- Email: [email protected]
Association between metabolic syndrome and subclinical coronary atherosclerosis in asymptomatic adults
9. Costa MA, Sabat M, van der Giessen WJ, Kay IP, Cervinka P, Ligthart JM,
13. Danenberg HD, Lotan C, Hasin Y, Gotsman MS, Rozenman Y. Acute
Serrano P, Coen VL, Levendag PC, Serruys PW. Late coronary occlusion after intracoronary brachytherapy. Circulation 1999;100:789 –792. 10. Waksman R, Bhargava B, Mintz GS, Mehran R, Lansky AJ, Satler LF, Pichard AD, Kent KM, Leon MB. Late total occlusion after intracoronary brachytherapy for patients with in-stent restenosis. J Am Coll Cardiol 2000;36: 65– 68. 11. Rozenman Y, Gilon D, Welber S, Sapoznikov D, Wexler D, Lotan C, Mosseri M, Weiss AT, Hasin Y, Gotsman MS. Total coronary artery occlusion late after successful coronary angioplasty of moderately severe lesions: incidence and clinical manifestations. Cardiology 1994;85:222–228. 12. Farb A, Burke AP, Kolodgie FD, Virmani R. Pathological mechanisms of fatal late coronary stent thrombosis in humans. Circulation 2003;108:1701–1706.
myocardial infarction—a late complication of intracoronary stent placement. Clin Cardiol 2000;23:376 –378. 14. Heller LI, Shemwell KC, Hug K. Late stent thrombosis in the absence of prior intracoronary brachytherapy. Catheter Cardiovasc Interventions 2001;53:23–28. 15. Cha DH, Malik IA, Cheneau E, Ajani AE, Leborgne L, Wolfram R, Porrazzo M, Satler LF, Kent KM, Pichard AD, et al. Use of restenting should be minimized with intracoronary radiation therapy for in-stent restenosis. Catheter Cardiovasc Interventions 2003;59:1–5. 16. Waksman R, Lew R, Ajani AE, Pichard AD, Satler LF, Kent KM, Chan R, White RL, Suddath WO, Pinnow E, et al. Repeat intracoronary radiation for recurrent in-stent restenosis in patients who failed intracoronary radiation. Circulation 2003;108:654 – 656.
Association Between Metabolic Syndrome and Subclinical Coronary Atherosclerosis in Asymptomatic Adults Iftikhar J. Kullo, MD, Andrea E. Cassidy, MPH, Patricia A. Peyser, PhD, Stephen T. Turner, MD, Patrick F. Sheedy II, MD, and Lawrence F. Bielak, DDS, Metabolic syndrome was associated with the presence and quantity of coronary artery calcium, a marker of subclinical coronary atherosclerosis, in 1,129 asymptomatic adults, ages 20 to 79 years, from a community-based study. The association was independent of 10-year risk of coronary heart disease based on the Framingham risk score. 䊚2004 by Excerpta Medica Inc. (Am J Cardiol 2004;94:1554 –1558)
he complex inter-relations among components of the metabolic syndrome and 10-year risk for corT onary heart disease (CHD) based on the Framingham risk score and their relations to noninvasive measures of subclinical coronary atherosclerosis are not well established. Although several studies1–3 have demonstrated an association of the metabolic syndrome with coronary artery calcium (CAC), none of studies used the strict definition of the metabolic syndrome of the Adult Treatment Panel III (ATP III) of the National Cholesterol Education Panel,4 or the study cohorts were comprised of physician- or self-referred subjects. The goal of the present investigation was to determine whether the metabolic syndrome was independently associated with the presence and quantity of CAC in asymptomatic subjects from a community after conFrom the Division of Cardiovascular Disease, Division of Hypertension, Department of Internal Medicine; and Department of Diagnostic Radiology, Mayo Clinic and Foundation, Rochester, Minnesota; and Department of Epidemiology, University of Michigan, Ann Arbor, Michigan. This study was supported by grants R01 HL46292 and M01 RR00585 from the National Institutes of Health, Bethesda, Maryland; grant T32 HG00040 from the National Human Genome Research Institute; and a Mentored Patient-Oriented Research Award to Dr. Kullo (K23 RR17720-01) from the National Institutes of Health, National Center of Research Resources. Dr. Bielak’s address is: University of Michigan, Department of Epidemiology, 611 Church Street, Ann Arbor, Michigan 48104-3028. E-mail: [email protected]. Manuscript received May 11, 2004; revised manuscript received and accepted August 6, 2004.
