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Eur J Pain. 2024;00:1–10.
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1
wileyonlinelibrary.com/journal/ejp
Received: 28 April 2024
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Revised: 11 September 2024
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Accepted: 15 September 2024
DOI: 10.1002/ejp.4735
ORIGINAL ARTICLE
Geographical disparities in fibromyalgia severity: An Italian
study
MarcoDiCarlo1
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SoniaFarah1
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FabiolaAtzeni2
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AlessandraAlciati3
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ManuelaDiFranco4
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CristinaIannuccelli4
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LauraBazzichi5
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GerolamoBianchi6
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MassimoGiovale6
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RosellaTirri7
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SerenaGuiducci8
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GiulianaGuggino9
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FrancoFranceschini10
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RosarioFoti11
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AlbertoLoGullo12
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GiovanniBiasi13
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ElisaGremese14
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LorenzoDagna15
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EnricoTirri16
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RobertoGiacomelli17
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AlbertoBatticiotto18
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MaurizioCutolo19
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PiercarloSarzi- Puttini20
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FaustoSalaffi1
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any
medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
© 2024 The Author(s). European Journal of Pain published by John Wiley & Sons Ltd on behalf of European Pain Federation - EFIC ®.
For affiliations refer to page 8.
Correspondence
Marco Di Carlo, Rheumatology Unit,
Università Politecnica delle Marche,
“Carlo Urbani” Hospital, Jesi (Ancona),
Italy.
Email: dica.marco@yahoo.it
Abstract
Background: Geographic origin may represent a variable capable of influencing
health status. This study aims to investigate the presence of differences of disease
severity in Italian patients with fibromyalgia from different macro- regions.
Methods: This retrospective, cross- sectional study involved patients included in
the Italian Fibromyalgia Registry. Three geographical macro- regions were identi-
fied, comprising patients from Northern Italy, Central Italy and Southern Italy.
Clinical differences (evaluated through PolySymptomatic Distress Scale [PSD],
revised Fibromyalgia Impact Questionnaire [FIQR] and modified Fibromyalgia
Assessment Status [FASmod]) among the geographical macro- regions were stud-
ied using one- way analysis of variance (ANOVA) and the Scheffé's test.
Results: A total of 6095 patients (5719 females and 376 males) were included,
with 1957 from Northern Italy, 2979 from Central Italy and 1159 from Southern
Italy. All studied clinical indices showed a trend indicative of greater disease
severity in Southern Italy, followed by Northern Italy and then Central Italy
(mean values for PSD: 19.97 ± 6.20 in Northern Italy, 18.61 ± 7.12 in Central Italy,
23.01 ± 5.66 in Souther Italy). These differences were statistically significant for
the overall scores of all studied indices, evaluated with ANOVA (all p < 0.001) and
in the head to head comparisons, evaluted with Scheffé's test.
Conclusions: Geographic background is significantly associated with variations
in the severity of fibromyalgia in Italian patients.
Significance Statement: This is the first study to demonstrate geographical
origin- dependent intra- national differences in the severity of fibromyalgia. The
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DI CARLO etal.
1
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INTRODUCTION
Fibromyalgia is a condition characterized by the pre-
dominant symptom of chronic widespread pain, ac-
companied by fatigue and non- restorative sleep in most
patients (Sarzi- Puttini et al., 2020). The diagnosis of
fibromyalgia is currently a purely clinical issue based
on the severity of symptoms (Wolfe etal.,2016). Over
the past few decades, several sets of diagnostic/classif-
icatory criteria have been proposed, and depending on
the set used, the prevalence of fibromyalgia may vary
(Jones etal.,2015). In the general population, the prev-
alence ranges from 2% to 3% (Ablin et al., 2012). In
certain populations, such as those with inflammatory
arthritis, the prevalence rate increases to over 20% (Di
Carlo etal.,2017). The variety of diagnostic and classi-
fication criteria, along with the resulting disparities in
prevalence, mirror the lack of diagnostic tests and uni-
fied pathophysiological theory for fibromyalgia (Clauw
etal.,2023).
Various risk factors contribute to the onset of fibro-
myalgia as well. The clear predominance in favour of the
female sex is well- known, along with associations with
potential triggers such as early psychological trauma or
joint hypermobility (Ablin & Buskila,2014; Yunus,2001).
Numerous variables have also been studied in relation
to symptom severity. In this regard, it has been demon-
strated that clinical variables, such as obesity or over-
weight, predispose to a higher disease burden (Atzeni
et al., 2021). However, an influence on symptom sever-
ity may also be exerted by socio- demographic variables,
with more severe disease observed in individuals with
lower educational levels or in separated or divorced males
(Atzeni etal.,2022). In this sense, chronic pain conditions
like fibromyalgia are currently framed within the biopsy-
chosocial model, which is a multifactorial context where
biological, psychological and social factors interact in de-
termining a clinical phenotype (Nicholas etal.,2019).
The geographic origin of an individual is a variable
that encompasses social aspects and can have significant
implications for health. Italy is one of the European coun-
tries where regional health disparities are among the most
pronounced: the percentages of residents reporting poor
health vary from 4% in northern regions (e.g. Trentino-
Alto Adige) to 10% in southern regions (e.g. Calabria and
Sicily) (Franzini & Giannoni, 2010). Regarding fibro-
myalgia in particular, the potential presence of regional
differences in terms of symptom severity is currently an
under- researched topic.
