Journal of
Clinical Medicine
Review
Associates of Insomnia in People with Chronic Spinal Pain:
A Systematic Review and Meta-Analysis
Thomas Bilterys1,2,3 , Carolie Siffain1 , Ina De Maeyer1, Eveline Van Looveren1,2,3 , Olivier Mairesse4,5, Jo Nijs1,3,6 , Mira Meeus2,3,7, Kelly Ickmans1,3,6,8 , Barbara Cagnie2 , Dorien Goubert2,
Lieven Danneels2, Maarten Moens9,10and Anneleen Malfliet1,3,6,8,*
Citation: Bilterys, T.; Siffain, C.;
De Maeyer, I.; Van Looveren, E.;
Mairesse, O.; Nijs, J.; Meeus, M.;
Ickmans, K.; Cagnie, B.; Goubert, D.;
et al. Associates of Insomnia in People with Chronic Spinal Pain: A Systematic Review and
Meta-Analysis.J. Clin. Med.2021,10, 3175. https://doi.org/10.3390/
jcm10143175
Academic Editor: Markus W. Hollmann
Received: 18 June 2021 Accepted: 14 July 2021 Published: 19 July 2021
Publisher’s Note:MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1 Pain in Motion Research Group (PAIN), Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, 1090 Brussels, Belgium;
thomas.bilterys@vub.be (T.B.); carolie18@hotmail.com (C.S.); Ina_dm@hotmail.com (I.D.M.);
Eveline.VanLooveren@UGent.be (E.V.L.); jo.nijs@vub.be (J.N.); kelly.ickmans@vub.be (K.I.)
2 Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine & Health Sciences, Ghent University, 9000 Ghent, Belgium; Mira.Meeus@UGent.be (M.M.); barbara.cagnie@ugent.be (B.C.);
goubertdorien@gmail.com (D.G.); lieven.danneels@ugent.be (L.D.)
3 Pain in Motion International Research Group, 1090 Brussels, Belgium
4 Experimental and Applied Psychology, Faculty of Psychology and Educational Sciences, Vrije Universiteit Brussel, 1050 Brussels, Belgium; olivier.mairesse@vub.be
5 Sleep Laboratory and Unit for Chronobiology, Brugmann University Hospital, 1020 Brussels, Belgium
6 Department of Physical Medicine and Physiotherapy, University Hospital Brussels, 1090 Brussels, Belgium
7 Department of Rehabilitation Sciences and Physiotherapy (MOVANT), Faculty of Medicine and Health Sciences, University of Antwerp, 2610 Antwerpen, Belgium
8 Research Foundation Flanders (FWO), 1000 Brussels, Belgium
9 Department of Neurosurgery and Radiology, University Hospital Brussels, 1090 Brussels, Belgium;
maarten.TA.moens@vub.be
10 Center for Neuroscience, Vrije Universiteit Brussel, 1090 Brussels, Belgium
* Correspondence: anneleen.malfliet@vub.be
Abstract:Insomnia is a major problem in the chronic spinal pain (CSP) population and has a negative impact on health and well-being. While insomnia is commonly reported, underlying mechanisms explaining the relation between sleep and pain are still not fully understood. Additionally, no reviews regarding the prevention of insomnia and/or associated factors in people with CSP are currently available. To gain a better understanding of the occurrence of insomnia and associated factors in this population, we conducted a systematic review of the literature exploring associates for insomnia in people with CSP in PubMed, Web of Science and Embase. Three independent reviewers extracted the data and performed the quality assessment. A meta-analysis was conducted for every potential associate presented in at least two studies. A total of 13 studies were found eligible, which together identified 25 different potential associates of insomnia in 24,817 people with CSP. Twelve studies had a cross-sectional design. Moderate-quality evidence showed a significantly higher rate for insomnia when one of the following factors was present: high pain intensity, anxiety and depression. Low-quality evidence showed increased odds for insomnia when one of the following factors was present: female sex, performing no professional activities and physical/musculoskeletal comorbidities. Higher healthcare use was also significantly related to the presence of insomnia. One study showed a strong association between high levels of pain catastrophizing and insomnia in people with chronic neck pain. Last, reduced odds for insomnia were found in physically active people with chronic low back pain compared to inactive people with chronic low back pain. This review provides an overview of the available literature regarding potential associates of insomnia in people with CSP. Several significant associates of insomnia were identified. These findings can be helpful to gain a better understanding of the characteristics and potential origin of insomnia in people witch CSP, to identify people with CSP who are (less) likely to have insomnia and to determine directions of future research in this area.
