Эпидемиология множественного склероза: глобальные, региональные, национальные и субнациональные оценки и будущие прогнозы.

Introduction

Multiple sclerosis (MS) is a chronic autoimmune disease in which the immune system targets the myelin sheath insulating the nerve fibers in the central nervous system (CNS). The aberrant autoimmune attack leads to neuroinflammation, and subsequent demyelination and axonal damage [ 1 , 3 ]. As the disease progresses, repeated cycles of neuroinflammation and repair, result in the formation of scar tissues, known as sclerotic plaques [ 4 ]. Patients with this debilitating disease suffer from a range of symptoms, including visual disturbances, muscle weakness and coordination problems [ 5 ]. Over time, the continued axonal damage and neurodegeneration contribute to the decreased cognitive capacity and the permanent disability seen in advanced stages of the disease, making MS amongst the leading cause of neurological disability in young adults, particularly women [ 4 ].

There are four major clinical presentations of MS: relapsing-remitting (RRMS), primary-progressive (PPMS), secondary-progressive (SPMS), and progressive-relapsing [ 5 ]. More than three quarters of patients present with a clinical course of RRMS, which manifests as clearly defined attacks of worsening neurologic function followed by partial or complete recovery periods. Although a number of drugs can slow down or modify the progression of the disease, there is currently no cure for MS. Moreover, little is known regarding its etiology or the pathogenic mechanisms that drive the chronic inflammation leading to the autoimmune destruction of the myelin sheath. A concordance rate of under 30% in monozygotic twins and the variation in the geographical distribution of MS, implicate both genetic and environmental factors in the pathogenesis of the disease [ 6 , 7 ]. With little chance of influencing genetic predisposition, the importance of modulating environmental risk factors is becoming an area of great interest in the continuing search for ways to either prevent the onset of MS, or to ameliorate the course of the disease once established. Of the environmental factors, infection with Epstein-Barr virus (EBV) [ 8 , 11 ] and hypovitaminosis D have consistently been linked to MS pathogenesis [ 12 , 14 ].

Understanding the global, regional, and country-level variations in MS prevalence and incidence is important for addressing the growing burden of this disease. This manuscript aims to provide a comprehensive overview of the current state of MS epidemiology, highlighting key trends, disparities, and emerging patterns across different regions and countries. Such knowledge is crucial for developing targeted public health strategies, optimizing resource allocation, and ultimately enhancing the lives of individuals living with MS.

Methods

Data Source

The latest datasets on multiple sclerosis from the Global Burden of Disease (GBD) study 2021 were retrieved from the portal of the Institute of Health Metrics and Evaluation (IHME), University of Washington, Seattle. GBD2021 provides estimates for 371 diseases, from over 200 countries and territories from 1990 to 2021 [ 15 , 16 ]. GBD estimates are based on over 150,000 sources, including disease registries, vital statistics, surveys, electronic health records, census data, epidemiological and modelling studies [ 15 ]. These are the most current and updated estimates based on a comprehensive analysis of global, regional, national and sub-national data.

In this study we retrieved and analyzed the data on MS for incidence, prevalence and disability adjusted life years (DALYs), by age and sex, at global, regional and national levels from 1990 to 2021. Additionally, for United States, we analyzed data at subnational level to determine the trends within the country and assess how the different states have fared over the past three decades. Such comparisons could shed light on the risk factors that may be involved in the pathogenesis of MS in a given region.

Additionally, we analyzed data on socio-demographic factors obtained from the World Bank. GBD data on MS prevalence was merged with socio-demographic data from the World Bank for all countries. The latest World Bank data were obtained for infant mortality, physician density (per 1000 population), adult literacy rate, urbanization (percent of population living in urban areas), electricity availability, health expenditure per capita PPP (purchasing power parity), air pollution (particulate matter PM2.5 air pollution mean annual exposure), gross domestic product (GDP), and human development index. Social and economic factors that were epidemiologically associated with MS prevalence were ascertained using multivariate analysis.

