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EXTENDED REPORT
Lifestyle factors may modify the effect
of disease activity on radiographic
progression in patients with ankylosing
spondylitis: a longitudinal analysis
Sofia Ramiro,
1,2
Robert Landewé,
1,3
Astrid van Tubergen,
4,5
Annelies Boonen,
4,5
Carmen Stolwijk,
4,5
Maxime Dougados,
6,7
Filip van den Bosch,
8
Désirée van der Heijde
9
To cite: Ramiro S,
Landewé R, van Tubergen A,
et al. Lifestyle factors may
modify the effect of disease
activity on radiographic
progression in patients with
ankylosing spondylitis:
a longitudinal analysis. RMD
Open 2015;1:e000153.
doi:10.1136/rmdopen-2015-
000153
▸Prepublication history for
this paper is available online.
To view these files please
visit the journal online
(http://dx.doi.org/10.1136/
rmdopen-2015-000153).
Received 16 July 2015
Revised 18 August 2015
Accepted 22 August 2015
For numbered affiliations see
end of article.
Correspondence to
Dr Sofia Ramiro;
sofiaramiro@gmail.com
ABSTRACT
Objectives: To investigate the complex relationship
between inflammation, mechanical stress and
radiographic progression in patients with ankylosing
spondylitis (AS), using job type as a proxy for
continuous mechanical stress.
Methods: Patients from the Outcome in Ankylosing
Spondylitis International Study were followed up for
12 years, with 2-yearly assessments. Two readers
independently scored the X-rays according to the
modified Stoke Ankylosing Spondylitis Spine Score
(mSASSS). Disease activity was assessed by the AS
Disease Activity Score C reactive protein (ASDAS-
CRP). The relationship between ASDAS and spinal
radiographic progression was investigated with
longitudinal analysis, with job type at baseline
(physically demanding (‘blue-collar’) versus
sedentary (‘white-collar’) labour) as a potential factor
influencing this relationship. The effects of smoking
status and socioeconomic factors were also
investigated.
Results: In total, 184 patients were included in the
analyses (70% males, 83% human leucocyte
antigen-B27 positive, 39% smokers, 48% blue-collar
workers (65/136 patients in whom data on job type
were available)). The relationship between disease
activity and radiographic progression was
significantly and independently modified by job type:
In ‘blue-collar’workers versus ‘white-collar’workers,
every additional unit of ASDAS resulted in an
increase of 1.2 versus 0.2 mSASSS-units/2-years
(p=0.014 for the difference between blue-collar
and white-collar workers). In smokers versus
non-smokers, every additional unit of ASDAS
resulted in an increase of 1.9 versus 0.4 mSASSS-
units/2-years.
Conclusions: Physically demanding jobs may
amplify the potentiating effects of inflammation
on bone formation in AS. Smoking and
socioeconomic factors most likely confound this
relationship and may have separate effects on bone
formation.
INTRODUCTION
In ankylosing spondylitis (AS), radiographic
progression of the spine is faster in males, in
human leucocyte antigen (HLA)-B27-positive
patients, in patients with active disease and in
those who already have signs of damage.
1–5
We have recently shown that disease activity is
longitudinally associated with radiographic
progression.
5
This effect is amplified in males
and in patients with shorter symptom dur-
ation.
5
Part of syndesmophyte formation was
‘constitutive’: even in the absence of disease
activity patients had some progression.
5
A clear and overarching biological explan-
ation of syndesmophyte formation in AS is
still lacking, but, in analogy with osteophyte
formation in osteoarthritis,
6
there may be a
contributory role for mechanical stress.
Key messages
What is already known about this subject?
▸Higher disease activity leads to radiographic pro-
gression in ankylosing spondylitis (AS).
What does this study add?
▸Physically demanding jobs may amplify the
potentiating effects of inflammation on bone for-
mation in AS.
▸Smoking and socioeconomic factors confound
this relationship and may have separate effects
on bone formation.
How might this impact on clinical practice?
▸More research is needed, specifically into the
type of physical activity that may be deleterious
and lead to radiographic progression, before
these findings can have an impact on clinical
practice.
Ramiro S, et al.RMD Open 2015;1:e000153. doi:10.1136/rmdopen-2015-000153 1
Spondyloarthritis
Mice that were tail suspended, so that mechanical
loading on paws was low, showed less bone formation
than those kept in regular cages,
7
which is a proof of
concept for the proposition that mechanical strain
drives new bone formation in spondyloarthritis (SpA).
In addition, sparse data have suggested that jobs with
physically demanding activities are associated with more
radiographic damage.