Starting from these considerations, the objective of this
study is to investigate the differences in fibromyalgia se-
verity in Italy by grouping regional data into three macro-
regions, namely Northern, Central and Southern Italy.
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METHODS
2.1
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Setting and patients
The data analysed in this retrospective, cross- sectional
study originate from a national database named the
Italian Fibromyalgia Registry (IFR). The data collection
period spans from November 2018 to June 2023. The IFR
exclusively encompasses Italian rheumatology centers
experienced in diagnosing and treating fibromyalgia, cur-
rently comprising 57 centers. To ensure certain uniform-
ity among regions, for the objectives of this study, only
Italian regions with at least 500 patients included in the
IFR were incorporated into each macro- regions. This cri-
terion was met by the Lombardy and Liguria regions for
Northern Italy, the Marche, Tuscany and Lazio regions
for Central Italy, and the Campania and Sicily regions for
Southern Italy. In addition, all the centres included in the
present study were actively enrolling patients throughout
the entire study period.
The IFR includes adult patients diagnosed with fi-
bromyalgia according to the American College of
Rheumatology (ACR) 2010/2011 criteria, regardless of dis-
ease severity and ongoing therapy (Wolfe etal.,2010). The
IFR is exclusively observational, focusing specifically on
the collection of clinimetric data and does not encompass
any interventional objectives (Salaffi, Farah, etal.,2020).
The patient population included in the IFR refers to the
so- called ‘primary’ fibromyalgia, excluding patients with
rheumatological conditions (e.g. chronic inflammatory
joint diseases, connective tissue diseases and vasculitis),
neurological disorders (e.g. demyelinating diseases, de-
mentias), psychiatric conditions (e.g. psychosis, severe
depression) or more broadly internal medical conditions
(e.g. congestive heart failure, uncontrolled endocrine dis-
orders and ongoing malignancies) capable of interfering
with clinimetric evaluation. In each centre, the fulfilment
of inclusion and exclusion criteria was verified by a rheu-
matologist with at least 10 years of clinical experience.
results confirm the necessity of considering fibromyalgia within the context of
the biopsychosocial model and of implementing healthcare policies targeted to-
wards the most underserved regions.
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DI CARLO etal.
All patients included in the IFR provided written in-
formed consent. The procedures conducted within the
IFR were approved by the ethical committee of the coordi-
nating center (Regional Ethics Committee, number 1970/
AV2, of the coordinating center of the IFR—Rheumatology
Clinic of the Polytechnic University of the Marche), and
this approval was subsequently obtained from the ethics
committees of all other centres.
2.2
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Assessment
Upon entry into the IFR and during subsequent evalua-
tions, anonymous collection of demographic variables
such as age, gender, education level, marital status, as
well as clinical metrics including the Widespread Pain
Index (WPI), Symptom Severity Scale (SSS) referring to
the PolySymptomatic Distress scale (PSD) from the ACR
2010/2011 criteria, the revised FIQ (FIQR) and the modi-
fied Fibromyalgia Assessment Status (FASmod) are gath-
ered for each patient (Salaffi etal.,2013; Salaffi, Di Carlo,
etal.,2020; Wolfe et al., 2010). For the purposes of this
study, data from each patient's first entry into the IFR
were used.
2.2.1
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PSD
The PSD is essentially based on the diagnostic criteria ACR
2010/2011, comprising the WPI that assesses tenderness
in 19 body areas (each area registering 1 for tenderness,
range 0–19) and the SSS, which evaluates the severity of
non- pain symptoms like fatigue, fibro fog and cognitive
disturbances (each on a scale from 0 to 3, range 0–12). The
final score, ranging from 0 to 31, is not only used for di-
agnostic purposes but can also be employed for a clinical
assessment of disease severity (Wolfe etal.,2010).
2.2.2
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FIQR
The FIQR investigates the severity of fibromyalgia through
21 items represented by 11- point numerical rating scales
(NRS, 0–10 scales), referring to the last 7 days. Three
health domains are covered, with the first nine items deal-
ing with physical function, followed by two items covering
overall general health status and the last domain focusing
on 10 items referring to symptoms. The total FIQR score
ranges from 0 to 100, with higher scores indicating greater
disease severity. The overall score is the algebraic sum of
the individual domains, where the score of the physical
function domain has to be divided by three, the two items
of the overall impact are considered as they are, while the
score of the symptom domain has to be divided by two
(Salaffi etal.,2013).
2.2.3
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FASmod
The FASmod is a revised and simplified version of the
Fibromyalgia Assessment Status (FAS). FASmod is made
by two sections recalling symptoms over the last 7 days:
the first one is represented by two 11- points NRS scales in-
vestigating fatigue and unrefreshing sleep; the second is a
front- back manikin with 19 body areas, realized to analyse
widespread pain, where patients are asked to rate the pres-
ence/absence of pain in each area (the presence of pain on
each area is scored 1). The final score, ranging from 0 to
39, is the sum of the two NRS scales and the painful areas
of the manikin (Salaffi, Di Carlo, etal.,2020).
2.3
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Statistical analysis
The results of the studied variables are presented as means
and standard deviations (SD) and as medians and inter-
quartile ranges (IQR), assessing normal distribution using
the Shapiro–Wilk test.
