Journal of Preventive Medicine and Public Health

The Korean Society for Preventive Medicine (대한예방의학회)
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The Relationship between Metabolic Syndrome and Korean Cardiocerebrovascular Risk Assessment: for Male Researchers in a Workplace

대사증후군과 뇌심혈관질환 발병위험도 평가와의 연관성: 일개 사업장 남성 근로자를 대상으로

  • Yoon, Jong-Wan (Department of Occupational & Environmental Medicine, Eulji University Hospital) ;
  • Yi, Kyung-Jin (Department of Occupational & Environmental Medicine, Eulji University Hospital) ;
  • Lee, Sang-Yun (Department of Occupational & Environmental Medicine, School of Public Health, Seoul National University) ;
  • Oh, Jang-Gyun (Department of Occupational & Environmental Medicine, Eulji University Hospital)
  • 윤종완 (을지대학교병원 산업의학과) ;
  • 이경진 (을지대학교병원 산업의학과) ;
  • 이상윤 (서울대학교 보건대학원 산업의학과) ;
  • 오장균 (을지대학교병원 산업의학과)
  • Published : 2007.09.30
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Abstract

Objectives: The prevalence of metabolic syndrome has recently increased, Payments from the Korea Labor Welfare Corporation for compensation for mortality in workers caused by cardiovascular and cerebrovascular diseases have also increased in Korea in recent years. The association of metabolic syndrome and cardiocerebrovascular disease has been investigated by several researchers in recent studies, This study was conducted in an attempt to characterize the relationship between metabolic syndrome and Korean cardiocerebrovascular disease risk assessment, and to provide basic data to group health practices for the prevention of cardiocerebrovascular disease. Methods: Health examinations were previously conducted for 1526 male researchers at a private laboratory. The prevalence by age and the odds ratio of metabolic syndrome scores into the "cardiocerebrovascular risk group" (sum of low, intermediate, and high risk groups) of the Korean cardiocerebrovascular disease risk assessment were assessed, in an effort to elucidate the associations between metabolic syndrome and cardiocere brovascular disease risk assessment. Results: The prevalence of metabolic syndrome and inclusion in the cardiocerebrovascular risk group was 11,7% and 22.1% respectively. The severity of metabolic syndrome and cardiocerebrovascular risk assessment showed that individuals in their 40's and 50's were at higher risk than those in their 30's (p<0,001). The age-adjusted odds ratio of metabolic syndrome to cardiocere brovascular risk group inclusion was 5.6. Conclusions: An active prevention program for cardiocerebrovascular disease needs to begin in the 40's, as the prevalence of metabolic syndrome and the risk group of cardiocerebrovascular risk assessment peak in the 40's age group. The odds ratio between metabolic syndrome and the cardiocerebrovascular risk group was high, which indicates that metabolic syndrome scores should be utilized as guidelines during the consultation and behavioral modification program for the workplace prevention of cardiocerebrovascular diseases in group health practices.