8
A detailed analysis of how mechanical stress and
inflammation may interact in explaining radiographic
progression has never been conducted, because the idea
of lifetime mechanical stress is difficult to quantify and
because the contribution of inflammation to syndesmo-
phyte formation has long been obscure. However, it is
rational to postulate that radiographic progression is the
result of a combination of different factors (among
which are disease activity and mechanical stress), rather
than the sole consequence of one factor.
We have recently established the potential contribution
of inflammation to radiographic progression in the
Outcome in Ankylosing Spondylitis International Study
(OASIS cohort), using the AS Disease Activity Score
(ASDAS) as a proxy for inflammation; we have also for-
mulated the idea of ‘constitutive progression’(independ-
ent of inflammation).
5
We think the OASIS cohort may
be the appropriate template to study the interplay
between inflammation and mechanical stress. In the light
of the problem to quantify ‘long-term mechanical stress’,
and in the absence of appropriate direct data, we have
chosen ‘job type’(physically demanding vs sedentary) as
a proxy for ‘lifetime mechanical stress’on the spine.
We have also taken potential confounders into consid-
eration: smoking was shown to be predictive of radio-
graphic progression in patients with axial SpA.
3
It is easy
to hypothesise that smoking is associated with ‘job type’,
but smoking may also have an independent effect on
radiographic progression. Likewise, socioeconomic
factors such as personal income may interfere because
they may be associated with ‘job type’.
9–11
We have performed a detailed aggregated analysis
focusing on the effects of ‘job type’, smoking and factors
reflecting socioeconomic status on radiographic progres-
sion in AS.
METHODS
Study population
Data from OASIS were used. OASIS is a prevalence
cohort starting (1996) with 217 consecutive patients with
AS from the Netherlands, Belgium and France.
12
Clinical and radiographic (cervical and lumbar spine)
data were collected every 2 years during a period of
12 years. Patients were included in the present study if
they had at least two subsequent radiographs and data
on disease activity as well as on occupational activities
and/or smoking status and/or socioeconomic factors
(educational level, personal income and/or family
income) were available. All patients gave informed
consent and the ethics committee from all participating
hospitals approved the study.
Radiographic damage
Radiographs were scored using the modified Stoke
Ankylosing Spondylitis Spine Score (mSASSS), which
ranges from 0 (no damage) to 72 (maximal damage).
13
Two well-trained readers (SR and CS) independently
scored all available radiographs per patient, blinded to
demographic and clinical data, but with known chron-
ology.
14
Mean reader scores were used. Details of the
reading methodology have been reported elsewhere.
1
Disease activity and occupational activity, smoking status
and socioeconomic factors
The disease activity measure of choice was ASDAS,
15
which best reflects the association between disease activ-
ity and radiographic progression.
5
Patient-reported information about occupation (col-
lected at baseline by an open question) was used as a
proxy for unmeasured lifetime mechanical stress on the
spine. ‘Job type’was determined by consensus, without
knowledge of disease activity and/or radiographic
damage. Two job types were distinguished: ‘blue-collar’
and ‘white-collar’jobs, which are common circumscrip-
tions for manual jobs (that imply more physical labour)
and more sedentary jobs (that imply less physical activ-
ities), respectively.
16 17
Examples of ‘blue-collar workers’
are craftworkers, labourers and transportation opera-
tives. Examples of ‘white-collar workers’are managers,
administrative workers, teachers and engineers. The ana-
lyses were performed under the assumptions that (1)
‘job type’at baseline reflects ‘lifetime job type’; and (2)
‘blue-collar jobs’are associated with more mechanical
stress on the spine than ‘white-collar jobs’.
Smokers versus non-smokers were distinguished based
on baseline smoking status. If baseline information was
not available, patients were retrospectively questioned in
order to minimise missing data.
Socioeconomic factors were collected at baseline and
included (1) educational level (collected in seven cat-
egories and dichotomised into higher professional and
university education vs any other level of education; (2)
baseline gross monthly personal income and family
income (collected in 10 categories and dichotomised at
€1588 (personal income) and €3176 (family income),
respectively. These amounts demarcate income classes
1–4 versus 5–10.
Statistical analysis
The template for the analysis of the effects of ‘job type’
on radiographic progression was based on the longitu-
dinal analysis that has been presented in detail else-
where.
5
In brief, mSASSS over time (t) (mSASSS
t
)was
longitudinally modelled using generalised estimating
equations (GEE), assuming an exchangeable working
correlation structure for mSASSS in order to adjust for
within-patient correlation.
