{"product_id":"fatigue-and-multiple-sclerosis-a-global-look-at-how-common-it-really-is","title":"Fatigue and Multiple Sclerosis: A Global Look at How Common It Really Is","description":"\u003cp\u003eFatigue affects a striking number of people with multiple sclerosis (MS) worldwide. In this comprehensive systematic review and meta-analysis, researchers combined data from 69 studies across 27 countries—including more than 44,000 people with MS—and found that 59.1%, or nearly 6 out of 10, experience clinically significant fatigue. The study also revealed that fatigue rates have been declining each decade since 2000, and that the choice of fatigue measurement scale is the single largest factor driving the wide variation in prevalence rates reported across different studies. These findings highlight an urgent need for routine fatigue screening in MS care and for global consensus on the best tool to measure MS-related fatigue.\u003c\/p\u003e\n\n\u003ch1\u003eFatigue and Multiple Sclerosis: A Global Look at How Common It Really Is\u003c\/h1\u003e\n\n\u003ch2\u003eTable of Contents\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"#ddn-key-points\"\u003eKey Points\u003c\/a\u003e\u003c\/li\u003e\n\n  \u003cli\u003e\u003ca href=\"#background\"\u003eUnderstanding Multiple Sclerosis and Fatigue\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#methods\"\u003eHow the Research Was Conducted\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#studies\"\u003eThe Studies Behind the Numbers\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#measurement\"\u003eHow Fatigue Was Measured\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#quality\"\u003eQuality of the Included Studies\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#prevalence\"\u003eThe Big Picture: Global Fatigue Prevalence\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#subgroups\"\u003eWho Is Most Affected by MS Fatigue?\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#heterogeneity\"\u003eWhy Do the Numbers Differ So Much?\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#implications\"\u003eWhat This Means for Patients and Doctors\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#limitations\"\u003eStudy Limitations\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#recommendations\"\u003eRecommendations\u003c\/a\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003ca href=\"#ddn-faq\"\u003eFrequently Asked Questions\u003c\/a\u003e\u003c\/li\u003e\n\u003cli\u003e\u003ca href=\"#source\"\u003eSource Information\u003c\/a\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003c!-- ddn:keypoints:start --\u003e\n\u003ch2 id=\"ddn-key-points\"\u003eKey Points\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eAbout 59% of people with MS have clinically significant fatigue, based on 69 studies with 44,468 participants.\u003c\/li\u003e\n\u003cli\u003eThe choice of fatigue scale and cut-off explains 46.4% of variation; with disability, age, MS duration, it explains 86.4%.\u003c\/li\u003e\n\u003cli\u003eFatigue prevalence has declined each decade since 2000: 64.4%, 59.6%, and 51% in 2020–2023.\u003c\/li\u003e\n\u003cli\u003eSecondary progressive MS has the highest fatigue (74.4%), followed by primary progressive (64.3%) and relapsing-remitting (54.7%).\u003c\/li\u003e\n\u003cli\u003eNo pharmacological treatments reliably relieve MS fatigue; physical activity, diet changes, and CBT may help.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c!-- ddn:keypoints:end --\u003e\n\n\n\u003ch2 id=\"background\"\u003eUnderstanding Multiple Sclerosis and Fatigue\u003c\/h2\u003e\n\n\u003cp\u003eMultiple sclerosis (MS) is a chronic, inflammatory disease that damages the myelin sheath—the protective coating around nerve fibers—in the central nervous system (the brain and spinal cord). It is one of the most common causes of non-traumatic disability among young adults. The global burden of MS has been growing: an estimated \u003cstrong\u003e2.8 million people worldwide\u003c\/strong\u003e now live with MS, according to the latest Atlas of MS data. The highest rates are found in the WHO European Region (EUR) and the Region of the Americas (AMR), while the lowest rates are in the African Region (AFR) and the Western Pacific Region (WPR).