To compare differences in disease severity (PSD and its
subscales, FASmod, and FIQR and its subscales) among
macro- regions, one- way analysis of variance (ANOVA)
was employed. Meanwhile, the Scheffé's test was utilized
for one- to- one comparisons between macro- regions, spe-
cifically comparing North versus Centre, North versus
South and Centre versus South.
The chi- squared test was employed to compare macro-
regions on variables inferred from the IFR, which are po-
tential factors influencing disease severity. Specifically,
the variables analysed were educational status (catego-
rized as elementary school certificate, middle school cer-
tificate, high school diploma or university degree), marital
status (categorized as married, divorced, widowed, single
or other) and body weight (categorized as underweight for
BMI <18.5 kg/m2, normal weight for BMI between 18.5
and 24.9 kg/m2, overweight for BMI between 25.0 and 29.9
kg/m2 and obese for BMI >29.9 kg/m2).
Statistical significance was set at p < 0.05 for all con-
ducted analyses. Analyses have been conducted with
MedCalc, version 19.6.4 (MedCalc Software, Mariakerke,
Belgium).
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RESULTS
The study included 6095 patients, comprising 5719
(93.83%) females and 376 (6.17%) males, from the
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DI CARLO etal.
following macro- regions: 1957 (32.10%) patients from
Northern Italy (1862 females and 95 males), 2979
(48.88%) patients from Central Italy (2771 females and
208 males) and 1159 (19.02%) patients from Southern
Italy (1086 females and 73 males). The mean age was
54.33 ± 11.77 years.
The mean values (± SD) of the investigated clinical
indices were as follows: FIQR total score 62.64 ± 21.43,
FIQR physical function 17.41 ± 7.37, FIQR symptoms
33.26 ± 10.15, FIQR overall health status 11.99 ± 5.78,
FASmod 26.64 ± 7.96, PSD 19.88 ± 6.77, WPI 11.60 ± 4.84
and SSS 8.28 ± 2.95 (Table1).
All the clinical indices considered showed differences
according to the geographical macro- region evaluated.
Specifically, both FIQR (and its subscales), FASmod and
PSD (including its subscales WPI and SSS) revealed higher
scores, indicating greater disease severity, in Southern
Italy, followed by Northern Italy and then Central Italy
(Table2, Figure1a,b).
TABLE Demographic and clinical characteristics of the
whole study population.
Variables Mean (%) SD
Age 54.33 11.77
Sex
Female 5719 (93.83) -
Male 376 (6.17) -
Marital status
Married 4603 (75.52) -
Single 854 (14.02) -
Widow 138 (2.26) -
Divorced 500 (8.20) -
Education level
Primary school 231 (3.79) -
Secondary school 1461 (23.97) -
High school 2665 (43.72) -
Degree 1738 (28.51) -
BMI (kg/m2) 27.85 8.89
WPI 11.60 4.84
PSD 19.88 6.77
FASmod 26.64 7.96
FIQR total score 62.64 21.43
FIQR physical function 17.41 7.37
FIQR overall health status 11.97 5.78
FIQR symptoms 33.26 10.15
Abbreviations: BMI, body mass index; FASmod, modified Fibromyalgia
Assessment Status; FIQR, revised Fibromyalgia Impact Questionnaire;PSD,
PolySymptomatic Distress scale; SD, standard deviation; WPI, Widespread
Pain Index.
TABLE Mean values of FIQR (and its subscales), FASmod and PSD (and its subscales WPI and SSS), distributed across geographical macro- regions.
Geographical macro- regions
FIQR total
FIQR physical
function FIQR symptoms
FIQR overall
impact FASmod PSD WPI SSS
Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD)
Northern Italy 63.53 (20.08) 17.69 (7.11) 33.71 (9.25) 12.13 (5.69) 26.67 (7.33) 19.97 (6.20) 11.29 (4.77) 8.68 (2.44)
Central Italy 59.54 (22.70) 16.48 (7.59) 31.80 (10.89) 11.29 (5.98) 25.38 (8.50) 18.61 (7.12) 10.93 (4.81) 7.68 (3.30)
Southern Italy 69.11 (18.52) 19.32 (6.81) 36.26 (8.88) 13.57 (5.06) 29.83 (6.49) 23.01 (5.66) 13.86 (4.38) 9.15 (2.42)
Abbreviations: FASmod, modified Fibromyalgia Assessment Status; FIQR, revised Fibromyalgia Impact Questionnaire; PSD, PolySymptomatic Distress scale; SD, standard deviation; SSS, Symptom Severity Scale; WPI,
Widespread Pain Index.
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DI CARLO etal.
The ANOVA has documented statistically signifi-
cant differences among macro- regions. In each individ-
ual comparison between macro- regions, the differences
for the studied clinical indices were significant, all with
p < 0.0001, concerning Centre versus South and North ver-
sus South. The smallest difference (p = 0.0134) emerged
in the comparison of WPI between North versus Centre
(Table3).
Potential factors influencing the severity of FM, such
as educational level, marital status and body weight
categories, did not show significant differences across
the three macro- regions (p > 0.05 for all the categorical
variables).