J. Clin. Med.2021,10, 3175. https://doi.org/10.3390/jcm10143175 https://www.mdpi.com/journal/jcm
Keywords:back pain; neck pain; associates; socio-demographic factors; psychosocial factors; lifestyle factors; sleep–wake disorders; systematic review
1. Introduction
Chronic spinal pain (CSP) is a highly prevalent and debilitating condition associated with poor quality of life and high socioeconomic impact [1–5]. Furthermore, CSP can coexist with many comorbidities (like other chronic diseases), which generally leads to larger negative effects on physical and mental functioning, a reduced treatment response, higher levels of disability and higher costs compared to CSP alone [6–8].
Insomnia, defined as the presence of a long sleep latency, frequent nocturnal awak- enings, prolonged periods of wakefulness during the sleep period or early awakenings, is common in people with CSP [9–12]. Up to 59% report insomnia, making it one of the most reported comorbidities in CSP [9–12]. Moreover, people with chronic low back pain are 18 times more likely to experience insomnia compared to people without chronic low back pain [11]. If left untreated, insomnia negatively impacts mood, physical symptoms, pain sensitivity, fatigue and health-related quality of life [13,14]. Additionally, insomnia is related to less productivity and increased work absenteeism [15]. Considering all of the above, co-occurring CSP and insomnia present a serious public health challenge which is currently rarely addressed in treatment [11].
Currently, underlying mechanisms explaining the relation between sleep and pain are still not fully understood [16]. A recent review provided an overview of the available evidence regarding investigated putative mediating variables on the pathway between sleep variables and pain intensity [17]. Based on the available body of research, they speculated that psychological and physiological components of emotional experience and attentional processes are likely mediators. However, this review focusses on the factors influencing the link between sleep and pain (i.e., mediators) in the general pain population.
None of the included studies investigated mediators or associated factors specifically in people with CSP. Additionally, the review did not include studies which investigated potential associated factors if no formal test of mediation or a test of the significance of mediated effects was conducted.
A clear overview of factors (including socio-demographic, psycho-social and lifestyle factors) associated with insomnia in people with CSP could lead to a better understanding, a change in decision making and further improvement of preventive and treatment strate- gies (i.e., targeting possible identified factors). Yet, since such an overview is currently unavailable, the purpose of this systematic review and meta-analysis is to provide an overview of associates of insomnia in people with CSP. The primary aim of this review is to determine which factors are associated with insomnia in people with CSP. The secondary aim is to determine the strength of association for these factors.
2. Methods
This systematic review was conducted in accordance with the PRISMA guidelines and initially registered in the PROSPERO database (registry number CRD42018116710) [18]. A search for eligible studies was performed in three electronic databases, i.e., PubMed, Web of Science and Embase. The last search was conducted on 12 September 2019.
2.1. Identification and Selection of Studies 2.1.1. Eligibility Criteria
Studies were eligible when meeting the following criteria: (1) including adults (>18 years) suffering from non-specific CSP (i.e., low back pain or neck pain not attributable to a specific pathology) for at least 3 months, (2) reporting insomnia-related outcomes [19,20], such as variables described in terms of sleep disturbances, sleep difficulties, sleep problems, restless sleep, disturbed sleep and sleep continuity;,(3) presenting data to identify associated factors
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with insomnia (i.e., odds ratios (ORs) or sufficient data to calculate the ORs) and (4) being written in English, French or Dutch.
