Article Sidebar

Submitted
February 3, 2022
Accepted
July 6, 2022
Published
July 6, 2022
Download
Download PDF
Statistic
Read Counter : 165

Main Article Content

Abstract

Background: High inflammation levels and obesity are each linked to worse health outcomes. Low-quality sleep is linked to higher inflammation.


Method: This cross-sectional study investigated whether: individuals with low-quality sleep have higher inflammation; regardless of BMI; low-quality sleep interacts with BMI regarding cross-sectional prediction of inflammation; and whether sleep quality questions could identify this association. We utilized linear regression with 500 African American and Caucasian adults from an Adventist Health Study-2 subset, who completed additional biological indicator testing.


Results: Higher total sleep disturbance (TSD) was associated with increased C-reactive Protein (CRP), p= 0.008, (95% CI = 0.22 to 1.42). The interaction of TSD and BMI was significant in a curvilinear association, p = 0.018,(95% CI = -0.05 to -0.01). As TSD increased, CRP increased; however, the association existed primarily in obese individuals (BMI >30). Low-quality sleep is associated with increased CRP levels, which is a consistent inflammation indicator.


Conclusion: Obesity was not a risk factor for significantly increased CRP until sleep disturbance was indicated as “often” or “almost every day”. This study supports asking sleep quality questions in primary care, for early identification of risk.

Keywords

Inflammation cross-sectional sleep disturbance body mass index sleep questions primary care United States C-reactive protein obesity sleep quality

