Journal of Korean Biological Nursing Science

Korean society of Biological Nursing Science (한국기초간호학회)
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Identification of Subgroups with Poor Glycemic Control among Patients with Type 2 Diabetes Mellitus: Based on the Korean National Health and Nutrition Examination Survey from KNHANES VII (2016 to 2018)

제 2형 성인 당뇨병 유병자의 혈당조절 취약군 예측: 제7기(2016-2018년도) 국민건강영양조사 자료 활용

  • Kim, Hee Sun (College of Nursing.Research Institute of Nursing Science, Jeonbuk National University) ;
  • Jeong, Seok Hee (College of Nursing.Research Institute of Nursing Science, Jeonbuk National University)
  • 김희선 (전북대학교 간호대학.간호과학연구소) ;
  • 정석희 (전북대학교 간호대학.간호과학연구소)
  • Received : 2020.12.31
  • Accepted : 2021.02.16
  • Published : 2021.02.28
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Abstract

Purpose: This study was performed to assess the level of blood glucose and to identify poor glycemic control groups among patients with type 2 diabetes mellitus (DM). Methods: Data of 1,022 Korean type 2 DM patients aged 30-64 years were extracted from the Korea National Health and Nutrition Examination Survey VII. Complex samples analysis and a decision-tree analysis were performed using the SPSS WIN 26.0 program. Results: The mean level of hemoglobin A1c (HbA1c) was 7.22±0.25%, and 69.0% of the participants showed abnormal glycemic control (HbA1c≥6.5%). The characteristics of participants associated with poor glycemic control groups were presented with six different pathways by the decision-tree analysis. Poor glycemic control groups were classified according to the patients' characteristics such as period after DM diagnosis, awareness of DM, sleep duration, gender, alcohol drinking, occupation, income status, low density lipoprotein-cholesterol, abdominal obesity, and number of walking days per week. Period of DM diagnosis with a cut-off point of 6 years was the most significant predictor of the poor glycemic control group. Conclusion: The findings showed the predictable characteristics of the poor glycemic control groups, and they can be used to screen the poor glycemic control groups among adults with type 2 DM.

