Better sleep, better life? How sleep quality influences children’s life satisfaction

Abstract

Purpose

To assess the association between children’s sleep quality and life satisfaction; and to evaluate the underlying mechanisms of this relationship.

Methods

Three pediatric cohorts in the National Institutes of Health (NIH) Environmental influences on Child Health (ECHO) Research Program administered Patient-Reported Outcome Measurement Information System (PROMIS®) parent-proxy measures to caregivers (n = 1111) who reported on their 5- to 9-year-old children’s (n = 1251) sleep quality, psychological stress, general health, and life satisfaction; extant sociodemographic data were harmonized across cohorts. Bootstrapped path modeling of individual patient data meta-analysis was used to determine whether and to what extent stress and general health mediate the relationship between children’s sleep quality and life satisfaction.

Results

Nonparametric bootstrapped path analyses with 1000 replications suggested children’s sleep quality was associated with lower levels of stress and better general health, which, in turn, predicted higher levels of life satisfaction. Family environmental factors (i.e., income and maternal mental health) moderated these relationships.

Conclusion

Children who sleep well have happier lives than those with more disturbed sleep. Given the modifiable nature of children’s sleep quality, this study offers evidence to inform future interventional studies on specific mechanisms to improve children’s well-being.

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Fig. 1

Abbreviations

ANOVA:

Analysis of variance

CFI:

Comparative fit index

CI:

Confidence interval

ECHO:

Environmental influences on Child Health Outcomes

HRQoL:

Health-Related Quality of Life

LRT:

Likelihood ratio test

NIH:

National Institutes of Health

PROMIS:

Patient-Reported Outcomes Measurement Information System

RMSEA:

Root Mean Square Error of Approximation

SD:

Standard deviation

SRMR:

Standardized root mean squared residual

TLI:

Tucker–Lewis Index

References

  1. 1.

    Buysse, D. J. (2014). Sleep health: Can we define it? Does it matter? Sleep, 37(1), 9–17.

    PubMed  PubMed Central  Google Scholar 

  2. 2.

    Ohayon, M., et al. (2017). National Sleep Foundation's sleep quality recommendations: First report. Sleep Health, 3(1), 6–19.

    PubMed  Google Scholar 

  3. 3.

    US Department of Health and Human Services. (2014). 2020 Topics & objectives: Sleep health. Washington, DC: US Department of Health and Human Services.

    Google Scholar 

  4. 4.

    US Department of Health and Human Services. Secretary’s Advisory Committee on National Health Promotion and Disease Prevention Objectives for 2030. (2019). Report #7: Assessment and Recommendations for Proposed Objectives for Healthy People 2030. Washington, DC.

  5. 5.

    Hawkins, S. S., & Takeuchi, D. T. (2016). Social determinants of inadequate sleep in US children and adolescents. Public Health, 138, 119–126.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Hatzinger, M., et al. (2008). Electroencephalographic sleep profiles and hypothalamic-pituitary-adrenocortical (HPA)-activity in kindergarten children: Early indication of poor sleep quality associated with increased cortisol secretion. Journal of Psychiatric Research, 42(7), 532–543.

    PubMed  Google Scholar 

  7. 7.

    Javaheri, S., et al. (2008). Sleep quality and elevated blood pressure in adolescents. Circulation, 118(10), 1034–1040.

    PubMed  PubMed Central  Google Scholar 

  8. 8.

    Van Cauter, E., & Knutson, K. L. (2008). Sleep and the epidemic of obesity in children and adults. European Journal of Endocrinology, 159(Suppl 1), S59–66.

    PubMed  PubMed Central  Google Scholar 

  9. 9.

    Gregory, A. M., & Sadeh, A. (2012). Sleep, emotional and behavioral difficulties in children and adolescents. Sleep Medicine Reviews, 16(2), 129–136.

    PubMed  Google Scholar 

  10. 10.

    Beebe, D. W. (2011). Cognitive, behavioral, and functional consequences of inadequate sleep in children and adolescents. Pediatric Clinics of North America, 58(3), 649–665.

