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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

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Abstract

Purpose

To report evidence of chronic physical illnesses, mental health disorders, and psychological features as potential risk factors for back pain in children, adolescents, and young adults.

Methods

This systematic review and meta-analysis included cohort and inception cohort studies that investigated potential risk factors for back pain in young people. Potential risk factors of interest were chronic physical illnesses, mental health disorders (e.g. depression, anxiety), and other psychological features (e.g. coping, resistance). Searches were conducted in MEDLINE, Embase, CINAHL, and Scopus from inception to July 2019.

Results

Nineteen of 2167 screened articles were included in the qualitative synthesis, and data from 12 articles were included in the meta-analysis. Evidence from inception cohort studies demonstrated psychological distress, emotional coping problems, and somatosensory amplification to be likely risk factors for back pain. Evidence from non-inception cohort studies cannot distinguish between risk factors or back pain triggers. However, we identified several additional factors that were associated with back pain. Specifically, asthma, headaches, abdominal pain, depression, anxiety, conduct problems, somatization, and ‘feeling tense’ are potential risk factors or triggers for back pain. Results from the meta-analyses demonstrated the most likely risk factors for back pain in young people are psychological distress and emotional coping problems.

Conclusion

Psychological features are the most likely risk factors for back pain in young people. Several other factors were associated with back pain, but their potential as risk factors was unclear due to risk of bias. Additional high-quality research is needed to better elucidate these relationships.

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Data availability

The data sets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

QUIPS:

Quality In Prognostic Studies tool

OR:

Odds ratio

RR:

Risk ratio

CI:

Confidence intervals

N :

Number of participants

SD:

Standard deviation

NR:

Not reported

NA:

Not applicable

BP:

Back pain

LBP:

Low back pain

MBP:

Mid-back pain

β :

Beta

BMI:

Body mass index

References

  1. 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

    Article  Google Scholar 

  2. Hoy D, Bain C, Williams G, March L, Brooks P, Blyth F, Woolf A, Vos T, Buchbinder R (2012) A systematic review of the global prevalence of low back pain. Arthritis Rheum 64(6):2028–2037. https://doi.org/10.1002/art.34347

    Article  PubMed  Google Scholar 

  3. Kamper SJ, Yamato TP, Williams CM (2016) The prevalence, risk factors, prognosis and treatment for back pain in children and adolescents: an overview of systematic reviews. Best Pract Res Clin Rheumatol 30(6):1021–1036. https://doi.org/10.1016/j.berh.2017.04.003

    Article  Google Scholar 

  4. Hartvigsen J, Hancock MJ, Kongsted A, Louw Q, Ferreira ML, Genevay S, Hoy D, Karppinen J, Pransky G, Sieper J (2018) What low back pain is and why we need to pay attention. Lancet 391(10137):2356–2367

    Article  Google Scholar 

  5. Hestbaek L, Leboeuf-Yde C, Kyvik KO (2006) Is comorbidity in adolescence a predictor for adult low back pain? A prospective study of a young population. BMC Musculoskelet Disord 7(1):29

    Article  Google Scholar 

  6. Hurwitz EL, Morgenstern H (1999) 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 150(10):1107–1116

    Article  CAS  Google Scholar 

  7. Ferreira PH, Beckenkamp P, Maher CG, Hopper JL, Ferreira ML (2013) Nature or nurture in low back pain? Results of a systematic review of studies based on twin samples. Eur J Pain 17(7):957–971

    Article  CAS  Google Scholar 

  8. Holmberg S, Thelin A, Stiernstrom E, Svardsudd K (2005) Low back pain comorbidity among male farmers and rural referents: a population-based study. Ann Agric Environ Med 12(2):261–268

    PubMed  Google Scholar 

  9. Smith MD, Russell A, Hodges PW (2009) Do incontinence, breathing difficulties, and gastrointestinal symptoms increase the risk of future back pain? J Pain 10(8):876–886. https://doi.org/10.1016/j.jpain.2009.03.003

    Article  PubMed  Google Scholar 

  10. Ha IH, Lee J, Kim MR, Kim H, Shin JS (2014) The association between the history of cardiovascular diseases and chronic low back pain in South Koreans: a cross-sectional study. PLoS ONE 9(4):e93671. https://doi.org/10.1371/journal.pone.0093671

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Currie SR, Wang J (2005) More data on major depression as an antecedent risk factor for first onset of chronic back pain. Psychol Med 35(9):1275–1282

