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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 was part of a cohort study designed to determine disease activity is associated with PA in RA patients. 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. We measured the wear time, time of vigorous-intensity PA, moderate-intensity PA, light-intensity PA, and sedentary behavior per day using a triaxial accelerometer. 34 patients were included in the study. The accelerometer-measured moderate-to-vigorous PA (MVPA) was 17.2 min/day and 10.6 min/day in the LDA group and MHDA group (p < 0.05), respectively. There was no significant association between RA disease activity level and accelerometer-measured PA with adjustment for age and Functional Assessment of Chronic Illness Therapy-Fatigue score. There was no correlation between accelerometer-measured MVPA and self-reported MVPA in the MHDA group, but these factors were correlated in the LDA group (rs = 0.57, p < 0.05). In conclusion, no significant association was noted between RA disease activity level and accelerometer-measured PA.

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) has a positive effect on preventing several chronic diseases and can reduce all-cause mortality [2, 3] 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 [4,5,6]. Comparing patients with RA and healthy subjects was reported that the amount of PA was significantly lower in patients with RA than in controls [7]. In several studies evaluating moderate-to-vigorous PA (MVPA) using accelerometers in patients with RA, RA patients showed lower MVPA than healthy subjects [7,8,9]. 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 [9, 10]. However, other studies using accelerometer reported that disease activity levels did not significantly correlate with PA [8, 11]. Patients with RA are more likely to feel fatigued and depression due to high disease activity, resulting in affected PA [12, 13]. There have been no reports evaluating PA and Disease activity adjusted for fatigue in the patient RA.

Previously, PA was converted into metabolic equivalents (METs) by using a self-reported questionnaire and was evaluated [14]. Recently, an accelerometer has attracted some attention as a valuable tool for evaluating PA [15,16,17,18]. The triaxial accelerometer can evaluate changes in activity levels and separate sedentary time and active time [19,20,21]. Population-based research, such as the National Health and Nutrition Examination Survey, have used accelerometers for PA measurements rather than conventional methods [22]. 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 [23, 24].

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 a self-reported questionnaire 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.

Main text

Materials and methods

The cross-sectional study was part of a cohort study designed to determine disease activity is associated with PA in RA patients. From November 22, 2015 through December 31, 2016, consecutive patients who visited their rheumatologist at the outpatient clinic of the Showa University Hospital in Tokyo, Japan were invited to participate. The eligibility criteria were as follows: (1) fulfillment of the American Rheumatism Association 1987 revised Criteria for RA [25] 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) lower limb deficiency that requires prosthesis for walking. 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) [26]. 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 [27]. 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) [28, 29].

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 [30, 31]. 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 [32]. 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 [28, 29, 33, 34]. 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 [35]. At the outpatient clinic visit, the subjective physical function was assessed using the Modified Health Assessment Questionnaire (mHAQ) [36]. The health-related quality of life was measured using the Medical Outcomes Study (MOS) 12-item Short-Form Health Survey (SF-12) [37]. The Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F version 4) questionnaire was used to calculate the level of fatigue [38, 39]. The Center for Epidemiologic Studies Depression Scale (CES-D) was used to assess depressive symptoms [40]. 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 [41].

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. To assess the association between RA disease activity level and physical activity, multilinear regression analysis with adjustment for age and the FACIT-F score was performed (regression coefficient – 2.97; 95% CI: − 8.46 to 2.52; p = 0.28). For all analyses, statistical tests were two-sided, and significance was defined as p < 0.05.

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 = 0.003).

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 = 0.018). A significant difference in SB between the two groups was not noted (p = 0.015).

Table 1 Comparison of PA in the LDA and MHDA groups

RA disease activity was not associated with the MVPA score in the multilinear regression analysis adjusted for age and FACIT-F score (regression coefficient – 2.97; 95% CI: − 8.46 to 2.52; p = 0.28). 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 = 0.57, p < 0.05) but not for all the patients or the MHDA group.

