Introduction

Restless legs syndrome (RLS)/WED is a sensorimotor disorder defined by a strong urge to move the legs usually associated with unpleasant sensations in the legs. [1] A review of RLS epidemiology studies from North America and Western Europe—comprising over 230,000 participants— reported a prevalence ranging from 4% to 29%.[2] Primary RLS (i.e., RLS not secondary to another pathology, such as iron deficiency or end-stage renal disease) is a common neurological disorder. Prevalence estimates range from 1.5–10% in industrialized countries, though are slightly higher in certain rural populations (e.g., U.S. Appalachia at 10.1–19.6%) and increases with age.[3–7] Representative US panel data estimate 1.5% of primary RLS sufferers experience symptoms at least twice per week (termed moderate to severe RLS), with women most likely to experience severe symptoms.[5,7] Despite its notable prevalence, less than 41% of severely-symptomatic patients report an actual physician diagnosis of RLS.[5]

Consequences of RLS include discomfort, pain, inability to rest, sleep loss, difficulties sitting/relaxing, decreased physical functioning, psychological distress, and lowered cognitive function—all of which are associated with reduced health-related quality of life (HR-QoL).[8,9] Patients with RLS show physical and mental health HR-QoL scores more than a standard deviation lower than sex- and age-adjusted general population norms.[10,11] Moreover, RLS patients show poorer HR-QoL than those with other chronic medical and psychiatric conditions, such as hypertension, type II diabetes, osteoarthritis, and depression.[2,4] Patients with untreated RLS show significantly higher depressive symptoms than treated patients and healthy controls.[12] Strikingly, male RLS patients show elevated mortality rates, independent of known risk factors.[13] RLS-related burden has been shown to increase with symptom severity, symptom frequency, and level of symptom-related distress.[5,10,14,15] For example, frequent symptoms (i.e., occurring at least two days per week) have been associated with impaired frontal lobe executive function (e.g., thinking about abstract concepts, attention, and verbal function).[16,17] These types of impairments are thought to relate to an increase in RLS-related sleep disturbances with greater severity.

A systematic literature review found that compared with matched controls, RLS patients show significantly higher health expenditures from a third-party payer’s perspective.[4] Indirect costs due to productivity loss, with loss as high as 20% of normal productive capacity, are also thought to be a large contributor to the economic burden associated with RLS.[2] Patients with symptoms at least two days per week and moderate-to-severe distress have shown mean productivity loss of one entire day per week, reported as directly-attributable to RLS.[5] This degree of productivity loss for RLS patients is similar to reports of productivity loss for diabetes with neuropathy, or bipolar disorder, and is thought to relate to RLS-associated sleep disturbances.[18–20]

RLS-related burden appears to be significant, but further research is needed to substantiate and clearly define the economic burden of RLS.[8] Existing economic studies, for example, have relied on claims data or did not account for potential confounding variables. Furthermore, U.S. studies have not included comparisons to control cohorts. In addition, there has been little U.S. research reported investigating the economic burden of RLS as a function of disease severity. Given this need for further research, the objectives of the current study were to examine the humanistic and economic effects of an RLS diagnosis and to evaluate whether or not increased RLS severity is associated with worse outcomes. To answer this question, we contrasted individuals with RLS and a matched comparison of patients not reporting a diagnosis of RLS across a variety of health outcomes including health-related quality of life, work productivity, healthcare resource use, and direct and indirect costs. For those with an RLS diagnosis, we also compared these outcomes across symptom severity groups (mild, moderate, and severe).

Methods

Results

Post-Match Analyses

Two RLS patients could not be matched to a compatible propensity score in the pool of non-RLS participants. This left two equally sized groups for comparison (n = 2,390 each). Race/ethnicity, BMI, and exercise status were still statistically significantly different between the groups post-match and were controlled for in subsequent analyses.