    Article  Google Scholar 

  12. Porta M (2014) A dictionary of epidemiology. Oxford University Press, Oxford

    Book  Google Scholar 

  13. Ardakani EM, Leboeuf-Yde C, Walker BF (2018) 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 26(1):1. https://doi.org/10.1186/s12998-017-0172-9

    Article  PubMed  PubMed Central  Google Scholar 

  14. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, Clarke M, Devereaux PJ, Kleijnen J, Moher D (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med 6(7):e1000100

    Article  Google Scholar 

  15. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, Moher D, Becker BJ, Sipe TA, Thacker SB (2000) Meta-analysis of observational studies in epidemiology: a proposal for reporting. JAMA 283(15):2008–2012

    Article  CAS  Google Scholar 

  16. Wilczynski NL, Haynes RB (2003) Developing optimal search strategies for detecting clinically sound causation studies in MEDLINE. In: Proceedings of the AMIA symposium, pp 719–723

  17. Leclercq E, Leeflang MM, van Dalen EC, Kremer LC (2013) Validation of search filters for identifying pediatric studies in PubMed. J Pediatr 162(3):629–634.e622

    Article  Google Scholar 

  18. Scottish Intercollegiate Guidelines Unit SIGN Observational Studies filter. https://www.sign.ac.uk/search-filters.html. Accessed 28 June 2018

  19. Moons KG, de Groot JA, Bouwmeester W, Vergouwe Y, Mallett S, Altman DG, Reitsma JB, Collins GS (2014) Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist. PLoS Med 11(10):e1001744

    Article  Google Scholar 

  20. Hayden JA, van der Windt DA, Cartwright JL, Côté P, Bombardier C (2013) Assessing bias in studies of prognostic factors. Ann Intern Med 158(4):280–286

    Article  Google Scholar 

  21. Hayden JA, Côté P, Bombardier C (2006) Evaluation of the quality of prognosis studies in systematic reviews. Ann Intern Med 144(6):427–437

    Article  Google Scholar 

  22. Borenstein M, Hedges LV, Higgins JP, Rothstein HR (2011) Introduction to meta-analysis. Wiley, Hoboken

    Google Scholar 

  23. Zhang J, Kai FY (1998) What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA 280(19):1690–1691

    Article  CAS  Google Scholar 

  24. Grant RL (2014) Converting an odds ratio to a range of plausible relative risks for better communication of research findings. BMJ 348:f7450

    Article  Google Scholar 

  25. Higgins JP, Green S (2008) Cochrane handbook for systematic reviews of interventions. Wiley, Hoboken

    Book  Google Scholar 

  26. Higgins JP (2008) Commentary: heterogeneity in meta-analysis should be expected and appropriately quantified. Int J Epidemiol 37(5):1158–1160

    Article  Google Scholar 

  27. Rücker G, Schwarzer G, Carpenter JR, Schumacher M (2008) Undue reliance on I 2 in assessing heterogeneity may mislead. BMC Med Res Methodol 8(1):79

    Article  Google Scholar 

  28. Brattberg G (1994) The incidence of back pain and headache among Swedish school children. Qual Life Res 3(Suppl 1):S27–S31

    Article  Google Scholar 

  29. Cheung K (2010) The incidence of low back problems among nursing students in Hong Kong. J Clin Nurs 19(15–16):2355–2362

    PubMed  Google Scholar 

  30. Coenen P, Smith A, Paananen M, O’Sullivan P, Beales D, Straker L (2017) Trajectories of low back pain from adolescence to young adulthood. Arthr Care Res 69(3):403–412

    Article  Google Scholar 

  31. Dunn KM, Jordan KP, Mancl L, Drangsholt MT, Le Resche L (2011) Trajectories of pain in adolescents: a prospective cohort study. Pain 152(1):66–73

    Article  Google Scholar 

  32. Feldman DE, Shrier I, Rossignol M, Abenhaim L (2001) Risk factors for the development of low back pain in adolescence. Am J Epidemiol 154(1):30–36

    Article  CAS  Google Scholar 

  33. Gill DK, Davis MC, Smith AJ, Straker LM (2014) Bidirectional relationships between cigarette use and spinal pain in adolescents accounting for psychosocial functioning. Br J Health Psychol 19(1):113–131. https://doi.org/10.1111/bjhp.12039