Statistical Data Analysis

Multivariate modeling was carried out using R module GAMLj3 in Jamovi statistical software. Generalized linear modeling was used with a linear continuous dependent variable. Collinearity was assessed using intervariable correlations. Forecasting of the disease burden was carried out using the exponential smoothing (ETS) algorithm in Microsoft Excel. As the historical trends did not show cyclic patterns, the seasonality option was not applied.

Results

Global Burden of MS and Future Projections

In 2021, there were 1.89 million (uncertainty interval: 1.688 to 2.113) people in the world living with MS. This corresponds to 23.9 cases per 100,000 population (uncertainty interval: 21.4 to 26.8). This rate has been increasing continuously since 1990 in all regions of the world with the greatest increase in more developed regions. Age-adjusted prevalence rates (which adjusts for changing population age structures over time) are also increasing in most regions although the rise is less marked (Fig.  1 A). This may indicate that the rising prevalence of MS is at least partly due to population growth and aging. Over 62,000 individuals are diagnosed with MS every year (uncertainty interval: 56.0 to 70.6 thousand). There are an estimated 16,000 deaths due to MS annually (uncertainty interval: 15.3 to 17.0 thousand). Without any interventions, future projections indicate that the burden of MS will continue to rise, particularly in Europe. By 2050, the incidence of new cases of MS in Europe will rise to approximately 2.5 cases/100,000 population (Fig.  1 B).

Trends in the burden of multiple sclerosis in world regions

Regional-Level Burden of MS

North America and Western Europe sustained the highest prevalence, incidence, DALYs and mortality due to MS compared Africa, Asia and Latin America (Fig.  2 ). In all regions of the world, the prevalence was significantly higher in females compared to males, with North America and Western Europe showing the greatest difference (Fig.  3 ). Moreover, the prevalence of MS has been gradually increasing globally over the past three decades, with an average increase of 26% (Table  1 ). In some countries however, the prevalence rate has more than doubled from what it was in 1990.

Global distribution of multiple sclerosis. Colors indicate the 2021 prevalence/DALYs rates of MS with red hues for higher rates and blue shades for lower values. DALY, disability-adjusted life years

Gender differences in prevalence of multiple sclerosis in different world regions

Table 1 Burden of multiple sclerosis in selected countries Region/country Prevalence (cases/100,000) (1990) Prevalence (cases/100,000) (2021) % Increase in prevalence (1990–2021) Burden (DALY/100,000) (2021) Total number of cases (2021)
Global

19

24

26

12
1 , 888 , 000
Europe

56

86

54

48
727 , 000  Sweden 160 219 37 89 23,000  Norway 98 176 80 89 10,000  Ireland 111 163 47 77 8,000  United Kingdom 98 158 61 100 107,000  Denmark 124 150 21 94 9,000  Germany 91 126 38 73 108,000  Switzerland 107 131 22 73 12,000  Netherlands 95 129 36 74 22,000  Italy 81 124 53 56 74,000  France 73 118 62 55 79,000  Finland 81 113 40 64 6,000  Spain 57 105 84 42 48,000  Turkey 37 55 49 22 46,000  Russia 28 37 32 26 53,000
Asia

5

9

80

4
413 , 000  Australia 45 84 87 40 22,000  Qatar 33 72 118 20 2,000  Lebanon 32 68 113 22 4,000  Iran 34 62 82 32 53,000  New Zealand 41 43 5 32 2,000  Saudi Arabia 15 35 133 13 13,000  Japan 11 15 36 6 18,000  South Korea 8 14 75 5 7,000  India 6 8 33 3 117,000  Taiwan 2 8 300 3 2,000  China 2 3 50 1 40,000
Americas

49

58

18

31
600 , 000  Canada 128 182 42 85 68,000  United States 107 126 18 66 419,000  Brazil 13 25 92 11 55,000
Africa