Fig. 1
figure 1

The relationship between DAS28-ESR and moderate-to-vigorous physical activity (MVPA) obtained from an accelerometer and iPAQ. There was no association between DAS28-ESR and accelerometer-measured MVPA in total patients (rs = 0.13, p = 0.03), LDA group (rs = 0.15, p = 0.31), or MHDA group (rs = 0.01, p = 0.59). Furthermore, there was no association between DAS28-ESR and self-reported MVPA in total patients (rs = 0.05, p = 0.19), LDA group (rs = 0.01, p = 0.92), and MHDA group (rs = 0.01, p = 0.8). DAS28-ESR, Disease Activity Score 28-joint count erythrocyte sedimentation rate

Table 2 Spearman’s correlations between iPAQ score and accelerometer measurement

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 [9, 24]. 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 [15, 16, 22], 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 [8, 42, 43]. 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 [44]. Third, we evaluated the relationship between disease activity and PA, adjusting for fatigue. Fatigue is a common symptom among RA patients [13]. Fatigue is associated with disease activity in RA, and also with PA in RA patients [13, 38]. Disease activity, fatigue, and PA might be associated in RA patients. For comprehensive health management of RA patients, it may be important not only to improve disease activity but also the treatment of fatigue by cognitive-behavioral therapy and improvement of physical function by physical exercise [45, 46].

The MVPA evaluated by self-report and accelerometer may not be correlated in moderate/high-disease-activity RA patients. Our results differ from previous reports where self-reported PA was relatively consistent with accelerometer-measured PA among healthy subjects [29, 47]. There are several possible reasons for this finding. First, the iPAQ only measures MVPA sustained for more than 10 min. However, the triaxial accelerometer can measure short-term MVPA lasting for fewer than 10 min. Therefore, the PA results obtained from the two methods were different [48, 49]. Second, MVPA is overestimated, and SB is underestimated in the self-reported questionnaire compared with that in the accelerometer [50,51,52]. Moderate PA might be overestimated by self-reported PA compared with the accelerometer-measured PA in the moderate/high-disease-activity RA patients.

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 [53,54,55]. 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 after adjusting for age and fatigue. 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.

Availability of data and materials

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

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

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 Rheum. 2008;59(1):42–50.

    Article  PubMed  Google Scholar 

  2. Warburton DER, Bredin SSD. Health benefits of physical activity: a systematic review of current systematic reviews. Curr Opin Cardiol. 2017;32(5):541–56.

    Article  PubMed  Google Scholar 

  3. Garber CE, Blissmer B, Deschenes MR, Franklin BA, Lamonte MJ, Lee IM, et al. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exercise. 2011;43(7):1334–59.

    Article  Google Scholar 

  4. Verhoeven F, Tordi N, Prati C, Demougeot C, Mougin F, Wendling D. Physical activity in patients with rheumatoid arthritis. Joint Bone Spine Rev Rhumat. 2016;83(3):265–70.

    Article  Google Scholar 

  5. 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. Cochrane Database Syst Rev. 2009;4:Cd006853.

    Google Scholar 

  6. Stenstrom CH, Minor MA. Evidence for the benefit of aerobic and strengthening exercise in rheumatoid arthritis. Arthritis Rheum. 2003;49(3):428–34.

    Article  PubMed  Google Scholar 

  7. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Prioreschi A, Hodkinson B, Avidon I, Tikly M, McVeigh JA. The clinical utility of accelerometry in patients with rheumatoid arthritis. Rheumatology (Oxford). 2013;52(9):1721–7.

    Article  Google Scholar 

  9. Hernandez-Hernandez V, Ferraz-Amaro I, Diaz-Gonzalez F. Influence of disease activity on the physical activity of rheumatoid arthritis patients. Rheumatology (Oxford). 2014;53(4):722–31.

    Article  Google Scholar 

  10. 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.

