Journal of Korean Biological Nursing Science

Korean society of Biological Nursing Science (한국기초간호학회)
권호 표지
DOI QR코드

DOI QR Code

Identification of Risky Subgroups with Sleep Problems Among Adult Cancer Survivors Using Decision-tree Analyses: Based on the Korean National Health and Nutrition Examination Survey from 2013 to 2016

의사결정나무 분석을 이용한 성인 암경험자의 문제수면 위험군 예측: 2013-2016년도 국민건강영양조사 자료 분석

  • Kim, Hee Sun (College of Nursing.Research Institute of Nursing Science, Chonbuk National University) ;
  • Jeong, Seok Hee (College of Nursing.Research Institute of Nursing Science, Chonbuk National University) ;
  • Park, Sook Kyoung (College of Nursing.Research Institute of Nursing Science, Chonbuk National University)
  • 김희선 (전북대학교 간호대학.간호과학연구소) ;
  • 정석희 (전북대학교 간호대학.간호과학연구소) ;
  • 박숙경 (전북대학교 간호대학.간호과학연구소)
  • Received : 2018.04.16
  • Accepted : 2018.05.16
  • Published : 2018.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose: This study was performed to assess problems associated with sleep (short and long sleep duration) and to identify risky subgroups with sleep problems among adult cancer survivors. The study is based on the Korea National Health and Nutrition Examination Survey (KNHANES VI and VII) from 2013 to 2016. Methods: The sociodemographic and clinical data of 504 Korean cancer survivors aged 20-64 years was extracted from the KNHANES VI and VII database. Descriptive statistics for complex samples was used, and decision-tree analyses were performed using the SPSS WIN 24.0 program. Results: The mean age for survivors was approximately 51 years. The mean sleep duration was 6.97 hours; 36.2% of participants had short (< 7 hours) and 9.9% had long (> 8 hours) sleep duration. From the decision-trees analyses, the characteristics of the adult cancer survivors related to sleep problems were presented with six different pathways. Sleep problems were analyzed according to the survivors' sociodemographic information (age, education, living status, and occupation), clinical characteristics (body mass index, hypercholesterolemia, and anemia) and health-related quality of life (HRQoL). The HRQoL (${\leq}0.5$ or > 0.5 cutoff point) was a significant predictor of the participants' sleep problems because all six pathways were started from this predictor in the model. Conclusion: Health care professionals could use the decision-tree model for screening adult cancer survivors with sleep problems in clinical or community settings. Nursing interventions considering these specific individual characteristics and HRQoL level should be developed to have adequate sleep duration for Korean adult cancer survivors.