    PubMed  PubMed Central  Google Scholar 

  11. 11.

    Matricciani, L., et al. (2019). Children’s sleep and health: A meta-review. Sleep Medicine Reviews, 46, 136–150.

    PubMed  Google Scholar 

  12. 12.

    Wong, M. M., et al. (2004). Sleep problems in early childhood and early onset of alcohol and other drug use in adolescence. Alcoholism: Clinical & Experimental Research, 28(4), 578–587.

    Google Scholar 

  13. 13.

    Reidy, B. L., et al. (2016). Prospective associations between chronic youth sleep problems and young adult health. Sleep Health, 2(1), 69–74.

    PubMed  Google Scholar 

  14. 14.

    Richards, M., & Huppert, F. A. (2011). Do positive children become positive adults? Evidence from a longitudinal birth cohort study. The Journal of Positive Psychology, 6(1), 75–87.

    PubMed  PubMed Central  Google Scholar 

  15. 15.

    Steptoe, A., et al. (2008). Positive affect, psychological well-being, and good sleep. Journal of Psychosomatic Research, 64(4), 409–415.

    PubMed  Google Scholar 

  16. 16.

    Strine, T. W., & Chapman, D. P. J. S. M. (2005). Associations of frequent sleep insufficiency with health-related quality of life and health behaviors. Sleep Medicine, 6(1), 23–27.

    PubMed  Google Scholar 

  17. 17.

    Perkinson-Gloor, N., Lemola, S., & Grob, A. (2013). Sleep duration, positive attitude toward life, and academic achievement: The role of daytime tiredness, behavioral persistence, and school start times. Journal of Adolescent, 36(2), 311–318.

    Google Scholar 

  18. 18.

    Roberts, R. E., Roberts, C. R., & Duong, H. T. (2009). Sleepless in adolescence: Prospective data on sleep deprivation, health and functioning. Journal of Adolescent, 32(5), 1045–1057.

    Google Scholar 

  19. 19.

    Magee, C. A., Robinson, L., & Keane, C. (2017). Sleep quality subtypes predict health-related quality of life in children. Sleep Medicine, 35, 67–73.

    PubMed  Google Scholar 

  20. 20.

    Huebner, E. S. (1991). Initial development of the student’s life satisfaction scale. School Psychology International, 12, 231–240.

    Google Scholar 

  21. 21.

    Huebner, E. S. (1994). Preliminary development and validation of a multidimensional life satisfaction scale for children. Psychological Assessment, 6(2), 149–158.

    Google Scholar 

  22. 22.

    Bevans, K. B., Riley, A. W., & Forrest, C. B. (2010). Development of the healthy pathways child-report scales. Quality of Life Research, 19(8), 1195–1214.

    PubMed  PubMed Central  Google Scholar 

  23. 23.

    Bevans, K. B., Riley, A. W., & Forrest, C. B. (2012). Development of the healthy pathways parent-report scales. Quality of Life Research, 21(10), 1755–1770.

    PubMed  Google Scholar 

  24. 24.

    Proctor, C. L., Linley, P. A., & Maltby, J. (2009). Youth life satisfaction: A review of the literature. Journal of Happiness Studies, 10, 583–630.

    Google Scholar 

  25. 25.

    Huebner, E. S., et al. (2004). Life satisfaction in children and youth: Empirical foundations and implications for school psychologists. Psychology in the Schools, 41(1), 81–93.

    Google Scholar 

  26. 26.

    Gilman, R., & Huebner, S. (2003). A review of life satisfaction research with children and adolescents. Sch Psych Q, 18, 192–205.

    Google Scholar 

  27. 27.

    Forrest, C. B., et al. (2018). Development and psychometric evaluation of the PROMIS® Pediatric Life Satisfaction item banks, child-report, and parent-proxy editions. Quality of Life Research, 27(1), 217–234.

    PubMed  Google Scholar 

  28. 28.

