Obesity, Risk Factors, and Predicting Cardiovascular Events
2005; Lippincott Williams & Wilkins; Volume: 111; Issue: 15 Linguagem: Inglês
10.1161/01.cir.0000163649.99244.a8
ISSN1524-4539
Autores Tópico(s)Obesity, Physical Activity, Diet
ResumoHomeCirculationVol. 111, No. 15Obesity, Risk Factors, and Predicting Cardiovascular Events Free AccessEditorialPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessEditorialPDF/EPUBObesity, Risk Factors, and Predicting Cardiovascular Events Michael H. Criqui Michael H. CriquiMichael H. Criqui From the Department of Family and Preventive Medicine, University of California–San Diego School of Medicine, La Jolla, Calif. Originally published19 Apr 2005https://doi.org/10.1161/01.CIR.0000163649.99244.A8Circulation. 2005;111:1869–1870A PubMed search in March 2005 with the key word "metabolic syndrome" yielded >10 000 references. Past labels for this disorder include "syndrome X," "deadly quartet," and "cardiovascular dysmetabolic syndrome."1–3 What is driving the current increased interest in the metabolic syndrome? Possibly the impetus comes from the dramatic increases in obesity in the United States and other developed countries.4 This pandemic has been blamed variously on fast food, high-fat foods, low-fat foods, overreliance on the automobile, television, the Internet, homes in which both parents work, unsafe streets, the disappearance of physical education from the K–12 school curriculum, neighborhoods unsuitable for walking, and some or all of the above. An extensive and consistent body of evidence predicts that accompanying this increase in obesity will be increases in insulin resistance/diabetes, hypertension, hypertriglyceridemia, and decreased HDL cholesterol, as well as unfavorable changes in endothelial function and a host of inflammatory, thrombotic, and fibrinolytic factors. Thus, there is, indeed, reason for concern.See p 1883In this issue of Circulation, Tankó and colleagues5 attempt a simplification of the National Cholesterol Education Program–Adult Treatment Panel III definition of metabolic syndrome (MS-NCEP) in postmenopausal women. They report that the combination of an enlarged waist and "elevated" triglycerides (EWET; enlarged waist, elevated triglycerides), as compared with the MS-NCEP, was equally prevalent, somewhat more predictive of cardiovascular disease (CVD) death, and somewhat more predictive of abdominal aortic calcium (AAC) progression. Their argument is carefully researched and presented but may strike the reader as counterintuitive. Why should a definition that uses only 2 criteria be a better predictor than the MS-NCEP, which requires at least 3 of 5 known atherogenic risk factors? The answer lies in the cutpoints for abnormality, the inclusion/exclusion nature of the 2 definitions, and the strength of the individual predictive components. First, the MS-NCEP uses a triglycerides cutpoint of 1.69 mmol/L (150 mg/dL), whereas the EWET cutpoint is lower, 1.45 mmol/L (128 mg/dL), and the risk associated with triglycerides appears to reach at least to the 1.45-mmol/L level.6 Thus, more women appropriately qualify as having elevated triglycerides in EWET. Second, the EWET definition requires that a woman have both a large waist circumference and elevated triglycerides, whereas women meeting the MS-NCEP definition may have normal values for any 2 of the following: waist, triglycerides, blood pressure, insulin resistance, and HDL cholesterol. Finally, the strongest predictor of outcome in this study was triglycerides, and in fact, enlarged waist was not significantly related to CVD mortality in multivariate analysis, a finding concordant with our results for CVD morbidity from a large national US sample.7 This does not mean that enlarged waist is not a CVD risk factor, but rather that the biological effect is mediated by correlated risk factors.7 There is a growing consensus about the importance of triglycerides, particularly in women, and we have shown in the same national US sample that triglyceride level was the single most predictive component of the MS-NCEP for CVD in multivariate analysis.7What the EWET definition really does is include all of the women with the highest risk component, triglycerides, whereas the MS-NCEP does not. This also likely explains why EWET showed a stronger relationship to AAC progression than did the MS-NCEP. The authors also report a strong association between any baseline AAC and CVD mortality, with an adjusted hazard ratio of 6.4. This is concordant with earlier studies, which similarly measured AAC with a lateral abdominal plain film.8,9 Several current studies are precisely quantifying AAC deposits with CT scans, and preliminary data indicate AAC may be a particularly useful "subclinical" measure. There is much interest in the idea that CVD risk equations can be improved by considering subclinical CVD measures or "newer" risk factors, such as inflammatory markers.10–12 The goal