Spatial and temporal distribution of the prevalence of unemployment and early retirement in people with multiple sclerosis: A systematic review with meta-analysis

Abstract

Background
We aimed to summarise the prevalence of unemployment and early retirement among people with MS and analyze data according to a spatio-temporal perspective.

Methods
We undertook a systematic search of PubMed/MEDLINE, Scopus, SciVerse ScienceDirect, and Web of Science. We included any peer-reviewed original article reporting the prevalence of unemployment and early retirement in the working-age population with MS. We excluded articles off-topic, with other study designs, whose study sample were unlikely to be representative of the MS population and in case of unavailability of the full text or essential information. A random-effects meta-analysis was used to measure overall prevalence estimates of unemployment and early retirement. We used meta-regression and subgroup analysis to evaluate potential moderators of prevalence estimates and the leave-one-out method for sensitivity analyses.

Results
Our research identified 153 studies across 29 countries encompassing 188436 subjects with MS. The pooled overall effect size for unemployment and early retirement was 35.6% (95% CI 32.8–38.4; I² = 99.31) and 17.2% (95% CI 14.6–20.2; I² = 99.13), respectively. The prevalence of unemployment varied according to the year of publication (p < 0.001) and there was a statistically significant decrease in the prevalence of unemployment over time (p = 0.042). Regarding early retirement, only seven (31.8%) estimates obtained from studies that were published before 2010 were below the overall effect size in comparison to 27 (60.0%) estimates extracted from data published between 2010 and 2021 (p = 0.039). There was a significant difference in prevalence according to countries (p < 0.001). Psychiatric illness was an important clinical feature responsible for patients leaving the workforce in regions with a high MS prevalence.

Conclusions
Unemployment and early retirement due to MS remain highly prevalent, despite a slight decline in the last decade. The prevalence of unemployment and early retirement varies globally.

Full text

RESEARCH ARTICLE
Spatial and temporal distribution of the
prevalence of unemployment and early
retirement in people with multiple sclerosis: A
systematic review with meta-analysis
Bruno Kusznir VitturiID
1
*, Alborz Rahmani
1,2
, Guglielmo Dini
1,2
, Alfredo Montecucco
1,2
,
Nicoletta Debarbieri
2
, Paolo Bandiera
3
, Mario Alberto Battaglia
4,5
, Tommaso Manacorda
4
,
Benedetta Persechino
6
, Giuliana Buresti
6
, Michela Ponzio
4
, Matilde Inglese
7,8
,
Paolo Durando
1,2
1Department of Health Sciences, University of Genoa, Genoa, Italy, 2IRCCS Ospedale Policlinico San
Martino, Occupational Medicine Unit, Genoa, Italy, 3Italian Multiple Sclerosis Association (AISM), Genoa,
Italy, 4Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy, 5Department of
Life Science, University of Siena, Siena, Italy, 6Italian Workers’ Compensation Authority (INAIL), Genoa,
Italy, 7Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health
(DiNOGMI) and Center of Excellence for Biomedical Research (CEBR), University of Genoa, Genoa, Italy,
8IRCCS Ospedale Policlinico San Martino, Genoa, Italy
*bruno.kusznir.vitturi@edu.unige.it
Abstract
Background
We aimed to summarise the prevalence of unemployment and early retirement among peo-
ple with MS and analyze data according to a spatio-temporal perspective.
Methods
We undertook a systematic search of PubMed/MEDLINE, Scopus, SciVerse ScienceDirect,
and Web of Science. We included any peer-reviewed original article reporting the preva-
lence of unemployment and early retirement in the working-age population with MS. We
excluded articles off-topic, with other study designs, whose study sample were unlikely to be
representative of the MS population and in case of unavailability of the full text or essential
information. A random-effects meta-analysis was used to measure overall prevalence esti-
mates of unemployment and early retirement. We used meta-regression and subgroup
analysis to evaluate potential moderators of prevalence estimates and the leave-one-out
method for sensitivity analyses.
Results
Our research identified 153 studies across 29 countries encompassing 188436 subjects
with MS. The pooled overall effect size for unemployment and early retirement was 35.6%
(95% CI 32.8–38.4; I
2
= 99.31) and 17.2% (95% CI 14.6–20.2; I
2
= 99.13), respectively. The
prevalence of unemployment varied according to the year of publication (p <0.001) and
there was a statistically significant decrease in the prevalence of unemployment over time
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OPEN ACCESS
Citation: Vitturi BK, Rahmani A, Dini G,
Montecucco A, Debarbieri N, Bandiera P, et al.
(2022) Spatial and temporal distribution of the
prevalence of unemployment and early retirement
in people with multiple sclerosis: A systematic
review with meta-analysis. PLoS ONE 17(7):
e0272156. https://doi.org/10.1371/journal.
pone.0272156
Editor: Marcello Moccia, Universita degli Studi di
Napoli Federico II, ITALY
Received: April 4, 2022
Accepted: July 14, 2022
Published: July 28, 2022
Copyright: ©2022 Vitturi et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting information
files.
Funding: This work was supported by the Italian
Multiple Sclerosis Association (AISM) and Italian
Workers’ Compensation Authority (INAIL), in the
framework of BRIC 2019: “PRISMA” project
(Bando BRIC 2019_ID 24). This work was
developed within the frameworks of the

(p = 0.042). Regarding early retirement, only seven (31.8%) estimates obtained from studies
that were published before 2010 were below the overall effect size in comparison to 27
(60.0%) estimates extracted from data published between 2010 and 2021 (p = 0.039).
There was a significant difference in prevalence according to countries (p <0.001). Psychi-
atric illness was an important clinical feature responsible for patients leaving the workforce
in regions with a high MS prevalence.
Conclusions
Unemployment and early retirement due to MS remain highly prevalent, despite a slight
decline in the last decade. The prevalence of unemployment and early retirement varies
globally.
Introduction
Multiple Sclerosis (MS) is a chronic autoimmune disease that causes demyelination and neu-
rodegeneration in the central nervous system. It mainly affects young people between 20 and
40 years of age and it is the main cause of non-traumatic disability among young adults in
the Western world [1]. About 2.8 million people worldwide suffer from MS, whose incidence
and prevalence increase in both developed and developing countries [2]. The symptoms are
extremely varied and the clinical course is within a spectrum that extends from relapsing-
remitting to progressive [3].
Besides the inherent clinical complexity of MS, the age of onset of the disease brings inevita-
ble repercussions to work activity, once it coincides with the moment in which people with
MS (PwMS) find themselves managing the already expected difficulties of the job market and
the beginning of the professional career [4,5]. Often limiting and disabling, symptoms such
as fatigue, neuropsychiatric impairment, and motor disturbances constantly threaten the full
performance at work and the search for new professional skills [6,7]. PwMS are vulnerable to
barriers related to the work environment (e.g. high temperature level, difficult access to the
workplace, noise) deterioration of social relationships at work, negative work events and
stigma and discrimination in the workplace. Moreover, intrinsic characteristics of the job such
as inflexible work schedules and extended standing time can make work unviable for PwMS
[8–10].
MS is recognized as a well-known risk factor for unemployment and early retirement. A
Norwegian study found that after 19 years of disease, only 45% of patients were still employed
[11]. In a Swedish cohort, only 28% and 23% of PwMS were working full- and part-time after a
follow-up of ten years, respectively [12]. In 2013, Krause et al. showed that 44.8% of PwMS
were forced to retire early due to their illness [13]. Once unemployed, PwMS face substantial
difficulties to return to the workforce [14]. In addition to the undeniable importance that
work plays in people’s lives and the financial and psychological consequences that the loss of a
job can entail, unemployed and early retired patients are known to be associated with a worse
level of quality of life [15].
Although unemployment and early retirement are already sufficiently eloquent conse-
quences in the personal life of PwMS, it is impossible not to recognize the economic burden
closely associated with these two outcomes. In Germany, approximately 27.300 persons
received early retirement pensions caused by MS [16]. Battaglia et al. showed that invalidity
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Department of Neurosciences, Rehabilitation,
Ophthalmology, Genetics, Maternal and Child
Health (DiNOGMI) of the University of Genoa -
Department of Excellence of MIUR 2018-2022
(legge 232 del 2016), of the Department of Health
Sciences (DISSAL) of the University of Genoa, and
of the Occupational Medicine Unit of the IRCCS
Ospedale Policlinico San Martino of Genoa, Italy.
The funders had no role in study design, data
collection and analysis, decision to publish, or
preparation of the manuscript.
Competing interests: The authors have declared
that no competing interests exist.