Article Details

How to Cite
Viehmann-Wical, K., Lee, J. W., Wiafe, S., Sathananthan, M., & Nelson, A. . (2022). Elevated C-Reactive Protein: Low Quality Sleep as an Inflammation Indicator . Pan-African Journal of Health and Environmental Science, 1(1). Retrieved from https://journals.aua.ke/ajhes/article/view/114
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Åkerstedt, T., Schwarz, J., Gruber, G., Lindberg, E., & Theorell-Haglöw, J. (2016). The relation between polysomnography and subjective sleep and its dependence on age - poor sleep may become good sleep. Journal of sleep research, 25(5), 565–570. https://doi.org/10.1111/jsr.12407
  2. Bassett, S. M., Lupis, S. B., Gianferante, D., Rohleder, N., & Wolf, J. M. (2015). Sleep quality but not sleep quantity effects on cortisol responses to acute psychosocial stress. Stress: The International Journal on the Biology of Stress, 18(6), 638- 644. https://doi.org/10.3109/10253890.2015.1087503
  3. Budhiraja, R., Thomas, R., Kim, M., & Redline, S. (2016). The role of big data in the management of sleep-disordered breathing. Sleep Medicine Clinics, 11(2), 241-255. https://doi.org/10.1016/j.jsmc.2016.01.009
  4. Butler, T. L., Fraser, G. E., Beeson, W. L., Knutsen, S. F., Herring, R. P., Chan, J., Sabate, J., Montgomery, S., Haddad, E., Preston- Martin, S., Bennett, H., & Jaceldo-Siegl, K. (2008). Cohort profile: The Adventist Health Study-2 (AHS-2). International Journal of Epidemiology, 37(2), 260-265. https://doi.org/10.1093/ije/dym165
  5. Castro-Diehl, C., Diez Roux, A. V., Redline, S., Seeman, T., Shrager, S. E., & Shea, S. (2015). Association of sleep duration and quality with alterations in the hypothalamic-pituitary adrenocortical axis: The multi-ethnic study of atherosclerosis (MESA). The Journal of Clinical Endocrinology and Metabolism, 100(8), 3149-3158. https://doi.org/10.1210/jc.2015-1198
  6. Chattu, V. K., Manzar, M. D., Kumary, S., Burman, D., Spence, D. W., & Pandi- Perumal, S. R. (2018). The global problem of insufficient sleep and its serious public health implications. Healthcare (Basel), 7(1). https://doi.org/10.3390/healthcare7010001
  7. Cole, J. C., Motivala, S. J., Buysse, D. J., Oxman, M. N., Levin, M. J., & Irwin, M. R. (2006). Validation of a 3-factor scoring model for the Pittsburgh sleep quality index in older adults. Sleep, 29(1), 112-116. https://pubmed.ncbi.nlm.nih.gov/16453989/
  8. IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp
  9. Ding, C., Chan, Z., & Magkos, F. (2016). Lean, but not healthy: the ‘metabolically obese, normal-weight’ phenotype. Current Opinion in Clinical Nutrition and Metabolic Care, 19(6), 408-417. https://doi.org/10.1097/mco.0000000000000317
  10. Engin, A. (2017). The definition and prevalence of obesity and metabolic syndrome. Advances in Experimental Medicine and Biology, 960, 1-17. https://doi.org/10.1007/978-3-319-48382-5_1
  11. Fair, B., Mellon, S. H., Epel, E. S., Lin, J., Révész, D., Verhoeven, J. E., Penninx, B. W., Reus, V. I., Rosser, R., Hough, C. M., Mahan, L., Burke, H. M., Blackburn, E. H., & Wolkowitz, O. M. (2017). Telomere length is inversely correlated with urinary stress hormone levels in healthy controls but not in un-medicated depressed individuals-preliminary findings. Journal of Psychosomatic Research, 99, 177-180. https://doi.org/https://doi.org/10.1016/j.jpsychores.2017.06.009
  12. Floam, S., Simpson, N., Nemeth, E., Scott- Sutherland, J., Gautam, S., & Haack, M. (2015). Sleep characteristics as predictor variables of stress systems markers in insomnia disorder. Journal of Sleep Research, 24(3), 296-304. https://doi.org/10.1111/jsr.12259
  13. Gaines, J., Vgontzas, A. N., Fernandez-Mendoza, J., & Bixler, E. O. (2018). Obstructive sleep apnea and the metabolic syndrome: The road to clinically-meaningful phenotyping, improved prognosis, and personalized treatment. Sleep Medicine Reviews, 42, 211-219. https://doi.org/10.1016/j.smrv.2018.08.009
  14. Grandner, M. A., Sands-Lincoln, M. R., Pak, V. M., & Garland, S. N. (2013). Sleep duration, cardiovascular disease, and proinflammatory biomarkers. Nat Sci Sleep, 5, 93. https://pubmed.ncbi.nlm.nih.gov/23901303/
  15. Guilleminault, C., Kirisoglu, C., & Ohayon, M. M. (2004). C-reactive protein and sleep-disordered breathing. Sleep, 27(8), 1507-1517. https://doi.org/10.1093/ sleep/27.8.1507
  16. Huang, T., Goodman, M., Li, X., Sands, S. A., Li, J., Stampfer, M. J., Saxena, R., Tworoger, S. S., & Redline, S. (2021). C-reactive protein and risk of OSA in four US cohorts. Chest, 159(6), 2439-2448. https://doi.org/https://doi.org/10.1016/j.chest.2021.01.060]
