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. Author manuscript; available in PMC: 2026 Aug 6.
Published in final edited form as: Disabil Rehabil. 2025 Mar 31;47(21):5496–5502. doi: 10.1080/09638288.2025.2481981

Sedentary behavior, physical activity, and health-related quality of life in adults with multiple sclerosis

Brenda Jeng 1,2,*, Katie L J Cederberg 2,3, Jeffer E Sasaki 2,4, Robert W Motl 1,2
PMCID: PMC13440293  NIHMSID: NIHMS2070023  PMID: 40165361

Abstract

Purpose:

We examined sedentary behavior as a correlate of health-related quality of life (HRQOL) in multiple sclerosis (MS), while accounting for levels of physical activity in this cross-sectional study.

Materials and Methods:

Participants with MS (N=233) wore an accelerometer, which measured time spent per day of sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), and completed the 29-item Multiple Sclerosis Impact Scale (MSIS-29) for physical and psychological HRQOL.

Results:

There was no main effect of sedentary behavior on physical or psychological HRQOL, and no further effect of sedentary behavior by LPA or MVPA. However, there were main effects of LPA (p<0.01) and MVPA (p<0.01) on physical HRQOL and a main effect of MVPA (p=0.02), but not LPA, on psychological HRQOL.

Conclusion:

Sedentary behavior was not associated with HRQOL, but those who engaged in higher levels of physical activity, particularly MVPA, reported better HRQOL in MS. This pattern may suggest that increasing physical activity rather than reducing sedentary behavior might yield better MS-specific quality of life.

Keywords: multiple sclerosis, sedentary behavior, physical activity, quality of life, health behavior, well-being

INTRODUCTION

Health-related quality of life (HRQOL) is an umbrella term that encompasses a person’s perception of the physical and psychological components of health status (Benito-Leon & Martinez-Martin, 2003; Mitchell et al., 2005; Rejeski & Mihalko, 2001; Stewart & King, 1991), and the manifestations of neurological diseases including body function, activities, and participation may have a significant impact on disease-specific physical and psychological quality of life (World Health Organization, 2007). For example, multiple sclerosis (MS) is a prevalent, immune-mediated disease of the central nervous system, and the damage and its location manifest as loss of cognitive and physical function as well as symptoms such as fatigue, pain, depression, drop foot, and spasticity (Briggs & Hill, 2019; Trapp & Nave, 2008). Those aforementioned outcomes of MS may result in lower levels of physical activity, higher levels of sedentary behavior, and compromised HRQOL consistent with the International Classification of Functioning, Disability and Health model (World Health Organization, 2007).

Physical activity has been associated with better HRQOL in persons with MS (Motl et al., 2009; Motl et al., 2013). Physical activity is defined as a behavior that consists of bodily movement produced by contraction of skeletal muscles resulting in increased energy expenditure above resting levels (Bouchard et al., 1994). One cross-sectional study of 292 persons with MS reported that higher physical activity levels were positively associated with better HRQOL (Motl et al., 2009). One longitudinal study of 269 persons with MS demonstrated that naturally-occurring increases (or decreases) in physical activity were associated with better (or worse) HRQOL across a one-year period (Motl et al., 2013), and fatigue, depressive symptoms, pain, social support, and self-efficacy mediated the association between physical activity and HRQOL (Motl et al., 2009; Motl et al., 2013).

Sedentary behavior too may be associated with HRQOL among persons living with MS. Unlike physical activity, sedentary behavior represents the other end of the activity spectrum and is defined as any waking activity performed while sitting or lying that does not increase energy expenditure above 1.5 metabolic equivalents (METs; one MET is equivalent to a person’s resting metabolic rate) (Manns et al., 2012; Owen et al., 2010). Sedentary behavior has been associated with health outcomes independently of physical activity, including all-cause mortality, type 2 diabetes, and metabolic syndrome, in the general population (de Rezende et al., 2014). There is consistent evidence that persons with MS are more sedentary than the general population (Sasaki et al., 2018; Zheng et al., 2023), yet there is limited information on why this difference exists between MS and controls. There further is limited information on sedentary behavior and its possible outcomes in this population (Veldhuijzen van Zanten et al., 2016). To date, researchers have reported that the volume of sedentary behavior may be associated with hypertension, MS type, mobility disability in MS (Hubbard & Motl, 2015; Hubbard et al., 2015; Hubbard et al., 2018), and these are possible determinants of HRQOL in MS (Benito-Leon & Martinez-Martin, 2003). However, these are non-modifiable factors, and we aimed to identify modifiable factors that future interventions may target to improve HRQOL in MS.