would be a parsimonious and ideally inexpensive set of markers that would explain a large proportion of the variance in CVD events.In paying such close attention to the MS-NCEP (a natural tendency, given the ongoing obesity epidemic), it is important to realize that the CVD risk factors that define the MS-NCEP and the EWET are not newly recognized. More than a half-century of prospective epidemiological research has identified several modifiable independent CVD risk factors, including cigarette smoking, hypertension, insulin resistance/diabetes, and dyslipidemia, with the best single marker of dyslipidemic risk being the total cholesterol to HDL cholesterol ratio.13 Our concern with the obesity epidemic rightly focuses our attention on the risk factors linked to obesity, which cluster in the MS-NCEP, but nothing we have learned in studying the MS-NCEP changes what we learned in earlier epidemiological studies. For example, in the study by Tankó et al,5 the 2 significant predictors of CVD mortality in their cohort other than triglycerides were low HDL cholesterol and hypertension, and again, enlarged waist was not predictive. The EWET ignores low HDL cholesterol and hypertension, although many women with EWET will of course have them because these risk factors are correlated.14 Thus, the findings of this study support an extensive body of literature showing that elevated triglycerides, low HDL cholesterol, and hypertension pose independent risks for CVD mortality in postmenopausal women. Cigarette smoking was presumably a risk factor as well, although hazard ratios for this variable were not presented.Tankó et al5 summarize by stating they believe that "EWET comprises a simple diagnostic tool" and "further evaluation of EWET as a universally applicable screening tool … is warranted." I believe the authors' data support a different conclusion: that abnormal triglycerides, HDL cholesterol, and blood pressure should be measured, along with other independent CVD risk factors, to provide the best estimate of CVD risk. Indeed, why would you not consider HDL cholesterol if you were planning to measure triglycerides? Why would you not consider the important and routinely available blood pressure? The authors further conclude, with admirable scientific caution, "intervention studies are awaited to test the hypothesis that decreases in waist circumference and serum levels of triglycerides confer beneficial effect in terms of reducing cardiovascular risk in postmenopausal women." This begs the question: How much more data do we really need? I think little doubt remains that weight loss in the obese patient will have a favorable impact on CVD risk.15 As for triglycerides intervention per se, one clinical trial showed that the benefit from drug therapy was related to a change in triglycerides but not cholesterol,16 and at least 3 other trials showed that the benefit of drug therapy was largely confined to subjects with high triglycerides, accompanied by low HDL cholesterol, because of its inverse correlation with triglycerides.17–19Methods to reduce obesity and improve obesity-related risk factors have not changed much throughout the course of history; they involve reduced calorie consumption or increased physical activity, and ideally both in the typical patient. Dietary weight loss and accompanying CVD risk factor reduction are direct results of reduced calorie intake and are largely unrelated to the composition of the diet used,20 although individual components of diet, such as fruit, omega-3 polyunsaturated fats, and fiber, may provide additional health benefits. Of course, not all risk factors accompany obesity, and some individuals have "obesity-related" risk factors without being obese. Although pharmacological therapy will remain a mainstay of treatment, significant improvement in CVD risk factors is possible with lifestyle changes alone. Curbing the obesity epidemic at an individual and a societal level is as daunting a challenge as it is worthy a goal.The opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.FootnotesCorrespondence to Michael H. Criqui, MD, MPH, Professor, Dept of Family and Preventive Medicine, UCSD School of Medicine, 9500 Gilman Dr, 352 SCRB, La Jolla, CA 92093-0607. E-mail [email protected] References 1 Reaven GM. Role of insulin resistance in human disease (syndrome X): an expanded definition. Annu Rev Med. 1993; 44: 121–131.CrossrefMedlineGoogle Scholar2 Kaplan NM. The deadly quartet. Upper-body obesity, glucose intolerance, hypertriglyceridemia, and hypertension. Arch Intern Med. 1989; 149: 1514–1520.CrossrefMedlineGoogle Scholar3 Fagan TC, Deedwania PC. The cardiovascular dysmetabolic syndrome. Am J Med. 1998; 105: 77S–82S.CrossrefMedlineGoogle Scholar4 James PT, Rigby N, Leach R; International Obesity Task Force. The obesity epidemic, metabolic syndrome and future prevention strategies. Eur J Cardiovasc Prev Rehabil. 