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References

  1. Korea Centers for Disease Control & Prevention. 2019 Chronic disease and issues [internet]. Seoul: Korea Centers for Disease Control & Prevention; 2019 [cited 2020 Dec 10]. Available from: https://www.kdca.go.kr/gallery.es?mid=a20503020000&bid=0003
  2. Korean Diabetes Association. 2020 Korean diabetes fact sheet in Korea. [internet]. Seoul: Korean Diabetes Association; 2020 [cited 2020 Dec 10]. Available from: https://www.diabetes.or.kr/bbs/index.html?code=e_resource&mode=tlist
  3. Kim JM, Kim SS. Management of hyperglycemia in type 2 diabetes: a summary of new consensus report from the american diabetes association and the european association for the study of diabetes in 2018. Journal of Korean Diabetes. 2019;20(1):6-9. https://doi.org/10.4093/jkd.2019.20.1.6
  4. Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA. 10-year follow-up of intensive glucose control in type 2 diabetes. New England Journal of Medicine. 2008;359:1577-1589. https://doi.org/10.1056/NEJMoa0806470
  5. Korean Diabetes Association. 2019 Clinical practice guidelines for type 2 diabetes mellitus. 6th ed. Seoul: Seoul Medcus Medical Publisher;2019. p.33-35.
  6. Lim JA. Treatment goals for glycemia in older patients with diabetes mellitus. Journal of Korean Diabetes. 2019;20(4):220-224. https://doi.org/10.4093/jkd.2019.20.4.220
  7. Haghighatpanah M, Nejad ASM, Haghighatpanah M, Thunga G, Mallayasamy S. Factors that correlate with poor glycemic control in type 2 diabetes mellitus patients with complications. Osong Public Health and Research Perspectives. 2018;9(4):167-174. https://doi.org/10.24171/j.phrp.2018.9.4.05
  8. Wake AD. Antidiabetic effects of physical activity: how it helps to control type 2 diabetes. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy. 2020;13:2909-2923. https://doi.org/10.2147/DMSO.S262289
  9. Gu MK. Factors influencing glycemic control among type 2 diabetes mellitus patients: the sixth korea national health and nutrition examination survey (2013-2015). Korean Journal of Adult Nursing. 2019:31(3);235-248. https://doi.org/10.7475/kjan.2019.31.3.235
  10. Biradar RA, Singh DP, Thakur H, Halli SS. Gender differences in the risk factors for high and very high blood glucose levels: a study of Kerala. diabetes & metabolic syndrome: Clinical Research & Reviews. 2020:14(4);627-636. https://doi.org/10.1016/j.dsx.2020.05.001
  11. Abdullah MFILB, Sidi H, Ravindran A, Gosse PJ, Kaunismaa ES, Mainland RL, et al. How much do we know about the biopsychosocial predictors of glycaemic control? age and clinical factors predict glycaemic control, but psychological factors do not. Journal of Diabetes Research. 2020;2020:1-11. https://doi.org/10.1155/2020/2654208
  12. Badedi M, Solan YM, Darraj H, Sabai A, Mahfouz MS, Alamodi S, et al. Factors associated with long-term control of type 2 diabetes mellitus. Journal of Diabetes Research. 2016;(2):1-8. https://doi.org/10.1155/2016/2109542
  13. Kim YJ, Cho E. Lifestyle factors related to glucose control for diabetes management strategies: nested case control design using KNHANES data. Journal of the Korea Convergence Society. 2019;10(11):501-510. http://doi.org/10.15207/JKCS.2019.10.11.501
  14. Lee KJ, Lee HJ, Oh KJ. Using fuzzy-neural network to predict hedge fund survival. Journal of Korean Data & Information Science Society. 2015;26(6):1189-1198. https://doi.org/10.7465/jkdi.2015.26.6.1189
  15. American Diabetes Association. Older adults: standards of medical care in diabetes. 2019. Diabetes Care 2019;42(Suppl 1):S139-S147. https://doi.org/10.2337/dc19-S012
  16. Park J, Lim S, Yim E, Kim Y, Chung W. Factors associated with poor glycemic control among patients with type 2 diabetes mellitus: the fifth Korea national health and nutrition examination survey (2010-2012). Health Policy and Management. 2016;26(2):125-134 https://doi.org/10.4332/KJHPA.2016.26.2.125
  17. Cheng LJ, Wang W, Lim ST, Wu VX. Factors associated with glycaemic control in patients with diabetes mellitus: A systematic literature review. Journal of Clinical Nursing. 2019;28(9-10):1433-1450. https://doi.org/10.1111/jocn.14795
  18. Emanuelsson F, Benn M. LDL-cholesterol versus glucose in microvascular and macrovascular disease. Clinical Chemistry. 2021;67(1):167-182. https://doi.org/10.1093/clinchem/hvaa242