The next criteria were applied for exclusion of studies: (1) abstracts, case reports, reviews, meta-analysis, letters and editorials, and (2) studies including participants diag- nosed with specific medical conditions that can explain CSP (e.g., neck or back surgery in the past three years, osteoporotic vertebral fractures or rheumatologic diseases), diagnosed with chronic widespread pain (fibromyalgia or chronic fatigue syndrome), being shift workers, suffering from severe underlying sleep-related comorbidities or being pregnant or were pregnant in the preceding year.
2.1.2. Information Sources
A systematic search was conducted in PubMed, Web of Science and Embase. The search in PubMed was performed using MeSH terms and free keywords based on the PECO-acronym, in which the “population” (P) was represented as people with CSP, the
“exposure” (E) as potential associates and the “outcome” (O) as insomnia. Since studies without comparison groups were eligible, no search terms for “comparison group” (C) were used in the final search. Using free keywords, a comparable search was performed in Web of Science and Embase. No search filters were used. An overview of the applied search terms can be found in Table S1. Full search strategies of all databases are presented in Supplementary file S1. Additionally, reference lists of the relevant articles were hand- searched for additional eligible papers.
2.1.3. Study Selection
After removing duplicates, three reviewers (C.S., I.D. and T.B.) independently screened all retrieved records to determine the eligibility. First, all records were screened by title and abstract in a blinded standardized manner using Rayyan software [21]. Studies that presented relevant data in accordance with the review question were included, even if the main research question was not relevant for this review. All discrepancies were resolved by consensus among the three researchers. When no agreement could be reached through discussion, a fourth author (A.M.) made the final decision. Reasons for exclusion were registered in all phases.
2.2. Data Collection Process
Three authors (C.S., I.D. and T.B) extracted the relevant data independently us- ing a self-created data extraction form containing the following items: (1) author, (2) year of publication, (3) study design, (4) sample size, (5) nature of the sample, (6) age (years±standard deviation), (7) assessment methods of insomnia, (8) prevalence rate of in- somnia and (9) investigated or determinable potential associates. Data of factors/variables investigated in each study were extracted and presented in the tables, figures and meta- analyses of this review if ORs could be determined. Variables presented in the included studies without sufficient data to determine ORs were not included. One reviewer (T.B.) checked the extracted data and resolved any disagreement.
2.3. Risk of Bias Assessment of Individual Studies
Three reviewers (C.S., I.D. and T.B.) evaluated the methodological quality and risk of bias by using an adapted form of the Newcastle-Ottawa Scale (NOS), independently [22,23].
The NOS assesses the quality of studies in three main areas, i.e., selection, comparability and outcome or exposure, and leads to a maximum total score of 10. The quality of indi- vidual studies was rated as high, moderate and low based on designated thresholds [24].
Studies with a score of≥7 out of 10 were considered high quality, studies with at least a score of 5 were rated as moderate quality and a score lower than 5 was considered low quality. Strict scoring criteria were determined a priori based on findings in the litera- ture [25–29]. The response-rate was considered “satisfactory” when it reached≥80% [25].
The sample size was considered “justified and satisfactory” if the number of needed partic-
ipants was reached based on a sample size calculation, or when the study is a national or epidemiological study. For the section “comparability”, two points were possibly awarded:
one for controlling for age or sex, and one for controlling for any other factor. Since age and sex differences in sleep are common [26–29], both factors were considered to be the most important factors to be controlled for. When an item was not described, a score of zero was given for that particular item. Overall risk of bias was considered “high” if the total score was 4 or lower. A score of at least 7 was considered as a “low” risk of bias. Uncertainties were solved by consensus among the three reviewers. The used NOS-version with details about the scoring criteria is provided in Supplementary file S2.
