DOI QR코드

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혈액학적 인자가 심혈관 질환 위험지수에 미치는 영향

Effect of Hematological Factors on the Risk Index of Cardiovascular Disease

  • 안현 (동의대학교 방사선학과) ;
  • 윤현서 (동의대학교 치위생학과) ;
  • 박충무 (동의대학교 임상병리학과)
  • Hyun An (Department of Radiological Science, Dong-eui University) ;
  • Hyun-Seo Yoon (Department of Dental Hygiene, Dong-eui University) ;
  • Chung-Mu Park (Department of Clinical Laboratory Science, Dong-eui University)
  • 투고 : 2023.07.25
  • 심사 : 2023.08.08
  • 발행 : 2023.08.31

초록

This study aimed to investigate the relevance of cardiovascular disease risk factors AI and AIP, divided into three groups, among 300 individuals who underwent health checkups at the hospital. Various variables such as Age, Sex, BMI, WC, TC, TG, HDL-C, LDL-C, FBS, HbA1C, SBP, DBP, HR, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) were analyzed using statistical methods including frequency analysis, cross-tabulation, one-way ANOVA, Pearson's correlation analysis, and multiple linear regression analysis. The cross-analysis based on cardiovascular disease risk criteria revealed that men and individuals in their 50s had higher cardiovascular disease risk based on AI and AIP. Significant differences were observed in TG, TC, HDL-C, LDL-C, SBP, DBP, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) according to AI criteria. For the AIP criteria, TG, TC, HDL-C, FBS, HbA1C, HR, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) were identified as cardiovascular disease risk factors. FBS and HbA1c showed the highest positive correlation In the correlation analysis, followed by TC and LDL-C. The lowest positive correlation was observed between LDL-C and DBP. In terms of negative correlation, HDL-C and AI had the highest negative correlation, while LDL-C and TG showed the lowest negative correlation. Multiple regression analysis indicated that the AI and AIP risk criteria had explanatory powers of 73.6% and 72.5%, respectively. HDL-C had the greatest negative effect on the AI risk criterion, while TG had the most significant influence on the AIP risk criterion. In conclusion, while other serological variables are important, managing HDL-C and TG levels may help reduce the risk of cardiovascular disease.

키워드

과제정보

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF-2022 R1G1A1008377)