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DISCUSSION
This study has demonstrated how geographical back-
ground is significantly associated with variations in the
severity of fibromyalgia in Italian patients. To the best
FIGURE Differences in mean values of FIQR (and subscales) (a), PSD (and subscales) and FASmod (b) according to the geographical
macro- regions. FIQR, revised Fibromyalgia Impact Questionnaire; WPI, Widespread Pain Index; SSS, Symptom Severity Scale; PSD,
PolySymptomatic Distress scale; FASmod, modified Fibromyalgia Assessment Status.
15322149, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/ejp.4735 by Marco Di Carlo - CochraneItalia , Wiley Online Library on [26/09/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
6
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DI CARLO etal.
of our knowledge, the data from the IFR are the first
to demonstrate a geographical characterization of fi-
bromyalgia severity. In particular, this trend is shown:
a higher disease severity in patients from Southern
Italy, followed by those from Northern Italy and then
individuals from Central Italy, who exhibit a less severe
condition.
Fibromyalgia, like all conditions characterized by
chronic pain, should be considered within the context of
the biopsychosocial model. While significant efforts have
been made to elucidate the neurobiological and psycho-
logical explanations for fibromyalgia, arguably less has
been done to understand how social reasons impact the
severity of the disease. Certainly, we are still quite far from
an integrated model that can be widely applied in daily
clinical practice for patients (Pontes- Silva,2023).
The reasons for these macro- regional differences
probably lie not in the biological or demographic char-
acteristics of the patients included in the IFR, but
more generally in the social and healthcare context.
Geographical differences in terms of fibromyalgia sever-
ity need to be framed on multiple levels: on one hand,
there are psychosocial variables capable of negatively
impacting the severity of a condition primarily charac-
terized by chronic pain; on the other hand, there are also
disparities that account for significant variability in ac-
cess to healthcare systems.
In recent decades, there has been an increasing ac-
knowledgment of the influence of geographical settings
on health outcomes, encompassing intricate inter-
plays of social, genetic, environmental and behavioural
processes.
Economic deprivation and the difficulties encountered
in the place of living are important aspects of chronic
pain. Jacobs and colleagues documented an increased se-
verity of fibromyalgia, in terms of pain severity and inter-
ference in daily life, among African American women and
those with low income (Jacobs etal., 2023). The role of
economic aspects also emerged from a study conducted
in Arizona which revealed how financial constraints and
concerns about one's financial situation are two determi-
nants capable of negatively influencing the daily assess-
ment of pain. This observation has been documented in
two chronic pain conditions such as osteoarthritis and fi-
bromyalgia (Rios & Zautra,2011).
From a historical point of view, socioeconomic con-
ditions within Italy have disadvantaged the Southern
regions. It has been demonstrated that residing in areas
characterized by increased poverty, higher unemployment
rates and greater inequalities correlates with poorer health
outcomes (Franzini & Giannoni,2010).
Even socioeconomic disadvantages in childhood
would seem to impact pain- related cognitions in later
years. Early difficult conditions result in higher future
levels of pain catastrophizing, higher perceived sensitivity
to pain and greater pain- related fear (Simon etal.,2022).
In fact, it is well known that, in addition to the biological
component, cognitive and emotional factors significantly
affect perception of pain. Race, ethnicity and culture have
a crucial impact on illness beliefs, health care preferences,
help- seeking behaviours and acceptance of medical inter-
ventions (Orhan etal.,2018).
A recent study, conducted using artificial intelligence
techniques, has revealed that mental health factors exhibit
a stronger correlation with fibromyalgia severity com-
pared to pain factors. Consequently, it is unsurprising to
find that FIQ depression scores are higher in the Southern
than in the Northern and Central regions (Moreno-
Sánchez etal.,2024).
Beyond how social factors can influence psychologi-
cal ones, an additional issue is represented by the inter-
regional diversity in healthcare access. Although in Italy,
healthcare access is universally guaranteed by the National
Health System, the decentralization of healthcare to
TABLE One- way analysis of variance data for PSD (its subscales), FIQR, FASmod and among geographical macro- regions and
significance of one- to- one comparisons (Scheffé's test) between macro- regions.
Clinimetric indices
ANOVA
Scheffé's test
North versus Centre North verus South
Centre versus
South
F- ratio p values p values p values p values
PSD 187.66 <0.001 <0.0001 <0.0001 <0.0001
WPI 167.31 <0.001 0.0134 <0.0001 <0.0001
SSS 136.10 <0.001 <0.0001 <0.0001 <0.0001
FIQR 88.02 <0.001 <0.0001 <0.0001 <0.0001
FASmod 136.83 <0.001 0.0001 <0.0001 <0.0001
Abbreviations: ANOVA, one- way analysis of variance; FASmod, modified Fibromyalgia Assessment Status; FIQR, revised Fibromyalgia Impact Questionnaire;
PSD, PolySymptomatic Distress scale; SSS, Symptom Severity Scale; WPI, Widespread Pain Index.
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DI CARLO etal.
individual regions has led to significant inter- regional
variability. As a result, some regions have been able to pos-
itively exploit this aspect, while others have failed to adapt
to the needs of their population.