  19. Shahwan MJ, Jairoun AA, Farajallaj A, Shanabli S. Prevalence of dyslipidemia and factors affecting lipid profile in patients with type 2 diabetes. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2019;13(4):2387-2392. https://doi.org/10.1016/j.dsx.2019.06.009
  20. Choi JH, Han ST, Kang HC, Kim ES, Kim MK, Lee SK. Prediction and utilization of data mining using answer tree 3.0. Seoul: SPSS Academy; 2002. p.17-31.
  21. Kirkman MS, Mahmud H, Korytkowski MT. Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes mellitus. Endocrinology and Metabolism Clinics of North America. 2018;47(1):81-96. https://doi.org/10.1016/j.ecl.2017.10.002.
  22. Sim KH, Hwang MS. Effect of self-monitoring of blood glucose based diabetes self-management education on glycemic control in type 2 diabetes. Journal of Korean Academic Society Nursing Education. 2013;19(2):127-136. https://doi.org/10.5977/jkasne.2013.19.2.127
  23. Moon SH, Lee YH, Ham OK, Kim SH. The effect of the experience of diabetes education on knowledge, self-care behavior and glycosylated hemoglobin in type 2 diabetic patients. Journal of Korean Academic Society Nursing Education. 2014;20(1):81-92. https://doi.org/10.5977/jkasne.2014.20.1.81
  24. Petrie JR, Guzik TJ, Touyz RM. Diabetes, hypertension, and cardiovascular disease: clinical insights and vascular mechanisms. Canadian Journal of Cardiology. 2018;34(5):575-584. https://doi.org/10.1016/j.cjca.2017.12.005
  25. Irazola V, Rubinstein A, Bazzano L, Calandrelli M, Chung-Shiuan C, Elorriaga N, et al. Prevalence, awareness, treatment and control of diabetes and impaired fasting glucose in the Southern cone of Latin America. Plos One. 2017;12(9): e0183953. https://doi.org/10.1371/journal.pone.0183953
  26. German CA, Laughey B, Bertoni AG, Yeboah J. Associations between BMI, waist circumference, central obesity and outcomes in type II diabetes mellitus: the ACCORD trial. Journal of Diabetes and Its Complication. 2020;34(3):1-6. https://doi.org/10.1016/j.jdiacomp.2019.107499
  27. Kumari G, Singh V, Jhingan AK, Chhajer B, Dahiya S. Effectiveness of lifestyle modification counseling on glycemic control in type 2 diabetes mellitus patients. Current Research in Nutrition and Food Science. 2018;6(1):70-82. https://doi.org/10.12944/CRNFSJ.6.1.07
  28. Zheng X, Qi Y, Bi L, Shi W, Zhang Y, Zhang D, et al. Effects of exercise on blood glucose and glycemic variability in type 2 diabetic patients with dawn phenomenon. BioMed Research International. 2020;2020:1-6. https://doi.org/10.1155/2020/6408724
  29. Lee SWH, Ng KY, Chin WK. The impact of sleep amount and sleep quality on glycemic control in type 2 diabetes: a systematic review and meta-analysis. Sleep Medicine Reviews. 2017;31:91-101. https://doi.org/10.1016/j.smrv.2016.02.001
  30. Mozaffarian D, Wilson PW, Kannel WB. Beyond established and novel risk factors: lifestyle risk factors for cardiovascular disease. Circulation. 2008;117(23):3031-3038. https://doi.org/10.1161/CIRCULATIONAHA.107.738732
  31. Andrews PJ, Sleeman DH, Statham PF, McQuatt A, Corruble V, Jones PA, et al. Predicting recovery in patients suffering from traumatic brain injury by using admission variables and physiological data: a comparison between decision tree analysis and logistic regression. Journal of Neurosurgery. 2002;97(2):326-336. https://doi.org/10.3171/jns.2002.97.2.0326
  32. Ledford CJW, Seehusen DA, Crawford PF. The relationship between patient perceptions of diabetes and glycemic control: a study of patients living with prediabetes or type 2 diabetes. Patient Education and Counseling. 2019;102(11): 2097-2101. https://doi.org/10.1016/j.pec.2019.05.023
  33. Chattu VK, Chattu SK, Burman D, Spence DW, Pandi-Perumal SR. The interlinked rising epidemic of insufficient sleep and diabetes mellitus. Healthcare. 2019;7(1):37-55. https://doi.org/10.3390/healthcare7010037
  34. Kim HS, Jeong SH, Park SK. 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. Journal of Korean Biological Nursing Science. 2018;20(2):103-113. https://doi.org/10.7586/jkbns.2018.20.2.103
  35. Xu H, Guan J, Yi H, Zou J, Meng L, Tang X, et al. Elevated low-density lipoprotein cholesterol is independently associated with obstructive sleep apnea: evidence from a large-scale cross-sectional study. Sleep and Breathing. 2016; 20(2):627-634. https://doi.org/10.1007/s11325-015-1262-3