Relationship Between Disease Activity Level and Physical Activity in Rheumatoid Arthritis Using a Triaxial Accelerometer and Self-reported Questionnaire

Abstract

Objective: This study evaluated the relationship between rheumatoid arthritis (RA) disease activity level and physical activity (PA) by using an accelerometer and self-reported questionnaire.

Results: The cross-sectional study included 34 patients with RA. We classified patients with a Disease Activity Score 28-erythrocyte sedimentation rate (DAS28-ESR) of less than and higher than 3.2 into the low-disease-activity (LDA) group and moderate/high-disease-activity (MHDA) group, respectively. PA was assessed using a triaxial accelerometer. We measured the wear time, time of vigorous-intensity PA (VPA), moderate-intensity PA (MPA), light-intensity PA (LPA), and sedentary behavior per day by using this device. Moreover, we evaluated the relationship between accelerometer-measured and self-reported PAs in each group. The accelerometer-measured moderate-to-vigorous PA (MVPA) was 17.2 min/day and 10.6 min/day in the MHDA group and LDA group (p < .05), respectively. No significant association was observed between RA disease activity level and accelerometer-measured PA with adjustment for age and Functional Assessment of Chronic Illness Therapy-Fatigue score. No correlation was noted between accelerometer-measured MVPA and self-reported MVPA in the MHDA group, but these factors were correlated in the LDA group (rs = 0.5, p < .05). The RA disease activity level and accelerometer-measured PA were not correlated.

Introduction

Rheumatoid arthritis (RA) is a systemic, progressive, chronic disease. Body functions in patients with RA are reduced compared with healthy individuals because of joint problems, systemic lesions, and fatigue.(1)

Physical activity (PA) was converted into metabolic equivalents (METs) by using a self-reported questionnaire and was evaluated.(2) Recently, an accelerometer has attracted some attention as a valuable tool for evaluating PA.(3–6) The triaxial accelerometer can evaluate changes in activity levels and separate sedentary time and active time.(7–9) Population-based research, such as the National Health and Nutrition Examination Survey, have used accelerometers for PA measurements rather than conventional methods.(10)

Evaluating PA and rehabilitation in RA patients can help prevent heart diseases, diabetes, hypertension, depression, and osteoporosis and are associated with an improved low mortality rate.(11–13) In several studies evaluating moderate-to-vigorous PA (MVPA) using accelerometers in patients with RA, RA patients showed lower MVPA than healthy subjects.(14–16) Hernandez-Hernandez et al. evaluated the relationship between delta MVPA and delta PA by using an accelerometer and found that PA increased with the improved disease activity.(16, 17) However, other studies using accelerometer reported that disease activity levels did not significantly correlate with PA.(15, 18) By contrast, some studies examining the relationship between RA disease activity and PA levels indicated a correlation between decreased disease activity and increased PA based on a self-reported questionnaire.(19, 20) As a method for evaluating PA levels in patients with a substantial amount of sedentary behavior (SB), no report has directly compared and examined the accuracy of the triaxial accelerometer and self-reported questionnaires based on the disease activity level of patients with RA.

This study aimed to evaluate the relationship between RA disease activity level and the amount of PA measured using a triaxial accelerometer and self-reported questionnaire. We hypothesized a significant correlation between disease activity levels and PA and between self-reported PA and accelerometer-measured PA.

Materials And Methods

This cross-sectional study was conducted between November 22, 2015, and December 31, 2016 at Showa University Hospital in Tokyo, Japan. We recruited patients when they visited the hospital as outpatients. The eligibility criteria were as follows: 1) fulfillment of the American Rheumatism Association 1987 revised Criteria for RA(21) and 2) age of 20–65 years at consent acquisition. The excluded patients were judged ineligible by the research doctor for the following reasons: 1) bedridden/requiring a wheelchair, 2) dementia, and 3) limb deficiency. For evaluating construct validity, a study with 50 participants was designed on our preliminary research, and 41 patients agreed to wear an accelerometer. However, seven patients were excluded (Additional file 1). Finally, 34 patients were included in the study. Disease activity was measured using the Disease Activity Score 28-erythrocyte sedimentation rate (DAS28-ESR).(22) We classified patients with a DAS28-ESR of less and more than 3.2 into the low-disease-activity (LDA) and moderate/high-disease-activity (MHDA) groups, respectively.(23) Of the 34 patients, 20 were classified in the LDA group and 14 in the MHDA group.