The disparities in unmet health needs are significant
between the Northeast and the South of Italy, with the dis-
advantaged South where regional health systems are char-
acterized by poor performance but high levels of spending
(Bruzzi etal., 2022; Cavalieri,2013). An Italian study in-
vestigated whether the probability of facing four barriers
to healthcare utilization (drugs or exams costs, long wait-
ing lists or difficult access to the healthcare service) varies
among individuals with different socio- economic status
and care needs, across Italian geographical areas. The
study showed an increasing North–South gradient for all
the considered barriers, with a higher probability of facing
a barrier due to exams' costs for females and people with
a low income (Matranga & Maniscalco,2022). With re-
gard to regional healthcare access, a study referencing the
year 2013 estimated that, in the Italian context, the wait-
ing time for access to a diagnostic test is minimal for the
regions of the Northeast and maximum in the regions of
the South, with the highest peaks concerning the Molise
region (Landi etal.,2021).
A significant challenge that has emerged within Italy's
National Health System in recent years is also the shortage
of medical practitioners. The retirements have not been
compensated by a sufficient number of new specialists.
These shortages have had an adverse impact nationwide
but have had (and continue to have) particularly serious
and negative effects not only in the area of fibromyal-
gia care but especially in those regions of Southern Italy
that were already starting from a deficit position (Pennisi
etal.,2023).
What is certain is that the more vulnerable the popu-
lation is from a socioeconomic standpoint, the longer the
wait. Longer waits, even just for a fibromyalgia diagnosis,
translate into greater disease severity. Diagnosing fibro-
myalgia within the first 2 years from the onset of symp-
toms has been shown to be associated with a reduction
in the SSS and the number of tender points (Moshrif
etal.,2023).
A certain role in influencing the severity of fibromyal-
gia can also be explained by the residential context of the
patients, that is, whether they reside in a rural or urban
setting. Patients living in rural areas, compared to those
in urban areas, describe greater pain severity but also a
greater acceptance of it and reduced levels of physical and
mental fatigue (Catalá etal., 2021). These aspects could
partly explain why data related to a lesser disease severity,
present for all clinimetric indexes, is observed in the popu-
lation of Central Italy when compared to that of Northern
and Southern Italy. Compared to Central Italy, in Northern
Italy (particularly in Northwestern Italy, which includes
Lombardy and Liguria) and in Southern Italy there is a
higher percentage of ‘urban’ and ‘extremely urban’ mu-
nicipalities (Anania & Tenuta,2008). However, although
Northern Italy and Southern Italy are more urbanized
geographical areas than Central Italy, patients were not
categorized on the basis of origin (urban vs. rural), so this
is essentially a hypothesis that may explain some of the
variability.
Investigating geographical disparities in chronic pain
has significant implications for health policies. The Pain
Divide study, conducted in England, demonstrated that
the prevalence and impact of chronic pain are greater in
the Northern regions of England compared to the South,
and that in areas with a higher prevalence of chronic
pain, there is significantly more prescription of opioids
(Todd etal., 2018). Wide regional variabilities are also
found in opioid prescriptions in the specific case of fi-
bromyalgia. Painter and colleagues revealed that the
prescription of opioids in patients with fibromyalgia
is largely variable across the United States of America
and is lower in those states where the prevalence of fi-
bromyalgia and the number of general practitioners
are higher, two contextual and structural variables that
go beyond the physician- patient relationship (Painter
etal.,2013).
Different limitations of the study need mentioning.
Although a substantial number of cases were analysed,
patients were compared for a limited number of variables
potentially influencing disease severity (e.g. marital status,
educational level, BMI category). Other variables capable
of influencing the symptoms of fibromyalgia, such as dis-
ease duration, race/ethnicity, cigarette smoking, socio-
economic level and adverse childhood experiences are not
included in the IFR and therefore could not be considered.
Additionally, only seven out of the 20 Italian regions were
included, attempting to maintain a certain level of distri-
bution homogeneity (two Northern, three Central and two
Southern regions). However, these regions were chosen
based on higher patient recruitment and affiliation with
high- volume reference centers.
In conclusion, this study demonstrates geographic
disparity in the severity of fibromyalgia among Italian
patients, where individuals from Southern Italy gener-
ally exhibit worse symptoms compared to those from the
North, who in turn fare worse than those from the Central
regions. These results could be explained by referring to
psychosocial factors, as well as to structural variables re-
lated to the inter- regional differences of healthcare sys-
tems. Considering the high prevalence of fibromyalgia
and its negative impact on function and quality of life
of affected patients, the results of this study could repre-
sent a first step towards more adaptable regional health
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8
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DI CARLO etal.
policies tailored to the needs of each region, aimed at
improving care where fibromyalgia has shown greater
severity.
AUTHOR CONTRIBUTIONS
Prof. Di Carlo, Prof. Salaffi, Prof. Atzeni and Dr. Alciati
gave substantial contributions to study conception and
design. All Authors gave substantial contribution in ac-
quisition of data. Prof. Di Carlo, Dr. Farah and Prof.
Salaffi gave substantial contributions to analysis and in-
terpretation of data. Dr. Farah and Prof. Salaffi had full
access to all of the data in the study and takes respon-
sibility for the integrity of the data and the accuracy of
the data analysis. Prof. Di Carlo drafted the article, all
Authors were involved in revising it critically for impor-
tant intellectual content. All authors approved the final
version to be published.