and early retirement can cost more than 18.000 €per patient every year [17]. Indeed, it is not
frivolous to affirm that MS is one of the most costly diseases, once it dialogues with the global
economy and the public health closely [18].
If, on the one hand, the literature is relatively abundant concerning data on unemployment
and early retirement in MS, on the other hand, there is an enormous diversity of data that pre-
vents clinicians and researchers from having the real dimension of this issue. In fact, there is
no study aimed at systematically synthesising the available data. Over time, there have been
remarkable advances in the understanding of MS and its treatment and, since 2010, several
disease-modifying drugs (DMDs) have been approved [19]. Nevertheless, there is still no evi-
dence indicating the temporal evolution of the occupational outcomes in PwMS. Moreover,
there is also a complete lack of studies describing and comparing the prevalence of unemploy-
ment and early retirement considering a geographical point of view. Strategies to prevent these
outcomes are complex and can vary substantially across countries. An accurate understanding
of the geographical particularities of unemployment and early retirement is crucial to guide
effective strategies to promote the integration of PwMS into work.
The influence of MS on unemployment and early retirement is a public health issue. In
almost 40 years of published data on the prevalence of unemployment and early retirement in
workers with MS, it is imperative to understand the full epidemiological and occupational con-
text of the disease. Effective public health strategies depend on this type of approach and are
crucial to promote the occupational outcomes and the quality of life of PwMS. Aware of this
scenario and the importance of this topic, we performed the first systematic review with meta-
analysis that address the prevalence of unemployment and early retirement in a temporal-spa-
tial perspective. The review aimed to summarize the prevalence of unemployment and early
retirement among PwMS, describe if there has been any significant change over time, and
compare these two outcomes from a geographical point of view.
Materials and methods
This study was carried out according to the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses Statement (PRISMA) [20] (S1 File) and the Joanna Briggs recom-
mendations for systematic reviews of observational epidemiological studies reporting preva-
lence and cumulative incidence data [21]. The protocol was registered in PROSPERO
(CRD42021285216). As this was a literature review, ethical approval wasn’t necessary as it
didn’t involve the recruitment of subjects and data were analyzed from already published origi-
nal articles.
Search strategy and selection criteria
From August 1, 2021, to October 30, 2021, we systematically searched on PubMed/MEDLINE,
Scopus, SciVerse ScienceDirect, and Web of Science the following keywords (Employ�OR
unemploy�OR occupation�OR “work” OR vocation�OR “work resumption” OR workplace�
OR “return to work” OR “workforce” OR “workforce” OR “labour force” OR “labor force” OR
Career�OR Job�OR “job retention” OR retire�OR “disability pension” OR “worker” OR “fit-
ness for work”) AND (“Multiple sclerosis” OR “Disseminated Sclerosis” OR “Demyelinating
Autoimmune Diseases” OR “Demyelinating Autoimmune Disorders” OR “Clinically Isolated
Syndrome” OR “Demyelinating”). The details of the search strategy used are reported in S1
Fig. We didn’t explore any grey literature sources. We adopted a broad search methodology to
ensure the maximum inclusion of studies reporting both outcomes.
Articles were selected according to the CoCoPop (Condition/Context/Population) strategy.
We included any peer-reviewed original article reporting the prevalence of unemployment
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and early retirement of PwMS in the working age. MS must have been diagnosed according to
accepted international criteria at the time of the study and/or confirmed by a doctor. No time
limits were set for the search. We included articles whose full text was published in English,
Italian, Spanish, French, and Portuguese. As this is a systematic review of epidemiological arti-
cles, studies should contain a minimum sample of 124 subjects. This number was calculated
according to the formula n = [Z
2
. P(1—P)] / d
2
, where nis the sample size, Zis the Z statistic
for a given level of confidence (1.96), Pis the expected global prevalence, and dis the precision
(in a proportion of one; if 5%, d = 0.05). Data were taken from cross-sectional cohort studies
and baseline measurements in longitudinal and interventional studies with clinical follow-up.
After we removed duplicate entries, we performed an initial screen of titles or abstracts to
assess potential relevance and remove those off-topic. Screening of titles, abstracts, and full
texts for each article was conducted by three experienced and trained investigators (BKV, AR,
and AM), each blinded to the other’s ratings. In case of discrepancy, a final decision was made
by a consensus. Afterward, we obtained relevant full-text articles, revaluated their eligibility,
and determined their final inclusion or exclusion.
Studies written in languages other than the five pre-specified above and studies designed as
reviews, letters to the editor, expert opinions, commentaries, case reports, case series, editorials
were excluded. In case of articles with missing or dubious data or without an available full text,
we tried to contact the corresponding author twice to obtain more information by email. The
study was excluded whenever our contact attempt failed. We didn’t accept studies whose sam-
ple deliberately included patients with more than a chronic disease or in which MS was not the
primary condition. When multiple articles reported data from the same population, the article
with the highest number of variables described was selected. We also excluded studies whose
study sample were unlikely to be representative of the total population with MS–for example,
studies that only focus on specific MS phenotype, only included PwMS with specific deficits or
comorbidities, studies that excluded subjects with any disability, or populations primarily
selected by the variables of interest. Fig 1 provides the PRISMA flowchart overview of the
search and screening strategy performed. Articles were exported and managed in Mendeley
1.19.8 (Elsevier, New York, USA).
Data analysis and quality assessment
Data extraction was done by two independent reviewers (BKV and AR) and eventual dis-
agreements were resolved by discussion until a consensus was reached. From each eligible
study, we extracted the prevalence of unemployment and early retirement. In the cases in
which the proportion was not explicit, we calculated it using as the denominator the entire
population of the study and as the numerator, the raw explicit number of subjects with any
of the outcomes studied. In addition to the outcomes of interest, the following variables were
extracted in a Microsoft Excel spreadsheet: name of the first author, year of publication,
country, sample size, average age, gender, higher educational attainment (defined as > 12
schooling years), study design, mean Expanded Disability Status Scale (EDSS), mean disease
duration, use of disease-modifying drugs (DMDs), MS phenotype (progressive or relapsing-
remitting), the prevalence of fatigue, neuropsychiatric symptoms and cognitive impairment.
Countries were grouped into continents and were classified by income according to the
World Bank country classification 2021 [22]. A data extraction form was used to extract
equivalent information in a standardized manner, and to also minimize the intra-examiner
variability, all the extracted data were double-checked. Categorical variables are reported as
prevalence (%) while numerical variables are reported as means with the respective standard
deviation (SD).
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Quality assessment of the included studies was carried out using JBI Critical Appraisal
Checklist for Studies Reporting Prevalence Data [23]. This checklist was developed to deter-
mine the extent to which a prevalence study has addressed the possibility of bias in its design,
conduct, and analysis. This questionnaire contains ten closed-ended questions related to the
methodological quality of the study. Answers can be "Yes", "No", "Unclear", or "Not/Applica-
ble". The higher the number of "Yes" answers, the higher the quality of the study.
Fig 1. PRISMA flowchart.
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We undertook an initial descriptive analysis of the studies. We used the random-effects
model based on the binomial distribution to calculate the pooled estimates of the prevalence of
unemployment and early retirement. Specifically, we explored the relationship between these
two outcomes with time and geographic variability. When multiple estimates existed for a
country and a publication year, these estimates were combined with a random-effects meta-
analysis to provide a single estimate for that country or year. We did not use any special statis-
tical treatment for analysing data coming from the same country over time. When at least ten
studies presented a specific covariate, we performed a weighted meta-regression with a ran-
dom-effects model to assess the effect of moderators on the pooled effect size. Differences
between the effects-sizes of categorical variables were assessed with the ANOVA Q-Test
Random-effects with separate estimates of T2. Effect sizes were reported as proportions. We
performed a subgroup analysis by year/time, country, continent, income-based country classi-
fication, younger age (<50 years old), absence of vocational or higher education, disease dura-
tion of more than ten years, EDSS greater than 3.0, countries and continents with the highest
prevalence of MS (>200 people with MS per 100.000) [24]. We also did a sensitivity analysis
to test the robustness of our findings and we removed possible outliers and studies with a high
risk of bias to explore the influence of individual studies on the main results.
Statistical heterogeneity was assessed using the I
2
statistic and visually inspecting the forest
plot. I
2
more than 75% was regarded as substantial heterogeneity [25]. We investigated the
existence of publication bias using Egger’s linear regression test [26], Duval and Tweedie’s
Trim and Fill analysis [27], and with the visual inspection of the funnel plots. A p <0.05 was
considered statistically significant. All statistical analyses were performed using ProMeta (ver-
sion 3.0) and SPSS (version 28.0.1).
Results
We identified 104228 potentially eligible studies from the systematic search. Removing dupli-
cates and screening the abstracts resulted in 1136 articles whose full-texts were assessed for
eligibility. After applying all the inclusion and exclusion criteria, 152 articles were finally con-
sidered relevant and included in the qualitative and quantitative analysis (Fig 1). Overall, the
total sample size comprised 188436 individuals with MS. The mean age ranged from 32.0 to
60.0 years, the female gender proportion ranged from 33.1 to 100.0%, and the prevalence of
individuals with higher educational attainment varied from 24.0% to 88.0%. Concerning the
disease characteristics, the mean EDSS and the mean disease duration ranged from 1.3 to 5.5
and 3.2 to 23.6 years, respectively. The proportion of subjects with progressive phenotype of
MS varied from 4.6% to 100.0% and the prevalence of fatigue, neuropsychiatric symptoms and
cognitive impairment ranged from 56.0% to 96.3%, 25.6% to 89.9%, and 48.1%–97.0%, respec-
tively. Regarding the use of DMDs, there were studies in which no subjects used them and oth-
ers in which all individuals used them. Data about the prevalence of unemployment and early
retirement were available from Data about the prevalence of unemployment and early retire-
ment were available from 151 (99.3%) and 66 (43.5%) studies published from 1981 to 2021,
respectively. From the results of the quality assessment, 59 (38.3%) studies were classified as
high quality. The minimum data set underlying the results is reported in the S2 Table.
The pooled overall effect size for unemployment was 35.6% (95% CI 32.8–38.4; I
2
= 99.31).
Seven (4.6%) studies resulted in effect sizes greater than 70.0%, with 5 (71.4%) published more
than a decade ago [28–34]. Four (2.6%) studies registered effect sizes smaller than 5.0%, of
which three were published between 2016 and 2019 [35–38]. Estimates of the prevalence of
unemployment ranged from 1.4% to 80.0% (median: 41.1%). The result of the Trim and Fill
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analysis (p < 0.001), Egger’s linear regression test (p < 0.004), and the visual inspection of the
funnel plot (S1 Fig) confirmed the possibility of publication bias.
The prevalence of unemployment varied according to the year of publication (p <0.001)
and there was a statistically significant decrease in the prevalence of unemployment over
time (p = 0.042) (Table 1,Fig 2). Globally, the proportion of unemployed subjects with MS
remained relatively stable from 1981 to 2010, after which it decreased. The use of DMDs was
associated with a reduced prevalence of unemployment (p = 0.021) (Fig 3), especially among
those with a longer disease duration (p = 0.035). The decrease in unemployment prevalence
over the years was more pronounced among younger individuals and those with a higher
EDSS (p = 0.024 and p = 0.010, respectively).
Data concerning the prevalence of unemployment among workers with MS were reported
from 29 countries. Austria [39], Czech Republic [40], Greece [41], Hungary [42], Kuwait [43],
Portugal [44], Russia [45], and Argentina [46] each contributed with one (0.6%) publication
reporting the prevalence of unemployed subjects. Ireland [47,48], Israel [49,50], Poland [51,
52], and Saudi Arabia [53,54] contributed with two (1.3%) studies each while Brazil [55–57],
Iran [58–60], Holland [61–63], Norway [11,64,65], and Switzerland [66–68] contributed with
Table 1. Effect sizes of prevalence of unemployment by year.
Effect size 95% CI Sample size
1981 0.44 0.32–0.57 454
1982 0.42 0.35–0.49 198
1985 0.74 0.69–0.79 312
1986 0.79 0.77–0.82 949
1987 0.12 0.09–0.15 439
1989 0.21 0.18–0.25 508
1991 0.50 0.46–0.54 551
1992 0.18 0.00–0.86 805
1996 0.20 0.14–0.28 532
1997 0.09 0.07–0.12 697
2001 0.51 0.39–0.62 3884
2003 0.46 0.07–0.91 945
2004 0.58 0.54–0.62 2149
2005 0.59 0.55–0.62 739
2006 0.52 0.43–0.61 16816
2007 0.33 0.10–0.67 1920
2008 0.49 0.33–0.64 17455
2009 0.23 0.08–0.48 1101
2010 0.42 0.13–0.77 11595
2011 0.27 0.11–0.50 2773
2012 0.28 0.16–0.45 12813
2013 0.34 0.29–0.41 12816
2014 0.29 0.21–0.39 14090
2015 0.46 0.29–0.64 14922
2016 0.23 0.13–0.37 4031
2017 0.37 0.29–0.45 27069
2018 0.28 0.19–0.38 5823
2019 0.27 0.19–0.37 15565
2020 0.28 0.17–0.41 7960
2021 0.41 0.30–0.52 5136
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three (2.0%) studies each. Most of the data on the estimates of the prevalence comes from Can-
ada (four, 2.6%) [69–72], Denmark (five, 3.3%) [73–77], Belgium (five, 3.3%) [35,78–81],
France (five, 3.3%) [82–86], Spain (five, 3.3%) [8,28,33,87,88], Sweden (seven, 4.6%) [89–
95], Germany (eight, 5.3%) [96–103], Australia (eight, 5.9%) [38,104–110], Italy (nine, 5.9%)
[111–119], United Kingdom (nine, 5.9%) [29,32,120–126] and the United States of America
(50, 32.9%) [14,15,30,31,34,36,37,127–169]. Five (3.3%) studies were conducted in more
than one nation [170–173]. Ireland (8.2%; 95% CI 4.2–15.3) [47,48], Greece (9.8%; 95% CI
6.4–14.7) [40] and Argentina (15.5%; 95% CI 12.4–19.2) [45,46] had the best estimates of
effect size while Holland (62.8%; 95% CI 60.6–65.0) [61–63], Austria (59.6%; 95% CI 56.5–
62.5) [39] and Portugal (46.6%; 95% CI 42.3–51.1) [44] accounted for the highest values. There
was a statistically significant difference between the effect sizes of countries (p < 0.001) (Fig 4).
From the perspective of continents, 73 (48.0%) studies were performed in Europe, 54 (35.5%)
in North America, eight (5.2%) in Asia, eight (5.2%) in Oceania, four (2.6%) in South America
and three (2.0%) in Europe and North America. The effect sizes varied in a statistically signifi-
cant way according to continents (p = 0.04), being North America the continent with the high-
est pooled prevalence estimate (39.1%; 95% CI 35.1–43.3). Data were provided mostly from
high-income countries (142, 93.4%). Upper-middle economy countries and lower-middle
economy countries accounted for six (3.9%) and three (2.0%) studies, respectively. The esti-
mates of the prevalence of unemployment significantly varied according to the economic crite-
ria (p = 0.04), being the highest estimate found in high-income economy countries (36.2%;
Fig 2. Meta-regression (random-effects model) of the prevalence of unemployment according to time.
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95% CI 33.3–39.1). Among countries with a high prevalence of MS, a higher educational level
was associated with higher proportions of unemployed MS subjects (p = 0.024). In parallel,
psychiatric disorders were associated with greater effect sizes of the prevalence of unemploy-
ment in Europe (p = 0.046). There was no statistical difference between countries classified
according to the prevalence of MS.
The pooled overall effect size for early retirement was 17.2% (95% CI 14.6–20.2; I
2
= 99.13).
In three (4.5%) studies from 2006, 2018, and 2021, the prevalence of early retirement was over
50% [74,122,174]. In the most recent studies, the subjects’ sample largely comprised patients
who attended rehabilitation clinics or were of advanced age. Five (7.5%) studies accounted for
the lowest estimates of early retirement. All were published in 2017 and were conducted in
Europe [63,66,86,97,120]. There was a significant publication bias demonstrated in the fun-
nel plot (S2 Fig), the Trim and Fill analysis (p < 0.001), and the Egger’s linear regression test
(p < 0.004).
More than half of the studies included (34, 50.7%) were published in the last seven years
(Table 2). Estimates of the prevalence of early retirement ranged from 1.7% to 64.0% (median:
19.2%). Only seven (31.8%) estimates obtained from studies that were published before 2010
were below the overall effect size in comparison to 27 (60.0%) estimates extracted from data
published between 2010 and 2021 (p = 0.039). Nevertheless, there was no significant difference
between the estimates of the prevalence of early retirement over time on meta-regression anal-
ysis (p = 0.082) (S3 Fig), except for the subgroup of younger subjects (p = 0.010) and higher
Fig 3. Meta-regression (random-effects model) of the prevalence of unemployment according to the use of DMDs (%).
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EDSS (p <0.001). High EDSS and progressive MS phenotype were covariates directly associ-
ated with early retirement among younger individuals (p = 0.005 and p = 0.017, respectively).
Among those with longer disease duration, the EDSS was a covariate associated with early
retirement while among those with higher EDSS, the presence of psychiatric symptoms was
the strongest determinant to the observed effect size (p = 0.007).
The studies that described the early retirement prevalence were performed in 25 countries:
The United States of America (19, 28.3%) [14,31,36,37,129–132,136,140,143–146,150,151,
160,167,168] Germany (five, 7.5%) [97,99,100,102,103] United Kingdom (five, 7.5%) [29,
Fig 4. Prevalence of unemployment (%) according to geographical location.
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32,120,122,123], Denmark (four, 6.0%) [73–76], Australia (three, 4.5%) [108,109,175], Bel-
gium (three, 4.5%) [35,79,80], Holland (three, 4.5%) [61,63,176], Italy (three, 4.5%) [111 –
113], Ireland (two, 3.0%) [47,48], Spain (two, 3.0%) [8,28], Sweden (two, 3.0%) [90,91], Swit-
zerland (two, 3.0%) [66,67], Argentina (one, 1.5%) [46], Austria (one, 1.5%) [39], Brazil (one,
1.5%) [55], the Czech Republic (one, 1.5%) [40], France (one, 1.5%) [85], Greece (one, 1.5%)
[41], Hungary (one, 1.5%) [42], Iran (one, 1.5%) [59], Israel (one, 1.5%) [49], Russia (one,
1.5%) [45], Norway (one, 1.5%) [65], and Portugal (one, 1.5%) [44]. One (1.5%) study was
multinational [170]. The overall pooled estimate of the prevalence of early retirement was
17.2% (CI 95% 14.6–20.2, I
2
= 99.13). The three countries with the highest effect sizes were the
Czech Republic (48.9%; 95% CI 45.7–52.2) [40], Austria (44.4%; 95% CI 41.4–47.5) [39] and
Brazil (37.1%; 95% CI 30.9–43.9) [56] while Russia (1.5%; 95% CI 0.4–4.5) [45], France (3.2%;
95% CI 1.9–5.5) [86] and Iran (3.7%; 95% CI 2.0–6.5) [59] had the lowest proportions (Fig 5).
The geographical distribution of the studies is uneven, with Europe (39, 58.2%) and North
America (18, 26.9%) accounting for most of the publications. Asia, Oceania, and South Amer-
ica were responsible for three (4.5%) studies each. One study (1.5%) involved both the Ameri-
can and European continents. We couldn’t find any study from Africa. When classifying the
countries based on the income criteria, the studies were performed in 62 (92.5%) high-income
countries, four (6.0%) upper-middle-income country and only one (1.5%) in a lower-middle-
income country. Comparing the effects sizes based on the geographic criteria, there was a sub-
stantial difference between countries (p < 0.001) and income-based classified countries (p <
0.001), but no statistically significant difference was found among continents (p < 0.478). We
didn’t find any statistical difference between countries classified according to the prevalence of
MS but psychiatric disorders were associated with higher estimates of the prevalence of early
retirement in countries with high MS prevalence (p = 0.022).
Motor symptoms, gender, cognitive impairment, and fatigue were not associated with any
of the outcomes. The sensitivity analysis demonstrated the robustness of our results. Excluding
Table 2. Effect sizes of early retirement by year.
Effect size 95% CI Sample size
1981 0.14 0.01–0.72 454
1989 0.15 0.12–0.18 508
1991 0.13 0.10–0.16 551
1992 0.20 0.11–0.34 814
2001 0.33 0.32–0.35 2793
2006 0.37 0.34–0.41 16650
2008 0.04 0.03–0.41 1942
2009 0.15 0.05–0.34 851
2010 0.29 0.28–0.31 2538
2012 0.30 0.09–0.65 11973
2013 0.21 0.06–0.52 9200
2014 0.15 0.07–0.29 3550
2015 0.07 0.06–0.08 4816
2016 0.19 0.09–0.34 2169
2017 0.06 0.03–0.11 13786
2018 0.17 0.09–0.29 2036
2019 0.12 0.07–0.18 5725
2020 0.13 0.05–0.28 1574
2021 0.63 0.58–0.68 417
https://doi.org/10.1371/journal.pone.0272156.t002
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low-quality studies and outliers detected in the funnel plot didn’t show different results for
both outcomes.
Discussion
To the best of our knowledge, this is the first systematic review with a meta-analysis describing
the prevalence of unemployment and early retirement in the population of PwMS. The find-
ings confirm the significant negative impact of MS on the occupational environment and the
consequently elevated proportions of individuals unemployed and early retired. According to
the World Bank Data, between 1991 and 2021, the worldwide unemployment rate ranged
from 4.80–6.47%, indicating that workers with MS exceed up to five times the global average
estimate [177]. The high prevalence of MS in the world, the manifestation of symptoms at
working age, and the presence of several potentially disabling symptoms justify these findings
and the particularity of MS at the public health level [66,178]. These eloquent numbers also
give an idea about the effectiveness of the set of actions implemented at the individual and
Fig 5. Prevalence of early retirement (%) according to geographical location.
https://doi.org/10.1371/journal.pone.0272156.g005
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collective level until now, since unemployment and early retirement can be considered senti-
nels of a spectrum of MS-related outcomes. The diversity of symptoms leaves PwMS vulnera-
ble to a wide variety of barriers at work. In this context, screening PwMS for working
difficulties may also prevent or at least postpone unfavourable occupational outcomes. Some
questionnaires have already been designed and validated as potential predictors of occupa-
tional status change [86]. Moreover, an active investigation of the quality of the integration
between worker and work by neurologists and occupational physicians may favour the early
recognition of the difficulties and demands of PwMS in the workplace.
We found that there was a decrease in the proportion of workers with MS unemployed over
time. This finding has been observed mainly in the last ten years, a period when there was a
significant increase in the availability of new DMDs [179]. Indeed, we observed that the use of
DMDs was associated with a decrease in the prevalence of unemployment over the years,
which is in line with some preliminary evidence [3]. The possibility to control the disease and
slow down its progression naturally affects the working capacity of the patient with MS [180].
Consistent with these results, we also found that the association was particularly significant in
populations with a high mean EDSS and longer disease duration, important risk factors that
are well known to be associated with worse occupational outcomes and that are thought to be
extremely influenced by the clinical efficacy of the new MS drugs [13,118,151]. The decrease
in the prevalence of unemployment was also particularly important among young workers,
possibly due to their greater capacity to readjust and engage in new forms of work [174]. Even
so, it should be mentioned that the overall observed drop was discrete and can be interpreted
as disproportionate to the therapeutic advances in MS and to the time elapsed since the first
study reporting the prevalence of unemployment was published. Possible explanations for this
lie in the lack of efficient and validated public strategies to promote job retention in workers
with MS and the lack of involvement of the occupational physician in this process. Forty per-
cent of patients did not even communicate the diagnosis of MS to their occupational physician
[181]. Many of the reasons for work withdrawal are associated with the workplace and could
be potentially managed by occupational health multidisciplinary teams [44,84,162]. In addi-
tion, there is a lack of evidence addressing the reintegration of the worker with MS into the
workforce so that nowadays unemployment usually means an irreversible outcome [181], even
though almost one-third feel they are still able to work [84]. Regarding specifically early retire-
ment, the results also reinforce the role of MS therapeutic improvement over the years [162].
In addition, aggressive disease characteristics were associated with worse effect estimates of
early retirement, which is also consistent with the findings of previous results [182,183].
We were able include a large number of countries in our analysis. There was a remarkable
diversity of estimates of the prevalence of unemployment and early retirement according to
the geographical classification. The wide diversity of illness-related unemployment and early
retirement across different countries, even from the same continent, is supported by the
pre-existing literature for other chronic diseases [184,185] and supports the argument that
occupational outcomes of PwMS are far from depending exclusively on their individual char-
acteristics and are also directly influenced by the public health context. Several national char-
acteristics may explain the differences between the results, so that, based on the global analysis,
future studies should be dedicated to better understanding the approach of MS from the occu-
pational viewpoint that justifies the effect sizes of each country. The accurate interpretation of
every single result must consider the complexity and particularity of each country’s socio-eco-
nomic characteristics. A lower unemployment rate at a national level may be associated with
larger effects of poor health on not entering employment [162]. Moreover, countries with a
high prevalence of unemployment in the general population may also influence the outcomes
of PwMS. A general high level of education or a country where there is high competitiveness
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for highly qualified jobs can explain why some estimates of the prevalence of unemployment
are high in Nord America or high-income economy countries. Psychiatric illness may be the
most influential clinical manifestation of MS responsible for patients leaving the workforce in
countries and continents with a high MS prevalence. It has already been demonstrated that
psychiatric illnesses play an important role in the exit of paid employment in Europe [186,
187]. Our study provides preliminary evidence concerning the observation that a higher edu-
cational level is associated with greater estimates of the prevalence of unemployment among
countries with a high MS prevalence. This finding must be interpreted with caution since fac-
tors related to the country’s social, economic and cultural context can have influenced it.
The analyses were made on a large number of subjects from many countries, which
strengthens the representativeness of our sample and the quality of the evidence found. We
also adopted strict inclusion and exclusion criteria that resulted in a significant proportion of
studies with low potential for methodological bias. Besides, our analysis did not include a large
number of articles with a high risk of methodological bias. To our knowledge, not only is it the
first systematic review with meta-analysis dedicated to analyzing the prevalence of unemploy-
ment and early retirement in PwMS, but it is also the first systematic review with meta-analysis
to analyze these outcomes in a non-communicable neurological disorder. Our study has also
some limitations that need to be acknowledged to allow an accurate interpretation of the
results. Although they are relatively simple variables to be measured, by aggregating different
types of studies, we could not standardize the way the studies addressed the outcomes, which
may be responsible for some kind of methodological bias and the significant heterogeneity. As
most of the studies had a cross-sectional design, it is not possible to draw definitive causal rela-
tions between the occupational outcomes and MS. We have seen an imbalance in the availabil-
ity of literature between countries and, therefore, our results might not be representative for
some countries or regions. Even though, our study provides a reasonable estimate for coun-
tries included in this review, in particular high-income countries. Our study did not include
other covariates that could be related to the outcomes. However, our decision was based on
which variables were more reported in all studies, preventing the inclusion of insufficient data
and the generation of non-significant and unrepresentative data. Finally, we didn’t calculate a
score of agreement between the researchers that were responsible for the screening and the
selection of articles.
Conclusions
This systematic review shows that unemployment and early retirement due to MS remain
highly prevalent, despite a slight decline in the last decade. This study adds precision and accu-
racy to the prevalence of unemployment and early retirement in PwMS reported by many pre-
vious studies performed in many different countries. Prospective and multicentre cohort
studies are encouraged to deepen the knowledge in this field, especially in under-represented
countries. The findings should spur more effective public health strategies capable of encom-
passing the occupational context in which PwMS are inserted to promote their occupational
outcomes. Collaboration among clinicians, neurologists, occupational physicians, employers,
researchers, and policymakers is urgently required to prevent and mitigate unemployment
and early retirement among PwMS.
Supporting information
S1 File. PRISMA checklist.
(DOCX)
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S1 Table. Detailed search strategy in PubMed, Scopus, SciVerse Science Direct and Web of
Science.
(DOCX)
S2 Table. Minimal data set underlying the results and full description of the articles
included in the review. NA = Not Applicable. �The JBI Critical Appraisal Checklist for Studies
Reporting Prevalence Data was used for the risk of bias assessment, with more stars equalling
lower risk.
(DOCX)
S1 Fig. Funnel plot of studies included in the analysis (unemployment).
(DOCX)
S2 Fig. Funnel plot of studies included in the analysis (early retirement).
(DOCX)
S3 Fig. Meta-regression (random-effects model) of the prevalence of early retirement
according to time.
(DOCX)
Author Contributions
Conceptualization: Bruno Kusznir Vitturi, Alborz Rahmani, Guglielmo Dini, Paolo Durando.
Data curation: Bruno Kusznir Vitturi, Alborz Rahmani, Alfredo Montecucco.
Formal analysis: Bruno Kusznir Vitturi, Alborz Rahmani.
Funding acquisition: Matilde Inglese, Paolo Durando.
Investigation: Bruno Kusznir Vitturi, Alborz Rahmani, Guglielmo Dini, Alfredo Montecucco.
Methodology: Bruno Kusznir Vitturi, Alborz Rahmani, Guglielmo Dini, Alfredo Montecucco.
Project administration: Bruno Kusznir Vitturi, Paolo Durando.
Resources: Nicoletta Debarbieri, Paolo Bandiera, Mario Alberto Battaglia, Tommaso Mana-
corda, Benedetta Persechino, Giuliana Buresti.
Supervision: Paolo Durando.
Writing – original draft: Bruno Kusznir Vitturi.
Writing – review & editing: Bruno Kusznir Vitturi, Alborz Rahmani, Guglielmo Dini,
Michela Ponzio, Matilde Inglese, Paolo Durando.
References
1. Filippi M, Bar-Or A, Piehl F, et al. Multiple sclerosis. Nat Rev Dis Prim. 2018; 4. https://doi.org/10.1038/
s41572-018-0041-4 PMID: 30410033
2. Leray E, Moreau T, Fromont A, Edan G. Epidemiology of multiple sclerosis. Rev Neurol (Paris). 2016;
172(1):3–13. https://doi.org/10.1016/j.neurol.2015.10.006 PMID: 26718593
3. Dobson R, Giovannoni G. Multiple sclerosis—a review. Eur J Neurol. 2019; 26(1):27–40. https://doi.
org/10.1111/ene.13819 PMID: 30300457
4. Rumrill PD, Roessler RT, Li J, Daly K, Leslie M. The employment concerns of Americans with multiple
sclerosis: Perspectives from a national sample. Work. 2015; 52(4):735–748. https://doi.org/10.3233/
WOR-152201 PMID: 26599671
5. Lorefice L, Fenu G, Frau J, Coghe G, Marrosu MG, Cocco E. The impact of visible and invisible symp-
toms on employment status, work and social functioning in Multiple Sclerosis. Work. 2018; 60(2):263–
270. https://doi.org/10.3233/WOR-182682 PMID: 29400690
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 15 / 25