7

11

57

6
145 , 000  Algeria 22 51 132 20 22,000  Egypt 12 31 158 8 32,000  South Africa 6 8 33 6 4,000

Burden of multiple sclerosis in selected countries

Country-Level Burden of MS

Countries with the highest percentage increase were Taiwan (300% increase), Egypt (158%), Algeria (132%), Qatar (118%) and Lebanon (113%) (Table  1 ). From the global north, Norway, France, and Spain experienced the greatest increase at 80%, 62% and 84% respectively. In 2021, countries with the highest prevalence of MS were Sweden (219 /100,000 population), Canada (182), Norway (176), Ireland (163), and the United Kingdom (158) (Table  1 ).

Subnational-Level Burden of MS

To assess subnational-level burden of MS, data was retrieved for United States. The prevalence of MS in United States was also fairly high (126/100,000), with northern states having higher prevalence rates compared to the southern states (Fig.  4 ). A ranked comparison of incidence rates at the individual state level within US revealed that states such as Utah, Montana, Rhode Island, Wyoming, and Idaho had the highest burden compared to states such Hawaii, Mississippi, Louisiana, and Texas (Table  2 ).

Prevalence of multiple sclerosis per 100,000 population in 2021 across the US

Table 2 Incidence rates of multiple sclerosis across the United States in 2021 Incidence 1990 Incidence 2021 % Increase
States with the highest rates
Utah 4.72 5.37 13.6 Montana 4.96 5.25 5.8 Rhode Island 4.38 5.15 17.4 Wyoming 4.40 5.08 15.6 Idaho 4.57 4.93 8.0 Colorado 4.46 4.73 6.1 Michigan 4.26 4.55 6.8 New Hampshire 4.34 4.48 3.3 South Dakota 4.05 4.45 10.0 Washington 4.45 4.45 0.1 Wisconsin 4.44 4.44 0.1 Vermont 4.15 4.40 6.0
States with the lowest rates
Tennessee 3.03 3.22 6.6 South Carolina 2.79 3.08 10.2 Georgia 2.63 2.90 10.0 Oklahoma 2.81 2.87 2.2 Alabama 2.68 2.85 6.5 Florida 2.76 2.85 3.2 Arkansas 2.60 2.85 9.7 California 2.63 2.61 -1.0 Texas 2.09 2.52 20.8 Louisiana 2.45 2.47 0.5 Mississippi 2.22 2.30 3.7 Hawaii 1.46 1.46 0.1 Notes: incidence rates are cases per 100,000 population in 2021. States with the highest and lowest rates shown only

Incidence rates of multiple sclerosis across the United States in 2021

Notes: incidence rates are cases per 100,000 population in 2021. States with the highest and lowest rates shown only

Age and Sex Associated Burden of MS

Women were twice as likely to be diagnosed with MS than men, particularly in the age group 15–40 years. The global prevalence of MS among women was 32.3 per 100,000 population (uncertainty interval: 29.1 to 36.1) compared 15.6 (13.8 to 17.6) in men. The peak incidence (age at diagnosis) was around the age 30–34 years, with new diagnoses occurring from as early as 10 years to the age of 60 years (Fig.  5 A). The age distribution of MS follows a rising pattern from the age group 10–34 years and thereafter gradually decreases, plateauing after the age of 60 (Fig.  5 B). This pattern of a unimodal peak is the same for males and females.

Age distribution of multiple sclerosis

Multivariate Analysis of Predictors of MS

On multivariate analysis, the predictors for the prevalence of MS were latitude of the country (adjusted odds ratio 1.69; p  < 0.001) (Fig.  6 A) and healthcare expenditure per capita PPP (adjusted odds ratio 1.01; p  < 0.001) (Fig.  6 B). The model had high explanatory power (adjusted R-squared 0.72). Variables that were not statistically significant predictors included infant mortality rate, electricity availability, physician density, air pollution, GDP per capita, urbanization, and human development index.

