Research Review By Dr. Jeff Muir©

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Date Posted:

May 2020

Study Title:

Chronic physical illnesses, mental health disorders, and psychological features as potential risk factors for back pain from childhood to young adulthood: a systematic review with meta‑analysis

Authors:

Beynon AM, Hebert JJ, Hodgetts CJ, Boulos LM & Walker BF

Author's Affiliations:

College of Science, Health, Engineering and Education, Murdoch University, Australia; Faculty of Kinesiology, University of New Brunswick, Canada; Maritime SPOR SUPPORT Unit, Halifax, Canada.

Publication Information:

European Spine Journal 2020; 29: 480–496.

Background Information:

Low back pain (LBP) affects people of all ages (1, 2) and remains a leading cause of years lived with disability (3). The etiology of LBP is complex and multifactorial and includes social, physical and psychological factors, plus the interplay with comorbidities (4). Various reports have indicated that conditions ranging from asthma and allergies (5, 6), respiratory and digestive disorders (7, 8) and cardiovascular disease (9) are all reported to have associations with LBP.

An important factor of etiological studies is the differentiation between risk factors for low back pain and factors that are associated with low back pain. Risk factors, or variables that are a causally related to a change in the risk of a health process, outcome or condition (10), are important in studies of LBP, as they allow identification of factors that may cause the initial onset of pain and/or triggers that may precipitate and episode (11). Such studies are common in adult populations, although properly identifying risk factors can be complicated by the unlikelihood of identifying a disease-free cohort (i.e. one with no history of low back pain). As such, studies in younger populations may prove beneficial in identifying risk factors for low back pain.

The purpose of this systematic review was to investigate the role of chronic physical illness, mental health disorders and psychological conditions as potential triggers or risk factors for low back pain in children, adolescents and young adults.

Pertinent Results:

Study Characteristics:
19 studies (34,279 participants) met the inclusion criteria, of which 12 (25,372 participants) could be included in the meta-analysis. 7 studies were excluded from the meta-analysis due to methodological heterogeneity. Of the 19 studies, 16 were prospective cohort studies while 3 were inception cohort studies.

Risk of Bias Assessment:
Overall, 2 studies were rated as having low risk of bias, 12 had moderate risk of bias and 5 were at high risk of risk of bias. Study attrition, study participation and outcome measurement were the most common sources of risk of bias amongst included studies.

Summary of Evidence

Physical Illness:
4 studies reported on headaches as a potential risk factor, with 2 reporting no association and 2 reporting increased odds of back pain (OR [95% CI] = 2.5 [1.6, 4.1] (n = 6554) (5); OR [95% CI) = 4.5 [1.8, 11.5] (n = 212) (12)).

Abdominal pain was assessed in 3 studies, with 2 reporting increased risk of low back pain (RR [95% CI] = 1.8 [1.1, 3.0] (n = 933) (13); RR [95% CI] = 1.8 [1.3, 2.4] (n = 3271) (14)) and 1 reporting no association.

One study (15) evaluated a group of chronic conditions (arthritis, asthma, missing fingers, blindness and speech problems) and found no association with low back pain. Another study (5) reported no association between atopic disease and low back pain; however, in that study, asthma was noted to increase low back pain odds in children and young adults (OR [95% CI] = 1.3 [1.1, 1.6] (n = 6554)).

Mental Health Disorders:
5 studies reported on overall mental health status as a risk factor for low back pain, 3 of which found positive associations, with 1 demonstrating increased odds of back pain (OR [95% CI] = 1.6 [1.1, 2.4] (boys), OR [95% CI] = 1.5 [1.1, 1.9] (girls) (n = 3316) (16)).

2 studies found positive associations between depression and low back pain, with 1 showing slightly increased odds of back pain (OR [95% CI] = 1.05 [1.02, 1.08] (n = 1291) (17)), although this study looked at mid-back pain, not low back pain.

1 study considered anxiety as a risk factor and found an increase in odds of back pain (OR [95% CI] = 4.6 [1.9, 11.1] (n = 212) (12)).

Psychological Features:
6 studies considered overall psychological state as a risk factor, of which 3 found no association and 3 found positive associations: OR [95% CI] = 1.8 [1.1, 3.2] (n = 1928) (15); OR [95% CI] = 2.5 [1.6, 3.9] (n = 5781) (18); RR [95% CI] = 1.6 [1.1, 2.3] (n = 933) (13).

Individual psychological features evaluated and deemed to be positively associated with risk of LBP included:
  • conduct problems (RR [95% CI] = 2.5 [1.7, 3.7] (n = 933) (13); RR [95% CI] = 2.1 [1.3, 3.4] (n = 3271) (14)),
  • somatization (OR [95% CI] = 1.3 [1.1, 1.5] (n = 1088) (19)),
  • peer problems (RR [95% CI] 2.3 [1.2, 4.2] (n = 178) (20)),
  • emotional or behavioural disorders (OR [95% CI] = 1.87 [1.02, 3.41] (n = 1928) (15)),
  • dysfunctional coping (OR [95% CI] = 1.4 [1.1, 2.0] (boys) (n = 2040) (21)),
  • anxiety sensitivity (OR [95% CI] = 1.5 [1.1, 2.0] (boys) (n = 2040) (21), and
  • somatosensory amplification (OR [95% CI] = 1.8 [1.0, 3.1] (girls) (n = 2040) (21)).
Meta-analysis:

Physical Illness:
A positive association was noted between headaches at age 11-22 and low back pain experienced 1-8 years later (pooled RR [95% CI] = 1.9 [1.4, 2.6]; n = 7665; I2 = 0.00). A positive association was also noted between abdominal pain experienced between ages 11-14 and low back pain 1-3 years later (pooled RR [95% CI] = 1.7 [1.3, 2.2]; n = 4382; I2 = 0.00).