The primary endpoint was PA evaluated using a triaxial accelerometer. The secondary endpoint was PA evaluated using the International Physical Activity Questionnaire (iPAQ).(24, 25)

PA was assessed using the triaxial accelerometer Active Style Pro HJA-750C (Omron Healthcare, Kyoto, Japan). We measured the wear time, time of vigorous-intensity PA (VPA), moderate-intensity PA (MPA), light-intensity PA (LPA), SB, and the number of steps per day using this device. MET-based cutoffs were used to define the intensity of each activity as follows: ≤1.5 METs for SB, 1.6–2.9 METs for LPA, and ≥ 3 METs for MVPA.(26, 27) The participants wore the accelerometer on their waist for seven consecutive days while they were awake. They did not wear the accelerometer when engaging in water-involving activities, such as swimming and showering. Records obtained when the accelerometer was worn for at least 10 h/day were considered valid, and data were considered as “nonwear” when acceleration signals were not observed continuously for more than 60 min.(28) The CSV data files of the accelerometer were downloaded using Omron health management software BI-LINK for PA Professional Edition ver. 1.0. The files were processed using custom software (i.e., a custom-written macro program for compiling data).

A short iPAQ form was used to determine PA during leisure time, domestic work, paid or unpaid work, and transportation.(24, 25, 29, 30) The patients were questioned regarding the following three specific types of PA, in which they participated at any time during their daily routine: walking, moderate-intensity activity, and vigorous-intensity activity. Scores for each type of activity were calculated by summing the scores for duration and frequency. Published guidelines for data processing and analysis of IPAQ data were used (available from: http://www.ipaq.ki.se). Comorbidities were evaluated using the Charlson comorbidity index.(31) At the outpatient clinic visit, the subjective physical function was assessed using the Modified Health Assessment Questionnaire (mHAQ).(32) The health-related quality of life was measured using the Medical Outcomes Study (MOS) 12-item Short-Form Health Survey (SF-12).(33) The Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F version 4) questionnaire was used to calculate the level of fatigue.(34, 35) The Center for Epidemiologic Studies Depression Scale (CES-D) was used to assess depressive symptoms.(36) Medical data (e.g., body mass index [BMI], disease duration, and medication history) of patients with RA were collected from medical charts. Radiological evaluation of the lower extremity involved six classes of the Larsen classification.(37)

Statistical analysis was performed using JMP® 13 software (SAS Institute Inc., Cary, NC, USA). Continuous data were expressed as means with standard deviations (SD) or medians with interquartile ranges (IQR). The normal distributions of each dataset were evaluated by performing the Shapiro–Wilk test. Spearman’s rank-sum test was used to assess the correlation. The variables obtained from an accelerometer and iPAQ for the LDA and MHDA groups were compared using multilinear regression analysis with adjustment for age and the FACIT-F score. For all analyses, statistical tests were two-sided, and significance was defined as p < .05.

Results

The baseline characteristics of the study patients was presented (Additional file 2). Significant differences were noted in the mHAQ scores, swollen joint count-28, tenderness joint count-28, C-reactive protein level, ESR, and MMP-3 level of the groups. The FACIT-F score was significantly higher in the MHDA group than the LDA group (p = .003).

The mean (SD) values of the variables of subjective measures (i.e., SF-12) for the LDA and MHDA groups was shown (Additional file 3). For all items, except emotional role in the SF-12, the scores were significantly higher for the LDA group than the MHDA group.

For all RA patients, the median accelerometer wear time, median SB time, and median MVPA were 696.0 min/day (IQR, 630.9–743.2), 424.6 min/day (IQR, 386.9–458.6), and 14.9 min/day (IQR, 10.5–20.8), respectively.

Table 1 presents time spent in objectively measured PA in the LDA and MHDA groups. The median accelerometer MVPA was 17.2 min/day (IQR, 13.5–21.8) and 10.6 min/day (IQR, 9.5–15.7) in the LDA group and MHDA group, respectively. Most of the wear time was spent during SB. The analysis showed that MVPA was significantly lower in the MHDA group than in the LDA group (p = .018). A significant difference in SB was noted between the two groups. RA disease activity was not associated with the MVPA score for the LDA and MHDA groups in the multilinear regression analysis adjusted for age and FACIT-F score (regression coefficient 7.29; 95% CI: −6.3 to 12.9; p = .28).