5
2Ramiro S, et al.RMD Open 2015;1:e000153. doi:10.1136/rmdopen-2015-000153
RMD Open
In the first model (referred to as the DIRECT model
since we investigated the direct effect of ‘job type’on
radiographic progression), ‘job type’was introduced by
testing the interaction of ‘job type’and ‘time’on
mSASSS
t
. Using similar methodology, we investigated the
effects of smoking and the socioeconomic factors, separ-
ately and in combination with ‘job type’.
Second, the potential of the ‘job type’to modify the
established relationship between disease activity and
mSASSS
t5
(referred to as the INDIRECT model, as we
investigated the effect of ‘job type’on the relationship
between ASDAS and radiographic progression) was ana-
lysed in our autoregressive model with 2-year time lags
as proposed previously.
5
Briefly, a ‘2-year time-lag’here
means that disease activity at the start of a 2-year interval
(ASDAS
t
) is associated with radiographic progression
during the subsequent 2-year interval (or: mSASSS
t
was
modelled by ASDAS
t−1
and by mSASSS
t−1
(autoregres-
sive component)). ‘Job type’was tested in interaction
with the longitudinal variable ‘ASDAS
t
’. Similar
INDIRECT models were run for the lifestyle factors
smoking and socioeconomic factors. In the presence of
relevant interactions (arbitrarily defined as interactions
with p<0.1), analyses were repeated in subgroups.
Figure 1 represents graphically the DIRECT and
INDIRECT models that were conducted to investigate
the effects that the ‘exposure’(eg, occupational activity)
could have on radiographic damage. Note that the con-
sequences of both models are fundamentally different.
Goodness-of-fit statistics (Quasi-likelihood under the
Independence model Criterion (QIC)), with lower QICs
reflecting better data fit, were used to select the best
models. Owing to missing information regarding occu-
pational activity, smoking status and the different socio-
economic factors, analyses were first conducted in all
patients with each of the variables available. Next, sensi-
tivity analysis in patients with complete data (missing
family income was allowed) was conducted. None of the
other measured variables in OASIS appeared to be
confounders of the relationship between disease activity
and radiographic progression as shown in previous ana-
lyses
5
and were omitted from this analysis.
Analyses were performed using Stata SE V.12
(Statacorp, College Station, Texas, USA).
RESULTS
In total, 184 patients (70% males, 83% HLA-B27 posi-
tive) were included in the analyses (table 1). These
patients had similar baseline characteristics as those
included in the entire OASIS cohort, and patients who
were followed up until year 12 were similar to those ini-
tially included in the study,
5
just as those included in the
sensitivity analysis (N=85; table 2). Of the 136 patients
with baseline occupational activity available, 65 (48%)
were assigned a ‘blue-collar’job.
Expectedly, ‘blue-collar’workers (86%) were more often
of male gender than ‘white-collar’workers (63%), and
men (82%) were more often smokers than women (63%).
Importantly, ‘blue-collar’workers had a higher level of
ASDAS than ‘white-collar’workers, as well as a higher
mSASSS at baseline (table 1). ‘White-collar’workers had a
higher level of education and a higher personal income.
At baseline, none of the patients were treated with tumour
necrosis factor inhibitors and 68% of the patients were
treated with non-steroidal anti-inflammatory drugs. More
details on this study population can be found in our previ-
ous publication.
5
Information of job type over time was
available for 92 patients, of whom only 1 patient had a
change in job type (from blue to white collar), and even
this was a temporary change; the others remained stable in
their job type throughout the entire follow-up.
The DIRECT model: effects of ‘job type’on radiographic
progression
Radiographic progression was slightly but significantly
higher in ‘blue-collar’than in ‘white-collar’workers:
2.18 mSASSS-units/2 years (95% CI 1.52 to 2.84) versus
Figure 1 Different scenarios that explain the effect that an external factor (here occupational activity—blue collar vs white collar
—used as an example) could hypothetically have on radiographic damage. (A) Occupational activity as a predictor of the course
of mSASSS over time, modifying this evolution over time; (B) occupational activity as a factor modifying the relationship between
ASDAS and mSASSS. Graphs represent hypothetical scenarios and not real data. mSASSS, modified Stoke Ankylosing
Spondylitis Spine Score; ASDAS, Ankylosing Spondylitis Disease Activity Score.