There is evidence of an association between sedentary behavior and HRQOL in adults from the general population as well as those living with chronic conditions. For example, a recent meta-analysis of 18 papers reported that persons of the general population who engaged in lower levels of sedentary behavior reported better physical HRQOL (Boberska et al., 2018). Another study of 54 non-specific cancer survivors reported that those who spent more time sedentary had worse physical HRQOL, even when controlling for moderate-to-vigorous physical activity (George et al., 2014). Such data support that persons who are more sedentary may have worse HRQOL; however, this relationship has not been examined in persons with MS, particularly its independence and interaction across levels of light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA).

The current study examined the associations between the volume of sedentary behavior and the physical and psychological domains of HRQOL in persons with MS, while considering levels of LPA and MVPA. We expected that lower levels of sedentary behavior would be associated with higher HRQOL, even when accounting for levels of LPA and MVPA. If our hypotheses are correct, such evidence would highlight the importance of designing interventions that reduce the volume of sedentary behavior, perhaps as a precursor for promoting LPA and MVPA, for improving HRQOL in MS.

METHODS

Participants

We recruited persons with MS who were members of the North American Research Committee on Multiple Sclerosis (NARCOMS) patient registry. Printed letters were distributed by the NARCOMS staff among a random sample of 1,000 persons with MS who completed the biannual registry update survey (Fall, 2017). Those who were interested in participating contacted the research team via email or telephone, and members of the research team screened interested individuals based on the following inclusion criteria: (1) randomly selected member of the NARCOMS registry and (2) willingness to complete the battery of questionnaires, wear the accelerometer, and return the materials via the United States Postal Service (USPS). Of the 1,000 persons with MS who were mailed flyers, 316 persons contacted the laboratory, and 296 of these persons underwent telephone screening; one person declined participation after description of the study. The research team then distributed the study materials. Of those who returned the packet, nine declined participation based on not providing informed consent, and one person declined participation based on no interest in wearing the accelerometer. Eleven persons did not return packets for unknown reasons. Of 275 persons with MS who participated in the study, 253 persons provided valid accelerometry data for inclusion in this paper. The final sample consisted of 233 persons with MS; we excluded those who used a wheelchair or scooter as the main form of mobility or were bedridden. Data from this sample were from a previously published paper (Jeng et al., 2019).

Measures

Device-measured sedentary behavior and physical activity.

The ActiGraph model GT3X+ accelerometer provided a device measurement of sedentary behavior and physical activity. The accelerometer was placed in a pouch on an elastic belt worn around the waist above the nondominant hip during the waking hours of the day, except while showering, bathing, and swimming, for 7 days. The participants were instructed to record the time that the accelerometer was worn daily in a log, and the log was initially inspected for days of wear time to be included in the processing of data. The accelerometer data were downloaded, processed into one-minute epoch with low frequency extension, and then scored for wear time spent in sedentary behavior, and LPA and MVPA per day and organized from Monday through Sunday. Time spent in sedentary behavior were based on less than 100 counts per minute. Cut-points for LPA were based on 100 to 1,744 counts, and cut-points for MVPA were 1,745 counts and above (Sandroff et al., 2014). We considered a day as valid if there was a minimum of 10 hours (i.e., 600 minutes) of total wear time without continuous zeros exceeding 30 minutes, and participants with 1 or more valid days of data were included in the analyses. The outcomes of interest were (a) total sedentary time spent per day, (b) minutes spent in LPA, and (c) minutes spent in MVPA.

Health-related quality of life.