6. Forslin M, Fink K, Hammar U, von Koch L, Johansson S. Predictors for Employment Status in People
With Multiple Sclerosis: A 10-Year Longitudinal Observational Study. Arch Phys Med Rehabil. 2018;
99(8):1483–1490. https://doi.org/10.1016/j.apmr.2017.12.028 PMID: 29407519
7. Li J, Roessler RT, Rumrill PD Jr., Ahmed ER. Factors Influencing Job Satisfaction for Employed Adults
With Multiple Sclerosis. Rehabil Couns Bull. 2017; 61(1):28–40. https://doi.org/10.1177/
0034355216662616
8. Maurino J, Martı
´nez-Gine
´s ML, Garcı
´a-Domı
´nguez JM, et al. Workplace difficulties, health-related
quality of life, and perception of stigma from the perspective of patients with Multiple Sclerosis. Mult
Scler Relat Disord. 2020; 41:102046. https://doi.org/10.1016/j.msard.2020.102046 PMID: 32179482
9. Abbas D, Gehanno J-F, Caillard J-F, Beuret-Blanquart F. [Characteristics of patients suffering from
multiple sclerosis according to professional situation]. Ann Readapt Med Phys Rev Sci la Soc Fr
Reeduc Fonct Readapt Med Phys. 2008; 51(5):386–393. https://doi.org/10.1016/j.annrmp.2008.03.
004 PMID: 18565608
10. Carrieri L, Sgaramella TM, Bortolon F, et al. Determinants of on-the-job-barriers in employed persons
with multiple sclerosis: the role of disability severity and cognitive indices. Work. 2014; 47(4):509–520.
https://doi.org/10.3233/WOR-131623 PMID: 23531588
11. Bøe Lunde HM, Telstad W, Grytten N, et al. Employment among Patients with Multiple Sclerosis-A
Population Study. PLoS One. 2014; 9(7):e103317. https://doi.org/10.1371/journal.pone.0103317
PMID: 25054972
12. Conradsson DM, Forslin M, Fink K, Johansson U, von Koch L, Johansson S. Employment status of
people with multiple sclerosis in relation to 10-year changes in functioning and perceived impact of the
disease. Mult Scler Relat Disord. 2020; 46:102519. https://doi.org/10.1016/j.msard.2020.102519
PMID: 32977076
13. Krause I, Kern S, Horntrich A, Ziemssen T. Employment status in multiple sclerosis: impact of dis-
ease-specific and non-disease-specific factors. Mult Scler. 2013; 19(13):1792–1799. https://doi.org/
10.1177/1352458513485655 PMID: 23635910
14. Julian LJ, Vella L, Vollmer T, Hadjimichael O, Mohr DC. Employment in multiple sclerosis. Exiting and
re-entering the work force. J Neurol. 2008; 255(9):1354–1360. https://doi.org/10.1007/s00415-008-
0910-y PMID: 18677639
15. Pack TG, Szirony GM, Kushner JD, Bellaw JR. Quality of life and employment in persons with multiple
sclerosis. Work. 2014; 49(2):281–287. https://doi.org/10.3233/WOR-131711 PMID: 24004768
16. Neusser S, Biermann J, Lux G, Wasem J, Reissner V, Neumann A. Economic burden of multiple scle-
rosis to the social insurance system in Germany. J Public Heal. 2018; 26(3):271–278. https://doi.org/
10.1007/s10389-017-0871-7
17. Battaglia M, Kobelt G, Ponzio M, Berg J, Capsa D, Dale
´n J. New insights into the burden and costs of
multiple sclerosis in Europe: Results for Italy. Mult Scler J. 2017; 23:104–116. https://doi.org/10.1177/
1352458517708176 PMID: 28643600
18. Murley C, Tinghog P, Karampampa K, Hillert J, Alexanderson K, Friberg E. Types of working-life
sequences among people recently diagnosed with multiple sclerosis in Sweden: a nationwide register-
based cohort study. BMJ Open. 2020; 10(12). https://doi.org/10.1136/bmjopen-2020-039228 PMID:
33376161
19. Bergamaschi R, Montomoli C, Candeloro E, et al. Bayesian mapping of multiple sclerosis prevalence
in the province of Pavia, northern Italy. J Neurol Sci. 2006; 244(1):127–131. https://doi.org/10.1016/j.
jns.2006.01.013 PMID: 16527310
20. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for
reporting systematic reviews. BMJ. 2021; 372:n71. https://doi.org/10.1136/bmj.n71 PMID: 33782057
21. Munn Z, Moola S, Lisy K, Riitano D, Tufanaru C. Methodological guidance for systematic reviews of
observational epidemiological studies reporting prevalence and cumulative incidence data. Int J Evid
Based Healthc. 2015; 13(3):147–153. https://doi.org/10.1097/XEB.0000000000000054 PMID:
26317388
22. https://blogs.worldbank.org/opendata/new-world-bank-country-classifications-income-level-2021-
2022. Access on 06/12/2021.
23. Joanna Briggs Institute Checklists. [Cited 6 December 2021]. https://jbi.global/sites/default/files/2019-
05/JBI_Critical_Appraisal-Checklist_for_Prevalence_Studies2017_0.pdf.
24. Atlas of MS. [Cited 6 December 2021] https://www.atlasofms.org/map/global/epidemiology/number-
of-people-with-ms.
25. Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002; 21
(11):1539–1558. https://doi.org/10.1002/sim.1186 PMID: 12111919
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 16 / 25

26. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical
test. BMJ. 1997; 315(7109):629–634. https://doi.org/10.1136/bmj.315.7109.629 PMID: 9310563
27. Duval S, Tweedie R. Trim and Fill: A Simple Funnel-Plot-Based Method of Testing and Adjusting for
Publication Bias in Meta-Analysis. Biometrics. 2000; 56(2):455–463. https://doi.org/10.1111/j.0006-
341x.2000.00455.x PMID: 10877304
28. Kobelt G, Berg J, Lindgren P, et al. Costs and quality of life of multiple sclerosis in Spain. Eur J Heal
Econ HEPAC Heal Econ Prev care. 2006; 7 Suppl 2:S65–74. https://doi.org/10.1007/s10198-006-
0381-y PMID: 17310340
29. Kobelt G, Berg J, Lindgren P, Kerrigan J, Russell N, Nixon R. Costs and quality of life of multiple sclero-
sis in the United Kingdom. Eur J Heal Econ HEPAC Heal Econ Prev care. 2006; 7 Suppl 2:S96–104.
https://doi.org/10.1007/s10198-006-0380-z PMID: 17310341
30. Chiu CY, Tansey TN, Chan F, Strauser D, Frain MP, Arora S. Effect of Rehabilitation Technology Ser-
vices on Vocational Rehabilitation Outcomes of Individuals With Multiple Sclerosis. Rehabil Res POL-
ICY Educ. 2015; 29(2):183–192. https://doi.org/10.1891/2168-6653.29.2.183
31. Larocca N, Kalb R, Scheinberg L, Kendall P. Factors associated with unemployment of patients with
multiple sclerosis. J Chronic Dis. 1985; 38(2):203–210. https://doi.org/10.1016/0021-9681(85)90093-1
PMID: 3156140
32. Riazi A, Hobart JC, Fitzpatrick R, Freeman JA, Thompson AJ. Socio-demographic variables are lim-
ited predictors of health status in multiple sclerosis. J Neurol. 2003; 250(9):1088–1093. https://doi.org/
10.1007/s00415-003-0160-y PMID: 14504971
33. Garcia-Dominguez JM, Maurino J, Martinez-Gines ML, et al. Economic burden of multiple sclerosis in
a population with low physical disability. BMC Public Health. 2019; 19. https://doi.org/10.1186/s12889-
019-6907-x PMID: 31109317
34. Kornblith AB, La Rocca NG, Baum HM. Employment in individuals with multiple sclerosis. Int J Rehabil
Res Int Zeitschrift fur Rehabil Rev Int Rech Readapt. 1986; 9(2):155–165. https://doi.org/10.1097/
00004356-198606000-00006 PMID: 3771036
35. D’hooghe MB, Haentjens P, Van Remoortel A, De Keyser J, Nagels G. Self-reported levels of educa-
tion and disability progression in multiple sclerosis. Acta Neurol Scand. 2016; 134(6):414–419. https://
doi.org/10.1111/ane.12555 PMID: 27761897
36. Catanzaro M, Weinert C. Economic status of families living with multiple sclerosis. Int J Rehabil Res
Int Zeitschrift fur Rehabil Rev Int Rech Readapt. 1992; 15(3):209–218. https://doi.org/10.1097/
00004356-199209000-00004 PMID: 1428386
37. Chiu C, Park M, Hoffman T, Campbell M, Bishop M. Descriptive analysis of free-text commentson
healthcare priorities and experiences in a national sample of people with multiple sclerosis. Mult
Scler Relat Disord. 2019; 34:141–149. https://doi.org/10.1016/j.msard.2019.06.023 PMID:
31277032
38. Chen J, Taylor B, Palmer AJ, et al. Estimating MS-related work productivity loss and factors associated
with work productivity loss in a representative Australian sample of people with multiple sclerosis. Mult
Scler. 2019; 25(7):994–1004. https://doi.org/10.1177/1352458518781971 PMID: 29911469
39. Kobelt G, Berg J, Lindgren P, et al. Costs and quality of life of multiple sclerosis in Austria. Eur J Heal
Econ HEPAC Heal Econ Prev care. 2006; 7 Suppl 2:S14–23. https://doi.org/10.1007/s10198-006-
0382-x PMID: 17310339
40. Blahova Dusankova J, Kalincik T, Dolezal T, Kobelt G, Havrdova E. Cost of multiple sclerosis in the
Czech Republic: the COMS study. Mult Scler. 2012; 18(5):662–668. https://doi.org/10.1177/
1352458511424422 PMID: 21965424
41. Hadjigeorgiou G, Dardiotis E, Tsivgoulis G, et al. Observational study assessing demographic, eco-
nomic and clinical factors associated with access and utilization of health care services of patients with
multiple sclerosis under treatment with interferon beta-1b (EXTAVIA). PLoS One. 2014; 9(11):
e113933. https://doi.org/10.1371/journal.pone.0113933 PMID: 25419842
42. Pe
´ntek M, Kobelt G, Berg J, et al. New insights into the burden and costs of multiple sclerosis in
Europe: Results for Hungary. Mult Scler. 2017; 23(2_suppl):91–103. https://doi.org/10.1177/
1352458517708142 PMID: 28643591
43. Al Khader H, Emran B, Al Sulaimi M, et al. Estimating the prevalence of cognition and mental health
among multiple sclerosis patients: A population-based cross-sectional study. Mult Scler Relat Disord.
2019; 36:101391. https://doi.org/10.1016/j.msard.2019.101391 PMID: 31557677
44. Sa MJ, Kobelt G, Berg J, Capsa D, Dalen J; European Multiple Sclerosis Platform. New insights into
the burden and costs of multiple sclerosis in Europe: Results for Portugal. Mult Scler J. 2017; 23:143–
154. https://doi.org/10.1177/1352458517708667 PMID: 28643585
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 17 / 25