\u003c\/p\u003e\n\n\u003cp\u003eMS is categorized into three main disease phenotypes, based on disease activity, progression, and clinical course:\u003c\/p\u003e\n\u003cul\u003e\n  \u003cli\u003e\n\u003cstrong\u003eRelapsing-remitting MS (RRMS):\u003c\/strong\u003e Approximately \u003cstrong\u003e85%\u003c\/strong\u003e of people with MS are initially diagnosed with this form, characterized by flare-ups followed by periods of recovery.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eSecondary progressive MS (SPMS):\u003c\/strong\u003e Many people with RRMS eventually develop this form, where disability steadily worsens with or without superimposed relapses.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003ePrimary progressive MS (PPMS):\u003c\/strong\u003e A less common form with continuous worsening from the start.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003ePeople with MS experience a wide range of symptoms that vary in severity, including spasticity (muscle stiffness), pain, fatigue, bladder and bowel problems, difficulty walking (gait impairments), mood disturbances, and sleep disorders.\u003c\/p\u003e\n\n\u003cp\u003eAmong all of these, \u003cstrong\u003efatigue is one of the most common and burdensome symptoms\u003c\/strong\u003e of MS. It can appear at any stage of the disease. The definition used by researchers is: \u003cem\u003e\"a significant lack of physical and\/or mental energy, perceived by the individual or caregiver, that interferes with normal and desired activities.\"\u003c\/em\u003e\u003c\/p\u003e\n\n\u003cp\u003eMS-related fatigue is fundamentally different from ordinary tiredness. Healthy people recover from fatigue with rest or sleep, but MS-related fatigue is disabling and often cannot be relieved that way. Patients describe having to put an \u003cstrong\u003eunduly high level of effort into daily tasks\u003c\/strong\u003e, which reduces their ability to perform everyday activities and to work.\u003c\/p\u003e\n\n\u003cp\u003eResearchers divide MS-related fatigue into two categories:\u003c\/p\u003e\n\u003cul\u003e\n  \u003cli\u003e\n\u003cstrong\u003ePrimary fatigue:\u003c\/strong\u003e Considered specific to MS itself. It occurs without an obvious trigger and is a direct consequence of the underlying disease process.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eSecondary fatigue:\u003c\/strong\u003e Caused by other factors, including sleep disturbances, mood disorders (anxiety and depression), side effects of disease-modifying treatments (DMTs), and decreased physical activity.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003eThe consequences are serious. Fatigue is one of the main drivers of \u003cstrong\u003elow health-related quality of life\u003c\/strong\u003e and unemployment in people with MS. It is also a major predictor of claims for social benefits, including sick leave and disability pensions. That makes fatigue one of the most urgent clinical problems in the treatment and management of MS.\u003c\/p\u003e\n\n\u003cp\u003eCurrently, there are no convincing pharmacological (drug) treatments proven to reliably relieve MS-related fatigue. Fortunately, nonpharmacological approaches—including physical activity, dietary modification, and cognitive behavioral therapy (CBT)—can be beneficial for many patients.\u003c\/p\u003e\n\n\u003cp\u003eThis study was motivated by a real problem: previous research on fatigue prevalence has produced wildly inconsistent numbers. Individual studies have reported fatigue in anywhere from \u003cstrong\u003e28.4% to 88.2%\u003c\/strong\u003e of people with MS. An earlier systematic literature review covering 12 studies found prevalence rates ranging from \u003cstrong\u003e36.5% to 78%\u003c\/strong\u003e. This wide variation probably reflects differences in measurement tools (more than a dozen fatigue questionnaires exist) and differences in patient characteristics. The researchers conducted this systematic review and meta-analysis to establish a reliable global figure and identify exactly what causes the numbers to vary so much.