Health-related quality of life was measured using the Multiple Sclerosis Impact Scale (MSIS-29) (Hobart et al., 2001). This 29-item questionnaire is a disease-specific measure of physical (20 items) and psychological (9 items) impact of MS from the participant’s perspective during the past two weeks. For example, item #1, “In the past two weeks, how much has your MS limited your ability to do physically demanding tasks?”, assessed physical HRQOL, whereas item #25, “In the past two weeks, how much have you been bothered by feeling anxious or tense?”, assessed psychological HRQOL. The items were rated from 1 (not at all) to 5 (extremely), and item scores were summed into subscales of physical and psychological domains of HRQOL and transformed into a scale of 0 through 100; higher scores on both subscales reflected greater impact of MS on HRQOL (i.e., worse physical and psychological HRQOL). There is evidence of reliability and validity in persons with MS in both community- and hospital-based settings (Hobart et al., 2001; Riazi et al., 2002).

Demographic and clinical characteristics.

Participants provided demographic and clinical information, which included age, sex, race, MS type, and disease duration. Disability status was assessed using the Patient Determined Disease Steps (PDDS), a self-report measure of disability level on a scale that ranges from 0 (normal) to 8 (bedridden) (Hohol et al., 1995). The scores have been validated as a measure of disability status in persons with MS based on being linearly and strongly correlated with physician-rated Expanded Disability Status Scale scores (Learmonth et al., 2013).

Procedure

The procedure was approved by a University Institutional Review Board, and all participants provided written informed consent for this cross-sectional study. After telephone screening, the research team sent all participants who verbally volunteered a packet containing the informed consent document, a battery of questionnaires, accelerometer with instructions and log, and a pre-stamped and pre-addressed envelope for return service through USPS. The researchers contacted participants to ensure that the packet was received and the instructions were understood. The participants were instructed to wear the accelerometer for 7 days and complete the questionnaires at the end of the 7-day period. The questionnaires were checked for completeness within 48 hours of receipt, and in the event of missing data, a member of the research team contacted the participant and collected the data over the phone. Participants received $10 for voluntary participation.

Data Analysis

All data were analyzed using SPSS, Version 25. We provided descriptive statistics as mean with standard deviation (SD), unless otherwise noted. We examined associations among volume of sedentary behavior, LPA, and MVPA with scores from the physical and psychological subscales of MSIS-29 using Spearman’s rank-order bivariate correlations (rs). We further conducted two, two-way univariate analyses of variance (ANOVA) wherein we examined the main effect and interaction terms for levels of sedentary behavior and physical activity on scores from the physical and psychological subscales of the MSIS-29. The volumes of sedentary behavior, LPA, and MVPA were trichotomized into low, moderate, and high groups based on tertiles (i.e., 3 levels of the two, between-subjects factors). We then conducted two-way (level of sedentary by either level of LPA or MVPA) ANOVAs on MSIS-29 subscale scores. The effect sizes for the ANOVAs were expressed as partial eta-squared (ηp2) with values of .01, .06, and .14 interpreted as small, moderate, and large effects, respectively (Cohen, 1988).

RESULTS

Sample Characteristics

The sample (N=233) consisted of persons with a mean age of 59.1 (9.8) years who were primarily female (n=188, 81%) and Caucasian (n=220, 94%). The sample further consisted mostly of persons with relapsing-remitting MS (n=168, 72%) with a mean disease duration of 19.8 (9.7) years and a median (range) PDDS score of 3 (0–6); the median score corresponded with moderate disability status.

Sedentary Behavior, Physical Activity, and Health-Related Quality of Life Characteristics

Descriptive statistics for the volume of device-measured sedentary behavior and physical activity as well as physical and psychological MSIS-29 scores are provided in Table 1. Total wear time per day was 812.2 (86.2) minutes. The mean total sedentary time per day of the overall sample was 542.8 (88.4) minutes per day; this value was higher in our sample than adults from the general population or persons with MS who had moderate disability (Ezeugwu et al., 2015; Healy et al., 2011). Regarding physical activity, our sample had 253.3 (80.3) minutes per day of LPA and 16.0 (21.2) minutes per day of MVPA. The value of LPA of the present sample is lower than samples of persons with mild and moderate MS, whereas the values of MVPA were lower than persons with mild MS, but higher than persons with moderate MS (Ezeugwu et al., 2015). The scores for the physical and the psychological subscales of MSIS-29 were 30.6 (22.8) and 24.9 (18.8), respectively; this indicated that our sample had better HRQOL than other samples with MS (Riazi et al., 2004).