    Forrest, C. B., et al. (2014). Development of the PROMIS® pediatric global health (PGH-7) measure. Quality of Life Research, 23(4), 1221–1231.

    PubMed  Google Scholar 

  29. 29.

    Bevans, K. B., et al. (2018). Psychometric evaluation of the PROMIS® pediatric psychological and physical stress experiences measures. Journal of Pediatric Psychology, 43(6), 678–692.

    PubMed  PubMed Central  Google Scholar 

  30. 30.

    Suldo, S. M., & Huebner, E. S. (2004). Does life satisfaction moderate the effects of stressful life events on psychopathological behavior during adolescence? School Psychology Quarterly, 19(2), 93–105.

    Google Scholar 

  31. 31.

    Benham, G. (2010). Sleep: An important factor in stress-health models. Stress and Health, 26(3), 204–214.

    Google Scholar 

  32. 32.

    Forrest, C. B., et al. (2018). Development and validation of the PROMIS® Pediatric Sleep Disturbance and Sleep-Related Impairment item banks. Sleep, 41(6), zsy54.

    Google Scholar 

  33. 33.

    Blackwell, C. K., et al. (2019). For the ECHO Consortium. General health and life satisfaction in children with chronic illness. Pediatrics, 143(6), e20182988.

    PubMed  PubMed Central  Google Scholar 

  34. 34.

    Gillman, M. W., & Blaisdell, C. J. (2018). Environmental influences on child health outcomes, a research program of the National Institutes of Health. Current Opinion in Pediatrics, 30(2), 260–262.

    PubMed  PubMed Central  Google Scholar 

  35. 35.

    Forrest, C. B., et al. (2012). Commentary: The patient-reported outcome measurement information system (PROMIS®) for children and youth: Application to pediatric psychology. Journal of Pediatric Psychology, 37(6), 614–621.

    PubMed  PubMed Central  Google Scholar 

  36. 36.

    Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  37. 37.

    Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). New York: Guilford Publications.

    Google Scholar 

  38. 38.

    Yung, Y. F., & Bentler, P. M. (1996). Bootstrapping techniques in analysis of mean and covariance structures. In G. A. Marcoulides & R. E. Schumacker (Eds.), Advanced structural equation modeling: Issues and techniques (pp. 195–226). New York: Lawrence Erlbaum Associates Inc.

    Google Scholar 

  39. 39.

    Fan, X. (2003). Using commonly available software for bootstrapping in both substantive and measurement analyses. Educational and Psychological Measurement, 63(1), 24–50.

    Google Scholar 

  40. 40.

    Gitterman, B. A., et al. (2016). Poverty and child health in the United States. Pediatrics, 137(4), e20160339.

    Google Scholar 

  41. 41.

    Bannink, R., Pearce, A., & Hope, S. (2016). Family income and young adolescents’ perceived social position: Associations with self-esteem and life satisfaction in the UK Millennium Cohort Study. Archives Disease Childhood, 101(10), 917–921.

    Google Scholar 

  42. 42.

    Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

    Google Scholar 

  43. 43.

    McEwen, B. S. (2006). Sleep deprivation as a neurobiologic and physiologic stressor: Allostasis and allostatic load. Metabolism, 55, S20–S23.

    CAS  PubMed  Google Scholar 

  44. 44.

    Barber, L. K., & Munz, D. C. (2011). Consistent-sufficient sleep predicts improvements in self-regulatory performance and psychological strain. Stress and Health, 27(4), 314–324.

    Google Scholar 

  45. 45.

    C.S. Mott Children’s Hospital National Poll on Children’s Health. (2017).

  46. 46.

    Hale, L., et al. (2018). Youth screen media habits and sleep: Sleep-friendly screen behavior recommendations for clinicians, Educators, and Parents. Child and Adolescent Psychiatric Clinics, 27(2), 229–245.

    Google Scholar 

  47. 47.

    Mindell, J. A., Meltzer, L., Carskadon, M. A., & Chervin, R. D. (2009). Developmental aspects of sleep hygiene: Findings from the 2004 National Sleep Foundation Sleep in America Poll. Sleep Medicine, 10(7), 771–779.