No association was observed between DAS28-ESR and accelerometer-measured PA in any patients with RA, LDA group, or MHDA group. Furthermore, there was no association between DAS28-ESR and self-reported PA for any group (Fig. 1). We assessed the correlation between the accelerometer-measured and self-reported PA evaluated in all RA patients, the LDA group, and the MHDA group (Table 2). The MVPA measured using the accelerometer and the MVPA score identified using the iPAQ showed a relative correlation for the LDA group (rs = 0.5, p < .01) but not for all the patients or the MHDA group.

Discussion

In this study, we measured PA using a triaxial accelerometer and a self-reported questionnaire in patients with RA. The median time of the accelerometer-measured MVPA was 17.2 min/day and 10.6 min/day for the MHDA and LDA groups, respectively. No significant association was noted between the RA disease activity level and accelerometer-measured PA after adjusting for age and fatigue. No correlation was noted between the accelerometer-measured and self-reported PA for total RA patients or the MHDA group, but these two factors were correlated in the LDA group (rs = 0.5).

The results revealed no significant association between RA disease activity level and accelerometer-measured PA. Thus, disease activity in patients with RA and PA may not be related. The results of this study differed from previous studies that reported a relationship between RA disease activity and self-reported PA.(16, 20) The findings can be attributed to by several possible explanations. First, a different method was used to assess outcomes. PA was evaluated using a self-report questionnaire in previous studies,(3, 4, 10) whereas we measured PA using a triaxial accelerometer. The result of the relationship between disease activity and PA might have been different because self-reported PA and the more accurate accelerometer-measured PA results are different. Second, the DAS28-ESR may not be suitable for evaluating disease activity related to PA in patients with RA. Most of the joints evaluated using the DAS 28-ESR are upper extremity joints; only two extremity joints are assessed. Therefore, the DAS28-ESR, which evaluates 28 joints primarily located in the extremities, may not be suitable as an evaluation method to assess RA disease activity affecting PA, such as moderate and vigorous movement.(15, 38, 39) To evaluate the relationship between disease activity and PA for patients with RA, the joint destruction of both the lower and upper extremity joints should be evaluated.(40)

Self-reported PA and accelerometer-measured PA may not be correlated in patients with RA. Our results differ from previous reports where self-reported PA was relatively consistent with accelerometer-measured PA among healthy subjects.(25, 41) There are several possible reasons for this finding. First, the iPAQ only measures MVPA sustained for more than 10 minutes. However, the triaxial accelerometer can measure short-term MVPA lasting for fewer than 10 minutes. Therefore, the PA results obtained from the two methods were different.(42, 43) Second, MVPA is overestimated, and SB is underestimated in the self-reported questionnaire compared with that in the accelerometer.(44–46) Moderate PA might be overestimated by self-reported PA compared with the accelerometer-measured PA in the present study.

To the best of our knowledge, this is the first study to use a triaxial accelerometer and self-reported questionnaire for a direct comparison between habitual PA for LDA and MHDA patients with RA. Further, disease activity and PA were measured in continuously sampled patients in actual clinical practice. Finally, fatigue was adjusted as a relevant confounding factor that could affect the association between RA disease activity and PA.(47–49) In our study, patients with RA had limited time of MVPA despite very low levels of disease activity and disability, thus suggesting the possibility of additional factors influencing MVPA levels in this population.

In conclusion, no significant association was noted between RA disease activity level and accelerometer-measured PA, and PA cannot be fully evaluated with a self-reported questionnaire. The data will be useful for epidemiological studies and the self-health management of RA patients.

Limitations

This study has several limitations. First, because this is a cross-sectional study, we were unable to conclusively determine causality. However, we believe that disease activity in patients with RA reduces PA levels, which is biologically plausible, but reverse causality remains possible. Second, the sample size was small and was not an even set of subsamples. We could not control disease specificities (i.e., organ damage or disease activity affecting PA). Correlations may become stronger with smaller observation groups. This was a pilot study, and we will perform a further study with more subjects in the future.