Table 1.

Descriptive statistics for measures of sedentary behavior, physical activity, and health-related quality of life for the sample of 233 persons with multiple sclerosis.

Variable Mean (SD)
Sedentary Behavior Time per day of sedentary behavior (min/day) 542.8 (88.4)
Physical Activity Time per day of LPA (min/day) 253.3 (80.0)
Time per day of MVPA (min/day) 16.0 (21.2)
HRQOL Physical MSIS-29 30.6 (22.8)
Psychological MSIS-29 24.9 (18.8)
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Note: LPA, light physical activity; MVPA, moderate-to-vigorous physical activity; HRQOL, health-related quality of life; MSIS-29, 29-item Multiple Sclerosis Impact Scale.

Relationship between Sedentary Behavior and Health-Related Quality of Life

The Spearman rank-order bivariate correlations are provided in Table 2. The non-parametric bivariate correlations indicated that total sedentary time per day was significantly, albeit weakly associated with the physical subscale of the MSIS-29 (rs=.13, p<.05). Regarding physical activity, LPA was significantly associated with both physical (rs=–.32, p<.01) and psychological (rs=–.14, p<.05) subscales of the MSIS-29. There were significant, negative associations between MVPA and the physical (rs=–.52, p<.01) and psychological (rs=–.21, p<.01) subscales of the MSIS-29.

Table 2.

Spearman bivariate correlations among sedentary behavior, physical activity, and health-related quality of life among 233 persons with multiple sclerosis.

MSIS-29
Variable Physical Psychological
Sedentary Behavior Sedentary time .13* .03
Physical Activity LPA −.32* −.14*
MVPA −.52* −.21*
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Note: MSIS-29, 29-item Multiple Sclerosis Impact Scale; LPA, light physical activity; MVPA, moderate-to-vigorous physical activity.

*

p<0.05.

Sedentary Behavior and Health-Related Quality of Life Across Levels of Physical Activity

Figures 1 and 2 provide the physical and psychological MSIS-29 subscale scores for persons with MS by level of sedentary behavior and levels of LPA and MVPA, respectively.

Fig. 1.

Fig. 1

Fig. 1

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The level of sedentary behavior and physical MSIS-29 subscale scores for persons with multiple sclerosis who engage in low, moderate, and high levels of light physical activity (panel a) and moderate-to-vigorous physical activity (panel b)

Fig. 2.

Fig. 2

Fig. 2

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The level of sedentary behavior and psychological MSIS-29 subscale scores for persons with multiple sclerosis who engage in low, moderate, and high levels of light physical activity (panel a) and moderate-to-vigorous physical activity (panel b)

Physical Domain of MSIS-29.

The two-way ANOVA did not identify a statistically significant interaction between sedentary behavior and LPA (F[4,232]=2.36, p=0.54, ηp2=0.04) or MVPA (F[4,231]=0.70, p=0.59, ηp2=0.01) on the physical subscale scores of the MSIS-29 (Figure 1). There was no main effect of sedentary behavior on the physical domain subscales of the MSIS-29, when accounting for LPA (F[2,232]=0.27, p=0.77, ηp2=0.00) or MVPA (F[2,231]=0.03, p=0.97, ηp2=0.00). The analyses did identify a main effect of LPA on physical MSIS-29 subscale scores (F[2,232]=5.47, p<0.01, ηp2=0.05). The analyses further identified a main effect of MVPA on the physical domain subscale scores of the MSIS-29 (F[2,231]=25.85, p<0.01, ηp2=0.19). These results indicated that higher levels of LPA and MVPA were associated with better physical HRQOL.

Psychological Domain of MSIS-29.

