Publication
Research Article
The management of walking impairment and fatigue may be appropriate for improving physical health-related quality of life among Black and White people with multiple sclerosis.
Background: Health-related quality of life (HRQOL) is a key health outcome and often compromised in people with multiple sclerosis (MS). Yet the associations between symptoms and HRQOL across racial subgroups remain unclear. To that end, this cross-sectional, comparative study examined symptoms as correlates of HRQOL in Black and White individuals with MS.
Methods: Black (n = 136) and White (n = 273) individuals with MS completed an online survey assessing walking impairment (12-Item Multiple Sclerosis Walking Scale [MSWS-12]), fatigue (Fatigue Severity Scale [FSS]); depression and anxiety (Hospital Anxiety and Depression Scale [HADS-A and HADSD]); and HRQOL (12-Item Short Form Survey Physical and Mental). Bivariate correlations and stepwise linear regression were performed to identify associations between symptoms and HRQOL.
Results: MSWS-12, FSS, and HADS-D were significantly associated with physical HRQOL, and HADS-A, HADS-D, and FSS were significantly associated with mental HRQOL within both groups: Black (r range, –0.65 to –0.33; P < .01) and White (r range, –0.68 to –0.30; P < .01) individuals with MS. Regression analyses identified MSWS-12 and FSS as significant correlates of physical HRQOL in both groups (P < .05) after controlling for age and household income. For mental HRQOL, HADS-A and HADS-D were significant correlates among White participants (P < .05), whereas HADS-A was the only significant correlate among Black participants (P < .01) after controlling for age and disease duration.
Conclusions: Our findings highlight symptoms, including walking impairment, fatigue, anxiety, and depression, as correlates of HRQOL among Black and White individuals with MS and may inform intervention development that targets the symptoms to improve HRQOL across racial groups.
Multiple sclerosis (MS) is a debilitating, immune-mediated neurodegenerative disease with a prevalence of approximately 1 million adults in the United States.1 MS is characterized by the demyelination and transection of axons and the subsequent loss of neurons in the central nervous system (CNS).2 The extent and location of CNS damage result in physical, cognitive, and psychological impairments that compromise health-related quality of life (HRQOL) in people with MS.3 HRQOL is a multidimensional umbrella construct representing an individual’s physical, mental, and social well-being and serves as an important patient-reported outcome measure in MS research.4 Prior research data repeatedly report worse levels of physical and mental HRQOL in people with MS compared with the general population and people with other chronic conditions.5-7 This has prompted research on symptoms as correlates of HRQOL to inform the design of interventions that focus on symptom management to improve HRQOL in individuals with MS.
MS symptoms have demonstrated consistent correlations with HRQOL in people with MS.7 For example, in a study of 500 people with relapsing-remitting MS in the United States, participants who reported higher levels of fatigue also reported worse HRQOL⁸; this association is well-documented in patients with MS.⁹ Walking impairment, as well as symptoms of depression and anxiety, can significantly impact HRQOL in people with MS.10-12 Indeed, a study of 1985 participants with MS concluded that feelings of fatigue, walking difficulties, depression, and anxiety were associated with HRQOL and suggested that interventions targeting these symptoms may have the most impact on improvement of HRQOL.13 Multiple systematic reviews support depression, fatigue, and disability status as negatively impacting both physical and mental HRQOL.14-17 The data underscore the need for targeted approaches to manage symptoms as an avenue to improve HRQOL in people with MS.
Symptoms and disease burden are also associated with race in people with MS.14 Studies have demonstrated disparities in MS outcomes among racial and ethnic groups, with Black and Latinx/Hispanic individuals often experiencing greater disease burden than White individuals.18,19 Of note, research findings have identified variations in MS symptoms and disability levels across racial and ethnic backgrounds.20 Additionally, race has been associated with differences in symptom presentation and disability levels, with Black individuals often experiencing more severe motor symptoms and faster disease progression than White individuals.18 Nevertheless, there remains a gap in understanding the associations between symptoms and HRQOL outcomes as a function of MS subgroups that differ by racial and ethnic background. We believe that addressing this gap is crucial to developing targeted interventions that manage MS symptoms, improve HRQOL outcomes for diverse MS populations, and reduce health disparities in disease management and outcomes.