Abbreviations

RA: rheumatoid arthritis, PA: physical activity, DAS28-ESR: Disease Activity Score 28-erythrocyte sedimentation rate, LDA: low disease activity, MHDA: moderate/high disease activity, MVPA: moderate-to-vigorous PA, SB: sedentary behavior, iPAQ: International Physical Activity Questionnaire, VPA: vigorous-intensity PA, MPA: moderate-intensity PA, LPA: light-intensity PA, mHAQ: Modified Health Assessment Questionnaire, MOS: Medical Outcomes Study, SF-12: 12-item Short-Form Health Survey, FACIT-F: Functional Assessment of Chronic Illness Therapy-Fatigue, CES-D: Center for Epidemiologic Studies Depression Scale, BMI: body mass index, ACPA: anticitrullinated protein antibodies, RF: rheumatoid factor, SD: standard deviations, IQR: interquartile ranges.

Declarations

Ethics Approval and Consent to Participate

The procedures and materials were approved by the Institutional Review Board of Showa University (Tokyo, Japan) Approval Number –1947, Approval Date - 2015/12/3. All patients provided written consent to participate in the study.

Consent for Publication

Not applicable

Availability of Data and Materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing Interests

The authors declare that they have no competing interests.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sector.

Author’s Contributions

YT and YN designed the study. YT, YN, and ON were responsible for data collection. YT and YN prepared the data for analysis. YT and YN performed the statistical analyses in consultation. YT drafted the manuscript. NY, TN, and KI critically revised the manuscript. ON supervised and approved the final draft.

All authors read and approved the final manuscript.

Acknowledgments

The authors would like to thank Takeo Isozaki, Kuninobu Wakabayashi, and Yusuke Miwa for their assistance with recruiting participants. The authors would also like to thank Enago (www.enago.jp) for their English language editing.