Mental Health Disorders:
Significant methodological and statistical heterogeneity existed between studies reporting results related to depression and overall mental health status. As such, these results were not included in the meta-analysis.

Psychological Features:
Psychological distress increased the odds of low back pain (pooled OR [95% CI] = 2.2 [1.6, 3.1]; n = 7709; I2 = 0.00), although general psychological difficulties did not (pooled RR [95% CI] = 1.4 [0.96, 1.97]; n = 1111; I2 = 28.56).

Emotional coping problems were associated with increased odds of low back pain (pooled OR [95% CI] = 1.4 [1.1, 1.8]; 3968; I2 = 0.00 and pooled OR [95% CI] = 1.4 [1.0, 1.8]; n = 3062; I2 = 86.99) based on data from 6 total studies, although 4 other studies found no such association (pooled RR [95% CI] = 1.0 [0.8, 1.3]; n = 600; I2 = 31.45).

Peer-related issues were not associated with increased risk of low back pain (pooled RR [95% CI] = 1.6 [0.9, 2.8]; n = 1111; I2 = 57.46), although conduct problems were associated with increased risk (pooled RR [95% CI] = 1.8 [1.1, 2.9]; n = 4382; I2 = 72.08). These studies found that feeling “tense”, “stressed” or “nervous” increased low back pain odds (pooled OR [95% CI] = 2.7 [1.4, 5.2]; n = 682; I2 = 42.74). Finally, hyperactivity was not associated with increased risk of low back pain (pooled RR [95% CI] = 1.2 [0.9,1.7]; n = 1111; I2 = 11.31).

Clinical Application & Conclusions:

This study found that the most likely risk factors for future low back pain in children, adolescents or young adults are psychological distress, emotional coping problems and somatosensory amplification. The authors note that limitations of the literature render conclusions based on physical illness, mental health disorders and some psychological factors unavailable. They suggest that further research in these areas are warranted. Regardless, the role of psychological distress and coping issues in future low back pain should be noted by clinicians and appropriately-aged patients should be treated and monitored accordingly.

Study Methods:

Several databases were searched: MEDLINE (Ovid MEDLINE and Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Daily and Versions), Embase, CINAHL with Full Text, and Scopus were searched from inception to 30 July 2019. A modified age filter was applied to identify paediatric studies (22).

Eligibility:
2 authors independently screened relevant articles, with a third reviewer independently screening citations where consensus could not be reached.

Specific eligibility criteria included:
  • Peer-reviewed cohort or inception cohort studies of any language investigating potential risk factors for back pain (thoracic or lumbar spine) in children, adolescents and young adults,
  • Potential risk factors included chronic physical illness, mental health disorders or other psychological factors,
  • Back pain outcomes were self-reported or clinically evaluated
  • Study participants aged 24 years or younger.
Data Extraction:
Two reviewers extracted data using a data collection form based on the Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) guideline (23).

Methodological Quality:
Risk of bias was assessed by 2 reviewers using the Quality in Prognosis Studies (QUIPS) appraisal tool modified for risk studies (24, 25). One modification was made: risk factor language, rather than prognostic factor language, was adopted by changing the word “prognostic” to “risk”.

Data Synthesis and Analysis:
When possible, data was pooled for meta-analysis, using standard meta-analytic tests for heterogeneity (Q-value and I2 statistic). For studies reporting multiple potential risk factors, a fixed effect model was used initially, followed by a random effects model to pool data between studies (26). Where possible, odds ratios were converted to risk ratios (RR = OR/(1 − P0 + (P0 × OR), where P0 is the baseline risk or the incidence of the outcome of interest in the non-exposed group (27, 28)).

Study Strengths / Weaknesses:

Strengths:
  • Very strong, comprehensive search criteria.
  • Meta-analysis of data was attempted for all outcomes and available for many potential risk factors.
  • Independent reviewers screened eligible studies and extracted eligible data.
  • Critical appraisal via the QUIPS assessment tool was used.
Weaknesses:
  • High attrition rates among studies, with reasons for loss to follow-up unreported.
  • Source population and/or selection criteria often not well described.
  • Outcome measurement (i.e. back pain) often unclear and localization of pain (i.e. mid or low back) was lacking in many studies.
  • The temporal nature of back pain was not specified in many studies.