45. Boyko A, Kobelt G, Berg J, et al. New insights into the burden and costs of multiple sclerosis in Europe:
Results for Russia. Mult Scler. 2017; 23(2_suppl):155–165. https://doi.org/10.1177/
1352458517708668 PMID: 28643590
46. Carnero Contentti E, Pettinicchi JP, Lo
´pez PA, et al. Access and unmet needs to multiple sclerosis
care in a cohort of Argentinean patients. Mult Scler Relat Disord. 2019; 33:88–93. https://doi.org/10.
1016/j.msard.2019.05.024 PMID: 31174044
47. Carney P, O’Boyle D, Larkin A, McGuigan C, O’Rourke K. Societal costs of multiple sclerosis in Ire-
land. J Med Econ. 2018; 21(5):425–437. https://doi.org/10.1080/13696998.2018.1427100 PMID:
29320900
48. Fogarty E, Walsh C, McGuigan C, Tubridy N, Barry M. Direct and indirect economic consequences of
multiple sclerosis in Ireland. Appl Health Econ Health Policy. 2014; 12(6):635–645. https://doi.org/10.
1007/s40258-014-0128-3 PMID: 25227118
49. Miller A, Dishon S. Health-related quality of life in multiple sclerosis: The impact of disability, gender
and employment status. Qual life Res an Int J Qual life Asp Treat care Rehabil. 2006; 15(2):259–271.
https://doi.org/10.1007/s11136-005-0891-6 PMID: 16468081
50. Rozin R, Schiff Y, Cooper G, Kahana E. Vocational rehabilitation of multiple sclerosis (MS) patients I.
Analysis of clinical and demographic factors first in a series of articles. Disabil Rehabil. 1982; 4(2):75–
79. https://doi.org/10.3109/09638288209166882 PMID: 7174216
51. Rzepinski L, Zawadka-Kunikowska M, Kucharczuk J, Newton J, Zalewski P. New insights into the
socio-economic aspects of multiple sclerosis in a cohort of Polish patients. Ann Agric Environ Med.
2021; 28(1):99–106. https://doi.org/10.26444/aaem/117962 PMID: 33775074
52. Selmaj K, Kobelt G, Berg J, Orlewska E, Capsa D, Dale
´n J. New insights into the burden and costs of
multiple sclerosis in Europe: Results for Poland. Mult Scler. 2017; 23(2_suppl):130–142. https://doi.
org/10.1177/1352458517708666 PMID: 28643586
53. Alhussain H, Aldayel AA, Alenazi A, Alowain F. Multiple Sclerosis Patients in Saudi Arabia: Prevalence
of Depression and its Extent of Severity. Cureus. 2020; 12(2):e7005. https://doi.org/10.7759/cureus.
7005 PMID: 32206469
54. AlZahrani AS, Alshamrani FJ, Al-Khamis FA, et al. Association of acute stress with multiple sclerosis
onset and relapse in Saudi Arabia. Saudi Med J. 2019; 40(4):372–378. https://doi.org/10.15537/smj.
2019.4.24010 PMID: 30957131
55. da Silva NL, Takemoto MLS, Damasceno A, et al. Cost analysis of multiple sclerosis in Brazil: a cross-
sectional multicenter study. BMC Health Serv Res. 2016; 16. https://doi.org/10.1186/s12913-016-
1352-3 PMID: 27009599
56. Estrutti CM, Cardoso GSME, de Novais MAP, de Oliveira EML, Bichuetti DB. Employment status of
people diagnosed with multiple sclerosis in Brazil. Arq Neuropsiquiatr. 2019; 77(5):341–345. https://
doi.org/10.1590/0004-282X20190051 PMID: 31188998
57. Kobelt G, Teich V, Cavalcanti M, Canzonieri AM. Burden and cost of multiple sclerosis in Brazil. PLoS
One. 2019; 14(1):e0208837. https://doi.org/10.1371/journal.pone.0208837 PMID: 30673707
58. Farnoush R, Sahebolzamani M, Aliloo L, Rahmani A. Educational, psycho mental and socio economi-
cal needs of an iranian cohort with multiple sclerosis. Oman Med J. 2010; 25(1):22–25. https://doi.org/
10.5001/omj.2010.6 PMID: 22125693
59. Imani A, Gharibi F, Khezri A, Joudyian N, Dalal K. Economic costs incurred by the patients with multi-
ple sclerosis at different levels of the disease: a cross-sectional study in Northwest Iran. BMC Neurol.
2020; 20(1):205. https://doi.org/10.1186/s12883-020-01790-5 PMID: 32446303
60. Kalantari S, Karbakhsh M, Kamiab Z, Kalantari Z, Sahraian MA. Perceived Social Stigma in
Patients with Multiple Sclerosis: A Study from Iran. Acta Neurol Taiwan. 2018; 27(1):1–8. PMID:
30315555
61. Kobelt G, Berg J, Lindgren P, et al. Costs and quality of life in multiple sclerosis in The Netherlands.
Eur J Heal Econ HEPAC Heal Econ Prev care. 2006; 7 Suppl 2:S55–64. https://doi.org/10.1007/
s10198-006-0378-6 PMID: 17310343
62. van der Hiele K, van Gorp DAMAM, van Egmond EEAEA, et al. Self-reported occupational functioning
in persons with relapsing-remitting multiple sclerosis: Does personality matter? J Neurol Sci. 2021;
427:117561. https://doi.org/10.1016/j.jns.2021.117561 PMID: 34216973
63. Uitdehaag B, Kobelt G, Berg J, Capsa D, Dale
´n J. New insights into the burden and costs of multiple
sclerosis in Europe: Results for the Netherlands. Mult Scler. 2017; 23(2_suppl):117–129. https://doi.
org/10.1177/1352458517708663 PMID: 28643595
64. Midgard R, Riise T, Nyland H. Impairment, disability and handicap in multiple sclerosis—A cross-sec-
tional study in an incident cohort in More and Romsdal County, Norway. J Neurol. 1996; 243(4):337–
344. https://doi.org/10.1007/BF00868408 PMID: 8965107
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 18 / 25