    Article  PubMed  Google Scholar 

  11. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Fenton SAM, Veldhuijzen van Zanten JJCS, Metsios GS, Rouse PC, Yu C-A, Kitas GD, et al. Autonomy support, light physical activity and psychological well-being in rheumatoid arthritis: a cross-sectional study. Mental Health Phys Activity. 2018;14:11–8.

    Article  Google Scholar 

  13. Rongen-van Dartel SA, Repping-Wuts H, van Hoogmoed D, Knoop H, Bleijenberg G, van Riel PL, et al. Relationship between objectively assessed physical activity and fatigue in patients with rheumatoid arthritis: inverse correlation of activity and fatigue. Arthritis Care Res. 2014;66(6):852–60.

    Article  CAS  Google Scholar 

  14. Klesges RC, Eck LH, Mellon MW, Fulliton W, Somes GW, Hanson CL. The accuracy of self-reports of physical activity. Med Sci Sports Exerc. 1990;22(5):690–7.

    Article  CAS  PubMed  Google Scholar 

  15. Loprinzi PD, Sheffield J, Tyo BM, Fittipaldi-Wert J. Accelerometer-determined physical activity, mobility disability, and health. Disabil Health J. 2014;7(4):419–25.

    Article  PubMed  Google Scholar 

  16. 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.

    Article  CAS  PubMed  Google Scholar 

  17. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008;40(1):181–8.

    Article  PubMed  Google Scholar 

  18. Bonomi AG, Goris AH, Yin B, Westerterp KR. Detection of type, duration, and intensity of physical activity using an accelerometer. Med Sci Sports Exerc. 2009;41(9):1770–7.

    Article  PubMed  Google Scholar 

  19. 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. Br J Nutr. 2011;105(11):1681–91.

    Article  CAS  PubMed  Google Scholar 

  20. Rowlands AV, Yates T, Olds TS, Davies M, Khunti K, Edwardson CL. Sedentary sphere: wrist-worn accelerometer-brand independent posture classification. Med Sci Sports Exerc. 2016;48(4):748–54.

    Article  PubMed  Google Scholar 

  21. 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.

    Article  PubMed  Google Scholar 

  22. 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. J Epidemiol Commun Health. 2018;72:764–9.

    Article  Google Scholar 

  23. 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 Res. 2017;69(10):1535–45.

    Article  CAS  Google Scholar 

  24. 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 Res. 2016;68(2):280–4.

    Article  Google Scholar 

  25. 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 Rheum. 1988;31(3):315–24.

    Article  CAS  PubMed  Google Scholar 

  26. 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. Ann Rheum Dis. 2009;68(6):954–60.

    Article  CAS  PubMed  Google Scholar 

  27. 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? Ann Rheum Dis. 2015;74(6):1132–7.

    Article  CAS  PubMed  Google Scholar 

  28. 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. J Epidemiol. 2011;21(6):459–65.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–95.

    Article  PubMed  Google Scholar 

  30. Owen N, Healy GN, Matthews CE, Dunstan DW. Too much sitting: the population health science of sedentary behavior. Exerc Sport Sci Rev. 2010;38(3):105–13.

    Article  PubMed  PubMed Central  Google Scholar 

  31. 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. Med Sci Sports Exerc. 2011;43(8):1575–81.

    Article  PubMed  Google Scholar 

  32. Semanik P, Song J, Chang RW, Manheim L, Ainsworth B, Dunlop D. Assessing physical activity in persons with rheumatoid arthritis using accelerometry. Med Sci Sports Exerc. 2010;42(8):1493–501.

    Article  PubMed  PubMed Central  Google Scholar 

  33. 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).

    Google Scholar 

  34. 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. Int J Behav Nutr Phys Act. 2012;9:113.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83.

    Article  CAS  PubMed  Google Scholar 

  36. 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. Mod Rheumatol. 2016;26(4):529–33.

    Article  PubMed  Google Scholar 

  37. Ware J Jr, Kosinski M, Keller SD. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34(3):220–33.

    Article  PubMed  Google Scholar 

  38. 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. J Clin Rheumatol Pract Rep Rheumat Musculoskel Dis. 2014;20(2):87–90.