  17. Huang, W. Y., Huang, C. C., Chang, C. C., Kor, C. T., Chen, T. Y., & Wu, H. M. (2017). Associations of self-reported sleep quality with circulating interferon gamma-inducible protein 10, interleukin 6, and high-sensitivity c-reactive protein in healthy menopausal women. PloS One, 12(1), e0169216. https://doi.org/10.1371/journal.pone.0169216
  18. Jaiswal, S. J., Owens, R. L., & Malhotra, A. (2017). Raising awareness about sleep disorders. Lung India, 34(3), 262-268. https://doi.org/10.4103/0970-2113.205331
  19. Jennum, P., & Kjellberg, J. (2011). Health, social and economical consequences of sleep-disordered breathing: A controlled national study. Thorax, 66(7), 560-566. https://doi.org/10.1136/thx.2010.143958
  20. Kaplan, G. A. (2006). Alameda County [California] health and ways of living study, 1999 panel inter-university consortium for political and social research [distributor]. https://doi.org/10.3886/ICPSR04432.v1
  21. Kaufmann, C. N., Canham, S. L., Mojtabai, R., Gum, A. M., Dautovich, N. D., Kohn, R., & Spira, A. P. (2013). Insomnia and health services utilization in middle-aged and older adults: Results from the health and retirement study. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 68(12), 1512-1517. https://doi.org/10.1093/gerona/glt050
  22. Kushida, C. A., Chang, A., Gadkary, C., Guilleminault, C., Carrillo, O., & Dement, C. (2001). Comparison of actigraphic, polysomnographic, and subjective assessment of sleep parameters in sleep-disordered patients. Sleep Medicine, 2(5), 389-396. https://doi.org/10.1016/s1389-9457(00)00098-8
  23. Lee, J. W., Morton, K. R., Walters, J., Bellinger, D. L., Butler, T. L., Wilson, C., Walsh, E., Ellison, C. G., McKenzie, M. M., & Fraser, G. E. (2009). Cohort profile: The biopsychosocial religion and health study (BRHS). International Journal of Epidemiology, 38(6), 1470-1478. https://doi.org/10.1093/ije/dyn244
  24. Lin, H., Zhang, L., Zheng, R., & Zheng, Y. (2017). The prevalence, metabolic risk and effects of lifestyle intervention for metabolically healthy obesity: a systematic review and meta-analysis: A PRISMA- compliant article. Medicine (Baltimore), 96(47), e8838. https://doi.org/10.1097/md.0000000000008838
  25. Liu, R., Liu, X., Zee, P. C., Hou, L., Zheng, Z., Wei, Y., & Du, J. (2014). Association between sleep quality and C-reactive protein: results from national health and nutrition examination survey, 2005-2008. PloS One, 9(3), e92607. https://journals.plos.org/plosone/article?id=10.1371/journal. pone.0092607
  26. Massar, S. A. A., Liu, J. C. J., Mohammad, N. B., & Chee, M. W. L. (2017). Poor habitual sleep efficiency is associated with increased cardiovascular and cortisol stress reactivity in men. Psychoneuroendocrinology, 81, 151-156. https://doi.org/10.1016/j.psyneuen.2017.04.013
  27. National Heart, L., & Institute, B. (1998). Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: the evidence report. Obesity Res, 6, 51S-210S. https://www.ncbi.nlm.nih.gov/ books/NBK2003/ https://www.nhlbi.nih. gov/files/docs/guidelines/prctgd_c.pdf
  28. Nowakowski, S., Matthews, K. A., von Känel, R., Hall, M. H., & Thurston, R. C. (2018). Sleep characteristics and inflammatory biomarkers among midlife women. Sleep, 41(5). https://doi.org/10.1093/sleep/zsy049
  29. Potts, K. J., Butterfield, D. T., Sims, P., Henderson, M., & Shames, C. B. (2013). Cost savings associated with an education campaign on the diagnosis and management of sleep-disordered breathing: a retrospective, claims-based US study. Population Health Management, 16(1), 7-13. https://doi.org/10.1089/pop.2011.0102
  30. Punjabi, N. M., & Beamer, B. A. (2007). C-reactive protein is associated with sleep disordered breathing independent of adiposity. Sleep, 30(1), 29-34. https://doi.org/10.1093/sleep/30.1.29
  31. Singh-Manoux, A., Shipley, M. J., Bell, J. A., Canonico, M., Elbaz, A., & Kivimaki, M. (2017). Association between inflammatory biomarkers and all-cause, cardiovascular and cancer-related mortality. Canadian Medical Association Journal, 189(10), E384-e390. https://doi.org/10.1503/cmaj.160313
  32. Tomiyama, A. J., O’Donovan, A., Lin, J., Puterman, E., Lazaro, A., Chan, J., Dhabhar, F. S., Wolkowitz, O., Kirschbaum, C., Blackburn, E., & Epel, E. (2012). Does cellular aging relate to patterns of allostasis? An examination of basal and stress reactive HPA axis activity and telomere length. Physiology and Behavior, 106(1), 40-45. https://doi.org/10.1016/j.physbeh.2011.11.016