The analyses did not identify a significant interaction between sedentary behavior and LPA (F[4,232]=0.95, p=0.44, ηp2=0.02) or MVPA (F[4,231]=0.35, p=0.84, ηp2=0.01) on the psychological subscale scores of MSIS-29 (Figure 2). There were no main effects of sedentary behavior on the physical domain subscales of the MSIS-29 when accounting for LPA (F[2,232]=0.13, p=0.88, ηp2=0.00) or MVPA (F[2,231]=0.51, p=0.60, ηp2=0.01). We further note that the analyses revealed no main effect of LPA on psychological domain of MSIS-29 (F[2,232]=0.86, p=0.42, ηp2=0.01). However, the analyses identified a main effect of MVPA on the psychological domain of MSIS-29 (F[2,231]=3.86, p=0.02, ηp2=0.03); this indicated that higher levels of MVPA were associated with better psychological HRQOL.

DISCUSSION

The study examined the association between the volume of sedentary behavior and physical activity with the physical and psychological domains of HRQOL in persons with MS. We further examined the associations between sedentary behavior and the domains of HRQOL when taking physical activity into account. Our results indicated that volume of sedentary behavior was weakly associated with the physical domain, but not the psychological domain, of HRQOL, based on MSIS-29 scores. However, this association was not present in the analyses that included LPA and MVPA. Both LPA and MVPA were significantly associated with physical HRQOL, whereas only MVPA was associated with psychological HRQOL. Such results suggest that persons with MS who engage in more LPA and MVPA reported better physical and psychological HRQOL, regardless of sedentary behavior status. This may underscore the importance of designing interventions for increasing physical activity, and perhaps reducing sedentary behavior, as a behavioral approach for improving physical and psychological HRQOL in persons with MS.

We performed the first study that examined device-measured volume of sedentary behavior as a correlate of HRQOL in MS. Researchers have examined the relationship between device-measured volume of sedentary behavior and HRQOL in other chronic conditions. For example, one study reported that there was no relationship between sedentary time and HRQOL in 178 survivors of colon cancer (Vallance et al., 2014). By comparison, another study reported that breast cancer survivors who demonstrated prolonged sedentary time had worse physical HRQOL (George et al., 2014). Our bivariate results were consistent with observations of the latter study, as persons with MS who spent more time sedentary demonstrated worse physical HRQOL, although the association was weak in magnitude. However, the bivariate correlations between physical activity and physical and psychological HRQOL were stronger than those between sedentary behavior and HRQOL, and there was no association between sedentary behavior and HRQOL when accounting for physical activity. This may highlight the importance of increasing physical activity, and perhaps secondarily reducing sedentary behavior, for improving HRQOL in MS.

We observed that sedentary behavior was not associated with HRQOL when considering levels of LPA and MVPA, and this was consistent with previous research in survivors of breast cancer and persons with congestive heart failure. For example, a study of 358 breast cancer survivors reported no significant relationship between volume of sedentary behavior and HRQOL after controlling for physical activity (Phillips et al., 2015). Another study included 190 persons with congestive heart failure and reported that once LPA and MVPA were considered, sedentary behavior was not associated with HRQOL (Edwards & Loprinzi, 2016). Overall, this suggests that LPA and MVPA have independent associations with HRQOL in other populations, and this is consistent with the observations reported in the current paper. Indeed, there is evidence from cross-sectional and longitudinal studies of a significant association between physical activity and HRQOL in MS (Motl & McAuley, 2014; Motl et al., 2013). We further identified better physical, but not psychological, HRQOL with higher levels of LPA in our sample with MS. The physical domain of MSIS-29 takes all physical manifestations of MS (e.g., stiffness, spasms) into account, and physical activity is a modifiable behavior that may be used to improve physical HRQOL. Sedentary behavior was not associated with HRQOL after controlling for physical activity, but we do not interpret these findings as meaning that reducing sedentary behavior is unimportant. For example, it may still be beneficial to reduce sedentary behavior in persons with MS, as previous studies have identified hypertension and walking dysfunction as correlates of high volumes of sitting time (Hubbard & Motl, 2015; Hubbard et al., 2018), and transition towards the other end of the activity spectrum through increasing levels of LPA and then MVPA.