Ramiro S, et al.RMD Open 2015;1:e000153. doi:10.1136/rmdopen-2015-000153 3
Spondyloarthritis
Table 1 Baseline demographic, clinical and radiographic characteristics of all patients stratified by baseline smoking status
and by baseline occupational activity
Assessment
N=184
mean (SD)
or n (%)
Blue-collar jobs*
N=65 mean (SD)
or n (%)
White-collar jobs*
N=71 mean
(SD) or n (%)
Smokers†
N=49 mean
(SD) or n (%)
Non-smokers†
N=78
mean (SD)
or n (%)
Age (years) 43 (12) 40 (12) 41 (11) 38 (11) 42 (12)
Male gender (%) 129 (70) 56 (86) 45 (63) 40 (82) 49 (63)
HLA-B27 positive (%) 149 (83) 50 (79) 61 (88) 43 (88) 61 (78)
Symptoms duration (years) 20 (12) 17 (10) 18 (9) 16 (10) 20 (11)
Disease duration (years) 11 (9) 9 (8) 11 (8) 8 (6) 11 (9)
ASDAS-CRP 2.6 (1.0) 2.9 (1.0) 2.4 (0.9) 2.8 (1.0) 2.6 (1.1)
BASDAI (0–10) 3.4 (2.0) 3.7 (2.0) 2.9 (1.9) 3.4 (1.9) 3.2 (2.2)
CRP (mg/L) 17.4 (23.3) 18.2 (21.6) 15.7 (23.0) 18.9 (23.0) 17.9 (25.9)
Elevated CRP (%)‡85 (48) 30 (48) 34 (50) 25 (53) 37 (49)
mSASSS (0–72) 10.8 (15.2) 11.0 (14.7) 6.4 (8.6) 9.9 (15.9) 9.3 (13.7)
mSASSS >0 (%) 140 (81) 50 (81) 50 (78) 31 (72) 60 (80)
NSAIDs (%) 125 (68) 46 (71) 50 (70) 36 (73) 54 (69)
University education (%) 14 (8) 1 (2) 12 (17) 1 (2) 9 (12)
Monthly personal income
≥€1588 (%)
56 (35) 17 (28) 32 (52) 16 (38) 23 (34)
Monthly family income ≥€3176 (%) 21 (19) 4 (9) 14 (35) 6 (21) 10 (21)
Smoker (%) 49 (39) 23 (51) 17 (33) ––
Blue-collar worker (%) 65 (48) ––23 (58) 22 (39)
*Baseline occupational activity was missing for 48 patients (6 retired, 25 work-disabled, 4 housewives, 2 not working for own choice, 3
students, 1 unemployed and 7 with missing baseline occupational activity missing).
†Baseline smoking status was missing for 57 patients.
‡The cut-off was 10 mg/L for the Dutch patients and 5 mg/L for the Belgian and French patients.
ASDAS-CRP, Ankylosing Spondylitis Disease Activity Score (C reactive protein); BASDAI, Bath Ankylosing Spondylitis Disease Activity
Score; CRP, C reactive protein; HLA-B27, human leucocyte antigen; mSASSS, modified Stoke Ankylosing Spondylitis Spine Score; NSAIDs,
non-steroidal anti-inflammatory drugs.
Table 2 Baseline demographic, clinical and radiographic characteristics of all patients and the sensitivity analysis group*
Assessment
Patients included in this study
N=184 mean (SD) or n (%)
Sensitivity analysis group*
N=85 mean (SD) or n (%)
Age (years) 43 (12) 40 (10)
Male gender (%) 129 (70) 65 (76)
HLA-B27 positive (%) 149 (83) 70 (82)
Symptoms duration (years) 20 (12) 16 (9)
Disease duration (years) 11 (9) 9 (8)
ASDAS-CRP 2.6 (1.0) 2.7 (1.1)
BASDAI (0–10) 3.4 (2.0) 3.3 (2.2)
CRP (mg/L) 17.4 (23.3) 19.0 (24.9)
Elevated CRP (%)†85 (48) 44 (54)
mSASSS (0–72) 10.8 (15.2) 7.8 (11.3)
mSASSS >0 (%) 140 (81) 62 (81)
NSAIDs (%) 125 (68) 60 (71)
Tumour necrosis factor αinhibitors (%) 0 (0) 0 (0)
University education (%) 14 (8) 7 (8)
Monthly personal income ≥€1588 (%) 56 (35) 34 (40)
Monthly family income ≥€3176 (%) 21 (19) 13 (23)
Smoker (%) 49 (39) 35 (41)
Blue-collar worker (%) 65 (48) 40 (47)
*Sensitivity analysis group: patients included in the study and with the following variables available: occupational activity, smoking status,
education and personal income (availability of family income was not demanded because of the higher number of missing values in this
variable).
†The cut-off was 10 mg/L for the Dutch patients and 5 mg/L for the Belgian and French patients.
ASDAS-CRP, Ankylosing Spondylitis Disease Activity Score (C reactive protein); BASDAI, Bath Ankylosing Spondylitis Disease Activity
Score; CRP, C reactive protein; mSASSS, modified Stoke Ankylosing Spondylitis Spine Score; NSAIDs, non-steroidal anti-inflammatory
drugs.