AFFILIATIONS
1Rheumatology Unit, Dipartimento di Scienze Cliniche e Molecolari,
Università Politecnica Delle Marche, Ancona, Italy
2Rheumatology Unit, Department of Internal Medicine, University of
Messina, Messina, Italy
3Department of Clinical Neurosciences, Hermanas Hospitalarias, Villa
San Benedetto Menni Hospital, Como, and Humanitas Clinical and
Research Centre, Milan, Italy
4Rheumatology Unit, Department of Internal Clinical, Anesthesiologic
and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy
5Rheumatology Unit, AOU Pisana, Pisa, Italy
6Division of Rheumatology, La Colletta Hospital, Arenzano, Italy
7Dipartimento di Medicina di Precisione, Reumatologia, Università
Degli Studi Della Campania L.Vanvitelli, Naples, Italy
8Divisions of Internal Medicine and Rheumatology AOUC, Department
of Experimental and Clinical Medicine, University of Florence,
Florence, Italy
9Department of Health Promotion Sciences, Maternal and Infant Care,
Internal Medicine and Medical Specialties, University of Palermo,
Palermo, Italy
10Unit of Rheumatology and Clinical Immunology, ASST Spedali Civili,
Brescia, Italy
11Azienda Ospedaliera Universitaria Policlinico San Marco, Catania,
Italy
12Azienda Ospedaliera di Rilievo Nazionale e di Alta Specializzazione
(ARNAS) Garibaldi, Catania, Italy
13Rheumatology Unit, Department of Medical Sciences, Surgery and
Neurosciences, University of Siena, Siena, Italy
14UOC Reumatologia, Fondazione Policlinico Universitario A. Gemelli
IRCCS, Rome, Italy
15Unit of Immunology, Rheumatology, Allergy and Rare Diseases
(UnIRAR), IRCCS San Raffaele Scientific Institute, Milan, Italy
16ASL Napoli 1, Centro Ospedale San Giovanni Bosco, Naples, Italy
17Unit of Allergology, Clinical Immunology and Rheumatology,
Università Campus Bio- Medico di Roma, Rome, Italy
18ASST Sette Laghi, Varese, Italy
19Research Laboratory and Division of Clinical Rheumatology,
Department of Internal Medicine, University of Genova, IRCCS San
Martino, Genoa, Italy
20Rheumatology Unit, IRCCS Ospedale Galeazzi—S. Ambrogio,
Università Degli Studi di Milano, Milan, Italy
ACKNOWLEDGEMENTS
The Italian Fibromyalgia Registry is financially supported
by the Società Italiana di Reumatologia (SIR). Open ac-
cess publishing facilitated by Universita Politecnica delle
Marche, as part of the Wiley - CRUI- CARE agreement.
CONFLICT OF INTEREST STATEMENT
No financial or non- financial conflicts of interest to be
declared.
DATA AVAILABILITY STATEMENT
Data will be shared upon request to the corresponding
Author.
ORCID
Marco Di Carlo https://orcid.org/0000-0002-0906-4647
Sonia Farah https://orcid.org/0000-0002-9815-2621
Fabiola Atzeni https://orcid.org/0000-0002-9328-3075
Alessandra Alciati https://orcid.
org/0000-0002-8971-4696
Cristina Iannuccelli https://orcid.
org/0000-0003-1428-9725
Piercarlo Sarzi- Puttini https://orcid.
org/0000-0002-8673-5133
Fausto Salaffi https://orcid.org/0000-0002-3794-6831
REFERENCES
Ablin, J. N., & Buskila, D. (2014). Predicting fibromyalgia, a narra-
tive review: Are we better than fools and children? European
Journal of Pain, 18, 1060–1066. https:// doi. org/ 10. 1002/j. 1532-
2149. 2014. 00481. x
Ablin, J. N., Oren, A., Cohen, S., Aloush, V., Buskila, D., Elkayam, O.,
Wollman, Y., & Berman, M. (2012). Prevalence of fibromyalgia
in the Israeli population: A population- based study to estimate
the prevalence of fibromyalgia in the Israeli population using
the London fibromyalgia epidemiology study screening ques-
tionnaire (LFESSQ). Clinical and Experimental Rheumatology,
30(6 Suppl 74), 39–43.
Anania, G., & Tenuta, A. (2008). Ruralità, urbanità e ricchezza dei
comuni italiani. Retrieved from http:// www. ecost at. unical. it/
Anania/ varie% 20main/ Anania% 20e% 20Ten uta,% 20QA,% 20sec
onda% 20ver sione% 20riv ista% 20_ 10. 03. 08_. pdf
Atzeni, F., Alciati, A., Bazzichi, L., Govoni, M., Biasi, G., Di
Franco, M., Mozzani, F., Gremese, E., Dagna, L., Batticciotto,
A., Fischetti, F., Giacomelli, R., Guiducci, S., Guggino, G.,
Bentivegna, M., Gerli, R., Salvarani, C., Bajocchi, G., Ghini,
M., … Salaffi, F. (2022). Sociodemographic factors in fibromyal-
gia: Results from the Italian fibromyalgia registry. Clinical and
Experimental Rheumatology, 40, 1183–1188. https:// doi. org/ 10.