65. Svendsen B, Grytten N, BøL, Aarseth H, Smedal T, Myhr K-M. The economic impact of multiple scle-
rosis to the patients and their families in Norway. Eur J Heal Econ HEPAC Heal Econ Prev care. 2018;
19(9):1243–1257. https://doi.org/10.1007/s10198-018-0971-5 PMID: 29680926
66. Calabrese P, Kobelt G, Berg J, Capsa D, Eriksson J. New insights into the burden and costs of multiple
sclerosis in Europe: Results for Switzerland. Mult Scler. 2017; 23(2_suppl):192–203. https://doi.org/
10.1177/1352458517708685 PMID: 28643596
67. Kobelt G, Berg J, Lindgren P, Gerfin A, Lutz J. Costs and quality of life of multiple sclerosis in Switzer-
land. Eur J Heal Econ HEPAC Heal Econ Prev care. 2006; 7 Suppl 2:S86–95. https://doi.org/10.1007/
s10198-006-0383-9 PMID: 17310338
68. Lehmann AI, Rodgers S, Kamm CP, et al. Factors associated with employment and expected work
retention among persons with multiple sclerosis: findings of a cross-sectional citizen science study. J
Neurol. 2020; 267(10):3069–3082. https://doi.org/10.1007/s00415-020-09973-3 PMID: 32529580
69. Aronson KJ. Quality of life among persons with multiple sclerosis and their caregivers. Neurology.
1997; 48(1):74–80. https://doi.org/10.1212/wnl.48.1.74 PMID: 9008497
70. Hategeka C, Traboulsee AL, McMullen K, Lynd LD. Association of Unemployment and Informal Care
with Stigma in Multiple Sclerosis: Evidence from the Survey on Living with Neurological Conditions in
Canada. Int J MS Care. 2019; 21(5):214–225. https://doi.org/10.7224/1537-2073.2017-108 PMID:
31680783
71. Patten SB, Williams JVA, Lavorato DH, Berzins S, Metz LM, Bulloch AGM. Health status, stress and
life satisfaction in a community population with MS. Can J Neurol Sci. 2012; 39(2):206–212. https://
doi.org/10.1017/s031716710001324x PMID: 22343155
72. Patten SB, Williams JVA, Lavorato DH, Koch M, Metz LM. Depression as a predictor of occupational
transition in a multiple sclerosis cohort. Funct Neurol. 2013; 28(4):275–280. https://doi.org/10.11138/
FNeur/2013.28.4.275 PMID: 24598395
73. Jennum P, Wanscher B, Frederiksen J, Kjellberg J. The socioeconomic consequences of multiple
sclerosis: a controlled national study. Eur Neuropsychopharmacol J Eur Coll Neuropsychopharmacol.
2012; 22(1):36–43. https://doi.org/10.1016/j.euroneuro.2011.05.001 PMID: 21669514
74. Johansson S, Skjerbæk AG, Nørgaard M, Boesen F, Hvid LG, Dalgas U. Associations between fatigue
impact and lifestyle factors in people with multiple sclerosis—The Danish MS hospitals rehabilitation
study. Mult Scler Relat Disord. 2021; 50:102799. https://doi.org/10.1016/j.msard.2021.102799 PMID:
33582566
75. Pfleger CCH, Flachs EM, Koch-Henriksen N, Hilt Pfleger CC, Meulengracht Flachs E, Koch-Henriksen
N. Social consequences of multiple sclerosis (1): Early pension and temporary unemployment-a histor-
ical prospective cohort study. Mult Scler. 2010; 16(1):121–126. https://doi.org/10.1177/
1352458509352196 PMID: 20007430
76. Rasmussen PV, Kobelt G, Berg J, Capsa D, Gannedahl M. New insights into the burden and costs of
multiple sclerosis in Europe: Results for Denmark. Mult Scler. 2017; 23(2_suppl):53–64. https://doi.
org/10.1177/1352458517708118 PMID: 28643589
77. Johansson S, Ytterberg C, Gottberg K, Holmqvist LW, von Koch L, Conradsson D. Participation in
social/lifestyle activities in people with multiple sclerosis: Changes across 10 years and predictors of
sustained participation. Mult Scler. 2020; 26(13):1775–1784. https://doi.org/10.1177/
1352458519881991 PMID: 31621488
78. D’hooghe MB, De Cock A, Benedict RHB, et al. Perceived neuropsychological impairment inversely
related to self-reported health and employment in multiple sclerosis. Eur J Neurol. 2019; 26(12):1447–
1454. https://doi.org/10.1111/ene.14012 PMID: 31183915
79. Dubois B, Kobelt G, Berg J, Capsa D, Gannedahl M. New insights into the burden and costs of multiple
sclerosis in Europe: Results for Belgium. Mult Scler. 2017; 23(2_suppl):29–40. https://doi.org/10.
1177/1352458517708100 PMID: 28643598
80. Kobelt G. Costs and quality of life for patients with multiple sclerosis in Belgium. Eur J Heal Econ
HEPAC Heal Econ Prev care. 2006; 7 Suppl 2:S24–33. https://doi.org/10.1007/s10198-006-0377-7
PMID: 17318662
81. Kos D, Ferdinand S, Duportail M, et al. Assessing life balance of European people with multiple sclero-
sis: A multicenter clinimetric study within the RIMS network. Mult Scler Relat Disord. 2020; 39:101879.
https://doi.org/10.1016/j.msard.2019.101879
82. Baroin A, Chopard G, Siliman G, et al. Validation of a new quality of life scale related to multiple sclero-
sis and relapses. Qual life Res an Int J Qual life Asp Treat care Rehabil. 2013; 22(8):1943–1954.
https://doi.org/10.1007/s11136-012-0334-0 PMID: 23247892
83. Baumstarck K, Pelletier J, Aghababian V, et al. Is the concept of quality of life relevant for multiple scle-
rosis patients with cognitive impairment? Preliminary results of a cross-sectional study. PLoS One.
2012; 7(1):e30627. https://doi.org/10.1371/journal.pone.0030627 PMID: 22292002
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 19 / 25

84. Fantoni-Quinton S, Kwiatkowski A, Vermersch P, Roux B, Hautecoeur P, Leroyer A. Impact of multiple
sclerosis on employment and use of job-retention strategies: The situation in France in 2015. J Rehabil
Med. 2016; 48(6):535–540. https://doi.org/10.2340/16501977-2093 PMID: 27243419
85. Heinzlef O, Molinier G, van Hille B, Radoszycki L, Dourgnon P, Longin J. Economic Burden of the Out-
of-Pocket Expenses for People with Multiple Sclerosis in France. PharmacoEconomics—open. 2020;
4(4):593–603. https://doi.org/10.1007/s41669-020-00199-7 PMID: 32043229
86. Lebrun-Frenay C, Kobelt G, Berg J, Capsa D, Gannedahl M. New insights into the burden and costs of
multiple sclerosis in Europe: Results for France. Mult Scler. 2017; 23(2_suppl):65–77. https://doi.org/
10.1177/1352458517708125 PMID: 28643588
87. Arroyo R, Massana M, Vila C. Correlation between spasticity and quality of life in patients with multiple
sclerosis: the CANDLE study. Int J Neurosci. 2013; 123(12):850–858. https://doi.org/10.3109/
00207454.2013.812084 PMID: 23819835
88. Gil-Gonza
´lez I, Pe
´rez-San-Gregorio MA
´, Conrad R, Martı
´n-Rodrı
´guez A. Predicting improvement of
quality of life and mental health over 18-months in multiple sclerosis patients. Mult Scler Relat Disord.
2021; 53:103093. https://doi.org/10.1016/j.msard.2021.103093 PMID: 34175814
89. Sundstro
¨m P, Nystro
¨m L, Svenningsson A, et al. Sick leave and professional assistance for multiple
sclerosis individuals in Vasterbotten County, northern Sweden. Mult Scler. 2003; 9(5):515–520.
https://doi.org/10.1191/1352458503ms955oa PMID: 14582779
90. Berg J, Lindgren P, Fredrikson S, Kobelt G. Costs and quality of life of multiple sclerosis in Sweden.
Eur J Heal Econ HEPAC Heal Econ Prev care. 2006; 7 Suppl 2:S75–85. https://doi.org/10.1007/
s10198-006-0379-5 PMID: 17310342
91. Brundin L, Kobelt G, Berg J, Capsa D, Eriksson J. New insights into the burden and costs of multiple
sclerosis in Europe: Results for Sweden. Mult Scler. 2017; 23(2_suppl):179–191. https://doi.org/10.
1177/1352458517708682 PMID: 28643601
92. Flensner G, Landtblom AM, So
¨derhamn O, Ek AC. Work capacity and health-related quality of life
among individuals with multiple sclerosis reduced by fatigue: A cross-sectional study. BMC Public
Health. 2013; 13(1). https://doi.org/10.1186/1471-2458-13-224 PMID: 23497281
93. Gottberg K, Einarsson U, Ytterberg C, et al. Health-related quality of life in a population-based sample
of people with multiple sclerosis in Stockholm County. Mult Scler. 2006; 12(5):605–612. https://doi.
org/10.1177/1352458505070660 PMID: 17086907
94. Henriksson F, Fredrikson S, Masterman T, Jo
¨nsson B. Costs, quality of life and disease severity in
multiple sclerosis: a cross-sectional study in Sweden. Eur J Neurol. 2001; 8(1):27–35. https://doi.org/
10.1046/j.1468-1331.2001.00169.x PMID: 11509078
95. Murley C, Karampampa K, Alexanderson K, Hillert J, Friberg E. Diagnosis-specific sickness absence
and disability pension before and after multiple sclerosis diagnosis: An 8-year nationwide longitudinal
cohort study with matched references. Mult Scler Relat Disord. 2020; 42:102077. https://doi.org/10.
1016/j.msard.2020.102077 PMID: 32353754
96. Becker V, Heeschen V, Schuh K, Schieb H, Ziemssen T. Patient satisfaction and healthcare services
in specialized multiple sclerosis centres in Germany. Ther Adv Neurol Disord. 2018;
11:1756285617748845. https://doi.org/10.1177/1756285617748845 PMID: 29399052
97. Flachenecker P, Kobelt G, Berg J, Capsa D, Gannedahl M. New insights into the burden and costs of
multiple sclerosis in Europe: Results for Germany. Mult Scler. 2017; 23(2_suppl):78–90. https://doi.
org/10.1177/1352458517708141 PMID: 28643593
98. Kallmann BA, Tiel-Wilck K, Kullmann JS, Engelmann U, Chan A. Real-life outcomes of teriflunomide
treatment in patients with relapsing multiple sclerosis: TAURUS-MS observational study. Ther Adv
Neurol Disord. 2019; 12:1756286419835077. https://doi.org/10.1177/1756286419835077 PMID:
30944584
99. Kobelt G, Lindgren P, Smala A, et al. Costs and quality of life in multiple sclerosis. An observational
study in Germany. HEPAC Heal Econ Prev Care. 2001; 2(2):60–68. https://www.scopus.com/inward/
record.uri?eid=2-s2.0–0034751455&partnerID=40&md5=ee6df033a358e711b37f324b5d3122e7
100. Kobelt G, Berg J, Lindgren P, et al. Costs and quality of life of multiple sclerosis in Germany. Eur J
Heal Econ HEPAC Heal Econ Prev care. 2006; 7 Suppl 2:S34–44. https://doi.org/10.1007/s10198-
006-0384-8 PMID: 17310337
101. Nickel S, von dem Knesebeck O, Kofahl C. Self-assessments and determinants of HRQoL in a Ger-
man MS population. Acta Neurol Scand. 2018; 137(2):174–180. https://doi.org/10.1111/ane.12854
PMID: 28975610
102. Scheinberg L, Holland N, Larocca N, Laitin P, Bennett A, Hall H. Vocational disability and rehabilitation
in multiple sclerosis. Int J Rehabil Res Int Zeitschrift fur Rehabil Rev Int Rech Readapt. 1981; 4(1):61–
64. https://doi.org/10.1097/00004356-198103000-00008 PMID: 7216575
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 20 / 25