This cross-sectional, comparative study examined the associations between common MS symptoms (ie, walking impairment, fatigue, and depression and anxiety symptoms) and domains of HRQOL in Black and White individuals with MS. We hypothesized that HRQOL scores would be significantly worse in Black individuals than in White individuals based on prior evidence of racial disparities in disease burden and health outcomes.18,19 We further hypothesized that MS symptoms would significantly correlate with physical and mental HRQOL, such that walking impairment and fatigue would have strong negative correlations with physical HRQOL, whereas depressive and anxiety symptoms would have strong negative correlations with mental HRQOL in both Black and White individuals with MS.
Participants and Data Collection
This study analyzed data from an original, ongoing project focusing on race, ethnicity, and active lifestyle in MS. People with MS were recruited from across the US via advertisements or flyers distributed by the National MS Society, MS centers, community partners, university-based recruitment channels, social media, and word of mouth. Inclusion criteria were: 18 years and older; a physician-confirmed MS diagnosis; residing in the US; relapse-free for the past 30 days; able to walk with or without an assistive device; not currently pregnant or nursing; able to speak, read, and understand English; and willing to complete the study protocol.
Procedure
The study was reviewed and approved by the University of Illinois Chicago Institutional Review Board, and the research process occurred online. Participants provided informed consent electronically via REDCap prior to enrollment and completed a battery of questionnaires assessing demographic and clinical characteristics, MS symptoms, and HRQOL using the REDCap electronic data capture tool.21,22
Outcome Measures
Demographic and Clinical Characteristics
Demographic variables included age, sex, race, education, and household income. Clinical characteristics included disease duration, MS type, and disability level. Disability level was assessed using the Patient-Determined Disease Steps (PDDS), a self-report scale for measuring disability in persons with MS.23,24 PDDS scores range between 0 (no disability) and8 (bedridden).23
Symptoms
Walking Impairment
Walking impairment was assessed using the 12-Item Multiple Sclerosis Walking Scale (MSWS-12).25 The MSWS-12 is a self-reported measure of perceived walking impairment based on the previous 2 weeks and contains 12 items rated on a Likert scale ranging between 1 (not at all) and 5 (extremely). Overall, MSWS-12 scores are scaled to a range between 0 and 100 points.25 The MSWS-12 has strong internal consistency (Cronbach α ≥ 0.94)and good test-retest reliability (intraclass correlation coefficient [ICC] ≥ 0.78).25 Higher MSWS-12 scores reflect greater perceived walking impairment based on correlations with walking performance outcomes,25-27 and a score of 50 or higher indicates substantial walking impairment.25-27
Fatigue
Fatigue was assessed using the 9-Item Fatigue Severity Scale (FSS).28,29 The items are rated on a Likert scale with responses ranging between 1 (strongly disagree) and 7 (strongly agree). The item scores were averaged to yield a total score ranging from 1 to 7. The FSS has strong internal consistency (Cronbach α = 0.81) and good test-retest reliability (ICC = 0.75). Higher scores indicate more severe fatigue based on validation in people with MS,28,29 and a score of 4 or higher indicates elevated symptomatic fatigue in MS.28
Depressive and Anxiety Symptoms
Depressive and anxiety symptoms were assessed using the Hospital Anxiety and Depression Scale (HADS).30 HADS consists of 14 items categorized into 7 anxiety-related (HADS-A) and 7 depression-related (HADS-D) items rated on a Likert scale ranging between 0 (most of the time) and 3 (not at all). The item scores within each su scale are reverse-scored as necessary and then summed to yield a score ranging between 0 and 21. HADS scores demonstrate strong internal consistency (Cronbach α ≥ 0.81), test-retest reliability (ICC = 0.83), and specificity (80%-90%) using receiver operating characteristic analysis in people with MS.30-32 Higher scores indicate more elevated levels of depressive and anxiety symptoms.30 Scores of 8 or higher per subscale indicate elevated levels of depression or anxiety.30
Health-Related Quality of Life
HRQOL was assessed using the 12-item Short Form Survey (SF-12), which has been validated as a measure of HRQOL in MS and has demonstrated moderate test-retest reliability (ICC > 0.67).33,34 SF-12 includes the physical component score (SF-12 PCS) and mental component score (SF-12 MCS) of HRQOL and is one of the commonly used quality-of-life assessment tools in MS research.34 The response choices for the 12 items vary, but all are rated on 2- to 6-point Likert scales. SF-12 PCS and SF-12 MCS were calculated based on the algorithms described in the SF-12 how-to-score manual.35 The SF-12 PCS and MCS subscores range from 0 to 100, with higher scores indicating better physical and psychological HRQOL.35 Both subscores are norm-based, and the scores are standardized as a mean of 50 and an SD of 10 in the US general population.36,37 Scores below 50 indicate below-average health, whereas scores above 50 suggest better-than-average health.37