Keywords

References

  1. Department of Statistics (Korean Statistical Information System, Department of Statistics). The Mortality causal comparison 2004. [cited 2007 Feb 1]. Available from: URL:http:// www.nso.go.kr(Korean)
  2. Lim YL, Hwang SW, Sim HJ, Oh EH, Jang YS, Cho BR. The prevalence and risk factor analysis of metabolic syndrome by ATP III diagnostic criteria. J Korean Acad Fam Med 2003; 24(2): 135-143 (Korean)
  3. Antipatis VJ, Gill TP. Obesity as a Global Problem. In: Bjomtorp P. Editors. International Textbook of Obesity. West Sussex: John Wiley & Sons, Ltd.; 2001. p. 1-29
  4. KIHSA (Korea Institute of Health and Social Affair). Korea National Health and Nutrition Survey. [cited 2007 Feb 1]. Available from: URL:http://www.kihasa.re.kr/html/jsp/
  5. NHLBI (National Heart Lung and Blood Institute). Framingham heart study. [cited 2007 Jun 31]. Available from: URL:http://www.nhlbi. nih.gov/about/framingham/index.html
  6. Fisher NDL, Williams GH. Hypertensive vascular disease. In: Kasper DL, Braunwald E, Fauci A, Hauser S, Longo D, Jameson JL, editors. Harrison's Principles of Internal Medicine. 16th ed. New York: McGraw-Hill; 2004. p.1463-1480
  7. Lim S, Lee EJ, Koo BK, Cho SI, Park KS, Jang HC, Kim SY, Lee HK. Increasing trends of metabolic syndrome in Korea: Based on Korean national health and nutrition examination surveys. J Korean Diabetes Assoc 2005; 29(5): 432-439 (Korean)
  8. Alberti K, Zimmet P. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998; 15(7): 539-553 https://doi.org/10.1002/(SICI)1096-9136(199807)15:7<539::AID-DIA668>3.0.CO;2-S
  9. Braunwald E, Zipes D, Libby P. Heart Disease. 6th ed. Philadelphia: W.B. Saunders company; 2001. p. 2133-2142
  10. Ginnan CJ, Rhodes T, Mercuri M, Pyorala K, Kjekshus J, Pedersen T, Beere P, Gotto A, Clearfield M. The metabolic syndrome and risk of major coronary events in the scandinavian simvastatin survivalstudy (4s) and the air force/Texas coronary atherosclerosis prevention study (AFCAPS/TEXCAPS). Am J Cardiol 2004; 93(2): 136-141 https://doi.org/10.1016/j.amjcard.2003.09.028
  11. Kwon HM, Kim BJ, Lee SH, Choi SH, Oh BH, Yoon BW. Metabolic syndrome as an independent risk factor of silent brain infarction in healthy people. Stroke 2006; 37(2): 466-470 https://doi.org/10.1161/01.STR.0000199081.17935.81
  12. Gami AS, Witt BJ, Howard DE, Erwin Pl, Gami LA, Somers VK, Montori VM. Metabolic syndrome and risk of incident cardiovascular events and death: A systematic review and meta-analysis of longitudinal studies. J Am Coll Cardiol 2007; 49(4): 403-414 https://doi.org/10.1016/j.jacc.2006.09.032
  13. KDI (Korea Development Institute). Statistics of Industrial Hazard 1999. [cited 2007 Feb 1]. Available from: URL:http://epic.kdi.re.kr (Korean)
  14. KOSHA (Korean Safety and Health Affair). Risk assessment for the prevention of cardiocerebrovascular disease at workplace (KOSHA Code H-11-2004). [cited 2007 Feb 1]. Available from: URL:http://www.kosha.net (Korean)
  15. NIH(National Institute of Health). Estimating coronary heart disease (CHD) risk using Framingham heart study prediction score sheets. [cited 2007 Jun 31]. Available from: URL:http://www.nhlbi.nih.gov/about/framingham/riskabs.htm
  16. Walling A. New Sheffield table for assessing coronary risks. [cited 2007 Jun 31 ]. Available from: URL:http://www.aafp.org/afp/2000090l/tips/9.html
  17. 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
  18. NCEP-ATPIII (National Cholesterol Education Program- Adult Treatment Panel III). Third report of the expert panel on detection, evaluation, and treatment of high blood cholesterol in adults. [cited 2007 Feb 1]. Available from: URL: http://www.nhlbi.nih.gov/
  19. Bath P, Chalmers J, Powers W, Beilin L, Davis S, Lenfant C, Mancia G, Neal B, Whitworth J, Zanchetti A. International Society of Hypertension (ISH): Statement on the management of blood pressure in acute stroke. J Hypertens 2003; 21(4): 665-672 https://doi.org/10.1097/00004872-200304000-00003