103. Schmidt S, Jo
¨stingmeyer P. Depression, fatigue and disability are independently associated with qual-
ity of life in patients with multiple Sclerosis: Results of a cross-sectional study. Mult Scler Relat Disord.
2019; 35:262–269. https://doi.org/10.1016/j.msard.2019.07.029 PMID: 31437741
104. Chen J, Taylor B V, Blizzard L, Simpson SJ, Palmer AJ, van der Mei IAF. Effects of multiple sclerosis
disease-modifying therapies on employment measures using patient-reported data. J Neurol Neuro-
surg Psychiatry. 2018; 89(11):1200–1207. https://doi.org/10.1136/jnnp-2018-318228 PMID:
29921609
105. Chen J, Taylor B, Van der Mei I. Risk factors of leaving employment due to multiple sclerosis and
changes in risk over the past decades: survival analysis with competing risks. Mult Scler J. 2019; 25
MA-P(3):348.
106. Fidao A, De Livera A, Nag N, Neate S, Jelinek GA, Simpson-Yap S. Depression mediates the relation-
ship between fatigue and mental health-related quality of life in multiple sclerosis. Mult Scler Relat Dis-
ord. 2021;47. https://doi.org/10.1016/j.msard.2020.102620 PMID: 33242724
107. Honan CA, Brown RF, Hine DW. The multiple sclerosis work difficulties questionnaire (MSWDQ):
development of a shortened scale. Disabil Rehabil. 2014; 36(8):635–641. https://doi.org/10.3109/
09638288.2013.805258 PMID: 23786346
108. Kirk-Brown AK, Van Dijk PA, Simmons RD, Bourne MP, Cooper BK. Disclosure of diagnosis of multi-
ple sclerosis in the workplace positively affects employment status and job tenure. Mult Scler. 2014;
20(7):871–876. https://doi.org/10.1177/1352458513513967 PMID: 24263383
109. Marck CH, De Livera AM, Brown CR, et al. Health outcomes and adherence to a healthy lifestyle after
a multimodal intervention in people with multiple sclerosis: Three year follow-up. PLoS One. 2018; 13
(5). https://doi.org/10.1371/journal.pone.0197759 PMID: 29791509
110. Pakenham KI. The nature of sense making in caregiving for persons with multiple sclerosis.
Disabil Rehabil. 2008; 30(17):1263–1273. https://doi.org/10.1080/09638280701610320 PMID:
17896215
111. Battaglia M, Kobelt G, Ponzio M, Berg J, Capsa D, Dale
´n J. New insights into the burden and costs of
multiple sclerosis in Europe: Results for Italy. Mult Scler. 2017; 23(2_suppl):104–116. https://doi.org/
10.1177/1352458517708176 PMID: 28643600
112. Bo M, Charrier L, Bartalini S, et al. Access to social security benefits among multiple sclerosis patients
in Italy: A cross-sectional study. Mult Scler Relat Disord. 2018; 24:107–112. https://doi.org/10.1016/j.
msard.2018.06.016 PMID: 29982106
113. Esposito S, Sparaco M, Maniscalco GT, et al. Lifestyle and Mediterranean diet adherence in a cohort
of Southern Italian patients with Multiple Sclerosis. Mult Scler Relat Disord. 2021; 47:102636. https://
doi.org/10.1016/j.msard.2020.102636 PMID: 33333418
114. Kobelt G, Berg J, Lindgren P, Battaglia M, Lucioni C, Uccelli A. Costs and quality of life of multiple scle-
rosis in Italy. Eur J Heal Econ HEPAC Heal Econ Prev care. 2006; 7 Suppl 2:S45–54. https://doi.org/
10.1007/s10198-006-0385-7 PMID: 17310336
115. Patti F, Pozzilli C, Montanari E, et al. Effects of education level and employment status on HRQoL in
early relapsing-remitting multiple sclerosis. Mult Scler. 2007; 13(6):783–791. https://doi.org/10.1177/
1352458506073511 PMID: 17613607
116. Patti F, Russo P, Pappalardo A, Macchia F, Civalleri L, Paolillo A. Predictors of quality of life among
patients with multiple sclerosis: An Italian cross-sectional study. J Neurol Sci. 2007; 252(2):121–129.
https://doi.org/10.1016/j.jns.2006.10.017 PMID: 17188301
117. Ponzio M, Brichetto G, Zaratin P, Battaglia MA. Workers with disability: the case of multiple sclerosis.
Neurol Sci Off J Ital Neurol Soc Ital Soc Clin Neurophysiol. 2015; 36(10):1835–1841. https://doi.org/
10.1007/s10072-015-2265-3 PMID: 26017351
118. Ponzio M, Tacchino A, Vaccaro C, Brichetto G, Battaglia MA, Messmer Uccelli M. Disparity between
perceived needs and service provision: a cross-sectional study of Italians with multiple sclerosis. Neu-
rol Sci Off J Ital Neurol Soc Ital Soc Clin Neurophysiol. 2019; 40(6):1137–1144. https://doi.org/10.
1007/s10072-019-03780-z PMID: 30810827
119. Ponzio M, Tacchino A, Vaccaro C, et al. Unmet needs influence health-related quality of life in people
with multiple sclerosis. Mult Scler Relat Disord. 2020; 38:101877. https://doi.org/10.1016/j.msard.
2019.101877 PMID: 31812039
120. Forbes A, While A, Mathes L, Griffiths P. Health problems and health-related quality of life in people
with multiple sclerosis. Clin Rehabil. 2006; 20(1):67–78. https://doi.org/10.1191/0269215506cr880oa
PMID: 16502752
121. Ford HL, Gerry E, Johnson MH, Tennant A. Health status and quality of life of people with multiple scle-
rosis. Disabil Rehabil. 2001; 23(12):516–521. https://doi.org/10.1080/09638280010022090 PMID:
11432648
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 21 / 25

122. McCrone P, Heslin M, Knapp M, Bull P, Thompson A. Multiple sclerosis in the UK: service use, costs,
quality of life and disability. Pharmacoeconomics. 2008; 26(10):847–860. https://doi.org/10.2165/
00019053-200826100-00005 PMID: 18793032
123. McDonnell GV, Hawkins SA. An assessment of the spectrum of disability and handicap in multiple
sclerosis: a population-based study. Mult Scler. 2001; 7(2):111–117. https://doi.org/10.1177/
135245850100700207 PMID: 11424631
124. Mitchell JN. Multiple Sclerosis and the Prospects for Employment. J Soc Occup Med. 1981; 31
(4):134–138. https://doi.org/10.1093/occmed/31.4.134 PMID: 6460132
125. Nicholas RS, Heaven ML, Middleton RM, et al. Personal and societal costs of multiple sclerosis in the
UK: A population-based MS Registry study. Mult Scler J—Exp Transl Clin. 2020; 6
(1):2055217320901727. https://doi.org/10.1177/2055217320901727 PMID: 32030197
126. Thompson A, Kobelt G, Berg J, Capsa D, Eriksson J, Miller D. New insights into the burden and costs
of multiple sclerosis in Europe: Results for the United Kingdom. Mult Scler. 2017; 23(2_suppl):204–
216. https://doi.org/10.1177/1352458517708687 PMID: 28643587
127. Bamer AM, Cetin K, Johnson KL, Gibbons LE, Ehde DM. Validation study of prevalence and correlates
of depressive symptomatology in multiple sclerosis. Gen Hosp Psychiatry. 2008; 30(4):311–317.
https://doi.org/10.1016/j.genhosppsych.2008.04.006 PMID: 18585533
128. Beier M, Hartoonian N, D’Orio VL, et al. Relationship of perceived stress and employment status in
individuals with multiple sclerosis. Work. 2019; 62(2):243–249. https://doi.org/10.3233/WOR-192859
PMID: 30829635
129. Bishop M, Frain MP, Rumrill PD, Rymond C. The relationship of self-management and disease modify-
ing therapy use to employment status among adults with multiple sclerosis. J Vocat Rehabil. 2009; 31
(2):119–127.
130. Bishop M, Frain MP, Espinosa CT, Stenhoff DM. Sources of information about multiple sclerosis: Infor-
mation seeking and personal, demographic, and MS variables. J Vocat Rehabil. 2009; 31(2):107–117.
131. Bishop M, Roessler RT, Rumrill PD, et al. The relationship between housing accessibility variables
and employment status among adults with multiple sclerosis. J Rehabil. 2013; 79(4):4–14. https://
www.scopus.com/inward/record.uri?eid=2-s2.0–84890643468&partnerID=40&md5=
067585f49328fb87acacce9906198db2
132. Bishop M, Chan F, Rumrill PD, et al. Employment Among Working-Age Adults With Multiple Sclerosis:
A Data-Mining Approach to Identifying Employment Interventions. Rehabil Res POLICY Educ. 2015;
29(2):135–152. https://doi.org/10.1891/2168-6653.29.2.135
133. Bishop M, Fraser R, Li J, et al. Life domains that are important to quality of life for people with multiple
sclerosis: A population-based qualitative analysis. J Vocat Rehabil. 2019; 51(1):67–76. https://doi.org/
10.3233/JVR-191026
134. Buchanan RJ, Radin D, Chakravorty BJ, Tyry T. Informal care giving to more disabled people with mul-
tiple sclerosis. Disabil Rehabil. 2009; 31(15):1244–1256. https://doi.org/10.1080/
09638280802532779 PMID: 19802928
135. Buhse M, Banker WM, Clement LM. Factors associated with health-related quality of life among older
people with multiple sclerosis. Int J MS Care. 2014; 16(1):10–19. https://doi.org/10.7224/1537-2073.
2012-046 PMID: 24688350
136. Chamot E, Kister I, Cutter GR. Item response theory-based measure of global disability in multiple
sclerosis derived from the Performance Scales and related items. BMC Neurol. 2014; 14:192. https://
doi.org/10.1186/s12883-014-0192-1 PMID: 25278315
137. Chiu C-Y, Fitzgerald SD, Strand DM, Muller V, Brooks J, Chan F. Motivational and Volitional Variables
Associated With Stages of Change for Exercise in Multiple Sclerosis: A Multiple Discriminant Analysis.
Rehabil Couns Bull. 2012; 56(1):23–33. https://doi.org/10.1177/0034355212439898
138. Chwastiak LA, Gibbons LE, Ehde DM, et al. Fatigue and psychiatric illness in a large community sam-
ple of persons with multiple sclerosis. J Psychosom Res. 2005; 59(5):291–298. https://doi.org/10.
1016/j.jpsychores.2005.06.001 PMID: 16253619
139. Clingerman E, Stuifbergen A, Becker H. The influence of resources on perceived functional limitations
among women with multiple sclerosis. J Neurosci Nurs J Am Assoc Neurosci Nurses. 2004; 36
(6):312–321. https://doi.org/10.1097/01376517-200412000-00004 PMID: 15673206
140. Cofield SS, Thomas N, Tyry T, Fox RJ, Salter A. Shared Decision Making and Autonomy Among US
Participants with Multiple Sclerosis in the NARCOMS Registry. Int J MS Care. 2017; 19(6):303–312.
https://doi.org/10.7224/1537-2073.2016-091 PMID: 29270088
141. Coleman CI, Sidovar MF, Roberts MS, Kohn C. Impact of mobility impairment on indirect costs and
health-related quality of life in multiple sclerosis. PLoS One. 2013; 8(1):e54756. https://doi.org/10.
1371/journal.pone.0054756 PMID: 23355896
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 22 / 25