Data Analysis
The data analyses were performed using IBM SPSS Statistics, version 29 (IBM Corp). Descriptive values for continuous variables are presented as mean (SD), ordinal variables are presented as median (IQR), and categorical variables are presented as sample size and percentage. Normality and data outliers were examined using skewness and histograms. The differences between groups (ie, Black Americans vs White Americans) in demographics, clinical characteristics, and targeted outcomes (ie, walking impairment, fatigue, depressive and anxiety symptoms, and HRQOL) were examined using independent samples t tests for continuous variables and χ2 tests and nonparametric t tests for categorical variables. Analysis of covariance compared groups on targeted outcomes (ie, walking impairment, fatigue, depressive and anxiety symptoms, and HRQOL), accounting for the differences in demographics and clinical characteristics. Bivariate correlations between HRQOL (ie, SF-12 PCS and SF-12 MCS) with MS symptoms (ie, MSWS-12, FSS, HADS-D, HADS-A) were examined using Pearson correlation coefficients as all targeted outcomes were normally distributed, and the magnitudes of correlations were interpreted as small (0.1), moderate (0.3), and large (0.5).38 Demographic and clinical variables were further included in the bivariate correlation analysis to identify potential confounding factors and covariates. The associations between symptoms and SF-12 PCS and SF-12 MCS were then examined using stepwise linear regression and further controlled for the significant demographic and clinical variables as covariates. These analyses were performed within each group. Tolerance and variance inflation factor (VIF) were checked for collinearity between the predictor variables.39,40
Demographic and Clinical Characteristics
The descriptive statistics for the demographic and clinical characteristics of Black and White individuals with MS are provided in Table 1. There were significant group differences in age (P < .001), household income (P = .008), and disease duration (P < .001). MS symptoms of walking impairment, fatigue, depression, and anxiety, and HRQOL for Black and White individuals with MS are also provided in Table 1. There were significant differences in FSS (P = .026), HADS-D (P = .011), and SF-12 MCS (P = .008) between Black and White individuals with MS, even after controlling for the differences in age, household income, and disease duration.
Table 1. Demographic Characteristics, Symptoms, and Health-Related Quality of Life of the Study’s Overall Sample and Subgroups
Bivariate Correlation Analyses
The bivariate correlations between MSWS-12, FSS, HADS-D, and HADS-A and SF-12 PCS and SF-12 MCS are shown in Table 2. Among Black individuals with MS, MSWS-12 (r = –0.65, 95% CI, –0.73 to –0.53), FSS (r = –0.43, 95% CI, –0.56 to –0.28), and HADS-D (r = –0.43, 95% CI, –0.56 to –0.28) were significantly correlated with SF-12 PCS, whereas HADS-A (r = –0.58, 95% CI, –0.62 to –0.45), HADS-D (r = –0.44, 95% CI, –0.57 to –0.29), and FSS (r = –0.33, 95% CI, –0.47 to –0.17) were significantly correlated with SF-12 MCS. Among White participants with MS, MSWS-12 (r = –0.63, 95% CI, –0.69 to –0.55), FSS (r = –0.49, 95% CI, –0.57 to –0.39), and HADS-D (r = –0.30, 95% CI, –0.41 to –0.19) were significantly correlated with SF-12 PCS, whereas HADS-A (r = –0.68, 95% CI, –0.74 to –0.61), HADS-D (r = –0.60, 95% CI, –0.67 to –0.52), and FSS (r = –0.37, 95% CI, –0.46 to –0.26) were significantly correlated with SF-12 MCS.
Table 2. Pearson Bivariate Correlations Between Symptoms, Potential Covariates, and Health-Related Quality of Life in the Subgroups
Covariates
Possible covariates for inclusion in the stepwise linear regression analyses were identified through additional bivariate correlation analyses (Table 2). There were significant correlations between SF-12 PCS and age (r = –0.27, 95% CI, –0.42 to –0.11) and household income (r = 0.25, 95% CI, 0.08-0.40), as well as between SF-12 MCS and disease duration (r = 0.19, 95% CI, 0.02-0.35) among Black individuals with MS. There were significant correlations between SF-12 PCS with age (r = –0.15, 95% CI, –0.27 to –0.03) and household income (r = 0.14, 95% CI, 0.02-0.25), as well as between SF-12 MCS and age (r = 0.26, 95% CI, 0.14-0.36) and disease duration (r = 0.19, 95% CI, 0.07-0.30) among White individuals with MS. These demographic and clinical variables were included as covariates in the subsequent stepwise linear regression analyses by group.