참고문헌

  1. https://kostat.go.kr/board.es?mid=a10301060200&bid=218&act=view&list_no=420715
  2. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention. Korea health statistics 2012: Korea National Health and Nutrition Examination Survey(KNHANES V-3). Cheongwon: Korea Centers for Disease Control and Prevention; 2013.
  3. Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Blaha MJ, et al. Heart disease and stroke statistics-2014 update: A report from the American Heart Association. Circulation. 2014;129(3):e28-292.
  4. Dalen JE, Alpert JS, Goldberg RJ, Weinstein RS. The epidemic of the 20th century: Coronary heart disease. Am J Med. 2014;127(9):807-12. https://doi.org/10.1016/j.amjmed.2014.04.015
  5. Wilson PFW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Journal of the American Heart Association. 1998;97(18):1837-47. https://doi.org/10.1161/01.CIR.97.18.1837
  6. Klementina FT, Damjana R. Nonalcoholic fatty liver disease: Focus on lipoprotein and lipid deregulation. Journal of Lipids. 2011;2011:783976. DOI: https://doi. org/10.1155/2011/783976
  7. Ha AW, Kim WK, Kim SH. Intakes of milk and soymilk and cardiovascular disease risk in Korean adults: A study based on the 2012~2016 Korea National Health and Nutrition Examination Survey, J Korean Soc Food Sci Nutr. 2023;52(5):522-30. https://doi.org/10.3746/jkfn.2023.52.5.522
  8. D'Agostino Sr RB, Grundy S, Sullivan LM, Wilson P, CHD Risk Prediction Group. Validation of the Framingham coronary heart disease prediction scores: Results of a multiple ethnic groups investigation. JAMA. 2001;286(2):180-7. https://doi.org/10.1001/jama.286.2.180
  9. Lewington S, Clarke R, Qizilbash N, Peto R, Collins R, Prospective Studies Collaboration. Age-specific relevance of usual blood pressure to vascular mortality: A meta-analysis of individual data for one million adults in 61 prospective studies. Lancet. 2002;360(9349):1903-13. https://doi.org/10.1016/S0140-6736(02)11911-8
  10. Zhang Y, Lee ET, Devereux RB, Yeh J, Best LG, Fabsitz RR, et al. Prehypertension, diabetes, and cardiovascular disease risk in a population-based sample: The strong heart study. Hypertension. 2006;47(3):410-4. https://doi.org/10.1161/01.HYP.0000205119.19804.08
  11. Marroquin OC, Kip KE, Kelley DE, Johnson BD, Shaw LJ, Bairey Merz CN, et al. Metabolic syndrome modifies the cardiovascular risk associated with angiographic coronary artery disease in women: A report from the women's ischemia syndrome evaluation. Journal of the American Heart Association. 2004;109(6):714-21. https://doi.org/10.1161/01.CIR.0000115517.26897.A7
  12. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, et al. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Journal of the American Heart Association. 2005;112(17):2735-52.
  13. Rosenfeld L. Lipoprotein analysis. Arch Pathol Lab Med. 1989;113(10):1101-10.
  14. Dobiasova M, Frohlich J. The plasma parameter log (TG/HDL-C) as an atherogenic index: Correlation with lipoprotein particle size and esterification rate in apo B-lipoprotein-depleted plasma. (FERHDL) Clin Biochem. 2001;34(7):583-8.
  15. Jee SH, Jang Y, Oh DJ, Oh BH, Lee SH, Park SW, et al. A coronary heart disease prediction model: The Korean heart study. BMJ Open. 2014;4(5):e005025.
  16. Kim KS, Owen WL, Williams D, Adams-Campbell LL. A comparison between BMI and conicity index on predicting coronary heart disease. Ann Epidemiol. 2000;10(7):424-31. https://doi.org/10.1016/S1047-2797(00)00065-X
  17. Hong SJ, Oh DJ, Kim EJ, Lee SJ, Shin SH, Choi JI, Choi CW, et al. The comparison of serum lipid levels and risk factors according to the status of coronary atherosclerosis in Koreans. Korean Circulation Journal. 2003;33(6):465-74. https://doi.org/10.4070/kcj.2003.33.6.465
  18. Committee for the Korean Guidelines for the Management of Dyslipidemia. 2015 Korean guidelines for the management of dyslipidemia: Executive summary. Korean Circ J. 2016;46(3):275-306. https://doi.org/10.4070/kcj.2016.46.3.275
  19. National Cholesterol Education Program. Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III). JAMA. 2001;285(19):2486-97. https://doi.org/10.1001/jama.285.19.2486
  20. Gordon T, Castelli WP, Hjortland MC, Kannel WB, Dawber TR. High density lipoprotein as a protective factor against coronary heart disease. The Framingham study. Am J Med. 1977;62(5):707-14. https://doi.org/10.1016/0002-9343(77)90874-9
  21. Despres JP, Lemieux I, Dagenais GR, Cantin B, Lamarche B. HDL-cholesterol as a marker of coronary heart disease risk: The Quebec cardiovascular study. Atherosclerosis. 2000;153(2):263-72. https://doi.org/10.1016/S0021-9150(00)00603-1
  22. Park CS, Yang HM, Han KD, Lee HS, Kang JH, Han JK, et al. J-shaped association between LDL cholesterol and cardiovascular events: A longitudinal primary prevention cohort of over 2.4 million people nationwide. Journal of Advanced Research. DOI: https://doi.org/10.1016/j.jare.2023. 05.003
  23. https://www.u2labs.co.kr/information/checkDetail.do?pageIndex=1&ctId=C106700