    PubMed  Google Scholar 

  48. 48.

    Wartella, E. A., et al. (2013). Parenting in the age of digital technology: A national survey. Evanston, IL: Center on Media and Human Development, School of Communication, Northwestern University.

    Google Scholar 

  49. 49.

    Taylor, B., et al. (2011). Prevention of overweight in infancy (POI. nz) study: A randomised controlled trial of sleep, food and activity interventions for preventing overweight from birth. BMC Public Health, 11(1), 942.

    PubMed  PubMed Central  Google Scholar 

  50. 50.

    Garrison, M., & Christakis, D. (2012). The impact of a healthy media use intervention on sleep in preschool children. Pediatrics, 130(2), 492–499.

    PubMed  PubMed Central  Google Scholar 

  51. 51.

    Bowers, J., & Moyer, A. (2017). Effects of school start time on students’ sleep duration, daytime sleepiness, and attendance: A meta-analysis. Sleep Health, 3(6), 423–431.

    PubMed  Google Scholar 

  52. 52.

    Keller, P., et al. (2017). Earlier school start times are associated with higher rates of behavioral problems in elementary schools. Sleep Health, 3(2), 113–118.

    PubMed  Google Scholar 

  53. 53.

    Bin, Y. S. (2016). Is sleep quality more important than sleep duration for public health? Sleep, 39(9), 1629–1630.

    PubMed  PubMed Central  Google Scholar 

  54. 54.

    Upton, P., Lawford, J., & Eiser, C. J. Q. O. L. R. (2008). Parent–child agreement across child health-related quality of life instruments: A review of the literature. Quality of Life Research, 17(6), 895.

    PubMed  Google Scholar 

  55. 55.

    McGreavey, J., et al. (2005). The Tayside children's sleep questionnaire: A simple tool to evaluate sleep problems in young children. Child: Care, Health and Development, 31(5), 539–544.

    CAS  Google Scholar 

  56. 56.

    Bruni, O., et al. (1996). The Sleep Disturbance Scale for Children (SDSC) Construct ion and validation of an instrument to evaluate sleep disturbances in childhood and adolescence. Journal of Sleep Research, 5(4), 251–261.

    CAS  PubMed  Google Scholar 

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Acknowledgements

The authors wish to thank our ECHO colleagues, the medical, nursing and program staff, as well as the children and families participating in the ECHO cohorts.

Funding

Research reported in this publication was supported by the Environmental influences on Child Health Outcomes (ECHO) program, Office of The Director, National Institutes of Health, under Award Numbers U2COD023375 (Coordinating Center), U24OD023319 with co-funding from the Office of Behavioral and Social Sciences Research (OBSSR; Person Reported Outcomes Core, Blackwell & Forrest), UG3/UH3OD023313 (LeBourgeois & Hartstein); UG3/UH3OD023279 (Elliott), UG3/UH3OD023389 (Ganiban), UG3OD023316 (Hunt), and UG3/UH3OD023253 (Camargo). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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We also acknowledge the contributions of the following ECHO program collaborators: Duke Clinical Research Institute (Coordinating Center), Durham, NC: DKB, PBS, KLN, HB. Medical University of South Carolina, Charleston, SC: JEV, RW. National Institutes of Health (ECHO Program Office), Bethesda, MD: CB. Northwestern University (Person Reported Outcomes (PRO) Core), Evanston, IL: RG, DC. University of Oregon, Eugene, OR: LDL.

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Correspondence to Courtney K. Blackwell.

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Blackwell, C.K., Hartstein, L.E., Elliott, A.J. et al. Better sleep, better life? How sleep quality influences children’s life satisfaction. Qual Life Res 29, 2465–2474 (2020). https://doi.org/10.1007/s11136-020-02491-9

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Keywords

  • ECHO
  • Life satisfaction
  • Positive health
  • Sleep quality
  • Well-being