutes per day.
| N | Inactive | Active | |
|---|---|---|---|
| |||
| Age, years† | |||
| 21 to <45 | 37 | 19 | 81 |
| 45 to <65 | 97 | 40 | 60 |
| ≥65 | 42 | 69 | 31 |
| Sex | |||
| Female | 146 | 46 | 54 |
| Male | 30 | 27 | 73 |
| Race‡ | |||
| White | 127 | 37 | 63 |
| Nonwhite | 49 | 57 | 43 |
| Disease duration, mean ± SD years | 13.5 ± 10.2 | 15.2 ± 10.9 | 12.2 ± 9.5 |
| Education | |||
| College graduate | 149 | 41 | 59 |
| Non–college graduate | 27 | 52 | 48 |
| Mobility-limiting comorbidity | |||
| Yes | 67 | 48 | 52 |
| No | 109 | 39 | 61 |
Modifiable factors were evaluated to identify those factors specifically associated with physical inactivity. The frequency of inactivity and associated odds ratios (ORs) are summarized in Table 2. Factors most strongly related to inactivity were lack of strong motivation (unadjusted OR 2.24; 95% CI 1.18, 4.25), lack of strong positive beliefs in physical activity (unadjusted OR 2.13; 95% CI 1.07, 4.26), and being obese (OR 2.14; 95% CI 1.12, 4.10). Both strong motivation and strong positive beliefs were significantly related to inactivity after accounting for all descriptive factors (adjusted OR 2.85; 95% CI 1.31, 6.20 and OR 2.47, 95% CI 1.10, 5.56, respectively). The significant relationship between inactivity and being obese was attenuated after accounting for differences in descriptive factors. Pain and mental health status did not have a significant univariate or multivariate association with inactivity.
| Risk category on top | Frequency, % | Inactive, % | Unadjusted OR (95% CI) | Adjusted OR (95% CI)† |
|---|---|---|---|---|
| ||||
| Motivation | ||||
| Lack of strong motivation | 60 | 50 | 2.24 (1.18, 4.25)‡ | 2.85 (1.31, 6.20)‡ |
| Strong motivation | 40 | 30 | Reference | Reference |
| Belief | ||||
| Lack of strong belief | 67 | 47 | 2.13 (1.07, 4.26)‡ | 2.47 (1.10, 5.56)‡ |
| Strong belief | 33 | 30 | Reference | Reference |
| HAQ pain | ||||
| Some pain | 90 | 43 | 1.07 (0.39, 2.95) | 1.40 (0.45, 4.38) |
| No pain | 10 | 41 | Reference | Reference |
| Weight | ||||
| Obese | 31 | 56 | 2.14 (1.12, 4.10)‡ | 1.80 (0.85, 3.81) |
| Overweight/normal weight | 69 | 37 | Reference | Reference |
| Mental health status | ||||
| Poor mental health | 11 | 42 | 1.24 (0.48, 3.22) | 1.38 (0.47, 4.04) |
| Not poor mental health | 89 | 47 | Reference | Reference |
These modifiable risk factors were also investigated by estimating the AF associated with each modifiable risk factor, which is summarized in Table 3. The AF reflects both the risk factor frequency and its association with the inactivity. The 2 factors significantly associated with excess inactivity were lack of strong motivation (AF 53.1%; 95% CI 21.7, 74.6) and lack of strong positive beliefs in physical activity (AF 49.2%; 95% CI 7.0, 76.4). Although being obese and HAQ pain had substantial AFs, they were not significant after accounting for differences in descriptive factors (being obese: AF 23.6%; 95% CI −3.6, 47.5 and pain: AF 26.5%; 95% CI −51.1, 80.3). Together, these 2 factors were related to almost 65% excess inactivity in this sample (AF 64.6%; 95% CI −7.4, 92.3).
| Risk category on top | Unadjusted AF (95% CI) | Adjusted AF (95% CI)† |
|---|---|---|
| ||
| Motivation | ||
| Lack of strong motivation | 42.6 (10.9, 66.4)‡ | 53.1 (21.7, 74.6)‡ |
| Strong motivation | ||
| Belief | ||
| Lack of strong belief | 41.9 (6.2, 68.1)‡ | 49.2 (7.0, 76.4)‡ |
| Strong belief | ||
| HAQ pain | ||
| Some pain | 5.7 (−67.3, 73.1) | 26.5 (−51.1, 80.3) |
| No pain | ||
| Weight | ||
| Obese | 25.9 (1.4, 47.5)‡ | 23.6 (−3.6, 47.5) |
| Overweight/normal weight | ||
| Mental health status | ||
| Poor mental health | 2.5 (−9.6, 14.6) | 2.9 (−8.0, 13.8) |
| Not poor mental health | ||
DISCUSSION
This study contributes to public health efforts to improve health outcomes of persons with arthritis by examining the association of potentially modifiable risk factors associated with physical inactivity among adults with RA. An important strength of this study is the objective assessment of physical inactivity using accelerometer monitoring.