142. Genevie L, Kallos JE, Struening EL. Job Retention Among People with Multiple Sclerosis. Neuroreha-
bil Neural Repair. 1987; 1(3):131–135. https://doi.org/10.1177/136140968700100304
143. Glanz BI, De
´gano IR, Rintell DJ, Chitnis T, Weiner HL, Healy BC. Work productivity in relapsing multi-
ple sclerosis: associations with disability, depression, fatigue, anxiety, cognition, and health-related
quality of life. Value Heal J Int Soc Pharmacoeconomics Outcomes Res. 2012; 15(8):1029–1035.
https://doi.org/10.1016/j.jval.2012.07.010 PMID: 23244804
144. Gross HJ, Watson C. Characteristics, burden of illness, and physical functioning of patients with
relapsing-remitting and secondary progressive multiple sclerosis: a cross-sectional US survey. Neu-
ropsychiatr Dis Treat. 2017; 13:1349–1357. https://doi.org/10.2147/NDT.S132079 PMID: 28572730
145. Gulick EE, Yam M, Touw MM. Work performance by persons with multiple sclerosis: conditions that
impede or enable the performance of work. Int J Nurs Stud. 1989; 26(4):301–311. https://doi.org/10.
1016/0020-7489(89)90017-5 PMID: 2613450
146. Gulick EE. Reliability and validity of the work assessment scale for persons with multiple sclerosis.
Nurs Res. 1991; 40(2):107–112. PMID: 2003069
147. Gulick EE. Model for predicting work performance among persons with multiple sclerosis. Nurs Res.
1992; 41(5):266–272. PMID: 1523107
148. Gulick EE. Health status, work impediments, and coping related to work roles of women with multiple
sclerosis. Work. 1996; 6(3):153–166. https://doi.org/10.3233/WOR-1996-6303 PMID: 24441530
149. Iezzoni LI, Ngo L. Health, disability, and life insurance experiences of working-age persons with multi-
ple sclerosis. Mult Scler. 2007; 13(4):534–546. https://doi.org/10.1177/1352458506071356 PMID:
17463076
150. Iezzoni LI, Rao SR, Kinkel RP. Experiences acquiring and using mobility aids among working-age per-
sons with multiple sclerosis living in communities in the United States. Am J Phys Med Rehabil. 2010;
89(12):1010–1023. https://doi.org/10.1097/PHM.0b013e3181f70292 PMID: 20881588
151. Iwanaga K, Wu J-R, Chen X, et al. Person-environment contextual factors as mediators for the rela-
tionship between symptom cluster and employment outcome in multiple sclerosis. J Vocat Rehabil.
2018; 48(2):197–206. https://doi.org/10.3233/JVR-180930
152. Johnson KL, Bamer AM, Fraser RT. Disease and demographic characteristics associated with unem-
ployment among working-age adults with multiple sclerosis. Int J MS Care. 2013; 15(SUPPL.1):44–
51.
153. Jones E, Pike J, Marshall T, Ye X. Quantifying the relationship between increased disability and health
care resource utilization, quality of life, work productivity, health care costs in patients with multiple
sclerosis in the US. BMC Health Serv Res. 2016; 16:294. https://doi.org/10.1186/s12913-016-1532-1
PMID: 27443278
154. Kobelt G, Berg J, Atherly D, Hadjimichael O. Costs and quality of life in multiple sclerosis: a cross-sec-
tional study in the United States. Neurology. 2006; 66(11):1696–1702. https://doi.org/10.1212/01.wnl.
0000218309.01322.5c PMID: 16769943
155. Koch LC, Rumrill PD Jr., Roessler RT, Fitzgerald S. Illness and demographic correlates of quality of
life among people with multiple sclerosis. Rehabil Psychol. 2001; 46(2):154–164. https://doi.org/10.
1037/0090-5550.46.2.154
156. Kohn CG, Coleman CI, White CM, Sidovar MF, Sobieraj DM. Mobility, walking and physical activity in
persons with multiple sclerosis. Curr Med Res Opin. 2014; 30(9):1857–1862. https://doi.org/10.1185/
03007995.2014.921147 PMID: 24803286
157. Krause JS, Dismuke-Greer CE, Jarnecke M, Li C, Reed KS, Rumrill P. Employment and Gainful Earn-
ings Among Those With Multiple Sclerosis. Arch Phys Med Rehabil. 2019; 100(5):931–937.e1. https://
doi.org/10.1016/j.apmr.2018.11.005 PMID: 30529324
158. Krause JS, Li C, Backus D, et al. Barriers and Facilitators to Employment: A Comparison of Partici-
pants With Multiple Sclerosis and Spinal Cord Injury. Arch Phys Med Rehabil. Published online March
2021. https://doi.org/10.1016/j.apmr.2021.02.015 PMID: 33684369
159. Li J, Fitzgerald SM, Bishop M, Rumrill PD, Wang F. Disease-related and functional predictors of
employment status among adults with multiple sclerosis. Work. 2015; 52(4):789–797. https://doi.org/
10.3233/WOR-152206 PMID: 26599675
160. Motl RW, Suh Y, Weikert M, Dlugonski D, Balantrapu S, Sandroff B. Fatigue, depression, and physical
activity in relapsing-remitting multiple sclerosis: Results from a prospective, 18-month study. Mult
Scler Relat Disord. 2012; 1(1):43–48. https://doi.org/10.1016/j.msard.2011.08.003 PMID: 25876450
161. Nery-Hurwit M, Yun J, Ebbeck V. Examining the roles of self-compassion and resilience on health-
related quality of life for individuals with Multiple Sclerosis. Disabil Health J. 2018; 11(2):256–261.
https://doi.org/10.1016/j.dhjo.2017.10.010 PMID: 29089214
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 23 / 25

162. Neuberger EE, Abbass IM, Jones E, Engmann NJ. Work Productivity Outcomes Associated with Ocre-
lizumab Compared with Other Disease-Modifying Therapies for Multiple Sclerosis. Neurol Ther. 2021;
10(1):183–196. https://doi.org/10.1007/s40120-020-00224-1 PMID: 33244713
163. Ratajska A, Glanz BI, Chitnis T, Weiner HL, Healy BC. Social support in multiple sclerosis: Associa-
tions with quality of life, depression, and anxiety. J Psychosom Res. 2020; 138:110252. https://doi.org/
10.1016/j.jpsychores.2020.110252 PMID: 32971435
164. Roessler RT, Rumrill PD, Fitzgerald SM. Predictors of Employment Status for People with Multiple
Sclerosis. Rehabil Couns Bull. 2004; 47(2):96–103. https://doi.org/10.1177/00343552030470020401
165. Roessler RT, Rumrill PD, Li J, Daly K, Anhalt K. High-priority employment concerns of Hispanics/Lati-
nos with multiple sclerosis in the United States. J Vocat Rehabil. 2016; 45(2):121–131. https://doi.org/
10.3233/JVR-160817
166. Salter AR, Cutter GR, Tyry T, Marrie RA, Vollmer T. Impact of loss of mobility on instrumental activities
of daily living and socioeconomic status in patients with MS. Curr Med Res Opin. 2010; 26(2):493–
500. https://doi.org/10.1185/03007990903500649 PMID: 20014979
167. Salter A, Thomas N, Tyry T, Cutter G, Marrie RA. Employment and absenteeism in working-age per-
sons with multiple sclerosis. J Med Econ. 2017; 20(5):493–502. https://doi.org/10.1080/13696998.
2016.1277229 PMID: 28035846
168. Stuifbergen A, Brown A, Phillips L. Predictors and moderators of the disablement process in persons
with multiple sclerosis. NeuroRehabilitation. 2009; 24(2):119–129. https://doi.org/10.3233/NRE-2009-
0461 PMID: 19339751
169. Stuifbergen AK, Blozis S, Becker H, Harrison T, Kullberg V. Selected health behaviors moderate the
progression of functional limitations in persons with multiple sclerosis: Eleven years of annual follow-
up. Disabil Health J. 2016; 9(3):472–478. https://doi.org/10.1016/j.dhjo.2016.01.006 PMID: 26905974
170. Bass AD, Van Wijmeersch B, Mayer L, et al. Effect of Multiple Sclerosis on Daily Activities, Emotional
Well-being, and Relationships: The Global vsMS Survey. Int J MS Care. 2020; 22(4):158–164. https://
doi.org/10.7224/1537-2073.2018-087 PMID: 32863783
171. Fernandez O, Baumstarck-Barrau K, Simeoni M-CC, et al. Patient characteristics and determinants of
quality of life in an international population with multiple sclerosis: Assessment using the MusiQoL and
SF-36 questionnaires. Mult Scler J. 2011; 17(10):1238–1249. https://doi.org/10.1177/
1352458511407951 PMID: 21669936
172. Fernandez-Jimenez E, Panyavin I, Perez-San-Gregorio MA, Schultheis MT. Qualityof Life and
Depressive Symptomatology in Multiple Sclerosis: A Cross-Sectional Study Between the USA and
Spain. Psicothema. 2021; 33(1):60–69. https://doi.org/10.7334/psicothema2020.151 PMID:
33453737
173. Krokavcova M, Nagyova I, van Dijk JP, et al. Mastery, functional disability and perceived health status
in patients with multiple sclerosis. Eur J Neurol. 2008; 15(11):1237–1244. https://doi.org/10.1111/j.
1468-1331.2008.02304.x PMID: 18973613
174. Pluta-Fuerst A, Petrovic K, Berger T, et al. Patient-reported quality of life in multiple sclerosis differs
between cultures and countries: a cross-sectional Austrian-German-Polish study. Mult Scler. 2011; 17
(4):478–486. https://doi.org/10.1177/1352458510391341 PMID: 21148265
175. Taylor KL, Hadgkiss EJ, Jelinek GA, et al. Lifestyle factors, demographics and medications associated
with depression risk in an international sample of people with multiple sclerosis. BMC Psychiatry.
2014; 14:327. https://doi.org/10.1186/s12888-014-0327-3 PMID: 25467385
176. Broersma F, Oeseburg B, Dijkstra J, Wynia K. The impact of self-perceived limitations, stigma and
sense of coherence on quality of life in multiple sclerosis patients: results of a cross-sectional study.
Clin Rehabil. 2018; 32(4):536–545. https://doi.org/10.1177/0269215517730670 PMID: 28895427
177. The World Bank Data. [Cited 6 December 2021]. https://data.worldbank.org/indicator/SL.UEM.TOTL.
ZS. Access on 06/12/2021.
178. Honan CA, Brown RF, Hine DW, Vowels L, Wollin JA, Simmons RD, et al The multiple sclerosis work
difficulties questionnaire. Mult Scler. 2012 Jun; 18(6):871–80. https://doi.org/10.1177/
1352458511431724 Epub 2011 Dec 6. PMID: 22146603.
179. Walton C, King R, Rechtman L, et al. Rising prevalence of multiple sclerosis worldwide: Insights from
the Atlas of MS, third edition. Mult Scler J. 2020; 26(14):1816–1821. https://doi.org/10.1177/
1352458520970841 PMID: 33174475
180. McGinley MP, Goldschmidt CH, Rae-Grant AD. Diagnosis and Treatment of Multiple Sclerosis. JAMA.
2021; 325(8):765. https://doi.org/10.1001/jama.2020.26858 PMID: 33620411
181. Heinonen T, Castre
´n E, Luukkaala T, Ma
¨kinen K, Ruutiainen J, Kuusisto H. The retirement rate due to
multiple sclerosis has decreased since 1995– A retrospective study in a Finnish central hospital. Mult
Scler Relat Disord. 2020; 45:102360. https://doi.org/10.1016/j.msard.2020.102360 PMID: 32688302
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 24 / 25

182. Marck CH, Altken Z, Simpson S Jr, Welland TJ, Kavanagh, Jelinek GA. Predictors of Change in
Employment Status and Associations with Quality of Life: A Prospective International Study of People
with Multiple Sclerosis. Mult Scler. 2009; 15(9):S158–S159.
183. Phillips LJ, Stuifbergen AK. Predicting continued employment in persons with multiple sclerosis. J
Rehabil. 2006; 72(1):35–43. https://www.scopus.com/inward/record.uri?eid=2-s2.0–
33645781820&partnerID=40&md5=f8d8c4463a589c3000b290d862bac925
184. Schuring M, Burdorf L, Kunst A, Mackenbach J. The effects of ill health on entering and maintaining
paid employment: evidence in European countries. J Epidemiol Community Heal. 2007; 61(7):597–
604. https://doi.org/10.1136/jech.2006.047456 PMID: 17568051
185. Schuring M, Burdorf A, Kunst A, Voorham T, Mackenbach J. Ethnic differences in unemployment and
ill health. Int Arch Occup Environ Health. 2009; 82(8):1023–1030. https://doi.org/10.1007/s00420-009-
0408-7 PMID: 19234860
186. Alavinia SM, Burdorf A. Unemployment and retirement and ill-health: a cross-sectional analysis across
European countries. Int Arch Occup Environ Health. 2008; 82(1):39–45. https://doi.org/10.1007/
s00420-008-0304-6 PMID: 18264715
187. Porru F, Burdorf A, Robroek SJW. The impact of depressive symptoms on exit from paid employment
in Europe: a longitudinal study with 4 years follow-up. Eur J Public Health. 2019; 29(1):134–139.
https://doi.org/10.1093/eurpub/cky136 PMID: 30052918
PLOS ONE
Unemployment and early retirement in people with multiple sclerosis
PLOS ONE | https://doi.org/10.1371/journal.pone.0272156 July 28, 2022 25 / 25