There are limitations that should be considered when interpreting the results of this study. We had a relatively large sample of 233 persons, but our sample included primarily older and Caucasian women with relapsing-remitting MS; this sample may not be representative of the general population with MS. We further could not identify activities participants engaged in while sedentary (i.e., reading, board games, TV viewing, etc.), as some sedentary activities may differentially influence HRQOL, particularly in the psychological domain. Another limitation was that employment, particularly those that require long period of sitting, may have played a role in the amount of sedentary behavior a person engages in; however, a recent study reported that employment is not a predictor of accelerometry-based sedentary behavior in adults with MS (Jeng et al., 2019). An additional limitation was the cross-sectional study design in that persons only wore the accelerometer for one week and were asked about HRQOL for the past two weeks; this does not permit the inference of causality among sedentary behavior, physical activity, and HRQOL. Furthermore, a limitation of using this device measure of physical activity was that the unit was unable to capture any water-based activities such as swimming, as the unit is not waterproof. We further did not include data on comorbid conditions.

The present study indicated that sedentary behavior was not associated with HRQOL, but those who engaged in higher levels of physical activity, particularly MVPA, reported better physical and psychological HRQOL in MS. This pattern of results may suggest that increasing physical activity might yield better MS-specific quality of life. There is increasing interest in the approach of increasing physical activity through theory-based behavioral interventions (Pekmezi & Motl, 2022); however, this approach may possibly reduce sedentary behavior as a secondary benefit. One preliminary study reported that constructs from the social cognitive theory may be targets of behavioral interventions to reduce sedentary behavior in persons living with MS (Motl et al., 2019). This suggests that future research should consider interventions informed by theory targeted towards the reduction of sedentary behavior and promotion of physical activity, as our findings underscore the importance of focusing on the promotion physical activity to improve quality of life and manage secondary outcomes of MS.

Implications for Rehabilitation.

  • Sedentary behavior was not associated with health-related quality of life (HRQOL) in multiple sclerosis (MS).

  • Physical activity was positively associated with better HRQOL, regardless of sedentary behavior status, in MS.

  • Light and moderate-to-vigorous physical activity were associated with physical HRQOL, but only moderate-to-vigorous physical activity was associated with psychological HRQOL.

  • Rehabilitation professionals and healthcare providers should focus on promoting physical activity rather than reducing sedentary behavior for improving HRQOL in MS.

Funding:

The research was supported, in part, by a pilot grant from the National Multiple Sclerosis Society (PP 1412), a mentor-based post-doctoral fellowship from the National Multiple Sclerosis Society (MB 2110), and a post-doctoral fellowship from the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health (NIH F32HD113333). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Conflict of Interest: The authors report no conflicts of interest.