Additional References:

  1. Hoy D, Bain C, Williams G et al. A systematic review of the global prevalence of low back pain. Arthritis Rheum 2012; 64(6): 2028–2037.
  2. Kamper SJ, Yamato TP, Williams CM. The prevalence, risk factors, prognosis and treatment for back pain in children and adolescents: an overview of systematic reviews. Best Pract Res Clin Rheumatol 2016; 30(6): 1021–1036.
  3. Global Burden of Disease II, Prevalence Collaborators (2018) Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 392(10159): 1789–1858
  4. Hartvigsen J, Hancock MJ, Kongsted A et al. What low back pain is and why we need to pay attention. Lancet 2018; 391(10137): 2356–2367
  5. Hestbaek L, Leboeuf-Yde C, Kyvik KO. Is comorbidity in adolescence a predictor for adult low back pain? A prospective study of a young population. BMC Musculoskelet Disord 2006; 7(1): 29.
  6. Hurwitz EL, Morgenstern H. Cross-sectional associations of asthma, hay fever, and other allergies with major depression and low-back pain among adults aged 20–39 years in the United States. Am J Epidemiol 1999; 150(10): 1107–1116.
  7. Holmberg S, Thelin A, Stiernstrom E, Svardsudd K. Low back pain comorbidity among male farmers and rural referents: a population-based study. Ann Agric Environ Med 2005; 12(2): 261–268.
  8. Smith MD, Russell A, Hodges PW. Do incontinence, breathing difficulties, and gastrointestinal symptoms increase the risk of future back pain? J Pain 2009; 10(8): 876–886.
  9. Ha IH, Lee J, Kim MR, Kim H, Shin JS. The association between the history of cardiovascular diseases and chronic low back pain in South Koreans: a cross-sectional study. PLoS ONE 2014; 9(4): e93671.
  10. Porta M (2014) A dictionary of epidemiology. Oxford University Press, Oxford.
  11. Ardakani EM, Leboeuf-Yde C, Walker BF. Failure to define low back pain as a disease or an episode renders research on causality unsuitable: results of a systematic review. Chiropr Man Therap 2018; 26(1): 1.
  12. Cheung K. The incidence of low back problems among nursing students in Hong Kong. J Clin Nurs 2010; 19(15–16): 2355–2362.
  13. Jones GT, Watson KD, Silman AJ et al. Predictors of low back pain in British schoolchildren: a population-based prospective cohort study. Pediatrics 2003; 111(4 Pt 1): 822–828.
  14. Muthuri SG, Kuh D, Cooper R. Longitudinal profiles of back pain across adulthood and their relationship with childhood factors: evidence from the 1946 British birth cohort. Pain 2018; 159(4): 764.
  15. Mustard CA, Kalcevich C, Frank JW, Boyle M. Childhood and early adult predictors of risk of incident back pain: Ontario Child Health Study 2001 follow-up. Am J Epidemiol 2005; 162(8): 779–786.
  16. Lien L, Green K, Thoresen M, Bjertness E. Pain complaints as risk factor for mental distress: a three-year follow-up study. Eur Child Adolesc Psychiatry 2011; 20(10): 509.
  17. Gill DK, Davis MC, Smith AJ, Straker LM. Bidirectional relationships between cigarette use and spinal pain in adolescents accounting for psychosocial functioning. Br J Health Psychol 2014; 19(1): 113–131.
  18. Power C, Frank J, Hertzman C, Schierhout G, Li L. Predictors of low back pain onset in a prospective British study. Am J Public Health 2001; 91(10): 1671–1678.
  19. Smith A, Beales D, O’Sullivan P, Bear N, Straker L. Low back pain with impact at 17 years of age is predicted by early adolescent risk factors from multiple domains: analysis of the Western Australian Pregnancy Cohort (Raine) Study. J Orthop Sports Phys Ther 2017; 47(10): 752–762.
  20. Jones GT, Macfarlane GJ. Predicting persistent low back pain in schoolchildren: a prospective cohort study. Arthr Rheum 2009; 61(10): 1359–1366.
  21. Barke A, Gabmann J, Kröner-Herwig B. Cognitive processing styles of children and adolescents with headache and back pain: a longitudinal epidemiological study. J Pain Res 2014; 7: 405.
  22. Leclercq E, Leeflang MM, van Dalen EC, Kremer LC. Validation of search filters for identifying pediatric studies in PubMed. J Pediatr 2013; 162(3): 629–634. e622
  23. Moons KG, de Groot JA, Bouwmeester W et al. Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist. PLoS Med 2014; 11(10): e1001744.
  24. Hayden JA, van der Windt DA, Cartwright JL, Côté P, Bombardier C. Assessing bias in studies of prognostic factors. Ann Intern Med 2013; 158(4): 280–286.
  25. Hayden JA, Côté P, Bombardier C. Evaluation of the quality of prognosis studies in systematic reviews. Ann Intern Med 2006; 144(6): 427–437.
  26. Borenstein M, Hedges LV, Higgins JP, Rothstein HR (2011) Introduction to meta-analysis. Wiley, Hoboken.
  27. Zhang J, Kai FY. What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA 1998; 280(19): 1690–1691.
  28. Grant RL. Converting an odds ratio to a range of plausible relative risks for better communication of research findings. BMJ 2014; 348: f7450.