\u003c\/p\u003e\n\n\u003ch2 id=\"methods\"\u003eHow the Research Was Conducted\u003c\/h2\u003e\n\n\u003cp\u003eThe study was carefully designed according to international scientific standards. The research protocol was registered in the PROSPERO international prospective register of systematic reviews (registration number \u003cstrong\u003eCRD42024499139\u003c\/strong\u003e), and the study was reported following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines—the globally accepted standard for this type of research.\u003c\/p\u003e\n\n\u003cp\u003eThe research team conducted a comprehensive computerized search of \u003cstrong\u003eeight databases\u003c\/strong\u003e: PubMed, EMBASE, Cochrane Library, Web of Science, PsycINFO, CINAHL, and two Chinese databases (China National Knowledge Infrastructure [CNKI] and Wanfang). The search was completed on \u003cstrong\u003eJanuary 31, 2024\u003c\/strong\u003e, covering English- and Chinese-language studies published since 2000.\u003c\/p\u003e\n\n\u003cp\u003eTo be included in the analysis, studies had to meet all of the following criteria:\u003c\/p\u003e\n\u003col\u003e\n  \u003cli\u003eBe an observational study (cross-sectional, cohort, or case-control design)\u003c\/li\u003e\n  \u003cli\u003eInclude people aged 17 years or older with an MS diagnosis, confirmed either by self-report or by a clinician using the Poser or McDonald diagnostic criteria\u003c\/li\u003e\n  \u003cli\u003eBe published as full text in a peer-reviewed journal\u003c\/li\u003e\n  \u003cli\u003eUse a validated fatigue measurement scale with a defined cut-off value indicating clinically significant fatigue\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cp\u003eStudies were excluded if they involved only patients with clinically isolated syndrome (a single neurological episode that doesn't yet meet MS criteria) or only hospitalized inpatients; if fatigue was itself a requirement for entering the study; if the sample size was smaller than 100; if there wasn't enough information to calculate prevalence; or if they contained duplicated data.\u003c\/p\u003e\n\n\u003cp\u003eThe study selection process was rigorous. After removing duplicate records, \u003cstrong\u003etwo investigators independently screened\u003c\/strong\u003e all titles and abstracts. Whenever at least one reviewer thought an abstract might qualify, the full article was retrieved and evaluated by both reviewers. Disagreements were settled through consensus, or by a designated senior author if consensus couldn't be reached.\u003c\/p\u003e\n\n\u003cp\u003eData extraction was also done twice—independently by two pairs of reviewers—using standardized spreadsheets that were pilot-tested on 15 randomly selected articles. The extracted data covered study characteristics (design, sample size, country, diagnostic criteria), patient characteristics (age, sex, MS duration, disability scores, education level), and outcomes (fatigue cases, fatigue scale, and cut-off values). For longitudinal studies, baseline data were used.\u003c\/p\u003e\n\n\u003cp\u003eThe researchers assessed study quality with two established tools: the \u003cstrong\u003eAgency for Healthcare Research and Quality (AHRQ)\u003c\/strong\u003e criteria for cross-sectional studies (scoring 11 items, with total scores of 0–3 labeled \"low quality,\" 4–7 \"moderate quality,\" and 8–11 \"high quality\"), and the \u003cstrong\u003eNewcastle-Ottawa Scale (NOS)\u003c\/strong\u003e for case-control and cohort studies (scoring 0–9 stars, with 7–9 stars indicating low risk of bias, 5–6 moderate, and fewer than 4 high).\u003c\/p\u003e\n\n\u003cp\u003eFor the statistical analysis, the researchers used a random-effects model—the appropriate method when studies are expected to vary from each other—and applied a Freeman-Tukey transformation to correctly handle the non-normal distribution of prevalence data. Heterogeneity (how much results differ between studies) was measured with the χ²-based Cochrane Q statistic and the I² test. An I² value of \u003cstrong\u003e75% or higher\u003c\/strong\u003e indicates considerable heterogeneity. To find out what was driving the differences, the team ran subgroup analyses and meta-regression analyses on potential explanatory factors such as sample size, survey year, patient source, age, sex distribution, MS duration, disability score, fatigue scale, WHO region, and country income level. A minimum of three studies was required per subgroup. Statistical significance was set at p \u0026lt; 0.05.