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model 1), spread (Table III, multivariable model 1)
and sensitivity (Table IV, multivariable model 1). In
addition, being female was still a predictor of intensity
and spread of pain when pain variables at baseline were
included as regressors (Tables II, III, multivariable
model 2).
Low education level was a predictor for an increase
in the 3 characteristics of pain (Tables II–IV multiva-
riable models 1) and a predictor of pain intensity in
multivariable model 2. In cross-sectional studies, low
education has been related to CP intensity (56–58) and
spread (2, 5, 31, 59). These associations may reflect
physical exposures in working life that are more com-
mon among individuals with low education, which
contribute to the development of CP (60).
Being an immigrant was a predictor of the 3 charac-
teristics of pain (Tables II–IV, multivariable models 1)
and a predictor of pain sensitivity when pain variables
were included as predictors (Table IV, multivariable
model 2). Being an immigrant has been related to
spread of CP (61, 62) and to change in spread of pain
(63).
The current results of rather few sociodemographic
predictors for short- to medium-term (2 years in the
present study) results in CP (multivariable model 2)
are, to some extent, in line with a longitudinal study
on sociodemographic disparities in CP (64) and with a
study in which socioeconomic status seemingly related
to CP was explained by psychological factors (65).
Based on the results of multivariable model 1, it is
likely that the sociodemographic factors will be more
predictive of long-term development or changes in CP,
and this topic needs further investigation.
Traumatic injuries, RA/OA, GI disorders, pulmonary
disorders, CVD and/or CNS disorders were predictors
of changes in pain intensity and spread of pain in the
final models in this study (Tables II and III, model 2).
These comorbidities have been related to CP intensity
and spread (17, 18, 33, 66) and change in intensity (45,
67) and spread of pain (68, 69). Previous studies found
pulmonary diseases to be associated with pain intensity
(19) and GI disorders, such as irritable bowel disease
and spread of pain (70). In the current study, pulmonary
and GI disorders were also predictors of pain intensity
and spread of pain according to multivariable models
2, respectively. The current finding of RA/OA as
predictors for the 3 pain characteristics and change in
spread of pain (Table III, model 2), is in line with the
findings of cross-sectional studies (71–73). Several
comorbidities were predictive of pain characteristics
according to both multivariable models investigated
(Tables II–IV). From a clinical perspective, it appears
important that the assessment of people with pain
should include a broad screening of different medical
conditions. From the results of the present study it can
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also be concluded that physical comorbidities were
more important than psychological comorbidities, e.g.
depressive symptoms.
Strenghts and limitations
Major strengths of this study, in terms of solid inter-
pretations and precise estimation of predictors, are
the longitudinal study design and the large sample
size. The method of examining only the T0 predictors
signified that any new predictor (e.g. new incidence
of traumatic injury) would not be counted if it trig-
gered different pain characteristics at T1. Therefore,
the risk of single source bias was also decreased (e.g.
reporting of changed life circumstances influence re-
porting of pain when they are done at the same time).
Interestingly, strong associations were found between
the baseline and the 2-year follow-up regarding pain
characteristics. Nevertheless, it is important to note
there was no risk of multicollinearity (r < 0.75) between
the 3 pain characteristics.
A limitation of the current study is that the as-
sessments of pain characteristics and comorbidities
were based on self-reported instruments; nonetheless,
information on self-reported comorbidities has been
reported to be reliable (26). Furthermore, selective
participation both at baseline and during follow-up
is a concern. If participation is lower among subjects
with low socioeconomic status at baseline and worse
pain during follow-up, this would most likely lead to
underestimations. This may also explain why common
comorbidities to pain, such as depression and anxiety,
in cohorts with CP (5) had insignificant influence on
the pain characteristics when these baseline variables
were included in the current study (i.e. multivariable
model 2). The presence of certain comorbidities in the
present study to a great extent depended on diagnoses
made by physicians, and a recent report indicates that
the prevalence of clinically assessed depression and
anxiety are, in fact, relatively low compared with
reported depressive and anxiety symptoms (74). The
time investigated might be of importance as to whether
these comorbidities, as well as the other investigator
factors, are predictors. It might also be that some of
the identified predictors/risk factors in the current
study are due to reversed cause. For example, some
pain characteristics might, to some extent, influence
socioeconomic factors.
Conclusion
In planning treatment and rehabilitation, pain intensity,
spread, and sensitivity should be considered, because
these pain characteristics were stronger predictors of
the future pain situation than were socio-demographics
and co-morbidities.