    Google Scholar 

  39. 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. J Rheumatol. 2005;32(5):811–9.

    PubMed  Google Scholar 

  40. Radloff L. The CES-D Scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401.

    Article  Google Scholar 

  41. 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.

    Article  CAS  Google Scholar 

  42. 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. Clin Rheumatol. 2011;30(11):1475–9.

    Article  PubMed  PubMed Central  Google Scholar 

  43. 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 Rheum. 2012;64(5):1316–22.

    Article  PubMed  Google Scholar 

  44. 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. Mod Rheumatol. 2013;23(6):1053–62.

    Article  PubMed  Google Scholar 

  45. Hewlett S, Ambler N, Almeida C, Cliss A, Hammond A, Kitchen K, et al. Self-management of fatigue in rheumatoid arthritis: a randomised controlled trial of group cognitive-behavioural therapy. Ann Rheum Dis. 2011;70(6):1060–7.

    Article  PubMed  Google Scholar 

  46. Metsios GS, Kitas GD. Physical activity, exercise and rheumatoid arthritis: effectiveness, mechanisms and implementation. Best Pract Res Clin Rheumatol. 2018;32(5):669–82.

    Article  PubMed  Google Scholar 

  47. Mader U, Martin BW, Schutz Y, Marti B. Validity of four short physical activity questionnaires in middle-aged persons. Med Sci Sports Exerc. 2006;38(7):1255–66.

    Article  PubMed  Google Scholar 

  48. 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. Int J Behav Nutr Phys Act. 2016;13:36.

    Article  PubMed  PubMed Central  Google Scholar 

  49. 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. Int J Behav Nutr Phys Act. 2017;14(1):59.

    Article  PubMed  PubMed Central  Google Scholar 

  50. 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. Int J Behav Nutr Phys Act. 2008;5:56.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Eurenius E, Stenstrom CH. Physical activity, physical fitness, and general health perception among individuals with rheumatoid arthritis. Arthritis Rheum. 2005;53(1):48–55.

    Article  PubMed  Google Scholar 

  52. 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? J Clin Rheumatol Pract Rep Rheumat Musculoskel Dis. 2007;13(4):181–6.

    Google Scholar 

  53. van Hoogmoed D, Fransen J, Bleijenberg G, van Riel P. Physical and psychosocial correlates of severe fatigue in rheumatoid arthritis. Rheumatology (Oxford). 2010;49(7):1294–302.

    Article  Google Scholar 

  54. 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? Musculoskelet Care. 2005;3(3):131–42.

    Article  Google Scholar 

  55. 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.

    Article  PubMed  Google Scholar 

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Acknowledgements

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.

Funding

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

Author information

Authors and Affiliations

Authors

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.

Authors' informations

YT, TN, ON, and KI are associated with the Department of Orthopedics, Showa University School of Medicine, Shinagawa-ku, Tokyo, Japan. NB is associated with Department of Rheumatology, Department of Medicine, Showa University School of Medicine, Tokyo, Japan; Department of Healthcare Epidemiology, Kyoto University Graduate School of Medicine and Public Health, Kyoto, Japan; and Center for Innovative Research for Communities and Clinical Excellence, Fukushima Medical University, Fukushima, Japan.

Corresponding author

Correspondence to Nobuyuki Yajima.

Ethics 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.

Competing interests

The authors declare that they have no competing interests.

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Supplementary Information

Additional file 1:

A flowchart of our participants’ selection.

Additional file 2:

Title of data: Characteristics of the participants.

Additional file 3:

Title of data: Subscale of SF-12 of LDA and MHDA groups.

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Toyoshima, Y., Yajima, N., Nemoto, T. et al. Relationship between disease activity level and physical activity in rheumatoid arthritis using a triaxial accelerometer and self-reported questionnaire. BMC Res Notes 14, 242 (2021). https://doi.org/10.1186/s13104-021-05666-w

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