\u003c\/p\u003e\n\n\u003cp\u003eThe study did not formally evaluate publication bias, because established methods for this (such as funnel plot asymmetry tests) are known to be unreliable for prevalence studies. Instead, the researchers performed a \u003cstrong\u003esensitivity analysis\u003c\/strong\u003e—removing studies one by one to see whether any single study was skewing the results.\u003c\/p\u003e\n\n\u003ch2 id=\"studies\"\u003eThe Studies Behind the Numbers\u003c\/h2\u003e\n\n\u003cp\u003eThe database search initially produced \u003cstrong\u003e7,258 records\u003c\/strong\u003e. After removing duplicates, \u003cstrong\u003e4,838 titles and abstracts\u003c\/strong\u003e were screened, and \u003cstrong\u003e446 full-text articles\u003c\/strong\u003e were assessed against the eligibility criteria. In the end, \u003cstrong\u003e69 studies\u003c\/strong\u003e met all criteria and were included in the final analysis.\u003c\/p\u003e\n\n\u003cp\u003eTogether, these 69 studies included \u003cstrong\u003e44,468 people with MS\u003c\/strong\u003e. The average study had 644 participants, but sample sizes varied enormously, ranging from 100 to 9,077 participants. Across studies, the mean age of participants ranged from \u003cstrong\u003e32.4 to 59.3 years\u003c\/strong\u003e. The mean Expanded Disability Status Scale (EDSS) score—a standard measure of MS-related disability that runs from 0 (no disability) to 10 (death from MS)—ranged from \u003cstrong\u003e1.9 to 6.5\u003c\/strong\u003e. The mean MS duration ranged from \u003cstrong\u003e4.1 to 22.2 years\u003c\/strong\u003e, and the proportion of female participants ranged from \u003cstrong\u003e55% to 86%\u003c\/strong\u003e.\u003c\/p\u003e\n\n\u003cp\u003eGeographically, the studies spanned 27 countries across four WHO regions:\u003c\/p\u003e\n\u003cul\u003e\n  \u003cli\u003eOver half of the studies (n = 36) were conducted in Europe (EUR)\u003c\/li\u003e\n  \u003cli\u003eThere were no studies from Africa (AFR) or the Southeast Asia Region (SEAR)\u003c\/li\u003e\n  \u003cli\u003eThe United States contributed the most studies (n = 9), followed by Argentina (n = 5), and then the UK, Italy, and Australia (4 each)\u003c\/li\u003e\n  \u003cli\u003eSaudi Arabia, the Netherlands, China, and Finland each contributed 3 studies\u003c\/li\u003e\n  \u003cli\u003eTwo studies were binational (one in the USA and Sweden, another in Turkey and Israel), and three studies were multinational\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003eBy income level, the vast majority of studies (n = 53, \u003cstrong\u003e77%\u003c\/strong\u003e) were performed in high-income countries, with the remainder in upper-middle-income countries. In terms of patient recruitment, almost half of the studies (n = 34) were population-based, 24 took place in MS outpatient clinics, and 4 were conducted in MS Medical Research Centres. Most studies (n = 64, \u003cstrong\u003e93%\u003c\/strong\u003e) used a cross-sectional design (collecting data at a single point in time), 4 used a case-control design, and 1 used a cohort design (following patients over time).\u003c\/p\u003e\n\n\u003cp\u003eAmong the studies that reported specific patient characteristics: 15 provided data on sex distribution, 15 reported fatigue prevalence broken down by MS phenotype, and 4 estimated prevalence by education level. When diagnostic criteria were reported (34 studies), two earlier studies used the older Poser criteria, while all later studies used the continuously updated McDonald criteria (versions 2001, 2005, 2010, and 2017).\u003c\/p\u003e\n\n\u003ch2 id=\"measurement\"\u003eHow Fatigue Was Measured\u003c\/h2\u003e\n\n\u003cp\u003eThe included studies used \u003cstrong\u003efour different validated fatigue scales\u003c\/strong\u003e, and even within a single scale, different cut-off values were used to define \"clinically significant\" fatigue. This variation matters because it directly affects how many patients get counted as fatigued.