4Ramiro S, et al.RMD Open 2015;1:e000153. doi:10.1136/rmdopen-2015-000153
RMD Open
1.82 mSASSS-units/2 years (95% CI 1.54 to 2.11)
(p=0.05 for the difference between blue and white-collar
workers). When investigating the effect of job type on
radiographic progression in subgroups of males and
females, statistical significance was lost.
Smoking (p=0.22), education (p=0.44), personal
income (p=0.99) and family income ( p=0.80) were not
associated with radiographic progression.
The INDIRECT model: modification of the relationship
between disease activity and radiographic progression by
‘job type’
The relationship between ASDAS and radiographic pro-
gression was significantly dependent on job type
(p=0.014): an increase of one ASDAS-unit led to an
increase of 1.2 mSASSS-units per 2 years in ‘blue-collar’
workers but only of 0.2 mSASSS units per 2 years in
‘white-collar’workers (table 3). Similar effects were
found when the analysis was performed with ‘smoking’
or ‘personal income’instead of ‘job types’as explana-
tory factors, but not with ‘educational level’or ‘family
income’. Note that the effects of ‘job type’on this rela-
tionship (but also the effects of smoking and personal
income) are seen only in men but not in women: an
association between ASDAS and radiographic progres-
sion in women was almost absent.
5
In a subsequent analysis, we have tried to disentangle
the presumed effects of ‘job type’and ‘smoking’on the
relationship between disease activity and radiographic pro-
gression. In the subgroup of smokers, 2-year progression
per additional ASDAS-unit in ‘blue-collar’workers (1.52
(95% CI 0.29 to 2.74) mSASSS-units) was slightly higher
but not significantly different from that in ‘white-collar’
workers (1.24 (95% CI 0.09 to 2.40) mSASSS-units). In the
subgroup of non-smokers, ‘blue-collar’workers had a
2-year progression of 0.61 (95% CI 0.18 to 1.05) mSASSS
progression per additional ASDAS unit increase.
Unfortunately, the model did not reach convergence for
‘white-collar’workers (35 patients). Further subgroup ana-
lyses (in gender and/or personal income strata) were
impossible because of the small numbers.
When comparing the fit of the models (with each of
the interaction terms included), the model with
‘smoking status’had the best fit (QIC 4484), followed by
the model with ‘job type’(QIC 4565), personal income
(QIC 5486) and finally education (QIC 5714). Note that
the influence of smoking on the association between
ASDAS and radiographic progression was statistically
stronger than the effect of ‘job type’on this relationship.
Sensitivity analysis in patients with all variables available
(except for family income due to the higher number of
missing values) provided similar results (table 4).
DISCUSSION
In this study, we have proposed scientific arguments for
the hypothesis that long-term physically demanding
activities, here operationalised by ‘blue-collar job type’,
amplify the effects of inflammation on bone (syndesmo-
phyte) formation in AS.
We reiterate that the effect of ‘job type’on radio-
graphic progression was investigated in two different
ways (figure 1): First, we have investigated whether ‘job
type’was associated with the course of radiographic pro-
gression itself (the DIRECT model). In fact, this turned
out to be not the case: While progression was initially
Table 3 Effects of disease activity on radiographic progression in subgroups*
Subgroup†
Overall group Men Women
p Value
for the
interaction
2-year increase
in mSASSS per
one-ASDAS unit
increase (units,
(95% CI))
2-year increase
in mSASSS per
one-ASDAS unit
increase (units,
(95% CI))
2-year increase
in mSASSS per
one-ASDAS unit
increase (units,
(95% CI))
Smoking Smokers (n=49) <0.001 1.94 (1.00 to 2.87) 2.15 (1.01 to 3.30) 0.47 (−0.12 to 1.06)
Non-smokers (n=78) 0.35 (0.04 to 0.65) 0.44 (0.02 to 0.86) 0.16 (−0.13 to 0.44)
Job type ‘Blue collar’(n=65) 0.014 1.19 (0.58 to 1.79) 1.47 (0.81 to 2.14) −0.60 (−1.59 to 0.40)
‘White collar’(n=71) 0.20 (−0.23 to 0.64) 0.35 (−0.30 to 1.01) −0.08 (−0.43 to 0.28)
Education ‘Non-university’
(n=167)
0.364 0.74 (0.41 to 1.07) 1.00 (0.55 to 1.44) −0.04 (−0.39 to 0.30)
‘University’(n=14) −0.18 (−1.91 to 1.55) 0.81 (−3.15 to 4.78) −0.74 (−1.82 to 0.34)
Monthly gross
personal income
<€1588 (n=105) 0.059 0.93 (0.45 to 1.41) 1.31 (0.66 to 1.96) −0.20 (−0.66 to 0.25)
≥€1588 (n=56) 0.14 (−0.21 to 0.50) 0.18 (−0.24 to 0.59) −0.21 (−0.90 to 0.48)
Monthly gross
family income
<€3176 (n=90) 0.445 0.49 (0.09 to 0.89) 0.77 (0.27 to 1.27) −0.25 (−0.80 to 0.30)
≥€3176 (n=21) 0.15 (−0.35 to 0.65) 0.36 (−0.22 to 0.94) −0.15 (−0.93 to 0.63)
*All models are time-lagged (2 years of time lag) and autoregressive (ie, adjusted for mSASSS in the 2-years before). Progression per
subgroup is expressed in mSASSS units over 2 years per one-ASDAS unit increase.