Prevalence of multiple sclerosis and its association with latitude and healthcare expenditures

Discussion

In this study, we found that North America and Western Europe had a much higher burden as compared to Asia and Africa. Moreover, in many developed regions, such as Europe, the incidence has been gradually rising over the past three decades. The prevalence of MS was greater in higher latitudes and to a lesser extent in countries with higher healthcare expenditures. This finding was obtained in multivariate analysis which controls for other confounding variables.

Some low-to middle income countries such as Egypt, Algeria, Taiwan and Saudi Arabia, have witnessed a dramatic rise in prevalence rates over the past three decades. This rise could be a reflection of improvements in diagnostics, aging population and lifestyle changes. Even within a single country such as the United States, differences were noted in incidence rates between the northern and southern states. For example, rates in Utah, Montana, Rhode Island and Wyoming were double those compared to Hawaii, Mississippi, Louisiana, and Texas [ 17 ], suggesting the possible involvement of region-specific environmental factors [ 18 , 20 ]. The importance of environmental factors is further highlighted by studies which indicate that individuals moving from low-risk regions to high-risk regions tend to follow the risk tends of their host country [ 20 , 38 , 39 ].

Multiple sclerosis is an important global health problem. It is estimated that 2–3 million people live with MS [ 21 , 22 ]. Although MS can occur at any time, it typically manifests in young adults between the age 20–40 years, with a female predominance as high as 3:1 [ 22 , 23 ]. Globally, the incidence and prevalence of MS varies widely and is believed to be influenced by a number of different factors, including latitude, ethnicity, sex, socioeconomic conditions and infections [ 17 , 24 , 27 ]. Thus, the epidemiology of MS is complex and multifaceted, and the relative contribution and interaction of these risk factors could explain the global disease heterogeneity [ 28 , 29 ]. Indeed, majority of MS cases are attributable to known risk factors, the most important of which are HLA-DRB1*1501 genotype, infection with Epstein-Barr virus (EBV) and hypovitaminosis D [ 29 , 30 ]. For example, it has been shown that latitude is significantly associated with the prevalence of MS [ 17 , 31 , 32 ]. This geographical variation has been attributed to lower sunlight exposure and hence lower levels of plasma vitamin D [ 12 , 14 , 33 ]. Although numerous studies have indicated that low vitamin D levels are associated with increased risk of MS [ 34 , 37 ], the exact mechanism by which vitamin D lowers this risk remains unknown. Vitamin D is an important immunomodulator, effecting B-cells, T-cells, microglia and astrocytes, as well maintaining the blood-brain barrier integrity [ 38 , 38 ]. Thus, hypovitaminosis D could impact a number of different immunological processes, thereby increasing the risk of MS in genetically predisposed individuals [ 39 ].

Another important, and arguably the leading environmental risk factor implicated in the pathogenesis of MS is EBV [ 8 , 11 ]. A number of studies have shown that individuals who develop infectious mononucleosis upon primary acute EBV infection have 2–3 fold increased risk of developing MS [ 40 ]. In a recent longitudinal study involving over 10 million US military personnel over a period of 20-years, found that 801 individuals developed MS [ 10 ]. Importantly, 35 of 801 individuals were EBV seronegative before the start of the study, and except for one case, all seroconverted before the onset of MS, underscoring the importance of EBV as a leading risk factor in the pathogenesis of MS [ 10 ]. Individuals who are EBV negative, have a significantly reduced risk of developing MS [ 10 ]. Notably, the virus has been directly shown to be present in the brain of most cases of MS [ 41 , 43 ]. Although the details of how EBV triggers and drives MS is unclear, reports indicate that immunes responses triggered against the virus can cross react with self-proteins, in a process known as molecular mimicry [ 44 , 46 ]. A number of vaccines are currently being evaluated for their efficacy in preventing EBV infection [ 47 , 49 ]. If successful, this could potentially prevent, not only MS, but also a number of malignancies known to be caused by EBV [ 50 , 51 ].