\u003c\/p\u003e\n\n\u003cp\u003eThe most commonly used tool was the \u003cstrong\u003eFatigue Severity Scale (FSS)\u003c\/strong\u003e, used in 47 studies (two-thirds of the total). But even here, cut-off values varied:\u003c\/p\u003e\n\u003cul\u003e\n  \u003cli\u003e28 studies used a cut-off of 4 (mean score)\u003c\/li\u003e\n  \u003cli\u003e17 studies used a cut-off of 5 (mean score)\u003c\/li\u003e\n  \u003cli\u003e2 studies used cut-offs of 4.5 (mean score) or 28 (total score)\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003eThe \u003cstrong\u003eModified Fatigue Impact Scale (MFIS)\u003c\/strong\u003e was used in 16 studies (about one-fifth): 14 of these used a total score of 38 as the cut-off, while the other 2 used totals of 35.5 and 45. Four studies used the \u003cstrong\u003eFatigue Scale for Motor and Cognitive Functions (FSMC)\u003c\/strong\u003e with a total-score cut-off of 43. One study used the \u003cstrong\u003eEMIF-SEP\u003c\/strong\u003e, a validated French version of the Fatigue Impact Scale, with a total-score cut-off of 55. One additional study used both the FSS and MFIS, with cut-offs of 4 (mean score) and 38 (total score), respectively.\u003c\/p\u003e\n\n\u003cp\u003eThis patchwork of tools and thresholds is not just a technical detail—it turned out to be the single most important factor explaining why different studies report such different prevalence rates.\u003c\/p\u003e\n\n\u003ch2 id=\"quality\"\u003eQuality of the Included Studies\u003c\/h2\u003e\n\n\u003cp\u003eThe quality of the evidence matters for how much we can trust the results. In the 4 case-control studies and the single cohort study, Newcastle-Ottawa Scale scores ranged from 4 to 6 stars, indicating \u003cstrong\u003emoderate risk of bias\u003c\/strong\u003e on average.\u003c\/p\u003e\n\n\u003cp\u003eFor the 64 cross-sectional studies, the mean AHRQ quality score was \u003cstrong\u003e7.6 out of 11\u003c\/strong\u003e, with scores ranging from 5 to 10. Of these, \u003cstrong\u003e59% were rated \"moderate quality\"\u003c\/strong\u003e, and \u003cstrong\u003e28 studies (41%) were rated \"high quality.\"\u003c\/strong\u003e The main limitations flagged were: inadequate detail about quality-control methods for outcome measures, the use of non-blinded evaluators (who knew what the study was looking for), and unclear methods for handling missing data in the statistical analyses.\u003c\/p\u003e\n\n\u003cp\u003eReassuringly, when the researchers performed a sensitivity analysis—removing studies one at a time to see if any single study distorted the overall estimate—the results remained largely unchanged. This indicates that the findings were \u003cstrong\u003erobust and reliable\u003c\/strong\u003e despite the varying quality of the underlying studies.\u003c\/p\u003e\n\n\u003ch2 id=\"prevalence\"\u003eThe Big Picture: Global Fatigue Prevalence\u003c\/h2\u003e\n\n\u003cp\u003eAcross all 69 studies, the reported prevalence of fatigue ranged from a low of \u003cstrong\u003e28.4%\u003c\/strong\u003e to a high of \u003cstrong\u003e88.2%\u003c\/strong\u003e. When all the data were pooled together, the global prevalence of MS-related fatigue was \u003cstrong\u003e59.1%\u003c\/strong\u003e (95% confidence interval: 55.9% to 62.2%).\u003c\/p\u003e\n\n\u003cp\u003eIn plain language, this means that \u003cstrong\u003enearly 6 out of every 10 people with MS\u003c\/strong\u003e experience clinically significant fatigue. The 95% confidence interval indicates that if the analysis were repeated many times, the true global figure would fall between 55.9% and 62.2% in 95 out of 100 repetitions—giving us high confidence that the true number sits close to 59%.\u003c\/p\u003e\n\n\u003cp\u003eThere was significant heterogeneity among the studies (I² = 97.3%, p \u0026lt; 0.01), meaning that \u003cstrong\u003e97.3% of the variation between studies was due to real differences\u003c\/strong\u003e (rather than random chance), and the probability that these differences occurred by chance alone is less than 1%.