Linear Regression Analyses
The linear regression analyses are presented in Table 3. Of note, there was no collinearity between the predictor variables (ie, MSWS-12, FSS, HADS-D, and HADS-A) based on VIF and tolerance values (VIF = 1.00-4.00; tolerance = 0.25-1.00).40
Table 3. Linear Regression Analyses of Associations Between Symptoms and Health-Related Quality of Life Among Subgroups While Controlling for Covariates
Among the Black individuals with MS, SF-12 PCS was regressed on MSWS-12, FSS, and HADS-D, as well as age and household income (Table 3, part a). The regression model indicated that the variables accounted for 48% of the variance in SF-12 PCS. MSWS-12 and FSS were identified as significant correlates of SF-12 PCS, even when controlling for age and household income. SF-12 MCS was further regressed on HADS-A, HADS-D, and FSS, as well as disease duration (Table 3, part b). The regression model indicated that the variables accounted for 38% of the variance in SF-12 MCS. Only HADS-A was identified as a significant correlate of SF-12 MCS, even when controlling for disease duration.
Among White individuals with MS, SF-12 PCS was regressed on MSWS-12, FSS, and HADS-D, as well as age and household income (Table 3, part c). The regression model indicated that the variables accounted for 44% of the variance in SF-12 PCS. MSWS-12 and FSS were identified as significant correlates of SF-12 PCS, even when controlling for age and household income. SF-12 MCS was further regressed on HADS-A, HADS-D, and FSS as well as age and disease duration (Table 3, part d). The regression model indicated that the variables accounted for 51% of the variance in SF-12 MCS. HADS-A and HADS-D were identified as significant correlates of SF-12 MCS, even when controlling for age and disease duration.
This study examined the MS symptoms of walking impairment, fatigue, depression, and anxiety as correlates of HRQOL in Black and White individuals with MS. There were no significant differences in physical HRQOL between Black and White individuals with MS, yet mental HRQOL was worse in White individuals with MS than in their Black counterparts. Regression analyses indicated that walking impairment and fatigue were significantly associated with physical HRQOL in Black and White individuals with MS, even after accounting for age and household income. The regression analysis further indicated that anxiety and depressive symptoms were significantly correlated with mental HRQOL among White individuals with MS after controlling for age and disease duration, whereas only anxiety symptoms remained significant among Black individuals with MS after controlling for disease duration. These findings highlighted walking impairment and fatigue as potential targets for interventions focusing on physical HRQOL, whereas anxiety and depressive symptoms might be targeted differently for interventions focusing on mental HRQOL across racial groups.
Our findings suggest that Black individuals with MS experienced lower levels of fatigue and depression and reported higher mental HRQOL than White individuals after controlling for age, disease duration, and household income. Of note, we are not aware of any current study specifically reporting the difference in HRQOL between Black and White individuals with MS. However, our findings indirectly contrast with previous research reporting worse outcomes and disease burden for Black individuals with MS.18,19 There are some factors that may provide potential explanations for our observations, including social and cultural resilience and coping strategies in maintaining mental HRQOL and well-being despite systemic health disparities. Studies indicate that strong social networks and cultural identity can serve as protective factors against mental health challenges in Black communities.41 Research findings further indicate the mediating role of resilience in physical health and quality of life in people with MS.42,43 Additionally, research on resilience in marginalized people highlights the role of psychological adaptation and coping strategies in maintaining well-being in Black individuals.44,45 Thus, while previous studies have documented higher disease burden among Black individuals with MS, our findings may suggest that mental HRQOL could be influenced by factors (resilience, social support, psychological adaptation, and coping strategies) beyond clinical severity and health disparity.
On the other hand, there are some limitations in our study that may account for the results. For example, this study did not assess other social determinants of health (SDOH), such as employment status and access to health care. Prior study findings have highlighted that lower socioeconomic status correlates with worse affective symptoms in people with MS,46 with further review indicating associations between health disparities and lower SDOH, including low income and education levels.47 Other factors, such as age and MS disease duration, have also been associated with lower quality of life and higher symptom burden.14,48 Additionally, our entirely remote, self-reported design may have excluded individuals with more severe cognitive or vision impairments, lower technological literacy, or greater socioeconomic disadvantage. Collectively, this underscores the need for further investigation into how cultural resilience, social support, coping mechanisms, other clinical characteristics, and socioeconomic status impact mental HRQOL in people with MS and the need to provide a more nuanced understanding of health disparity and HRQOL in people with MS as a function of race.
