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Baseline musculoskeletal pain and impaired sleep related to school pressure influence the development of musculoskeletal pain in N = 107 adolescents in a 5-year longitudinal study

  • C. Rolli SalathéEmail author
  • W. Kälin
  • S. Zilse
  • A. Elfering
Original Article

Abstract

Purpose

This longitudinal study followed 10- to 13-year-old adolescents for 5 years to investigate the effects of juvenile musculoskeletal (MSK) pain and psychosocial risk factors on future pain. We further predicted that increased MSK pain at follow-up would be positively related to current school pressure at follow-up and negatively related to current sleep quality. Sleep quality was tested as a potential mediator of the link between school pressure and MSK pain at follow-up after controlling for baseline MSK pain.

Methods

The baseline sample comprised 189 adolescents, and 5-year follow-up resulted in 107 15- to 18-year-old adolescents who had completed mandatory education. Adolescents responded to an online questionnaire about psychosocial stressors, MSK pain, school achievement and leisure activities. A longitudinal hierarchic linear regression including all significant baseline predictors was run to assess their impact on MSK pain 5 years later. Mediation analysis was used to investigate sleep quality as a potential mediator of the relationship between school pressure and MSK pain at follow-up.

Results

Baseline MSK pain predicted MSK pain over a time lag of 5 years (ß = .26, p = .02). The relationship between follow-up school pressure and current MSK pain was mediated by sleep quality at follow-up (B = .17, SEB = .07, 95% CI .06–.34) when baseline MSK pain was controlled.

Conclusions

Juvenile MSK pain predicts MSK pain in adolescence. A psychosocial mediation model including school pressure and sleep impairments has the potential to explain MSK pain mechanisms in adolescents.

Graphic abstract

These slides can be retrieved under Electronic Supplementary Material.

Keywords

Musculoskeletal pain Longitudinal analysis Adolescents Psychosocial risk factors Sleep quality School characteristics 

Notes

Acknowledgements

We would like to thank Cordula Erne, M.Sc., for her support and Charlotte Holzer, M.Sc., and Manuela Luterbacher, M.Sc., for their work and support to this study.

Compliance with ethical standards

Conflict of interest

None of the authors has a potential conflict of interest.

Supplementary material

586_2019_6211_MOESM1_ESM.pptx (281 kb)
Supplementary material 1 (PPTX 280 kb)