†Subgroup analysis was conducted in all patients with the variable of each of the subgroup analyses available, which means that due to
missing values some patients were not included in some of the subgroup analyses. Numbers of included patients can be seen in front of the
corresponding stratum.
ASDAS, Ankylosing Spondylitis Disease Activity Score; mSASSS, modified Stoke Ankylosing Spondylitis Spine Score.
Ramiro S, et al.RMD Open 2015;1:e000153. doi:10.1136/rmdopen-2015-000153 5
Spondyloarthritis
found to be higher in ‘blue-collar’than in ‘white-collar’
workers, this contrast disappeared when repeating the
analysis separately in males and females. We have
already reported that radiographic progression was
higher in men
1
and ‘blue-collar’work is primarily per-
formed by men. The conclusion of this analysis is there-
fore that strenuous physical activities most likely do not
have a strong DIRECT effect on radiographic progres-
sion. An intriguing alternative explanation could be that
it is physical activity rather than gender that determines
radiographic progression in AS, under the assumption
that the intensity of physical labour is overall higher in
men than in women regardless of ‘job type’. However,
our study will not give further resolution.
The second type of analyses (the INDIRECT models),
however, showed an effect of ‘job type’on the reported
association of ASDAS and radiographic progression:
5
‘Blue-collar’work amplified the effect of ASDAS on
radiographic progression in comparison with ‘white-
collar’work. This means that lifetime strenuous physical
activities may increase the detrimental effects of inflam-
mation on radiographic progression. If these findings
are confirmed, the implications could be far stretching:
the commonly given advice to patients with AS to regu-
larly exercise in order to optimise mobility and quality of
life (which is supported by a Cochrane review
18
and
implemented in guidelines
19
) may eventually need to be
revised, as at least certain types of exercises or mechan-
ical stress on the spine seem to amplify progression of
structural damage. If confirmed, this would ultimately
imply that (specific types of ) physically demanding
labour should be discouraged. In what concerns physical
exercise in broader terms than professional activity,
future research will need to focus on the specific types
of physical activity that eventually lead to radiographic
progression, to the detriment of others that are more
beneficial, especially when taking all the effects of phys-
ical activity on health into account. There is some argu-
mentation in the literature to support our findings: The
amplifying effects of ‘blue-collar’job type on the associ-
ation between disease activity and radiographic progres-
sion can be a consequence of increased strenuous
mechanical forces exerted on the spine. This is in con-
cordance with what has recently been shown in animal
models, in which mechanical strain has led to new bone
formation.
7
Unfortunately, this study does not provide sufficient
explanation for several reasons. First, mechanical strain
has also been shown to directly result in inflammation
in animal models.
7
It is plausible that physically demand-
ing jobs in patients with AS may lead to more ‘true’
inflammation of the spine, and therefore to truly higher
ASDAS levels, which in turn may explain more progres-
sion. The higher ASDAS levels we found in patients with
‘blue-collar’jobs are concordant with such a hypothesis.