Physical inactivity among adults with arthritis is a recognized public health concern. However, assessing the magnitude of the problem has been a challenge due to differing methods to assess physical activity. Earlier studies that relied on self-reported physical activity levels estimate that 23.8–57.8% of adults with arthritis in the US are inactive (20–25). These earlier studies all measured physical activity with self-report instruments as opposed to objective assessment. Inactivity was defined by no reported leisure time activity (24, 25), leisure activities absent of moderate and vigorous intensity or less than 10 minutes/week of moderate intensity activities (20), less than 3 sessions/month lasting 15 minutes or more of activities associated with moderate intensity energy expenditure (22, 23), and no reported activities lasting 10 minutes or more (21). In the present study, our definition of physical inactivity is anchored on the federal DHHS definition and is assessed by objective accelerometer monitoring using methods validated in RA (26). In our sample of RA patients, 42% were classified as inactive based on objective assessment.
Modifiable factors were evaluated from 2 perspectives. The first perspective identifies factors that are associated with physical inactivity at the level of the individual as measured by an OR. Modifiable factors significantly associated with inactivity were lack of strong motivation to be physically active (OR 2.24), positive beliefs related to physical activity (OR 2.13), and being obese (OR 2.14). Motivation for physical activity is strongly related to self-reported physical activity participation in other adult populations with chronic conditions (e.g., cancer survivors [27] and type 2 diabetes mellitus [28]). Beliefs related to physical activity also influenced physical activity participation in adult population (e.g., multiple sclerosis [29]). However, these earlier studies did not examine the role of motivation or beliefs in relation to inactivity.
A second perspective is the public health importance of each modifiable factor on inactivity, as measured by the AF for the sample. The AF has public health relevance because the statistic incorporates criteria related to the risk factor frequency plus its association with the outcome. The 2 factors significantly associated with excess inactivity were lack of strong motivation (AF 53.1%; 95% CI 21.7, 74.6) and lack of strong positive beliefs in physical activity (AF 49.2%; 95% CI 7.0, 76.4). These findings indicate that low motivation for physical activity and weak beliefs that are related to physical activity barriers should be considered in public health interventions.
There were some limitations to this study. The physical activity experience of adults with RA participating in an RCT may be different from the general population of RA patients. However, a self-reported measure of time spent on physical activity measured in this study (25.5 hours/week) and an RA community sample (23.1 hours/week) was similar (30). The limitations of accelerometry include being unable to account for differences in physical activity intensity due to cardiorespiratory fitness level and variable gait patterns in persons with potential movement limitations/variations. Accelerometers do not provide qualitative information on the context of the physical activity (e.g., household, transportation, outdoor location), information that may be helpful to target interventions. It is likely that we did not find a higher and significant AF related to obesity because we excluded those with a BMI >35 kg/m2. Despite these limitations, the strengths of this study include the use of an objective measure of physical activity using an accelerometer, the assessment of inactivity as defined by the DHHS, and a method with public health value to prioritize the modifiable risk factors to identify targets for intervention.
Despite the benefits of physical activity, adults with RA are generally not physically active. A substantial 42% of adults with RA were classified as inactive, participating in no 10-minute episodes of MV activity in a week. Lack of strong motivation for physical activity and lack of strong beliefs related to the benefits of physical activity were related to approximately 53.1% and 49.2%, respectively, of excess inactivity in this group. Together, these 2 factors are related to almost 60% of the excess inactivity in this sample. These results suggest interventions on lack of strong motivation and strong belief for the benefits of physical activity should be considered in public health initiatives to reduce the prevalence of physical inactivity in adults with RA.
AUTHOR CONTRIBUTIONS
All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Lee 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 conception and design. Lee, Dunlop, Semanik, Song, Manheim, Chang.