Since, there is currently no cure for MS, strategies for reducing the burden of MS should to be directed at strengthening healthcare infrastructures, improving early diagnosis and treatment, better access to care and multidisciplinary support services involving MS neurologists, MS nurses, physiotherapists, neuropsychologists, and family physicians [ 52 , 53 ]. Additionally, improvements in education and awareness of the disease, and more investment in research to better understand the cause of the disease and how it could be prevented, is required [ 54 , 55 ]. Which of these strategies should be prioritized and adopted will depend on needs assessment of each country. For examples, in low resource countries, healthcare infrastructure, public awareness about the disease and its symptoms and access to affordable disease modifying therapy (DMT), will be higher on the priority list than basic research and development [ 56 ]. As MS is a multisystem disease, a holistic approach to patient care including continuity of care and community involvement is essential [ 57 ].

Although this study provides the most up to date estimates on the burden of MS at global, regional, national and sub-national levels, there are some limitations. In some countries or territories, data may not be available, or may be unreliable and inconsistent. In such situations, GBD provides the best estimates using statistical modeling methods [ 15 ]. GBD collects, collates and adjusts a very amount large amount of data from thousands of sources and uses sophisticated modelling systems to generate its final estimates [ 15 ]. GBD modelling also incorporates factors such as underreporting as well as overdiagnosis in tertiary care centers. Thus, the GDB estimates can differ from individual published studies. For example, the GBD 2021 dataset estimates the prevalence of MS in New Zealand to be 43 cases per 100,000 population, and in Australia to be 9/100,000, whilst some country-level studies have estimated the prevalence in New Zealand to be 72/100,000 in 2006 [ 58 ] and in Australia to be 125/100,000 in 2011 [ 59 ]. These differences are not only due to the different methods of data collection and analysis, but also due to differences in when the data was collected.

Another important source of MS epidemiology is the Atlas of MS [ 60 ]. Although, the GBD study and the Atlas of MS use different calculations and estimation tools, the findings point to similar conclusions. Both indicate that prevalence is higher in females, higher America and Western Europe and higher in higher income countries. Moreover, both indicate that the prevalence of MS is rising, although the estimates differ. GBD estimates the global prevalence to be 1.89 million in 2021 whilst the Atlas of MS estimates this to be 2.8 million in 2020.

Conclusions

The burden of MS has risen in many parts of the world over the last three decades. MS shows some epidemiologic associations with latitude, age of onset, and female predominance, indicating a complex interplay of environmental (EBV exposure, latitude), socio-economic (affluence), and polygenetic factors. This study provides an overview of the global, regional and country-level variations in MS prevalence and incidence. Such data is essential for guiding public health strategies, optimizing resource allocation, developing new research initiatives, and improving patient outcomes.

Acknowledgements

We would like to thank IHME and the World Bank for access to the data.

Abbreviations

Global Burden of Diseases

Disability-Adjusted Life-Years

Epstein-Barr Virus

Gross Domestic Product

Multiple Sclerosis

Purchasing Power Parity

Primary-Progressive Multiple Sclerosis

Progressive-Relapsing Multiple Sclerosis

Relapsing-Remitting Multiple Sclerosis

Secondary-Progressive Multiple Sclerosis

Author Contributions

GK: Conceptualization, Data analysis, Writing the first draft, Revising the final manuscript.MJH: Data analysis, Preparing the Figures, Writing the first draft, Revising the final manuscript.

Funding

Khan-Lab is supported by UAEU grant #12R168.

Data Availability

The datasets used are all publicly available.

Declarations

Ethics Approval

Not applicable. Publicly available data was used for the analysis.

Artificial Intelligence

No artificial intelligence tools were employed. All analyses and interpretations were conducted manually by the authors.

Consent for Publication

All authors confirm that they had full access to all the data in the study and accept responsibility to submit for publication.

Competing Interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

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References

Associated Data

Data Availability Statement

The datasets used are all publicly available.