2.4. Summary Measures
The primary outcome measures were ORs with 95% confidence intervals (CIs). For every meta-analysis, a pooled OR (ORp) with 95% CI andp-value is presented. The statistical significance level (alpha) was set at 0.05.
2.5. Methods of Analysis
The number of subjects within the investigated subgroups (exposed subgroup and unexposed subgroup to the potential associated factor) with and without insomnia were collected to calculate ORs for each factor using Revman software (Review manager 5.3).
Subsequently, random effects meta-analyses were performed for all the factors which were presented in at least two of the included studies [30]. The heterogeneity (I2) was assessed by the method proposed by Higgins et al. [30]. To determine the significance of the heterogeneity amongst studies, a Chi-squared (X2) test was conducted with an alpha set at 0.05 [31,32]. When a high heterogeneity (I2 > 50%) between studies was present [33], subgroup analyses (based on NOS-score, study design, pain location and used measurement tools) were performed to possibly clarify the underlying systematic differences and reduce the substantial heterogeneity.
2.6. Quality of Evidence
A modified version of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria was used to assess the quality of evidence for all analy- ses [34]. The criteria were modified to make them more suitable and relevant. The quality of evidence was downgraded from high by one level based on: phase of investigation (cross-sectional), study limitations (>25% of participants from studies with high risk of bias), inconsistency of results (I2> 50%), imprecision (sample size < 400 participants), indirectness (e.g., inclusion of different populations and interventions) and publication bias (funnel plot and the Egger test if≥10 studies [35]). Evidence was upgraded when there was at least a moderate effect size (OR > 2.5), or evidence of an exposure-response gradient.
3. Results
3.1. Study Selection
The systematic search resulted in a total of 953 articles on PubMed, 1790 articles on Web of Science and 1647 articles on Embase. A total of 13 articles were included after the removal of duplicates, title and abstract screening and full-text eligibility assessment.
No additional records were identified through hand-searching. The selection process is illustrated in Figure1. An overview of the excluded articles assessed at full text and the reason for exclusion is presented in Table S2.
J. Clin. Med.2021,10, 3175 5 of 22
J. Clin. Med. 2021, 10, x FOR PEER REVIEW 5 of 23
Figure 1. Flow diagram illustrating the study selection process.
3.2. Study Characteristics
Twelve out of thirteen included studies were cross-sectional studies [11,12,36–45].
One included study was a cohort study [46]. A total of 24,817 participants were included across all studies, with sample sizes ranging from 70 to 10,849 participants [11,41]. The prevalence rate of insomnia across the studies ranged from 11% to 92% [12,38]. Nine studies used a validated questionnaire to retrieve information regarding the presence of insomnia [11,12,36,39,40,42,44–46]. Three other studies used a self-designed questionnaire [38,41,43] and one study made use of a health database [37]. A detailed overview of the characteristics of the included studies can be found in Table 1.
Figure 1.Flow diagram illustrating the study selection process.
3.2. Study Characteristics
Twelve out of thirteen included studies were cross-sectional studies [11,12,36–45].
One included study was a cohort study [46]. A total of 24,817 participants were included across all studies, with sample sizes ranging from 70 to 10,849 participants [11,41]. The prevalence rate of insomnia across the studies ranged from 11% to 92% [12,38]. Nine studies used a validated questionnaire to retrieve information regarding the presence of insomnia [11,12,36,39,40,42,44–46]. Three other studies used a self-designed question- naire [38,41,43] and one study made use of a health database [37]. A detailed overview of the characteristics of the included studies can be found in Table1.
Table 1.Characteristics of the included studies.
Author Design Sample
Size (N)
Nature of the Sample
Age (Range and/or Years
±SD)
Pain
Duration Sleep Outcome
Prevalence Rates of Insomnia
Investigated Factors
Aili et al.