Acquisition of data. Lee, Dunlop, Ehrlich-Jones, Semanik, Song, Chang.
Analysis and interpretation of data. Lee, Dunlop, Ehrlich-Jones, Semanik, Song, Manheim, Chang.
REFERENCES
- 1, , , , , , et al. The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum 1988; 31: 315–24.
- 2American College of Rheumatology Ad Hoc Committee on Clinical Guidelines. Guidelines for the management of rheumatoid arthritis. Arthritis Rheum 1996; 39: 713–22.Direct Link:
- 3. Exercise in the treatment of osteoarthritis. Rheum Dis Clin North Am 1999; 25: 397–415.
- 4, . Recreational exercise in arthritis. Rheum Dis Clin North Am 1996; 22: 563–77.
- 5
- 6
- 7, . The Stanford Health Assessment Questionnaire: a review of its history, issues, progress, and documentation. J Rheumatol 2003; 30: 167–78.
- 8, , . How to score version 2 of the SF-36 health survey. Lincoln (RI): QualityMetric Incorporated; 2000.
- 9, , , Sources of variance in daily physical activity levels as measured by an accelerometer. Med Sci Sports Exerc 2002; 34: 1376–81.
- 10, , , , , , et al. The use of uniaxial accelerometry for the assessment of physical-activity-related energy expenditure: a validation study against whole-body indirect calorimetry. Br J Nutr 2004; 91: 235–43.
- 11, , , , . Reexamination of validity and reliability of the CSA monitor in walking and running. Med Sci Sports Exerc 2003; 35: 1447–54.
- 12, , Reliability of accelerometry- based activity monitors: a generalizability study. Med Sci Sports Exerc 2004; 36: 1637–45.
- 13, , , , , , et al. Physical activity levels in patients with early knee osteoarthritis measured by accelerometry. Arthritis Rheum 2008; 59: 1229–36.
- 14, , , , , , et al. Assessing physical activity in persons with knee osteoarthritis using accelerometers: data from the Osteoarthritis Initiative. Arthritis Care Res (Hoboken) 2010; 62: 1724–32.
- 15, , , , , . Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 2008; 40: 181–8.
- 16, , , , , . Assessing physical activity in persons with rheumatoid arthritis using accelerometry. Med Sci Sports Exerc 2010; 42: 1493–501.
- 17. A review of adjusted estimators of attributable risk. Stat Methods Med Res 2001; 10: 195–216.
- 18, , . Point and interval estimates of partial population attributable risks in cohort studies: examples and software. Cancer Causes Control 2007; 18: 571–9.
- 19. Software for computing full and partial population attributable risks and their confidence intervals. URL: http://www.hsph.harvard.edu/faculty/donna-spiegelman/software/par/index.html.
- 20, , . Are US adults with arthritis meeting public health recommendations for physical activity? Arthritis Rheum 2004; 50: 624–8.
- 21, , , . Physical activity in men and women with arthritis National Health Interview Survey, 2002. Am J Prev Med 2006; 30: 385–93.
- 22, . Arthritis and arthritis-attributable activity limitations in the United States and Canada: a cross-border comparison. Arthritis Care Res (Hoboken) 2010; 62: 308–15.
- 23, , , . Characteristics of physically inactive older adults with arthritis: results of a population-based study. Prev Med 2003; 37: 61–7.
- 24, , , , . Physical activity levels among the general US adult population and in adults with and without arthritis. Arthritis Rheum 2003; 49: 129–35.
- 25, , . Obesity and physical inactivity among Wisconsin adults with arthritis. WMJ 2003; 102: 24–8.
- 26, , , , , . Assessing physical activity in persons with rheumatoid arthritis using accelerometry. Med Sci Sports Exerc 2010; 42: 1493–501.
- 27, , , . Predicting physical activity and outcome expectations in cancer survivors: an application of self-determination theory. Psychooncology 2006; 15: 567–78.
- 28, , . Understanding physical activity facilitators and barriers during and following a supervised exercise programme in type 2 diabetes: a qualitative study. Diabet Med 2010; 27: 79–84.
- 29, , , , . Facilitators and barriers to engagement in physical activity for people with multiple sclerosis: a qualitative investigation. Disabil Rehabil 2011; 33: 625–42.
- 30, , , . Physical activity behavior in older women with rheumatoid arthritis. Arthritis Rheum 2004; 51: 246–52.

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