Keywords

References

  1. Lee HK. Factors influencing sleep in people with alcoholism. Journal of Korean Academic Psychiatric Mental Health Nursing. 2010;19(3):271-277. http://doi.org/10.12934/jkpmhn.2010.19.3.271
  2. Alvarez GG, Ayas NT. The impact of daily sleep duration on health: a review of the literature. Progress in Cardiovascular Nursing. 2004;19(2):56-59. http://doi.org/10.1111/j.0889-7204.2004.02422.x
  3. Gottlieb DJ, Redline S, Nieto FJ, Baldwin CM, Newman AB, Resnick HE, et al. Association of usual sleep duration with hypertension: The sleep heart health study. Sleep. 2006;29(8):1009-1014. http://doi.org/10.1093/sleep/29.8.1009
  4. Gottlieb DJ, Punjabi NM, Newman AB, Resnick HE, Redline S, Baldwin CM, et al. Association of sleep time with diabetes mellitus and impaired glucose tolerance. Archives Internal Medicine. 2005;165(8):863-867. http://doi.org/10.1001/archinte.165.8.863
  5. Taheri S, Lin L, Austin D, Young T, Mignot E. Short sleep duration is associated with reduced leptin, elevated ghrelin, and increased body mass index. PLoS Medicine. 2004;1(3):e62. http://doi.org/10.1371/journal.pmed.0010062
  6. Kim SY. Factors related to sleep duration in Korean adults. Journal of the Korean Data Information Science Society. 2018;29(1):153-165. http://doi.org/10.7465/jkdi.2018.29.1.153
  7. Yeo Y, Ma SH, Park SK, Chang SH, Shin HR, Kang D, et al. A prospective cohort study on the relationship of sleep duration with all-cause and disease specific mortality in the Korean multi-center cancer cohort study. Journal of Preventive Medicine & Public Health. 2013;46(5):271-281. http://doi.org/10.3961/jpmph. 2013.46.5.271
  8. Shin DW, Sunwoo S, Lee JK. Management of cancer survivors in Korea. Journal of Korean Med Association. 2015;58(3):216-226.http://doi.org/10.5124/jkma.2015.58.3.216
  9. Ministry of Health and Welfare, Korean Central Cancer Registry. National cancer registry statistics for 2014. Annual report. Seoul: National Cancer Center;2016 Dec. Report No.: 11-1352000-00145-10.
  10. Hammersen F, Lewin P, Gebauer J, Andermahr JK, Brabant G, Katalinic A, et al. Sleep quality and health-related quality of life among long-term survivors of (non-) Hodgkin lymphoma in Germany. PLoS One. 2017;12(11):e0187673. http://doi.org/10.1371/journal.pone.0187673
  11. Osthus AA, Aarstad AK, Olofsson J, Aarstad HJ. Prediction of survival by pretreatment health-related quality-of-life scores in a prospective cohort of patients with head and neck squamous cell carcinoma. JAMA Otolaryngo Head Neck Surgical. 2013;139(1):14-20. http://doi.org/10.1001/jamaoto.2013.1056
  12. Lim JT, Oh MK, Kim HK, Lee JH, Lee BS, Park SY. The relationship between the sleep duration and health-related quality of life (HRQL) in Korea-using data from the Korea National Health and Nutrition Examination Survey 2012. Korean Journal of Family Practice. 2015;5(suppl 3):S283-S290.
  13. Cappuccio FP, Cooper D, D'Elia L, Strazzullo P, Miller MA. Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies. European Heart Journal. 2011;32(12):1484-1492. http://doi.org/10.1093/eurheartj/ehr007
  14. Kwon AM, Shin C. Relation between health-related quality of life and sleep quality with adjustment for comorbidity among the Korean elderly: mixed-effects model with a 6-year follow-up study. Asia Pacific Journal of Public Health. 2016;28(3):271-279. http://doi.org/10.1177/1010539516628638
  15. Zhan Y, Chen R, Yu, J. Sleep duration and abnormal serum lipids: The China Health and Nutrition Survey. Sleep Medicine. 2014;15(7):833-839. http://doi.org/10.1016/j.sleep.2014.02.006
  16. Irwin MR, Olmstead RE, Ganz P, Haque R. Sleep disturbance, inflammation and depression risk in cancer survivors. Brain, Behavior, and Immunity. 2013;30:S58-S67. http://doi.org/10.1016/j.bbi.2012.05.002
  17. Park S, Cho MJ, Chang SM, Bae JM, Jeon HJ, Cho SJ, et al. Relationships of sleep duration with sociodemographic and health-related factors, psychiatric disorders and sleep disturbances in a community sample of Korean adults. Journal Sleep Research. 2010;19(4):567-577. http://doi.org/10.1111/j.1365-869.2010.00841.x
  18. Kim K, Park DH, Park D, Ru E. Effects of symptom severity and symptom interference on sleep disturbance in cancer patients. Asian Oncology Nursing. 2012;12(4):339-346. http://doi.org/10.5388/aon.2012.12.4.339
  19. Yu SY, Nho JH. Influence of sleep disturbance and depression on quality of life in ovarian cancer patients during chemotherapy. Asian Oncology Nursing. 2015;15(4):203-210. http://doi.org/10.5388/aon.2015.15.4.203
  20. Guen YL, Gagnadoux F, Hureaux J, Jeanfaivre T, Meslier N, Racineux JL, et al. Sleep disturbances and impaired daytime functioning in outpatients with newly diagnosed lung cancer. Lung Cancer. 2007;58(1):139-143. http://doi.org/10.1016/j.lungcan.2007.05.021