REFERENCES

  1. Benito-Leon J, & Martinez-Martin P. (2003). Health-related quality of life in multiple sclerosis. Neurologia, 18(4), 210–217. [PubMed] [Google Scholar]
  2. Boberska M, Szczuka Z, Kruk M, Knoll N, Keller J, Hohl DH, & Luszczynska A. (2018). Sedentary behaviours and health-related quality of life. A systematic review and meta-analysis. Health Psychol Rev, 12(2), 195–210. 10.1080/17437199.2017.1396191 [DOI] [PubMed] [Google Scholar]
  3. Bouchard CE, Shephard RJ, & Stephens TE (1994). Physical activity, fitness, and health: international proceedings and consensus statement. In International Consensus Symposium on Physical Activity, Fitness, and Health, 2nd, May, 1992, Toronto, ON, Canada. Human Kinetics Publishers. [Google Scholar]
  4. Briggs FB, & Hill E. (2019). Estimating the prevalence of multiple sclerosis using 56.6 million electronic health records from the United States. Mult Scler, 1352458519864681. 10.1177/1352458519864681 [DOI] [PubMed] [Google Scholar]
  5. Cohen J. (1988). Statistical power analysis for the behavioral science (2nd ed.). Lawrence Erlbaum Associates. [Google Scholar]
  6. de Rezende LF, Rodrigues Lopes M, Rey-Lopez JP, Matsudo VK, & Luiz Odo C. (2014). Sedentary behavior and health outcomes: an overview of systematic reviews. PLoS One, 9(8), e105620. 10.1371/journal.pone.0105620 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Edwards MK, & Loprinzi PD (2016). Sedentary behavior & health-related quality of life among congestive heart failure patients. Int J Cardiol 220, 520–523. 10.1016/j.ijcard.2016.06.256 [DOI] [PubMed] [Google Scholar]
  8. Ezeugwu V, Klaren RE, E AH, Manns PT, & Motl RW (2015). Mobility disability and the pattern of accelerometer-derived sedentary and physical activity behaviors in people with multiple sclerosis. Prev Med Rep, 2, 241–246. 10.1016/j.pmedr.2015.03.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. George SM, Alfano CM, Groves J, Karabulut Z, Haman KL, Murphy BA, & Matthews CE (2014). Objectively measured sedentary time is related to quality of life among cancer survivors. PLoS One, 9(2), e87937. 10.1371/journal.pone.0087937 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Healy GN, Clark BK, Winkler EA, Gardiner PA, Brown WJ, & Matthews CE (2011). Measurement of adults’ sedentary time in population-based studies. Am J Prev Med, 41(2), 216–227. 10.1016/j.amepre.2011.05.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Hobart J, Lamping D, Fitzpatrick R, Riazi A, & Thompson A. (2001). The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure. Brain, 124(Pt 5), 962–973. [DOI] [PubMed] [Google Scholar]
  12. Hohol MJ, Orav EJ, & Weiner HL (1995). Disease steps in multiple sclerosis: a simple approach to evaluate disease progression. Neurology, 45(2), 251–255. [DOI] [PubMed] [Google Scholar]
  13. Hubbard EA, & Motl RW (2015). Sedentary behavior is associated with disability status and walking performance, but not cognitive function, in multiple sclerosis. Appl Physiol Nutr Metab, 40(2), 203–206. 10.1139/apnm-2014-0271 [DOI] [PubMed] [Google Scholar]
  14. Hubbard EA, Motl RW, & Fernhall B. (2018). Sedentary behavior and blood pressure in patients with multiple sclerosis. Int J MS Care, 20(1), 1–8. 10.7224/1537-2073.2016-021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hubbard EA, Motl RW, & Manns PJ (2015). The descriptive epidemiology of daily sitting time as a sedentary behavior in multiple sclerosis. Disability and health journal, 8(4), 594–601. 10.1016/j.dhjo.2015.06.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Jeng B, Sasaki JE, Cederberg KL, & Motl RW (2019). Sociodemographic and clinical correlates of device-measured sedentary behaviour in multiple sclerosis. Disabil Rehabil, 1–7. 10.1080/09638288.2019.1614683 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Learmonth YC, Motl RW, Sandroff BM, Pula JH, & Cadavid D. (2013). Validation of Patient Determined Disease Steps (PDDS) scale scores in persons with multiple sclerosis. BMC Neurol 13, 37. 10.1186/1471-2377-13-37 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Manns PJ, Dunstan DW, Owen N, & Healy GN (2012). Addressing the nonexercise part of the activity continuum: a more realistic and achievable approach to activity programming for adults with mobility disability? Phys Ther, 92(4), 614–625. 10.2522/ptj.20110284 [DOI] [PubMed] [Google Scholar]
  19. Mitchell AJ, Benito-Leon J, Gonzalez JM, & Rivera-Navarro J. (2005). Quality of life and its assessment in multiple sclerosis: integrating physical and psychological components of wellbeing. Lancet Neurol, 4(9), 556–566. 10.1016/s1474-4422(05)70166-6 [DOI] [PubMed] [Google Scholar]