Compared to matched non-RLS patients, RLS patients had significantly lower MCS (44.60 vs. 48.92, p<.001), PCS (40.57 vs. 46.78, p<.001) and Health Utilities scores (.63 vs. .71, p<.001). These differences are considerable given that a difference of 3 points on the MCS and 2 points on the PCS scores constitute a “minimally important difference”.[24]

Fewer RLS patients were employed (34% vs. 43%, p<.001) and more were on short or long-term disability (15% vs. 7%, p<.001) than matched non-RLS patients. Across all work productivity metrics examined, RLS patients experienced significantly higher work productivity loss than non-RLS comparison patients (see Fig 1). RLS patients also reported significantly more activity impairment in their day-to-day lives than non-RLS patients (Fig 1).

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Fig 1. Percentage Work Productivity and Activity Impairment (past 7 days) by RLS Status.

Note:Values represent least square means controlling for significant post-match differences on Race/Ethnicity, BMI, and Exercise Status. All comparisons significant at p < .001.

https://doi.org/10.1371/journal.pone.0140632.g001

As can be seen in Fig 2, RLS also reported statistically significantly more healthcare resource use across use categories than matched non-RLS patients. Relatedly, RLS responds had significantly higher estimated annual costs for ER visits, hospitalizations, and physician visits, resulting in significantly higher overall direct healthcare resource costs (Fig 3). Similarly, RLS patients had significantly higher indirect costs from absenteeism and presenteeism than matched non-RLS patients (Fig 3).

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Fig 2. Healthcare Resource use by RLS Status (# of visits past 6 months).

Note:Values represent least square means controlling for significant post-match differences on Race/Ethnicity, BMI, and Exercise Status. All comparisons significant at p < .001.

https://doi.org/10.1371/journal.pone.0140632.g002

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Fig 3. Estimated Annualized Direct and Indirect Costs by RLS Status.

Note:Values represent least square means controlling for significant post-match differences on Race/Ethnicity, BMI, and Exercise Status. All comparisons significant at p < .001.

https://doi.org/10.1371/journal.pone.0140632.g003

Severity Analyses

The analyses above using the same outcomes (quality of life, work productivity, and healthcare resource use, direct and indirect costs) were replicated within RLS patients to determine the effect of severity (mild, moderate, severe) on these outcomes controlling for covariates.

There were several demographic differences that were significantly associated with RLS severity. Specifically, as severity increased, so did age (Mean age: Mild = 55.20, Moderate = 56.59, Severe = 56.01), the proportion of female patients (Mild = 54.2%, Moderate = 56.8%, Severe = 63.7%), and comorbidity burden (Mean CCI: Mild = .90, Moderate = 1.07, Severe = 1.73). In contrast, as severity increased, income decreased (% ≤ $50k: Mild = 49.2%, Moderate = 56.7%, Severe = 61.5%), as did the proportion currently consuming alcohol (Mild = 61.5%, Moderate = 54.5%, Severe = 51.4%), the proportion with a college degree (Mild = 48.6%, Moderate = 43.8%, Severe = 35.5%), and the proportion of patients who have exercised in the past 30 days (Mild = 58.6%, Moderate = 49.3%, Severe = 45.8%). Race/ethnicity, marital status, BMI, smoking status, and pregnancy status did not differ significantly by severity. To adjust for confounding and better isolate the unique association of severity with health outcomes, all of the above variables, regardless of whether or not they differed statistically between groups, were controlled for in subsequent analyses. Table 1 contains estimated least square means controlling for covariates for all health outcomes examined.

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Table 1. Health Outcomes by RLS Severity.

https://doi.org/10.1371/journal.pone.0140632.t001

As RLS symptom severity increased from mild to severe RLS, estimated means for health related quality of life decreased (Table 1). These trends were significant (all p<.001) for MCS, PCS, and Health Utility scores. Moreover, all levels of RLS severity were associated with lower health related quality of life scores relative to individuals with no symptoms at all (non-RLS). Similar to health related quality of life, increases in severity were associated with increases in likelihood of short or long term disability and decreased likelihood of labor force participation. Those without RLS (non-RLS) had significantly higher levels of employment and lower levels of disability than all levels of RLS severity.

Severity level was also significantly associated with work productivity loss and activity impairment such that individuals with higher levels of severity reported higher estimated levels of work productivity loss and impairment and in all cases productivity loss and impairment were higher for those with RLS symptoms than those without (Table 1).

Finally, severity was also associated with subsequently higher estimates of traditional health care provider visits, ER visits, and hospitalizations (Table 1). Relatedly, estimates of direct and indirect costs also increased as severity increased (Fig 4).