  21. Clevenger L, Schrepf A, Degeest K, Bender D, Goodheart M, Ahmed A, et al. Sleep disturbance, distress, and quality of life in ovarian cancer patients during the first year after diagnosis. Cancer. 2013;119(17):3234-3241. http://doi.org/10.1002/cncr.28188
  22. Bhargava N, Sharma G, Bhargava R, Mathuria M. Decision tree analysis on j48 algorithm for data mining. International Journal of Advanced Research in Computer Science and Software Engineering. 2013;3(6):1114-1119
  23. Kim HK, Choi KH, Lim SW, Rhee HS. Development of prediction model for prevalence of metabolic syndrome using data mining: Korea National Health and Nutrition Examination Study. Journal of Digital Convergence. 2016;14(2):325-332. http://doi.org/10.14400/JDC.2016.14.2.325
  24. Byeon H. The prediction model for self-reported voice problem using a decision tree model. Journal of the Korea Academia-Industrial cooperation Society. 2013;14(7):3368-3373. http://doi.org/10.5762/KAIS.2013.14.7.3368
  25. Mun J, Famsworth JL, Ragan BG, Kang M. Development of a model to estimate body fat percentage using decision tree analysis. Medicine and Scinece in Sports and Exercise. 2016;48:995-996. http://doi.org/10.1249/01.mss.0000487993.14293.5a
  26. Kang SH. Choi SH. Group classification on management behavior of diabetic mellitus. Journal of the Korea Academia-Industrial cooperation Society. 2011;12(2):765-774. http://doi.org/10.5762/kais.2011.12.2.765
  27. Kim YM, Chang DM, Kim SS, Park IS, Kang SH. A study on factors of management of diabetes mellitus using data mining. Journal of the Korea Academia-Industrial cooperation Society. 2009;10(5):1100-1108. http://doi.org/10.5762/kais.2009.10.5.1100
  28. Jike M, Itani O, Watanabe N, Buysse D, Kaneita Y. Long sleep duration and health outcomes: A systemic review, meta-analysis and meta-regression. Sleep Medicine Reviews. 2018;39:25-36. http://doi.org/10.1016/j.smrv.2017.06.011
  29. Lee YK, Nam HS, Chuang LH, Kim KY, Yang HK, Kwon IS, et al. South Korean time trade-off values for EQ-5D health states: Modeling with observed values for 101 health states. Value in Health. 2009;12(8):1187-1193. http://doi.org/10.1111/j.1524-4733.2009.00579.x
  30. The Korean Society of Lipid and Atherosclerosis. Atherosclerosis, dyslipidemia_ Diagnostic criteria. [Internet]. Seoul: Korea Lipid; 1996 Jan 1 [cited 2018 Apr 2]. Available from: http://www.lipid.or.kr/artery/diagnose1_2.php
  31. Huh MI. SPSS statistics classification analysis. Seoul: Data Solution; 2012.
  32. Howell1 D, Oliver TK, Keller-Olaman S, Davidson JR, Garland S, Samuels C, et al. Sleep disturbance in adults with cancer: a systematic review of evidence for best practices in assessment and management for clinical practice. Annals of Oncology. 2014;25(4):791-800. http://doi.org/10.1093/annonc/mdt506
  33. Kim H, Kim S, Lee H, Oh S. Factors affecting symptom experiences of breast cancer patients: Based on the theory of unpleasant symptoms. Asian Oncology Nursing. 2014;14(1):7-14. http://doi.org/10.5388/aon.2014.14.1.7
  34. Kim JH, Park EC, Yoo KB, Park S. The association between short or long sleep times and quality of life (QOL): Results of the Korea National Health and Nutrition Examination Survey (KNHANES IV-V). Journal of Clinical Sleep Medicine. 2015;11(6):625-634. http://doi.org/10.5664/jcsm.4772
  35. Bak YG. Park HS. Quality of sleep and serum lipid profile in patients with restless legs syndrome. Journal of Korean Academic Nursing. 2011;41(3):344-353. http://doi.org/10.4040/jkan.2011.41.3.344
  36. Jackowska M, Kumari M, Steptoe A. Sleep and biomakers in the english longitudinal study of ageing: Associations with c-reactive protein, fibrinogen, dehydroepiandrosterone sulfats and hemoglobin. Psychoeuroendocrinology. 2013;38(9):1484-1493. http://doi.org/10.1016/j.psyneuen.2012.12.015
  37. Byun MS. Kim NH. Energy intake and fatigue in patients receiving chemotherapy. Journal of Korean Biological Nursing Science.2012;14(4):258-267. http://doi.org/10.7586/jkbns.2012.14.4.258
  38. Kim HJ, Barsevick AM, Fang CY, Miaskowski C. Common biological pathways underlying the psychoneurological symptom cluster in cancer patients. Cancer Nursing. 2012;35(6):E1-E20. http://doi.org/10.1097/NCC.0b013e318233a811
  39. Ji EJ. Factors associated with hemoglobin A1c among oatient aged 40 years over with diabetes mellitus: 2012 Korea Health and Nutrition Examination Survey. Journal of Korean Academic Fundamantal Nursing. 2015;22(4):433-441. http://doi.org/10.7739/jkafn.2015.22.4.433
  40. Louie GH, Teknonidou MG, Caban-martinez AJ, Ward MM. Sleep disturbances in adults with arthritis: Prevalence, mediators, and subgroups at greatest risk. Data from the 2007 National Health Interview Survey. Arthritis Care & Research. 2011; 63(2):247-260. http://doi.org/10.1002/acr.20362

Cited by

  1. 제 2형 성인 당뇨병 유병자의 혈당조절 취약군 예측: 제7기(2016-2018년도) 국민건강영양조사 자료 활용 vol.23, pp.1, 2021, https://doi.org/10.7586/jkbns.2021.23.1.31