  20. Jeong BG, Moon OR, Kim NS, Kang JH, Yoon TH, Lee SY, Lee SJ. Socioeconomic costs of obesity for Korean adults. Korean J Prev Med 2002; 35(1): 1-12 (Korean) https://doi.org/10.1006/pmed.2002.1042
  21. Lee HJ, Kwon HS, Park YM, Chun HN, Choi YH, Ko SH, Lee JM, Yoon KH, Cha BY, Lee WC, Lee KW, Son HY, Kang SK, Ahn MS, Kang JM, Kim DS. Waist circumference as a risk factor for metabolic syndrome in Korean adult: Evaluation from 5 different criteria of metabolic syndrome. J Kor Diabetes Assoc 2005; 29(1): 48-56 (Korean)
  22. Ford ES. Prevalence of the metabolic syndrome defined by the International Diabetes Federation among adults in the U.S. Diabetes Care 2005; 28(11): 2745-2749 https://doi.org/10.2337/diacare.28.11.2745
  23. Senteri A, Najjar SS, Morrell CH, Lakatta EG. The metabolic syndrome in older individuals: Prevalence and prediction of cardiovascular events: The cardiovascular health study. Diabetes Care 2005; 28(4): 882-887 https://doi.org/10.2337/diacare.28.4.882
  24. Jaber LA, Brown MB, Hammad A, Zhu Q, Herman WH. The prevalence of the metabolic syndrome among Arab Americans. Diabetes Care 2004; 27(1): 234-238 https://doi.org/10.2337/diacare.27.1.234
  25. Hu G, Qiao Q, Tuomilehto J, Balkau B, Borch-Johnsen K, Pyorala K. Prevalence of the metabolic syndrome and its relation to all-cause and cardiovascular mortality in nondiabetic European men and women. Arch Intern Med 2004; 164(10): 1066-1076 https://doi.org/10.1001/archinte.164.10.1066
  26. McNeill AM, Rosamond WD, Girman CJ, Golden SH, Schmidt MI, East HE, Ballantyne CM, Heiss G. The metabolic syndrome and 11-year risk of incident cardiovascular disease in the atherosclerosis risk in communities study. Diabetes Care 2005; 28(2): 385-390 https://doi.org/10.2337/diacare.28.2.385
  27. Kolovou GD, Anagnostopoulou KK, Cokkinos DV. Pathophysiology of dyslipidaemia in the metabolic syndrome. Postgrad Med J 2005; 81(956): 358-366 https://doi.org/10.1136/pgmj.2004.025601
  28. Sobhanjan S, Mithun D, Barun M, Chandra SC, PM. P. Prevalence of metabolic syndrome in two tribal populations of the sub-Himalayan region of India: Ethnic and rural-urban differences. Am J Hum Biol 2005; 17(6): 814-817 https://doi.org/10.1002/ajhb.20448
  29. Liu J, Hong Y, D'Agostino Sr. RB, Wu Z, Wang W, Sun J, Wilson P. WF, Kannel WB, Zhao D. Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese multi-provincial cohort study. JAMA 2004; 291(21): 2591-2599 https://doi.org/10.1001/jama.291.21.2591
  30. Brindle P, Emberson J, Lampe F, Walker M, Whincup P, Fahey T, Ebrahim S. Predictive accuracy of the Framingham coronary risk score in British men: Prospective cohort study. BMJ 2003; 327(7426): 1267-1273 https://doi.org/10.1136/bmj.327.7426.1267
  31. Park JS, Park HD, Yoon JW, Jung CH, Lee WY, Kim SW. Prevalence of the metabolic syndrome as defined by NCEP-ATPIII among the urban Korean population. Korean J Med 2002; 63(3): 290-298 (Korean)
  32. Choi SH, Kim DJ, Lee KE, Kim YM, Song YD, Kim HD, Ahn CW, Cha BS, Huh GB, Lee HC. Cut off value of waist circumference for metabolic syndrome patients in Korean adult population. Korean J Obes 2004; 13(1): 53-60 (Korean)
  33. Pack KW, Hong YM. Health behavior factors affecting waist circumference as an indicator of abdominal obesity. J Prev Med Pub Health 2006; 39(1): 59-66 (Korean)
  34. Son MA. The relationship of social class and health behaviors with morbidity in Korea. Korean J Prev Med 2002; 35(1): 57-64 (Korean)
  35. Jang JP. A study of cerebrovascular disease evaluation in group health practice [dissertation]. Seoul: Seoul National Univ; 2006 (Korean)
  36. Cha YS, Khang YH, Lee MS, Kang W, Jeon SH, Kim KL, Lee SI. Cost-effectiveness analysis of a hyperlipidemia mass screening program in Korea. Korean J Prev Med 2002; 35(2): 99-106 (Korean)