Second, we have found similar (or even stronger)
interactions with other lifestyle factors such as
‘smoking’, and also with ‘socioeconomic determinants’
with regard to the association between ASDAS and
radiographic progression. On the other hand, ‘job type’,
‘smoking’and ‘socioeconomic status’are strongly
related. ‘Blue-collar’workers, for example, are more
often smokers than ‘white-collar’workers,
20
and ‘blue-
collar’workers have on average less income than ‘white-
collar’workers. The model with ‘smoking’had a better
data fit (lower QIC) than the model with ‘job type’. This
raises the question of ‘what is the determinant and what
is the confounder’?Isit‘job type’that eventually results
Table 4 Effects of disease activity on radiographic progression in subgroups—sensitivity analysis*
Subgroup
Overall group Men Women
p Value
for the
interaction
2-year increase
in mSASSS per
one-ASDAS unit
increase (units,
(95% CI))
2-year increase
in mSASSS per
one-ASDAS unit
increase (units,
(95% CI))
2-year increase
in mSASSS per
one-ASDAS unit
increase (units,
(95% CI))
Smoking Smokers (n=35) <0.001 2.13 (1.01 to 3.26) 2.56 (1.19 to 3.94) –†
Non-smokers (n=50) 0.34 (−0.03 to 0.70) 0.45 (−0.03 to 0.93) 0.06 (−0.22 to 0.34)
Occupation ‘Blue collar’(n=40) 0.031 1.33 (0.66 to 2.00) 1.54 (0.78 to 2.29) 0.06 (−0.16 to 0.28)
‘White collar’(n=45) 0.20 (−0.36 to 0.77) 0.25 (−0.58 to 1.08) −0.01 (−0.39 to 0.37)
Education ‘Non-university’(n=78) 0.678 0.93 (0.47 to 1.39) 1.13 (0.56 to 1.71) 0.06 (−0.22 to 0.33)
‘University’(n=7) −0.19 (−0.57 to 0.18) −0.34 (−0.97 to 0.29) 0.00 (0.00 to 0.00)
Monthly gross
personal income
<€1588 (n=51) 0.066 1.13 (0.51 to 1.75) 1.37 (0.58 to 2.16) –†
≥€1588 (n=34) 0.21 (−0.19 to 0.61) 0.26 (−0.21 to 0.72) −0.09 (−0.99 to 0.81)
Monthly gross
family income
<€3176 (n=43) 0.497 0.47 (0.01 to 0.92) 0.60 (0.06 to 1.13) 0.13 (−0.15 to 0.41)
≥€3176 (n=13) −0.05 (−0.45 to 0.35) 0.03 (−0.25 to 0.30) −0.18 (−1.08 to 0.72)
*All models are time-lagged (2 years of time lag) and autoregressive (ie, adjusted for mSASSS in the 2-years before). Progression per
subgroup is expressed in mSASSS units over 2 years per one-ASDAS unit increase. Sensitivity analysis group: patients included in the study
and with the following variables available: occupational activity, smoking status, education and personal income (availability of family income
was not demanded because of the higher number of missing values in this variable).
†Model does not reach convergence due to a small group of patients (N=5).
ASDAS, Ankylosing Spondylitis Disease Activity Score; mSASSS, modified Stoke Ankylosing Spondylitis Spine Score.
6Ramiro S, et al.RMD Open 2015;1:e000153. doi:10.1136/rmdopen-2015-000153
RMD Open
in more progression, and is ‘smoking’an epidemio-
logical confounder; is it ‘smoking’that is the primary
cause of progression, and is ‘job type’the confounder;
or do both factors independently convey certain effects
(figure 2)? In the appreciation that this study will not
give a final verdict, biological plausibility may give some
resolution: smoking has been associated in rheumatic
diseases with worse outcomes, particularly in rheumatoid
arthritis, where it provides an attractive explanation in
the debate of citrullinisation of peptides.
21
While
smoking has been associated with several factors of SpA,
such as early onset of back pain, more disease activity
and more MRI inflammation,
22–24
and it has also been
associated with spinal damage in AS in one study,
3
an
attractive biological explanation is still lacking or at least
unproven.
3
Mechanical stress, on the other hand, has
been brought into relation with inappropriate bone for-
mation in several conditions such as SpA
7
and osteoarth-
ritis.
6
It is therefore much more attractive and plausible to
suggest that mechanical stress (here somewhat artificially
operationalised as ‘blue-collar’vs ‘white-collar’jobs) is the
causative provoking factor, and ‘smoking’—known to be
associated with ‘blue-collar’work—the confounder, rather
than vice versa. An explanation that cannot be excluded is
that both ‘job type’and ‘smoking’are independently con-
tributory. In this discussion, we propose that ‘personal
income’and, to a lesser extent, ‘education’and ‘family
income’, while being proven modifiers of the relationship
between ASDAS and radiographic progression, do not
have biological plausibility and should be considered as
confounders, id est: ‘personal income’and others are sub-
ordinate to ‘job type’. In analogy with many rheumatic dis-
eases, the association of socioeconomic variables with
outcome of disease also is intriguingly present here.
25–28
As far as we know, the role of occupational activities,
smoking or socioeconomic factors on the course of
radiographic progression over the long term has not
been investigated previously and we cannot compare our
findings with others.