55563/ cline xprhe umatol/ 64963d
Atzeni, F., Alciati, A., Salaffi, F., Di Carlo, M., Bazzichi, L., Govoni,
M., Biasi, G., Di Franco, M., Mozzani, F., Gremese, E., Dagna,
L., Batticciotto, A., Fischetti, F., Giacomelli, R., Guiducci, S.,
Guggino, G., Bentivegna, M., Gerli, R., Salvarani, C., … Sarzi-
Puttini, P. (2021). The association between body mass index
and fibromyalgia severity: Data from a cross- sectional survey
15322149, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/ejp.4735 by Marco Di Carlo - CochraneItalia , Wiley Online Library on [26/09/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
|
9
DI CARLO etal.
of 2339 patients. Rheumatology advances. Practice, 5, rkab015.
https:// doi. org/ 10. 1093/ rap/ rkab015
Bruzzi, S., Ivaldi, E., & Santagata, M. (2022). Measuring regional per-
formance in the Italian NHS: Are disparities decreasing? Social
Indicators Research, 159, 1057–1084. https:// doi. org/ 10. 1007/
s1120 5- 021- 02775 - 8
Catalá, P., Blanco, S., Perez- Calvo, S., Luque- Reca, O., Bedmar, D.,
& Peñacoba, C. (2021). Does the rural environment influence
symptomatology and optimize the effectiveness of disease ac-
ceptance? A study among women with fibromyalgia. Frontiers
in Psychology, 12, 658974. https:// doi. org/ 10. 3389/ fpsyg. 2021.
658974
Cavalieri, M. (2013). Geographical variation of unmet medical
needs in Italy: A multivariate logistic regression analysis.
International Journal of Health Geographics, 12, 27. https:// doi.
org/ 10. 1186/ 1476- 072X- 12- 27
Clauw, D., Sarzi- Puttini, P., Pellegrino, G., & Shoenfeld, Y. (2023). Is
fibromyalgia an autoimmune disorder? Autoimmunity Reviews,
25, 103424. https:// doi. org/ 10. 1016/j. autrev. 2023. 103424
Di Carlo, M., Becciolini, A., Lato, V., Crotti, C., Favalli, E. G., &
Salaffi, F. (2017). The 12- item psoriatic arthritis impact of dis-
ease questionnaire: Construct validity, reliability, and interpret-
ability in a clinical setting. The Journal of Rheumatology, 44,
279–285. https:// doi. org/ 10. 3899/ jrheum. 160924
Franzini, L., & Giannoni, M. (2010). Determinants of health dis-
parities between Italian regions. BMC Public Health, 10, 296.
https:// doi. org/ 10. 1186/ 1471- 2458- 10- 296
Jacobs, M. M., Crall, E., & Menzies, V. (2023). Racial disparities in
pain among women with fibromyalgia: Secondary data analysis
of severity, interference with function, and response to guided
imagery. Journal of Integrative and Complementary Medicine,
29, 757–766. https:// doi. org/ 10. 1089/ jicm. 2023. 0020
Jones, G. T., Atzeni, F., Beasley, M., Flüß, E., Sarzi- Puttini, P., &
Macfarlane, G. J. (2015). The prevalence of fibromyalgia in the
general population: A comparison of the American College of
Rheumatology 1990, 2010, and modified 2010 classification cri-
teria. Arthritis and Rheumatology, 67, 568–575. https:// doi. org/
10. 1002/ art. 38905
Landi, S., Ivaldi, E., & Testi, A. (2021). The role of regional health
systems on the waiting time inequalities in health care services:
Evidences from Italy. Health Services Management Research, 34,
136–147. https:// doi. org/ 10. 1177/ 09514 84820 928302
Matranga, D., & Maniscalco, L. (2022). Inequality in healthcare
utilization in Italy: How important are barriers to access?
International Journal of Environmental Research and Public
Health, 19, 1697. https:// doi. org/ 10. 3390/ ijerp h1903 1697
Moreno- Sánchez, P. A., Arroyo- Fernández, R., Bravo- Esteban, E.,
Ferri- Morales, A., & van Gils, M. (2024). Assessing the rele-
vance of mental health factors in fibromyalgia severity: A data-
driven case study using explainable AI. International Journal
of Medical Informatics, 181, 105280. https:// doi. org/ 10. 1016/j.
ijmed inf. 2023. 105280
Moshrif, A., Mosallam, A., Abu- Zaid, M. H., & Gouda, W. (2023).
Evaluating the effect of delayed diagnosis on disease outcome
in fibromyalgia: A multi- center cross- sectional study. Journal
of Pain Research, 16, 1355–1365. https:// doi. org/ 10. 2147/ JPR.
S381314
Nicholas, M., Vlaeyen, J. W. S., Rief, W., Barke, A., Aziz, Q., Benoliel,
R., Cohen, M., Evers, S., Giamberardino, M. A., Goebel, A.,
Korwisi, B., Perrot, S., Svensson, P., Wang, S. J., Treede, R. D.,
& IASP Taskforce for the Classification of Chronic. (2019). The
IASP classification of chronic pain for ICD- 11: Chronic pri-
mary pain. Pain, 160, 28–37. https:// doi. org/ 10. 1097/j. pain
Orhan, C., Van Looveren, E., Cagnie, B., Mukhtar, N. B., Lenoir,
D., & Meeus, M. (2018). Are pain beliefs, cognitions, and be-
haviors influenced by race, ethnicity, and culture in patients
with chronic musculoskeletal pain: A systematic review. Pain
Physician, 21, 541–558.