\u003c\/p\u003e\n\n\u003cp\u003eThe five countries with the highest prevalence of MS-related fatigue were:\u003c\/p\u003e\n\u003col\u003e\n  \u003cli\u003eAustria: \u003cstrong\u003e80%\u003c\/strong\u003e\n\u003c\/li\u003e\n  \u003cli\u003eNorway: \u003cstrong\u003e79.5%\u003c\/strong\u003e\n\u003c\/li\u003e\n  \u003cli\u003eUnited Kingdom: \u003cstrong\u003e69.8%\u003c\/strong\u003e\n\u003c\/li\u003e\n  \u003cli\u003eSwitzerland: \u003cstrong\u003e69.2%\u003c\/strong\u003e\n\u003c\/li\u003e\n  \u003cli\u003eLithuania: \u003cstrong\u003e68.6%\u003c\/strong\u003e\n\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cp\u003eThe researchers also pooled results by demographic group. In the 15 studies that reported data by sex, fatigue prevalence was slightly higher in women (\u003cstrong\u003e58%\u003c\/strong\u003e of 6,982 females) than in men (\u003cstrong\u003e56.5%\u003c\/strong\u003e of 2,598 males). By MS phenotype, \u003cstrong\u003esecondary progressive MS (SPMS) had the highest prevalence at 74.4%\u003c\/strong\u003e (10 studies), followed by primary progressive MS (PPMS) at 64.3% (8 studies), and relapsing-remitting MS (RRMS) at 54.7% (15 studies). Education also mattered: among the 4 studies reporting this, people with more than 12 years of education had a fatigue prevalence of \u003cstrong\u003e47.9%\u003c\/strong\u003e, compared with \u003cstrong\u003e64.3%\u003c\/strong\u003e among those with 12 or fewer years of education.\u003c\/p\u003e\n\n\u003ch2 id=\"subgroups\"\u003eWho Is Most Affected by MS Fatigue?\u003c\/h2\u003e\n\n\u003cp\u003eTo explore why prevalence rates varied so much between studies, the researchers regrouped the studies by study- and patient-level characteristics. The subgroup analysis produced clear patterns:\u003c\/p\u003e\n\n\u003cul\u003e\n  \u003cli\u003e\n\u003cstrong\u003eSample size:\u003c\/strong\u003e Studies with more than 1,000 participants reported higher fatigue prevalence (\u003cstrong\u003e67%\u003c\/strong\u003e) than smaller studies (\u003cstrong\u003e59.9%\u003c\/strong\u003e).\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eSurvey year:\u003c\/strong\u003e Fatigue prevalence has \u003cstrong\u003edecreased every decade since 2000\u003c\/strong\u003e: 64.4% in 2000–2009, 59.6% in 2010–2019, and 51% in 2020–2023.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eSex distribution:\u003c\/strong\u003e Prevalence rose with the proportion of female participants: \u003cstrong\u003e49.9%\u003c\/strong\u003e in studies with fewer than 60% women, \u003cstrong\u003e58.5%\u003c\/strong\u003e in studies with 60–80% women, and \u003cstrong\u003e64.6%\u003c\/strong\u003e in studies with 80% or more women.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eAge:\u003c\/strong\u003e Fatigue became more common with age—\u003cstrong\u003e54.7%\u003c\/strong\u003e in studies with mean ages of 30–40 years, \u003cstrong\u003e58.6%\u003c\/strong\u003e in those aged 40–50, and \u003cstrong\u003e69.3%\u003c\/strong\u003e in those aged 50–60.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eDisability (EDSS score):\u003c\/strong\u003e People with greater disability (EDSS score greater than 4) had much higher fatigue prevalence (\u003cstrong\u003e73.7%\u003c\/strong\u003e) than those with milder disability (EDSS ≤ 4).\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eMS duration:\u003c\/strong\u003e Patients who had MS for more than 10 years had higher prevalence (\u003cstrong\u003e63.4%\u003c\/strong\u003e) than those with a shorter disease duration (\u003cstrong\u003e55.6%\u003c\/strong\u003e).\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eFatigue scale used:\u003c\/strong\u003e The FSMC produced the highest estimate (\u003cstrong\u003e70.4%\u003c\/strong\u003e), while the MFIS with a cut-off of 38 produced the lowest (\u003cstrong\u003e51%\u003c\/strong\u003e). Within the most common scale (FSS), a cut-off of 4 yielded a prevalence of \u003cstrong\u003e65.6%\u003c\/strong\u003e, versus \u003cstrong\u003e54.3%\u003c\/strong\u003e with a cut-off of 5.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003ePatient source:\u003c\/strong\u003e Population-based studies reported \u003cstrong\u003e61.4%\u003c\/strong\u003e, outpatient studies \u003cstrong\u003e58.9%\u003c\/strong\u003e, MS Medical Research Centres \u003cstrong\u003e50.2%\u003c\/strong\u003e, and mixed populations \u003cstrong\u003e54.9%\u003c\/strong\u003e.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eWHO region:\u003c\/strong\u003e Europe had the highest estimate (\u003cstrong\u003e61.2%\u003c\/strong\u003e), while the Western Pacific had the lowest (\u003cstrong\u003e54.2%\u003c\/strong\u003e).\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eCountry income level:\u003c\/strong\u003e High-income countries reported significantly higher prevalence (\u003cstrong\u003e59.9%\u003c\/strong\u003e) than upper-middle-income countries (\u003cstrong\u003e53.4%\u003c\/strong\u003e).