References

1. Sokka T, Hakkinen A, Kautiainen H, Maillefert JF, Toloza S, Mork Hansen T, et al. Physical inactivity in patients with rheumatoid arthritis: data from twenty-one countries in a cross-sectional, international study. Arthritis and rheumatism. 2008;59(1):42-50.
2. Klesges RC, Eck LH, Mellon MW, Fulliton W, Somes GW, Hanson CL. The accuracy of self-reports of physical activity. Medicine and science in sports and exercise. 1990;22(5):690-7.
3. Loprinzi PD, Sheffield J, Tyo BM, Fittipaldi-Wert J. Accelerometer-determined physical activity, mobility disability, and health. Disability and health journal. 2014;7(4):419-25.
4. Wallis JA, Webster KE, Levinger P, Taylor NF. What proportion of people with hip and knee osteoarthritis meet physical activity guidelines? A systematic review and meta-analysis. Osteoarthritis Cartilage. 2013;21(11):1648-59.
5. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Medicine and science in sports and exercise. 2008;40(1):181-8.
6. Bonomi AG, Goris AH, Yin B, Westerterp KR. Detection of type, duration, and intensity of physical activity using an accelerometer. Medicine and science in sports and exercise. 2009;41(9):1770-7.
7. Ohkawara K, Oshima Y, Hikihara Y, Ishikawa-Takata K, Tabata I, Tanaka S. Real-time estimation of daily physical activity intensity by a triaxial accelerometer and a gravity-removal classification algorithm. The British journal of nutrition. 2011;105(11):1681-91.
8. Rowlands AV, Yates T, Olds TS, Davies M, Khunti K, Edwardson CL. Sedentary Sphere: Wrist-Worn Accelerometer-Brand Independent Posture Classification. Medicine and science in sports and exercise. 2016;48(4):748-54.
9. Oshima Y, Kawaguchi K, Tanaka S, Ohkawara K, Hikihara Y, Ishikawa-Takata K, et al. Classifying household and locomotive activities using a triaxial accelerometer. Gait & posture. 2010;31(3):370-4.
10. Yang L, Hu L, Hipp JA, Imm KR, Schutte R, Stubbs B, et al. Cross-sectional associations of active transport, employment status and objectively measured physical activity: analyses from the National Health and Nutrition Examination Survey. Journal of epidemiology and community health. 2018.
11. Verhoeven F, Tordi N, Prati C, Demougeot C, Mougin F, Wendling D. Physical activity in patients with rheumatoid arthritis. Joint, bone, spine : revue du rhumatisme. 2016;83(3):265-70.
12. Hurkmans E, van der Giesen FJ, Vliet Vlieland TP, Schoones J, Van den Ende EC. Dynamic exercise programs (aerobic capacity and/or muscle strength training) in patients with rheumatoid arthritis. The Cochrane database of systematic reviews. 2009(4):Cd006853.
13. Stenstrom CH, Minor MA. Evidence for the benefit of aerobic and strengthening exercise in rheumatoid arthritis. Arthritis and rheumatism. 2003;49(3):428-34.
14. Hashimoto T, Yoshiuchi K, Inada S, Shirakura K, Wada N, Takeuchi K, et al. Physical activity of elderly patients with rheumatoid arthritis and healthy individuals: an actigraphy study. Biopsychosoc Med. 2015;9:19.
15. Prioreschi A, Hodkinson B, Avidon I, Tikly M, McVeigh JA. The clinical utility of accelerometry in patients with rheumatoid arthritis. Rheumatology (Oxford, England). 2013;52(9):1721-7.
16. Hernandez-Hernandez V, Ferraz-Amaro I, Diaz-Gonzalez F. Influence of disease activity on the physical activity of rheumatoid arthritis patients. Rheumatology (Oxford, England). 2014;53(4):722-31.
17. Hernandez-Hernandez MV, Diaz-Gonzalez F. Role of physical activity in the management and assessment of rheumatoid arthritis patients. Reumatol Clin. 2017;13(4):214-20.
18. Summers G, Booth A, Brooke-Wavell K, Barami T, Clemes S. Physical activity and sedentary behavior in women with rheumatoid arthritis: a comparison of patients with low and high disease activity and healthy controls. Open Access Rheumatol. 2019;11:133-42.
19. Iversen MD, Frits M, von Heideken J, Cui J, Weinblatt M, Shadick NA. Physical Activity and Correlates of Physical Activity Participation Over Three Years in Adults With Rheumatoid Arthritis. Arthritis care & research. 2017;69(10):1535-45.
20. Konijn NP, van Tuyl LH, Boers M, den Uyl D, Ter Wee MM, Kerstens P, et al. Effective Treatment for Rapid Improvement of Both Disease Activity and Self-Reported Physical Activity in Early Rheumatoid Arthritis. Arthritis care & research. 2016;68(2):280-4.
21. Arnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF, Cooper NS, et al. The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis and rheumatism. 1988;31(3):315-24.
22. Wells G, Becker JC, Teng J, Dougados M, Schiff M, Smolen J, et al. Validation of the 28-joint Disease Activity Score (DAS28) and European League Against Rheumatism response criteria based on C-reactive protein against disease progression in patients with rheumatoid arthritis, and comparison with the DAS28 based on erythrocyte sedimentation rate. Annals of the rheumatic diseases. 2009;68(6):954-60.
23. Fleischmann R, van der Heijde D, Koenig AS, Pedersen R, Szumski A, Marshall L, et al. How much does Disease Activity Score in 28 joints ESR and CRP calculations underestimate disease activity compared with the Simplified Disease Activity Index? Annals of the rheumatic diseases. 2015;74(6):1132-7.
24. Tomioka K, Iwamoto J, Saeki K, Okamoto N. Reliability and validity of the International Physical Activity Questionnaire (IPAQ) in elderly adults: the Fujiwara-kyo Study. Journal of epidemiology. 2011;21(6):459-65.
25. Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Medicine and science in sports and exercise. 2003;35(8):1381-95.