This study has several additional limitations worth
mentioning. The sample size of this observational study
is not large enough to allow subtle but complex relation-
ships in critically relevant subgroups (eg, smokers vs
non-smokers and men vs women). On the other hand,
larger cohorts without biological treatment but a more
meticulous follow-up than this one will most likely never
be conducted.
An important limitation is that we assumed the dichot-
omy of ‘blue-collar’versus ‘white-collar’jobs as being
representative of a high versus low level of mechanical
stress on the spine. We cannot exclude the possibility
that ‘white-collar’workers follow more thoroughly the
physicians’recommendations to intensively exercise and
thus compensate lower levels of physical activity during
working hours with higher levels of exercise. However,
regardless of what epidemiological mechanism may have
worked against the effects of ‘job type’, the effects are
significant and relevant.
Another limitation of this study is that we have mod-
elled ‘job type’at baseline as being representative of ‘job
type’during follow-up. However, from the patients with
data on job type over time available, only one patient
changed his job type, which confirms that people tend
to practise the same type of profession over several years.
Moreover, since OASIS is not an inception cohort but
symptom duration was on average 20 years at the start, it
is most likely that changes due to the onset of back pain
are made before the inclusion in the cohort.
What impact do the findings in this study and the pre-
vious one
5
have with regard to explaining syndesmo-
phyte formation in AS? We have previously identified
important determinants of syndesmophyte formation in
patients with AS: it occurs primarily in HLA-B27-positive
male patients, reiterating the constitutive (genetic) com-
ponent.
1
Disease activity (inflammation) does have an
influence on the rate of progression, but primarily in
(genetically) susceptible (male) patients.
5
In addition,
we have now made likely that—among other factors still
Figure 2 Factors influencing the relationship between
disease activity (as measured with the ASDAS) and
radiographic progression (as measured with the 2-year
mSASSS progression) and possible relationships between
them (A) hypothesis 1: occupational activity modifies the
relationship between disease activity and radiographic
progression and this effect might be confounded by the effect
of gender, smoking status and/or low socioeconomic status,
which can, for example, be measured with education,
personal income, family income. (B) Hypothesis 2: smoking
status modifies the relationship between disease activity and
radiographic progression and this effect might be confounded
by the effect of gender, occupational activity and/or low
socioeconomic status. ASDAS, Ankylosing Spondylitis
Disease Activity Score; mSASSS, modified Stoke Ankylosing
Spondylitis Spine Score.
Ramiro S, et al.RMD Open 2015;1:e000153. doi:10.1136/rmdopen-2015-000153 7
Spondyloarthritis
to be identified—lifetime physical activities during
working hours may amplify the detrimental effects of
inflammation on radiographic progression. Whether
smoking is an independent modifier of this relationship
or only a confounder still needs to be elucidated.
Author affiliations
1
Department of Clinical Immunology & Rheumatology, Amsterdam
Rheumatology Center, University of Amsterdam, Amsterdam, The Netherlands
2
Department of Rheumatology, Hospital Garcia de Orta, Almada, Portugal
3
Department of Rheumatology, Atrium Medical Center, Heerlen,
The Netherlands
4
Department of Medicine, Division of Rheumatology, Maastricht University
Medical Center, Maastricht, The Netherlands
5
School for Public Health and Primary Care (CAPHRI), University of
Maastricht, Maastricht, The Netherlands
6
Department of Rheumatology, Hôpital Cochin, Paris-Descartes University,
Paris, France
7
Clinical Epidemiology and Biostatistics, PRES Sorbonne Paris-Cité, Paris,
France
8
Department of Rheumatology, University of Ghent, Ghent, Belgium
9
Department of Rheumatology, Leiden University Medical Center, Leiden,
The Netherlands
Contributors SR, RL, AvT, AB and DvdH designed the study. SR, RL, AvT,
AB, CS, FvdB, MD and DvdH collected the data. SR and CS read the
radiographs. AvT was the adjudicator. SR, RL, AvT, AB and DvdH analysed the
data and critically interpreted the results. SR prepared the first version of the
manuscript. All authors reviewed the draft versions and gave their approval of
the final version of the manuscript.
Funding SR was supported by the Fundação para a Ciência e Tecnologia
(FCT) grant SFRH/BD/68684/2010
Competing interests None declared.
Patient consent Obtained.
Ethics approval The ethics committee from all participating hospitals
approved the study (Paris, Maastricht, Ghent).
Provenance and peer review Not commissioned; externally peer reviewed.
Open Access This is an Open Access article distributed in accordance with
the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license,
which permits others to distribute, remix, adapt, build upon this work non-
commercially, and license their derivative works on different terms, provided
the original work is properly cited and the use is non-commercial. See: http://
creativecommons.org/licenses/by-nc/4.0/
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