References

  1. 1.
    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 30:1021–1036.  https://doi.org/10.1016/j.berh.2017.04.003 CrossRefPubMedGoogle Scholar
  2. 2.
    Lazary A, Szövérfi Z, Szita J, Somhegyi A, Kümin M, Varga PP (2014) Primary prevention of disc degeneration-related symptoms. Eur Spine J 23(Suppl 3):S385–S393.  https://doi.org/10.1007/s00586-013-3069-x CrossRefPubMedGoogle Scholar
  3. 3.
    Kamper SJ, Henschke N, Hestbaek L, Dunn KM, Williams CM (2016) Musculoskeletal pain in children and adolescents. Braz J Phys Ther 20:275–284.  https://doi.org/10.1590/bjptrbf.2014.0149 CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Trevelyan FC, Legg SJ (2006) Back pain in school children—where to from here? Appl Ergon 37:45–54.  https://doi.org/10.1016/j.apergo.2004.02.008 CrossRefPubMedGoogle Scholar
  5. 5.
    Clinch J, Eccleston C (2009) Chronic musculoskeletal pain in children: assessment and management. Rheumatology 48:466–474.  https://doi.org/10.1093/rheumatology/kep001 CrossRefPubMedGoogle Scholar
  6. 6.
    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 157:2640–2656.  https://doi.org/10.1097/j.pain.0000000000000685 CrossRefPubMedGoogle Scholar
  7. 7.
    El-Metwally A, Mikkelsson M, Ståhl M, Macfarlane GJ, Jones GT, Pulkkinen L, Rose RJ, Kaprio J (2008) Genetic and environmental influences on non-specific low back pain in children: a twin study. Eur Spine J 17:502–508.  https://doi.org/10.1007/s00586-008-0605-1 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Balagué F, Troussier B, Salminen JJ (1999) Non-specific low back pain in children and adolescents: risk factors. Eur Spine J 8:429–438.  https://doi.org/10.1007/s005860050201 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Erne C, Elfering A (2011) Low back pain at school: unique risk deriving from unsatisfactory grade in maths and school-type recommendation. Eur Spine J 20:2126–2133.  https://doi.org/10.1007/s00586-011-1803-9 CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Zhang Y, Deng G, Zhang Z, Zhou Q, Gao X, Di L, Che Q, Du X, Cai Y, Han X, Zhao Q (2015) A cross sectional study between the prevalence of chronic pain and academic pressure in adolescents in China (Shanghai). BMC Musculoskel Dis 16:219.  https://doi.org/10.1186/s12891-015-0625-z CrossRefGoogle Scholar
  11. 11.
    Zhou L, Huang YY, Chen DY, Zhang D, Luo QS, Wang Y, Wu Y (2018) Correlation between both neck/shoulder and low back pain and daily behavioral habits among middle school students in Shenzhen. Zhonghua Liuxingbingxue Zazhi 39:469–473.  https://doi.org/10.3760/cma.j.issn.0254-6450.2018.04.016(in Chinese) CrossRefPubMedGoogle Scholar
  12. 12.
    Wiklund M, Malmgren-Olsson E-B, Öhman A, Bergström E, Fjellman-Wiklund A (2012) Subjective health complaints in older adolescents are related to perceived stress, anxiety and gender—a cross-sectional school study in Northern Sweden. BMC Public Health 12:993.  https://doi.org/10.1186/1471-2458-12-993 CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Østerås B, Sigmundsson H, Haga M (2015) Perceived stress and musculoskeletal pain are prevalent and significantly associated in adolescents: an epidemiological cross-sectional study. BMC Public Health 15:1081.  https://doi.org/10.1186/s12889-015-2414-x CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Torsheim T, Wold B (2001) School-related stress, school support, and somatic complaints. A general populations study. J Adolesc Res 16:293–303.  https://doi.org/10.1177/0743558401163003 CrossRefGoogle Scholar
  15. 15.
    Murberg TA, Bru E (2004) School-related stress and psychosomatic symptoms among Norwegian adolescents. School Psychol Int 25:317–332.  https://doi.org/10.1177/0143034304046904 CrossRefGoogle Scholar
  16. 16.
    Kottwitz MU, Rolli Salathé C, Buser C, Elfering A (2017) Emotion work and musculoskeletal pain in supermarket cashiers: a test of a sleep-mediation model. Scand J Work Organ Psychol 2:1–13.  https://doi.org/10.16993/sjwop.25 CrossRefGoogle Scholar
  17. 17.
    Andersen T, Christensen FB, Høy KW, Helmig P, Niedermann B, Hansen ES, Bünger C (2010) The predictive value of pain drawings in lumbar spinal fusion surgery. Spine J 10:372–379.  https://doi.org/10.1016/j.spinee.2010.02.002 CrossRefPubMedGoogle Scholar
  18. 18.
    Eschenbeck H, Lohaus A, Kohlmann CW (2007) Instrumente zur Erfassung von Stress und Coping im Kindesalter (Stress and coping assessment instruments in children). In: Seiffge-Krenke I, Lohaus A (eds) Stress und Stressbewältigung im Kindes- und Jugendalter. Hogrefe, Göttingen, pp 29–46Google Scholar
  19. 19.
    Hayes AF (2017) Introduction to mediation, moderation, and conditional process analysis. A regression-based approach, 2nd edn. Guilford Press, New YorkGoogle Scholar
  20. 20.
    Preacher KJ, Hayes AF (2008) Asymptomatic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods 40:879–891.  https://doi.org/10.3758/BRM.40.3.879 CrossRefPubMedGoogle Scholar
  21. 21.
    Winsper C (2018) Sleep disorders: prevalence and assessment in childhood. In: Matson J (ed) Handbook of childhood psychopathology and developmental disabilities assessment. Springer Nature, Cham, pp 331–357CrossRefGoogle Scholar
  22. 22.
    Harrison L, Wilson S, Munafò MR (2016) Pain-related and psychological symptoms in adolescents with musculoskeletal and sleep problems. Clin J Pain 32:246–253.  https://doi.org/10.1097/AJP.0000000000000252 CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Silva AG, Sa-Couto P, Queirós A, Neto M, Rocha NP (2017) Pain, pain intensity and pain disability in high school students are differently associated with physical activity, screening hours and sleep. BMC Musculoskel Dis 18:194.  https://doi.org/10.1186/s12891-017-1557-6 CrossRefGoogle Scholar
  24. 24.
    Yabe Y, Hagiwara Y, Sekiguchi T, Momma H, Tsuchiya M, Kuroki K, Kanazawa K, Koide M, Itaya N, Itoi E, Nagatomi R (2018) Late bedtimes, short sleeping time, and longtime video-game playing are associated with low back pain in school-aged athletes. Eur Spine J 27:1112–1118.  https://doi.org/10.1007/s00586-017-5177-5 CrossRefPubMedGoogle Scholar
  25. 25.
    Auvinen JP, Tammelin TH, Taimela SP, Zitting PJ, Järvelin M-R, Taanila AM, Karppinen JI (2010) Is insuffient quantity and quality of sleep a risk factor for neck, shoulder and low back pain? A longitudinal study among adolescents. Eur Spine J 19:641–649.  https://doi.org/10.1007/s00586-009-1215-2 CrossRefPubMedGoogle Scholar
  26. 26.
    Szita J, Boja S, Szilagyi A, Somhegyi A, Varga PP, Lazary A (2018) Risk factors of non-specific spinal pain in childhood. Eur Spine J 27:1119–1126.  https://doi.org/10.1007/s00586-018-5516-1 CrossRefPubMedGoogle Scholar
  27. 27.
    Rutherford C, Costa D, Mercieca-Bebber R, Rice H, Gabb L, King M (2016) Mode of administration does not cause bias in patient-reported outcome results: a meta-analysis. Qual Life Res 25:559–574.  https://doi.org/10.1007/s11136-015-1110-8 CrossRefPubMedGoogle Scholar
  28. 28.
    Shapka JD, Domene JF, Khan S, Yang LM (2016) Online versus in-person interviews with adolescents: an exploration of data equivalence. Comput Hum Behav 58:361–367.  https://doi.org/10.1016/j.chb.2016.01.016 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Psychology, Institute for PsychologyUniversity of BernBernSwitzerland
  2. 2.National Centre of Competence in Research, Affective Sciences, CISAUniversity of GenevaGenevaSwitzerland

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