26. Owen N, Healy GN, Matthews CE, Dunstan DW. Too much sitting: the population health science of sedentary behavior. Exercise and sport sciences reviews. 2010;38(3):105-13.
27. Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Bassett DR, Jr., Tudor-Locke C, et al. 2011 Compendium of Physical Activities: a second update of codes and MET values. Medicine and science in sports and exercise. 2011;43(8):1575-81.
28. Semanik P, Song J, Chang RW, Manheim L, Ainsworth B, Dunlop D. Assessing physical activity in persons with rheumatoid arthritis using accelerometry. Medicine and science in sports and exercise. 2010;42(8):1493-501.
29. Murase N, Katumura T, Ueda C, Inoue S, Shimomistu T. Reliability and validity of the Japanese version of the International Physical Activity Questionnaire (IPAQ). Kousei no Shihyou. 2002;49:1-9 (in japanese).
30. Ried-Larsen M, Brond JC, Brage S, Hansen BH, Grydeland M, Andersen LB, et al. Mechanical and free living comparisons of four generations of the Actigraph activity monitor. The international journal of behavioral nutrition and physical activity. 2012;9:113.
31. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of chronic diseases. 1987;40(5):373-83.
32. Ono K, Ohashi S, Oka H, Kadono Y, Yasui T, Omata Y, et al. The impact of joint disease on the Modified Health Assessment Questionnaire scores in rheumatoid arthritis patients: A cross-sectional study using the National Database of Rheumatic Diseases by iR-net in Japan. Modern rheumatology. 2016;26(4):529-33.
33. Ware J, Jr., Kosinski M, Keller SD. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Medical care. 1996;34(3):220-33.
34. Singh H, Arya S, Talapatra P, Lather K, Mathur R, Singhania A, et al. Assessment of fatigue in rheumatoid arthritis (by Functional Assessment of Chronic Illness Therapy-Fatigue score) and its relation to disease activity and anemia. Journal of clinical rheumatology : practical reports on rheumatic & musculoskeletal diseases. 2014;20(2):87-90.
35. Cella D, Yount S, Sorensen M, Chartash E, Sengupta N, Grober J. Validation of the Functional Assessment of Chronic Illness Therapy Fatigue Scale relative to other instrumentation in patients with rheumatoid arthritis. The Journal of rheumatology. 2005;32(5):811-9.
36. Radloff L. The CES-D Scale: A Self-Report Depression Scale for Research in the General Population. Applied Psychological Measurement. 1977;1(3):385-401.
37. Larsen A, Dale K, Eek M. Radiographic evaluation of rheumatoid arthritis and related conditions by standard reference films. Acta Radiol Diagn (Stockh). 1977;18(4):481-91.
38. Baan H, Drossaers-Bakker W, Dubbeldam R, van de Laar M. We should not forget the foot: relations between signs and symptoms, damage, and function in rheumatoid arthritis. Clinical rheumatology. 2011;30(11):1475-9.
39. Wechalekar MD, Lester S, Proudman SM, Cleland LG, Whittle SL, Rischmueller M, et al. Active foot synovitis in patients with rheumatoid arthritis: applying clinical criteria for disease activity and remission may result in underestimation of foot joint involvement. Arthritis and rheumatism. 2012;64(5):1316-22.
40. Kaneko A, Matsushita I, Kanbe K, Arai K, Kuga Y, Abe A, et al. Development and validation of a new radiographic scoring system to evaluate bone and cartilage destruction and healing of large joints with rheumatoid arthritis: ARASHI (Assessment of rheumatoid arthritis by scoring of large joint destruction and healing in radiographic imaging) study. Modern rheumatology. 2013;23(6):1053-62.
41. Mader U, Martin BW, Schutz Y, Marti B. Validity of four short physical activity questionnaires in middle-aged persons. Medicine and science in sports and exercise. 2006;38(7):1255-66.
42. Jefferis BJ, Parsons TJ, Sartini C, Ash S, Lennon LT, Wannamethee SG, et al. Does duration of physical activity bouts matter for adiposity and metabolic syndrome? A cross-sectional study of older British men. The international journal of behavioral nutrition and physical activity. 2016;13:36.
43. Amagasa S, Fukushima N, Kikuchi H, Takamiya T, Oka K, Inoue S. Light and sporadic physical activity overlooked by current guidelines makes older women more active than older men. The international journal of behavioral nutrition and physical activity. 2017;14(1):59.
44. Prince SA, Adamo KB, Hamel ME, Hardt J, Connor Gorber S, Tremblay M. A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review. The international journal of behavioral nutrition and physical activity. 2008;5:56.
45. Eurenius E, Stenstrom CH. Physical activity, physical fitness, and general health perception among individuals with rheumatoid arthritis. Arthritis and rheumatism. 2005;53(1):48-55.
46. van den Berg MH, de Boer IG, le Cessie S, Breedveld FC, Vliet Vlieland TP. Are patients with rheumatoid arthritis less physically active than the general population? Journal of clinical rheumatology : practical reports on rheumatic & musculoskeletal diseases. 2007;13(4):181-6.
47. van Hoogmoed D, Fransen J, Bleijenberg G, van Riel P. Physical and psychosocial correlates of severe fatigue in rheumatoid arthritis. Rheumatology (Oxford, England). 2010;49(7):1294-302.
48. Hewlett S, Carr M, Ryan S, Kirwan J, Richards P, Carr A, et al. Outcomes generated by patients with rheumatoid arthritis: how important are they? Musculoskeletal care. 2005;3(3):131-42.
49. Hammer NM, Midtgaard J, Hetland ML, Krogh NS, Esbensen BA. Physical activity behaviour in men with inflammatory joint disease: a cross-sectional register-based study. Rheumatology. 2018;57(5):803-12.