    Article  PubMed  Google Scholar 

  34. Gustafsson M-L, Laaksonen C, Aromaa M, Löyttyniemi E, Salanterä S (2018) The prevalence of neck-shoulder pain, back pain and psychological symptoms in association with daytime sleepiness–a prospective follow-up study of school children aged 10 to 15. Scand J Pain 18(3):389–397

    Article  Google Scholar 

  35. Jones GT, Macfarlane GJ (2009) Predicting persistent low back pain in schoolchildren: a prospective cohort study. Arthr Rheum 61(10):1359–1366. https://doi.org/10.1002/art.24696

    Article  Google Scholar 

  36. Jones GT, Watson KD, Silman AJ, Symmons DP, Macfarlane GJ (2003) Predictors of low back pain in British schoolchildren: a population-based prospective cohort study. Pediatrics 111(4 Pt 1):822–828

    Article  Google Scholar 

  37. Kanchanomai S, Janwantanakul P, Pensri P, Jiamjarasrangsi W (2015) A prospective study of incidence and risk factors for the onset and persistence of low back pain in Thai university students. Asia Pac J Public Health 27(2):Np106–115. https://doi.org/10.1177/1010539511427579

    Article  PubMed  Google Scholar 

  38. Lien L, Green K, Thoresen M, Bjertness E (2011) Pain complaints as risk factor for mental distress: a three-year follow-up study. Eur Child Adolesc Psychiatry 20(10):509

    Article  Google Scholar 

  39. Mikkonen P, Heikkala E, Paananen M, Remes J, Taimela S, Auvinen J, Karppinen J (2016) Accumulation of psychosocial and lifestyle factors and risk of low back pain in adolescence: a cohort study. Eur Spine J 25(2):635–642. https://doi.org/10.1007/s00586-015-4065-0

    Article  PubMed  Google Scholar 

  40. Muthuri SG, Kuh D, Cooper R (2018) Longitudinal profiles of back pain across adulthood and their relationship with childhood factors: evidence from the 1946 British birth cohort. Pain 159(4):764

    Article  Google Scholar 

  41. Smith A, Beales D, O’Sullivan P, Bear N, Straker L (2017) 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 47(10):752–762. https://doi.org/10.2519/jospt.2017.7464

    Article  PubMed  Google Scholar 

  42. Stanford EA, Chambers CT, Biesanz JC, Chen E (2008) The frequency, trajectories and predictors of adolescent recurrent pain: a population-based approach. Pain 138(1):11–21

    Article  Google Scholar 

  43. Barke A, Gaßmann J, Kröner-Herwig B (2014) Cognitive processing styles of children and adolescents with headache and back pain: a longitudinal epidemiological study. J Pain Res 7:405

    Article  Google Scholar 

  44. Mustard CA, Kalcevich C, Frank JW, Boyle M (2005) Childhood and early adult predictors of risk of incident back pain: Ontario Child Health Study 2001 follow-up. Am J Epidemiol 162(8):779–786. https://doi.org/10.1093/aje/kwi271

    Article  CAS  PubMed  Google Scholar 

  45. Power C, Frank J, Hertzman C, Schierhout G, Li L (2001) Predictors of low back pain onset in a prospective British study. Am J Public Health 91(10):1671–1678

    Article  CAS  Google Scholar 

  46. Huguet A, Tougas ME, Hayden J, McGrath PJ, Stinson JN, Chambers CT (2016) Systematic review with meta-analysis of childhood and adolescent risk and prognostic factors for musculoskeletal pain. Pain 157(12):2640–2656

    Article  Google Scholar 

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Acknowledgements

We would like to thank Cody Davenport for his assistance with the study screening process.

Funding

This study was funded by a scholarship from Murdoch University, Western Australia and funding provided by Chiropractic Australia Research Foundation. JH receives salary support from the Canadian Chiropractic Research Foundation and the New Brunswick Health Research Foundation. The funding sources had no involvement in study design, analysis, interpretation, or manuscript preparation.

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Authors

Contributions

AB, JH, and BW were involved with the concept and design of the study. LB conducted the searches. AB and CH conducted study selection and data extraction. AB analysed and interpreted the data with the assistance of BW, JH, and CH. AB drafted the manuscript and performed revisions with substantial feedback and editing from all authors. All authors read and approved the final manuscript.

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Correspondence to Amber M. Beynon.

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The authors declare that they have no conflict of interest.

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Beynon, A.M., Hebert, J.J., Hodgetts, C.J. et al. 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. Eur Spine J 29, 480–496 (2020). https://doi.org/10.1007/s00586-019-06278-6

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