Journal of Korean Academy of Nursing (대한간호학회지)

Korean Society of Nursing Science (한국간호과학회)
권호 표지
DOI QR코드

DOI QR Code

Identifying Latent Classes of Risk Factors for Coronary Artery Disease

잠재계층분석을 활용한 관상동맥질환 위험요인의 유형화

  • Ju, Eunsil (Kyung Hee University Hospital at Gangdong) ;
  • Choi, JiSun (College of Nursing Science.East-West Nursing Research Institute, Kyung Hee University)
  • 주은실 (강동경희대학교병원) ;
  • 최지선 (경희대학교 간호과학대학.동서간호학연구소)
  • Received : 2017.09.28
  • Accepted : 2017.12.02
  • Published : 2017.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose: This study aimed to identify latent classes based on major modifiable risk factors for coronary artery disease. Methods: This was a secondary analysis using data from the electronic medical records of 2,022 patients, who were newly diagnosed with coronary artery disease at a university medical center, from January 2010 to December 2015. Data were analyzed using SPSS version 20.0 for descriptive analysis and Mplus version 7.4 for latent class analysis. Results: Four latent classes of risk factors for coronary artery disease were identified in the final model: 'smoking-drinking', 'high-risk for dyslipidemia', 'high-risk for metabolic syndrome', and 'high-risk for diabetes and malnutrition'. The likelihood of these latent classes varied significantly based on socio-demographic characteristics, including age, gender, educational level, and occupation. Conclusion: The results showed significant heterogeneity in the pattern of risk factors for coronary artery disease. These findings provide helpful data to develop intervention strategies for the effective prevention of coronary artery disease. Specific characteristics depending on the subpopulation should be considered during the development of interventions.