2004; 11: 3–8.CrossrefMedlineGoogle Scholar5 Tankó LB, Bagger YZ, Qin G, Alexandersen P, Larsen PJ, Christiansen C. Enlarged waist combined with elevated triglycerides is a strong predictor of accelerated atherogenesis and related cardiovascular mortality in postmenopausal women. Circulation. 2005; 111: 1883–1890.LinkGoogle Scholar6 Criqui MH, Heiss G, Cohn R, Cowan LD, Suchindran CM, Bangdiwala S, Kritchevsky S, Jacobs DR Jr, O'Grady HK, Davis CE. Plasma triglyceride level and mortality from coronary heart disease. N Engl J Med. 1993; 328: 1220–1225.CrossrefMedlineGoogle Scholar7 Ninomiya JK, L'Italien G, Criqui MH, Whyte JL, Gamst A, Chen RS. Association of the metabolic syndrome with history of myocardial infarction and stroke in the Third National Health and Nutrition Examination Survey. Circulation. 2004; 109: 42–46.LinkGoogle Scholar8 Witteman JC, Kok FJ, van Saase JL, Valkenburg HA. Aortic calcification as a predictor of cardiovascular mortality. Lancet. 1986; 2: 1120–1122.CrossrefMedlineGoogle Scholar9 Wilson PW, Kauppila LI, O'Donnell CJ, Kiel DP, Hannan M, Polak JM, Cupples LA. Abdominal aortic calcific deposits are an important predictor of vascular morbidity and mortality. Circulation. 2001; 103: 1529–1534.CrossrefMedlineGoogle Scholar10 Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux AV, Folsom AR, Greenland P, Jacob DR Jr, Kronmal R, Liu K, Nelson JC, O'Leary D, Saad MF, Shea S, Szklo M, Tracy RP. Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol. 2002; 156: 871–881.CrossrefMedlineGoogle Scholar11 Ridker PM, Rifai N, Rose L, Buring JE, Cook NR. Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events. N Engl J Med. 2002; 347: 1557–1565.CrossrefMedlineGoogle Scholar12 Greenland P, LaBree L, Azen SP, Doherty TM, Detrano RC. Coronary artery calcium score combined with Framingham score for risk prediction in asymptomatic individuals. JAMA. 2004; 291: 210–215.CrossrefMedlineGoogle Scholar13 Natarajan S, Glick H, Criqui M, Horowitz D, Lipsitz SR, Kinosian B. Cholesterol measures to identify and treat individuals at risk for coronary heart disease. Am J Prev Med. 2003; 25: 50–57.CrossrefMedlineGoogle Scholar14 Criqui MH, Barrett-Connor E, Holdbrook MJ, Austin M, Turner JD. Clustering of cardiovascular disease risk factors. Prev Med. 1980; 9: 525–533.CrossrefMedlineGoogle Scholar15 Eilat-Adar S, Eldar M, Goldbourt U. Association of intentional changes in body weight with coronary heart disease event rates in overweight subjects who have an additional coronary risk factor. Am J Epidemiol. 2005; 161: 352–358.CrossrefMedlineGoogle Scholar16 Carlson LA, Rosenhamer G. Reduction of mortality in the Stockholm Ischaemic Heart Disease Secondary Prevention Study by combined treatment with clofibrate and nicotinic acid. Acta Med Scand. 1988; 223: 405–418.CrossrefMedlineGoogle Scholar17 Miller BD, Krauss RM, Cashin-Hemphill L, Blankenhorn DH. Baseline triglyceride levels predict angiographic benefit of colestipol plus niacin therapy in the Cholesterol-Lowering Atherosclerosis Study (CLAS). Circulation. 1993; 88: S1–S363.Google Scholar18 Manninen V, Tenkanen L, Koskinen P, Huttunen JK, Manttari M, Heinonen OP, Frick MH. Joint effects of serum triglyceride and LDL cholesterol and HDL cholesterol concentrations on coronary heart disease risk in the Helsinki Heart Study. Implications for treatment. Circulation. 1992; 85: 37–45.CrossrefMedlineGoogle Scholar19 Ballantyne CM, Olsson AG, Cook TJ, Mercuri MF, Pedersen TR, Kjekshus J. Influence of low high-density lipoprotein cholesterol and elevated triglyceride on coronary heart disease events and response to simvastatin therapy in 4S. Circulation. 2001; 104: 3046–3051.CrossrefMedlineGoogle Scholar20 Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for weight loss and heart disease risk reduction: a randomized trial. JAMA. 2005; 293: 43–53.CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetailsCited By Rodriguez-Moran M, Aradillas-Garcia C, Simental-Mendia L, Monreal-Escalante E, de la Cruz Mendoza E, Davila Esqueda M and Guerrero-Romero F (2010) Family History of Hypertension and Cardiovascular Risk Factors in Prepubertal Children, American Journal of Hypertension, 10.1038/ajh.2009.257, 23:3, (299-304), Online publication date: 1-Mar-2010. Rayssac A, Neveu C, Pucelle M, Van den Berghe L, Prado-Lourenco L, Arnal J, Chaufour X and Prats A (2009) IRES-based Vector Coexpressing FGF2 and Cyr61 Provides Synergistic and Safe Therapeutics of Lower Limb Ischemia, Molecular Therapy, 10.1038/mt.2009.211, 17:12, (2010-2019), Online publication date: 1-Dec-2009. 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April 19, 2005Vol 111, Issue 15 Advertisement Article InformationMetrics https://doi.org/10.1161/01.CIR.0000163649.99244.A8PMID: 15837937 Originally publishedApril 19, 2005 KeywordsobesityEditorialsrisk factorscardiovascular diseaseswomenPDF download Advertisement SubjectsEpidemiologyObesityPrimary Prevention
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