\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003eOf the 10 characteristics examined, \u003cstrong\u003eall but WHO region and patient source had a statistically significant impact\u003c\/strong\u003e on reported fatigue prevalence—meaning these factors are genuine sources of the differences seen between studies.\u003c\/p\u003e\n\n\u003ch2 id=\"heterogeneity\"\u003eWhy Do the Numbers Differ So Much?\u003c\/h2\u003e\n\n\u003cp\u003eSubgroup analyses help, but large variation still remained within each subgroup. To dig deeper, the researchers performed a meta-regression analysis that simultaneously evaluated multiple study and patient characteristics to see how much each factor explains the differences between studies.\u003c\/p\u003e\n\n\u003cp\u003eThe results were striking. Four factors were significantly correlated with the variation between studies, and together they explained \u003cstrong\u003e86.4% of the total between-study variance\u003c\/strong\u003e:\u003c\/p\u003e\n\u003cul\u003e\n  \u003cli\u003e\n\u003cstrong\u003eFatigue scale used: 46.4%\u003c\/strong\u003e—this was by far the largest source of heterogeneity\u003c\/li\u003e\n  \u003cli\u003e\u003cstrong\u003eEDSS score (disability level): 18.4%\u003c\/strong\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003cstrong\u003eAge: 14.6%\u003c\/strong\u003e\u003c\/li\u003e\n  \u003cli\u003e\u003cstrong\u003eMS duration: 7.1%\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003eIn other words, the single most important reason that one study finds 30% fatigue while another finds 80% is simply the choice of fatigue questionnaire and its cut-off value. This is a critical insight: it\n\n\u003c!-- ddn:faq:start --\u003e\n\u003c\/p\u003e\u003ch2 id=\"ddn-faq\"\u003eFrequently Asked Questions\u003c\/h2\u003e\n\u003ch3\u003eWhat causes fatigue in multiple sclerosis?\u003c\/h3\u003e\n\u003cp\u003eResearchers divide MS-related fatigue into primary fatigue, caused by the disease itself, and secondary fatigue, caused by factors like sleep issues, mood disorders, medication side effects, and reduced physical activity. Primary fatigue occurs without an obvious trigger and stems directly from the underlying MS process.\u003c\/p\u003e\n\u003ch3\u003eWhy do different studies report very different fatigue rates in MS?\u003c\/h3\u003e\n\u003cp\u003eThe main reason is the choice of fatigue measurement scale and its cut-off value, which alone explained 46.4% of the variation between studies. Other factors include patient disability level, age, and MS duration. Together, these four factors accounted for 86.4% of the differences.\u003c\/p\u003e\n\u003ch3\u003eHow was fatigue measured in the studies included in this meta-analysis?\u003c\/h3\u003e\n\u003cp\u003eThe studies used four validated fatigue scales: the Fatigue Severity Scale (FSS), Modified Fatigue Impact Scale (MFIS), Fatigue Scale for Motor and Cognitive Functions (FSMC), and EMIF-SEP. Even within the same scale, different cut-off values were used, which affected prevalence estimates.\u003c\/p\u003e\n\u003ch3\u003eWhen should a person with multiple sclerosis and severe fatigue seek a second opinion?\u003c\/h3\u003e\n\u003cp\u003eFatigue affects nearly 6 out of 10 people with MS worldwide. If your fatigue is disabling or unresponsive to physical activity, dietary changes, or cognitive behavioral therapy, a second opinion can help. Fatigue may be primary, from MS itself, or secondary to sleep issues, mood disorders, or medication side effects—so a thorough evaluation matters. There is no convincing drug treatment for MS fatigue, but nonpharmacological approaches can help. A specialist review can confirm your fatigue is properly measured and managed. Diagnostic Detectives Network provides independent expert second opinions.\u003c\/p\u003e\n\u003c!-- ddn:faq:end --\u003e","brand":"DiagnosticDetectives.Com","offers":[{"title":"Default Title","offer_id":47494452740252,"sku":null,"price":0.0,"currency_code":"KRW","in_stock":true}],"url":"https:\/\/diagnosticdetectives.kr\/products\/fatigue-and-multiple-sclerosis-a-global-look-at-how-common-it-really-is","provider":"DiagnosticDetectives.Com","version":"1.0","type":"link"}