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Fig 4. Estimated Direct and Indirect Costs by RLS Severity.

Values represent least square means controlling for significant differences on age, gender, income, alcohol status, college degree status, and exercise status. ER = Emergency Room, HCP = Healthcare provider, M = Mean, 95% CI = 95% confidence interval.

https://doi.org/10.1371/journal.pone.0140632.g004

Discussion

This study illustrates the magnitude of the humanistic and economic burden associated with RLS and lends further insight into the effect of RLS severity on these outcomes. To our knowledge, this is the most comprehensive survey study to describe RLS-associated humanistic and economic burden across these domains. Consistent with the available literature, patients reporting an RLS diagnosis experienced significantly worse health outcomes, including lower HR-QoL, and more healthcare resource use than comparison individuals. Diagnosed patients reported significantly more work productivity loss (both for absenteeism and presenteeism) and overall activity impairment than their matched counterparts. Furthermore, it appears that RLS diagnosis places a significant financial burden on those diagnosed and the healthcare system, as diagnosed patients had higher estimated direct, indirect, and total costs of healthcare resource use compared to comparison individuals. This finding corroborates other available estimates in the literature. For example, in a large U.S. managed care database study, 91% of patients had one or more RLS-related office visits, and patients filled an average of 6.5 RLS-related prescriptions during a one-year follow-up period, with opioids being the most common adjunctive treatment. RLS-related health care costs were 6.7% of total all-cause health care costs [M = $774(SD = $1,504)]. Furthermore, higher symptom frequency/degree of disease-related distress may relate to increasing economic costs.[5,8] For example, the mean direct annualized costs of RLS-specific healthcare resources/medications were estimated at USD $350.54 per patient—with an increase to $490.70 for patients with symptoms at least two days per week and moderate-to-severe distress.[5] This effect is striking when considered in the context of estimated costs for other diseases (e.g., bipolar disorder and asthma)[29] It should be noted, however, that the overall estimates found here are higher than those previously reported which was likely due to the fact that we annualized general healthcare resource use as opposed to the RLS-specific healthcare resource use. Finally, in line with the small body of previous literature, the degree of RLS symptom severity was found to be associated with an increase in the humanistic and economic burden of RLS.[2,5,10,14,15]

Strengths of this study included the recency of the data, the sample size relative to previous work, and the use of a propensity score matching approach. Such an approach allowed for the comparison of groups based on measured confounders, which is essential in a cross-sectional study. Data were self-reported so the limitations self-report (e.g., recall bias) applied to this study and it was not possible to verify responses (e.g., diagnosis) via some other means (e.g., physician assessment). Moreover, as the NHWS is a broad general health survey, it did not include diagnostic criteria or validated instruments for measuring RLS diagnosis and severity. The degree to which this may have affected the results is unclear and these results should be interpreted with these caveats in mind. The NHWS is a cross-sectional study and this analysis was restricted to U.S. respondents—therefore, only correlational inferences to be made and the results may not generalize to ex-U.S. populations. We chose an a priori significance cutoff of p < .05 for all our conducted analyses, given this and the number of comparisons conducted there is a higher likelihood of Type 1 error in these results than if we had chosen a smaller p critical value and/or conducted fewer comparisons. Previous research studies have eliminated conditions that might be mistaken for RLS, such as end-stage renal disease from analyses. As the NHWS is a general survey, we were restricted to the conditions surveyed and were thus limited in our ability to eliminate these conditions. It is reasonable to speculate that, were we able to remove those patients from the analyses the estimated burden of RLS may have been lower than what was found in these analyses. Finally, this study adjusted for measured confounders but results could have been affected by non-measured confounders.

Conclusion

An RLS diagnosis confers a heavy humanistic and economic burden. This burden increases with symptom severity and is highest in certain demographic groups. The burden affects diagnosed individuals across a range of health domains. This strain may be directly and indirectly affecting the work force, the healthcare system, and individuals’ finances—and may be worse in those with severe symptoms—who may also have lower income levels to begin with. Improved management of RLS symptoms may offset this degree of distress, dysfunction, and disability endured by patients and effects on economic and health care systems.