Painter, J. T., Crofford, L. J., & Talbert, J. (2013). Geographic variation
of chronic opioid use in fibromyalgia. Clinical Therapeutics, 35,
303–311. https:// doi. org/ 10. 1016/j. clint hera. 2013. 02. 003
Pennisi, F., Minerva, M., Dalla Valle, Z., Odone, A., & Signorelli,
C. (2023). Genesis and prospects of the shortage of special-
ist physicians in Italy and indicators of the 39 schools of
hygiene and preventive medicine. Acta Bio- Medica: Atenei
Parmensis, 94(S3), e2023159. https:// doi. org/ 10. 23750/ abm.
v94iS3. 14512
Pontes- Silva, A. (2023). Fibromyalgia: Are we using the biopsychoso-
cial model? Autoimmunity Reviews, 22, 103235. https:// doi. org/
10. 1016/j. autrev. 2022. 103235
Rios, R., & Zautra, A. J. (2011). Socioeconomic disparities in
pain: The role of economic hardship and daily financial
worry. Health Psychology, 30, 58–66. https:// doi. org/ 10. 1037/
a0022025
Salaffi, F., Di Carlo, M., Farah, S., Atzeni, F., Buskila, D., Ablin, J.
N., Häuser, W., & Sarzi- Puttini, P. (2020). Diagnosis of fibro-
myalgia: Comparison of the 2011/2016 ACR and AAPT criteria
and validation of the modified fibromyalgia assessment sta-
tus. Rheumatology (Oxford), 59, 3042–3049. https:// doi. org/ 10.
1093/ rheum atolo gy/ keaa061
Salaffi, F., Farah, S., Di Carlo, M., Sinigaglia, L., Galeazzi, M., Gerli,
R., Sonnati, M., Giorgi, V., Sarzi- Puttini, P., & Masullo, M.
(2020). The Italian fibromyalgia registry: A new way of using
routine real- world data concerning patient- reported disease
status in healthcare research and clinical practice. Clinical and
Experimental Rheumatology, 38(Suppl 123), 65–71.
Salaffi, F., Franchignoni, F., Giordano, A., Ciapetti, A., Sarzi- Puttini,
P., & Ottonello, M. (2013). Psychometric characteristics of the
Italian version of the revised fibromyalgia impact question-
naire using classical test theory and Rasch analysis. Clinical
and Experimental Rheumatology, 31(Suppl 79), 41–49.
Sarzi- Puttini, P., Giorgi, V., Marotto, D., & Atzeni, F. (2020).
Fibromyalgia: An update on clinical characteristics, aetio-
pathogenesis and treatment. Nature Reviews Rheumatology, 16,
645–660. https:// doi. org/ 10. 1038/ s4158 4- 020- 00506 - w
Simon, E., Zsidó, A. N., Birkás, B., & Csathó, Á. (2022). Pain catastro-
phizing, pain sensitivity and fear of pain are associated with
early life environmental unpredictability: A path model ap-
proach. BMC Psychology, 10, 97. https:// doi. org/ 10. 1186/ s4035
9- 022- 00800 - 0
Todd, A., Akhter, N., Cairns, J. M., Kasim, A., Walton, N., Ellison, A.,
Chazot, P., Eldabe, S., & Bambra, C. (2018). The pain divide: A
cross- sectional analysis of chronic pain prevalence, pain inten-
sity and opioid utilisation in England. BMJ Open, 8, e023391.
https:// doi. org/ 10. 1136/ bmjop en- 2018- 023391
Wolfe, F., Clauw, D. J., Fitzcharles, M. A., Goldenberg, D. L.,
Häuser, W., Katz, R. L., Mease, P. J., Russell, A. S., Russell,
I. J., & Walitt, B. (2016). 2016 revisions to the 2010/2011
15322149, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/ejp.4735 by Marco Di Carlo - CochraneItalia , Wiley Online Library on [26/09/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
10
|
DI CARLO etal.
fibromyalgia diagnostic criteria. Seminars in Arthritis and
Rheumatism, 46, 319–329. https:// doi. org/ 10. 1016/j. semar thrit.
2016. 08. 012
Wolfe, F., Clauw, D. J., Fitzcharles, M. A., Goldenberg, D. L., Katz,
R. S., Mease, P., Russell, A. S., Russell, I. J., Winfield, J. B., &
Yunus, M. B. (2010). The American College of Rheumatology
preliminary diagnostic criteria for fibromyalgia and measure-
ment of symptom severity. Arthritis Care & Research, 62, 600–
610. https:// doi. org/ 10. 1002/ acr. 20140
Yunus, M. B. (2001). The role of gender in fibromyalgia syndrome.
Current Rheumatology Reports, 3, 128–134. https:// doi. org/ 10.
1007/ s1192 6- 001- 0008- 3
How to cite this article: Di Carlo, M., Farah, S.,
Atzeni, F., Alciati, A., Di Franco, M., Iannuccelli,
C., Bazzichi, L., Bianchi, G., Giovale, M., Tirri, R.,
Guiducci, S., Guggino, G., Franceschini, F., Foti, R.,
Lo Gullo, A., Biasi, G., Gremese, E., Dagna, L.,
Tirri, E., … Salaffi, F. (2024). Geographical
disparities in fibromyalgia severity: An Italian
study. European Journal of Pain, 00, 1–10. https://
doi.org/10.1002/ejp.4735
15322149, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/ejp.4735 by Marco Di Carlo - CochraneItalia , Wiley Online Library on [26/09/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