2015 C 1408
Care seeking CLBP and CNP, community sample
Range: 20–59 y ≥6 mo Karolinska Sleep
Questionnaire NM
Sex, age, other physical illness, professional
activity
Blay et al.
2007 CS 2997
CLBP, population-based
sample
Range: 60–81 y ≥6 mo
Short Psychiatric Evaluation
Schedule
42.5% sleep disturbance
Professional activity, income, medical
consultation, hospitalizations, self-rated health, physical activity
Dimarco
et al. 2018 CS 709 CLBP, sample in
clinical setting 34.9±11.9 y
Opioid naïve:
26.04±50.21 mo Prior opioid users: 22.64±
46.26 mo
Data extracted from Military Health System Data Repository
19% insomnia Prior opioid use
Ho et al.
2019 CS 6559 CLBP, community
sample
52.2±15.2 y Range:
19.1–95.9 y
≥3 mo
Modified insomnia criteria from
DSM-5
10.9%
insomnia High CRP level
Kim et al.
2015 CS 218 CNP, sample in
clinical setting
52.8±14.3 y
Range: 20–83 y ≥3 mo Insomnia Severity Index
53.7% mild to severe insomnia
Sex, age, BMI, pain duration, pain score, spine surgery history, shoulder or arm pain, neck mobility problems,
myofascial pain components, anxiety, depression, headache,
comorbid musculoskeletal
conditions Majid et al.
2017 CS 358 CLBP, sample in
clinical setting NM ≥3 mo Insomnia Severity
Index
58.7% sleep
disturbance Sex
Marin et al.
2006 CS 268 CLBP, sample in
clinical setting
47 y±NM
Range: 18–89 y ≥6 mo Pittsburgh Sleep Quality Index
92% sleep disturbances
Sleep medication intake after pain Mork et al.
2013 CS 10,849 CLBP and CNP,
community sample 43.0±13.9 y ≥3 mo Self-Reported
Questionnaire NM Sex, physical activity, BMI Park et al.
2016 CS 256 CNP, sample in
clinical setting
52.8±14.7 y
Range: 20–84 y ≥3 mo Insomnia Severity Index
24.22% clinical
insomnia Pain catastrophizing
Ris et al.
2017 CS 200 CNP, sample in
clinical setting
Traumatic:
43.5±11.4 y Non- traumatic: 47.5
±11.3 y
≥6 mo
Self-reported Disturbed nights/week
19.5% sleep
disturbances Traumatic Onset
Shmagel
et al. 2016 CS 700 CLBP, community
sample Range: 20–69 y ≥3 mo NAHANS
Questionnaires
52.7% sleep
disturbances Healthcare Use Tang et al.
2007 CS 70 CLBP, sample in
clinical setting
46±10.9 y
Range: 18–65 y ≥6 mo Insomnia Severity Index
53% with moderate or
severe insomnia
Sex, race
Wang et al.
2016 CS 225 CLBP 40.7±11.4 y ≥3 mo Insomnia Severity
Index
25.8% clinical insomnia
Depression, anxiety, severity of CLBP Abbreviations: BMI, body mass index; C, cohort; CLBP, chronic low back pain; CNP, chronic neck pain; CRP, C-reactive protein; CS, cross-sectional; DSM-5, the Diagnostic and Statistical Manual of Mental Disorders 5th Edition; mo, month; NHANES, National Health and Nutrition Examination Survey; NM, not mentioned; y, year.
3.3. Risk of Bias within Studies
The overall methodological quality of the included studies is moderate to high, with scores ranging from 5 to 8 out of 10. Five out of thirteen studies were rated high quality, implying a “low” risk of bias. The other seven studies were rated as moderate quality, implying a “moderate” risk of bias. The main weakness was the relatively low response rate and the lack of comparison between the non-respondents and respondents (11 studies).
The second most common source of bias was the lack of control for confounders (6 studies).
The results of the quality assessment are presented in Table2.