Keywords

References

  1. Sanchis-Gomar F, Perez-Quilis C, Leischik R, Lucia A. Epidemiology of coronary heart disease and acute coronary syndrome. Annals of Translational Medicine. 2016;4(13):256. https://doi.org/10.21037/atm.2016.06.33
  2. Statistics Korea. 2015 annual report on the cause of death statistics [Internet]. Daejeon: Statistics Korea; c2015 [cited 2017 Aug 20]. Available from: http://kostat.go.kr/portal/korea/kor_nw/2/1/index.board.
  3. Niccoli G, Montone RA, Lanza GA, Crea F. Angina after percutaneous coronary intervention: The need for precision medicine. International Journal of Cardiology. 2017;248:14-19. https://doi.org/10.1016/j.ijcard.2017.07.105
  4. Thune JJ, Signorovitch JE, Kober L, McMurray JJ, Swedberg K, Rouleau J, et al. Predictors and prognostic impact of recurrent myocardial infarction in patients with left ventricular dysfunction, heart failure, or both following a first myocardial infarction. European Journal of Heart Failure. 2011;13(2):148-153. https://doi.org/10.1093/eurjhf/hfq194
  5. Kim HJ. Healthcare RnD expert report: Cardiovascular disease. Seoul: Health Industry Development Institute (Korea); 2016 Dec. Report No.: 48.
  6. Goff DC, Lloyd-Jones DM, Bennett G, Coady S, D'Agostino RB, Gibbons R, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk. Journal of the American College of Cardiology. 2014;63(25):2935-2959. https://doi.org/10.1016/j.jacc.2013.11.005
  7. Park KO, Seo JY. Gender differences in factors influencing the Framingham Risk Score-Coronary Heart Disease by BMI. Journal of Korean Academy Community Health Nursing. 2014;25(4):248-258. https://doi.org/10.12799/jkachn.2014.25.4.248
  8. Dawber TR, Felix EM, George VM. Coronary heart disease in the Framingham Study. International Journal of Epidemiology. 2015;44(6):1767-1780. https://doi.org/10.1093/ije/dyv346
  9. Bae Y, Lee K. Risk factors for cardiovascular disease in adults aged 30 years and older. Journal of the Korean Society of Integrative Medicine. 2016;4(2):97-107. https://doi.org/10.15268/ksim.2016.4.2.097
  10. Perk J, De Backer G, Gohlke H, Graham I, Reiner Z, Verschuren WM, et al. European guidelines on cardiovascular disease prevention in clinical practice (version 2012): The fifth joint task force of the European society of cardiology and other societies on cardiovascular disease prevention in clinical practice (constituted by representatives of nine societies and by invited experts). International Journal of Behavioral Medicine. 2012;19(4):403-488. https://doi.org/10.1007/s12529-012-9242-5
  11. Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97(18):1837-1847. https://doi.org/10.1161/01.cir.97.18.1837
  12. Bang SY, Park MY. The analysis of risk factor management programs for patients with coronary artery disease. Korean Journal of Rehabilitation Nursing. 2013;16(1):27-36. https://doi.org/10.7587/kjrehn.2013.27
  13. Brindle P, Beswick A, Fahey T, Ebrahim S. Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: A systematic review. Heart. 2006;92(12):1752-1759. https://doi.org/10.1136/hrt.2006.087932
  14. Nylund KL, Asparouhov T, Muthen BO. Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal. 2007;14(4):535-569. https://doi.org/10.1080/10705510701575396
  15. Lanza ST, Rhoades BL, Nix RL, Greenberg MT. Modeling the interplay of multilevel risk factors for future academic and behavior problems: A person-centered approach. Development and Psychopathology. 2010;22(2):313-335. https://doi.org/10.1017/S0954579410000088
  16. Kim ES, Kim KH, Cho YC. Prevalence of clustering of coronary risk factors in health checkup examinees. Journal of the Korea Academia-Industrial Cooperation Society. 2009;10(3):625-633. https://doi.org/10.5762/KAIS.2009.10.3.625
  17. Korean Society for Laboratory Medicine. Lab tests online [Internet]. Seoul: Korean Society for Laboratory Medicine; c2017 [cited 2017 Aug 20]. Available from: http://labtestsonline.kr/.
  18. World Health Organization. Obesity and overweight [Internet]. Geneva: Author; c2016 [cited 2017 Aug 20]. Available from: http://www.who.int/mediacentre/factsheets/fs311/en/.
  19. Lee JS, Cho MR, Lee GJ. Validation of the developed nutritional screening tool for hospital patients. Korean Journal of Nutrition. 2010;43(2):189-196. https://doi.org/10.4163/kjn.2010.43.2.189
  20. Alberti KG, Zimmet P, Shaw J; IDF Epidemiology Task Force Consensus Group. The metabolic syndrome: A new worldwide definition. The Lancet. 2005;366(9491):1059-1062. https://doi.org/10.1016/S0140-6736(05)67402-8
  21. Kim HM, Choi CJ, Seung KB, Chung WS, Kahng HB. Smoking behavior following diagnosis of the coronary artery disease and factors influencing smoking cessation. Korean Journal of Family Medicine. 2005;26(10):629-635.
  22. Hong JY, Kim JH, Kim OS. Factors influencing problem drinking of male drinkers according to life cycle. Korean Journal of Adult Nursing. 2014;26(2):139-148. https://doi.org/10.7475/kjan.2014.26.2.139
  23. Lee YM. Smoking cessation intention and related factors in current smokers diagnosed with coronary artery disease: A cross-sectional study using the community health survey. Journal of Health Informatics and Statistics. 2016;41(2):165-173. https://doi.org/10.21032/jhis.2016.41.2.165
  24. Committee for Guidelines for Management of Dyslipidemia. 2015 Korean guidelines for management of dyslipidemia. Journal of Lipid and Atherosclerosis. 2015;4(1):61-92. https://doi.org/10.12997/jla.2015.4.1.61
  25. Kim HC. Epidemiology of dyslipidemia in Korea. Journal of Korean Medical Association. 2016;59(5):352-357. https://doi.org/10.5124/jkma.2016.59.5.352
  26. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention. Korea Health Statistics 2015: Korea National Health and Nutrition Examination Survey (KNHANES). Cheongju: Korea Centers for Disease Control and Prevention; 2016. p. 20-26.
  27. Lim JW, Kim SY, Ke SS, Cho BL. The prevalence of obesity, abdominal obesity and metabolic syndrome among elderly in general population. Korean Journal of Family Medicine. 2011;32(2):128-134. https://doi.org/10.4082/kjfm.2011.32.2.128
  28. Kim CH, Hwang IK, Yoo WS. The common patterns of multimorbidity and its impact on healthcare cost in Korea. Health Policy and Management. 2014;24(3):219-227. https://doi.org/10.4332/KJHPA.2014.24.3.219
  29. Hyun HS, Lee IS. Nutrition status and risk factors for malnutrition in low-income urban elders. Journal of Korean Academy of Nursing. 2014;44(6):708-716. https://doi.org/10.4040/jkan.2014.44.6.708
  30. Sung MJ, Kim EJ, Lee HJ, Noh JW. Analysis of the prevalence of diabetes mellitus and related factors for the local seniors. Journal of the Korea Contents Association. 2014;14(5):244-250. https://doi.org/10.5392/JKCA.2014.14.05.244

Cited by

  1. 한국 중년남성의 건강관련 삶의 질에 대한 잠재계층분석 vol.49, pp.1, 2017, https://doi.org/10.4040/jkan.2019.49.1.104
  2. 잠재계층분석을 활용한 노인의 건강 관련 삶의 질에 대한 유형화와 영향요인 분석 vol.31, pp.2, 2017, https://doi.org/10.12799/jkachn.2020.31.2.212