  20. Motl RW & McAuley E. (2014). Physical activity and health-related quality of life over time in adults with multiple sclerosis. Rehabil Psychol, 59(4), 415–421. 10.1037/a0037739 [DOI] [PubMed] [Google Scholar]
  21. Motl RW, McAuley E, Snook EM, & Gliottoni RC (2009). Physical activity and quality of life in multiple sclerosis: intermediary roles of disability, fatigue, mood, pain, self-efficacy and social support. Psychol Health Med, 14(1), 111–124. 10.1080/13548500802241902 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Motl RW, McAuley E, Wynn D, Sandroff B, & Suh Y. (2013). Physical activity, self-efficacy, and health-related quality of life in persons with multiple sclerosis: analysis of associations between individual-level changes over one year. Qual Life Res, 22(2), 253–261. 10.1007/s11136-012-0149-z [DOI] [PubMed] [Google Scholar]
  23. Motl RW, Sasaki JE, Cederberg KL, & Jeng B. (2019). Social-cognitive theory variables as correlates of sedentary behavior in multiple sclerosis: Preliminary evidence. Disabil Health J. 10.1016/j.dhjo.2019.05.002 [DOI] [PubMed] [Google Scholar]
  24. Owen N, Healy GN, Matthews CE, & Dunstan DW (2010). Too much sitting: the population health science of sedentary behavior. Exerc Sport Sci Rev, 38(3), 105–113. 10.1097/JES.0b013e3181e373a2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Pekmezi D, & Motl R. (2022). Targeting physical inactivity using behavioral theory in chronic, disabling diseases. Exerc Sport Sci Rev, 50(3), 156–161. 10.1249/jes.0000000000000291 [DOI] [PubMed] [Google Scholar]
  26. Phillips SM, Awick EA, Conroy DE, Pellegrini CA, Mailey EL, & McAuley E. (2015). Objectively measured physical activity and sedentary behavior and quality of life indicators in survivors of breast cancer. Cancer, 121(22), 4044–4052. 10.1002/cncr.29620 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Rejeski WJ, & Mihalko SL (2001). Physical activity and quality of life in older adults. J Gerontol A Biol Sci Med Sci, 56 Spec No 2, 23–35. 10.1093/gerona/56.suppl_2.23 [DOI] [PubMed] [Google Scholar]
  28. Riazi A, Hobart JC, Lamping DL, Fitzpatrick R, & Thompson AJ (2002). Multiple Sclerosis Impact Scale (MSIS-29): reliability and validity in hospital based samples. J Neurol Neurosurg Psychiatry, 73(6), 701–704. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Riazi A, Thompson AJ, & Hobart JC (2004). Self-efficacy predicts self-reported health status in multiple sclerosis. Mult Scler, 10(1), 61–66. 10.1191/1352458504ms986oa [DOI] [PubMed] [Google Scholar]
  30. Sandroff BM, Riskin BJ, Agiovlasitis S, & Motl RW (2014). Accelerometer cut-points derived during over-ground walking in persons with mild, moderate, and severe multiple sclerosis. J Neurol Sci, 340(1–2), 50–57. 10.1016/j.jns.2014.02.024 [DOI] [PubMed] [Google Scholar]
  31. Sasaki JE, Motl RW, Cutter G, Marrie RA, Tyry T, & Salter A. (2018). National estimates of self-reported sitting time in adults with multiple sclerosis. Mult Scler J Exp Transl Clin, 4(1), 2055217318754368. 10.1177/2055217318754368 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Stewart AL, & King AC (1991). Evaluating the efficacy of physical activity for influencing quality-of-life outcomes in older adults. Ann Behav Med, 13(3), 108–116. 10.1093/abm/13.3.108 [DOI] [Google Scholar]
  33. Trapp BD, & Nave KA (2008). Multiple sclerosis: an immune or neurodegenerative disorder? Annu Rev Neurosci, 31, 247–269. 10.1146/annurev.neuro.30.051606.094313 [DOI] [PubMed] [Google Scholar]
  34. Vallance JK, Boyle T, Courneya KS, & Lynch BM (2014). Associations of objectively assessed physical activity and sedentary time with health-related quality of life among colon cancer survivors. Cancer, 120(18), 2919–2926. 10.1002/cncr.28779 [DOI] [PubMed] [Google Scholar]
  35. Veldhuijzen van Zanten JJ, Pilutti LA, Duda JL, & Motl RW (2016). Sedentary behaviour in people with multiple sclerosis: Is it time to stand up against MS? Mult Scler, 22(10), 1250–1256. 10.1177/1352458516644340 [DOI] [PubMed] [Google Scholar]
  36. World Health Organization. (2007). International Classification of Functioning, Disability, and Health: Children & Youth Version: ICF-CY. World Health Organization. [Google Scholar]
  37. Zheng P, DeJonge SR, Flores VA, Jeng B, & Motl RW (2023). Systematic review and meta-analysis of sedentary behavior in persons with multiple sclerosis. Mult Scler Relat Disord, 80, 105124. 10.1016/j.msard.2023.105124 [DOI] [PubMed] [Google Scholar]

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