Through bivariate correlation analysis, there are strong associations between walking impairment, fatigue, and depressive symptoms and physical HRQOL. The findings align with prior research data on the relationship between MS symptoms and physical HRQOL in MS13-16 and further reinforce the relevance of these symptoms in understanding the physical domain of HRQOL across race in MS. Further, linear regression models indicate that walking impairment and fatigue are significantly correlated with physical HRQOL, independent of the covariates (age and household income) in Black and White individuals with MS. One previous study reported differences in physical function between Black and White individuals with MS,49 and the current findings suggest the substantial roles walking impairment and fatigue play in shaping the physical component of HRQOL within both groups, regardless of the level of physical function. Researchers and clinicians should consider improving walking ability and addressing fatigue to enhance physical HRQOL in both Black and White Americans with MS.
Bivariate correlations further indicate significant associations between symptoms of anxiety, depression, and fatigue and mental HRQOL in both Black individuals and White individuals with MS. However, we observed differences in the correlation patterns between the 2 groups after these variables were entered into the linear regression model and were controlled for covariates. Among White individuals with MS, anxiety and depressive symptoms were significant correlates of mental HRQOL, even after controlling for covariates. However, among Black individuals with MS, only anxiety symptoms were significantly associated with mental HRQOL after controlling for covariates. This significant association with anxiety among Black individuals with MS may reflect the influence of socioeconomic factors (eg, household income). Prior research indicated that lower household income has been linked to greater anxiety levels and affective symptom burden in MS, particularly among racial minorities.46 This finding suggests different targets for interventions to improve mental HRQOL among groups. Of note, our finding further suggests an important role for anxiety symptoms in explaining the mental HRQOL status of both groups, and this aligns with previous studies suggesting that anxiety has a greater impact on HRQOL in MS compared with depressive symptoms.50 This difference may pinpoint how anxiety and depressive symptoms affect the mental component of HRQOL in different ways across racial groups. Future studies are needed to better understand these differences and how they can guide more tailored interventions to improve mental health and HRQOL in people with MS.
There are important limitations to acknowledge in this study. One limitation is the cross-sectional design, which precludes the inferences regarding causality between MS symptoms and HRQOL among the MS subgroups as a function of race. This design captures HRQOL and symptoms at a single time point, and they may be influenced by transient life events. Another limitation is that other factors that influence HRQOL, such as cognitive impairment, pain, comorbidities, and medications, were not included in this study. The reliance on self-reported measures is a limitation, as it may have introduced recall bias, and reported symptoms were not clinically confirmed. It should further be noted that although race and household income were included in the data analysis, other SDOH, such as employment status, education levels, and health care access, may have been missed and warrant further research. Finally, restricting assessments to English and electronic formats may have excluded individuals with limited English proficiency or limited access to technology. This could further affect the generalizability of our findings.
The present findings provide novel evidence on MS symptoms as correlates of HRQOL within Black and White individuals with MS. After controlling for covariates, walking impairment and fatigue were significantly associated with the physical component of HRQOL in both Black and White individuals with MS. Further, also after controlling for covariates, anxiety and depressive symptoms were significantly associated with mental HRQOL among White individuals with MS, whereas anxiety symptoms were the only correlates of mental HRQOL in Black individuals with MS. Overall, our findings suggest a critical implication: The MS symptoms of walking impairment, fatigue, anxiety, and depressive symptoms should be considered prominent targets for managing MS and improving HRQOL among Black and White individuals with MS. These results warrant more research to deepen our understanding of the differences in correlates across the MS subgroups as a function of race. Such insights could inform future research and clinical practices aimed at tailored interventions to manage MS symptoms and improve HRQOL in people with MS from different racial backgrounds
Acknowledgments: We would like to express our gratitude to the individuals who participated in this study. We further thank the National MS Society and other collaborators for assistance with the recruitment process.
Financial Disclosures: The authors have reported no relevant disclosures.
Funding: Research reported in this publication was supported in part by the National Heart, Lung, and Blood Institute (T32HL134634), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (F32HD113333), and the National Cancer Institute (1F31CA295016-01). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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