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sidering (1) conventional CHD risk factors and (2) the estimated 10-year risk for a CHD event. •••
The Epidemiology of Coronary Artery Calcification Study is an ongoing community-based study of the etiology of CAC in Rochester, Minnesota.5,6 Subjects were recruited from the community-based Rochester Family Heart Study, were not self or physician referred, and did not have previous bypass surgery, angioplasty, or other coronary surgery.7,8 Between December 1990 and May 1998, 1,240 subjects were examined for CAC with electron beam computed tomography. We excluded 8 subjects who were ⱖ80 years of age, 23 who had a history of stroke or myocardial infarction, 5 who were nonwhite, 19 who had diabetes mellitus, 37 who had missing data (including 17 who had missing fasting glucose values), and 19 who had outliers for risk factor data. The final study group consisted of 1,129 asymptomatic white subjects (548 men and 581 women). Subjects belonged to 843 sibships (668 singletons, 105 sibships of size 2, 45 sibships of size 3, 3 sibships of size 4, 2 sibships of size 5, and 3 sibships of size 6). Study protocols were approved by the institutional review boards of the Mayo Clinic and the University of Michigan, and subjects gave written informed consent. During an interview, subjects reported current medication use, history of smoking, physician-diagnosed hypertension, myocardial infarction, stroke, or diabetes. Systolic and diastolic blood pressures at rest were measured in the right arm with a random-zero sphygmomanometer (Hawksley and Sons, London, United Kingdom). Three measurements ⱖ2 minutes apart were taken, and the average of the second and third measurements was used. Waist circumference was measured between the lowest rib and the iliac crest. Blood samples were obtained after an overnight fast. Standard enzymatic methods were used to measure plasma glucose, total cholesterol, high-density lipoprotein cholesterol, and triglycerides. Low-density lipoprotein cholesterol was calculated with Friede0002-9149/04/$–see front matter doi:10.1016/j.amjcard.2004.08.038
TABLE 1 Subjects’ Characteristics Men (n ⫽ 548)*
Variable Age (yrs) Waist circumference (cm) Total cholesterol (mmol/L) Total cholesterol (mg/dl) Triglycerides (mmol/L) Triglycerides (mg/dl) LDL cholesterol (mmol/L) LDL cholesterol (mg/dl) HDL cholesterol (mmol/l) HDL cholesterol (mg/dl) Systolic BP (mm Hg) Diastolic BP (mm Hg) Fasting glucose (mmol/L) Fasting glucose (mg/dl) 10-year risk for CHD (%) CAC score Presence of CAC Current smoker Abdominal obesity Hypertriglyceridemia‡ Low HDL cholesterol High blood pressure Hyperglycemia ⱖ1 Component of the metabolic syndrome ⱖ2 Components of the metabolic syndrome Metabolic syndrome
47.2 92.4 4.9 190.4 1.5 135.2 3.2 124.1 1.0 39.4 119.1 78.0 5.0 89.9 7.6 101.5
⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾
14.6 (20.0–78.8) 10.6 (68.0–135.0) 1.0 (2.6–8.5) 37.5 (99.0–327.0) 0.9 (0.4–8.6) 79.5 (37.0–759.0) 0.9 (0.7–6.1) 33.2 (26.4–236.8) 0.3 (0.5–2.0) 9.5 (18.0–75.8) 15.5 (84.0–184.0) 9.8 (43.0–120.0) 0.6 (2.5–8.0) 9.9 (44.3–144.8) 7.1 (1.0–30.0) 277.5 (0.0–3,036.7) 289 (52.7%) 85 (15.5%) 96 (17.5%) 160 (29.2%) 316 (57.7%) 188 (34.3%) 20 (3.7%) 416 (75.9%) 224 (40.9%) 99 (18.1%)
Women (n ⫽ 581)† 48.5 80.5 5.0 191.7 1.4 120.9 3.0 116.3 1.3 51.1 116.8 73.9 4.9 87.4 2.3 41.5
⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾
14.3 (20.2–79.2) 13.6 (55.1–147.6) 1.0 (2.4–8.6) 39.7 (94.0–331.0) 0.7 (0.2–5.4) 63.5 (21.0–477.0) 0.9 (0.5–6.9) 33.7 (18.5–266.9) 0.4 (0.4–2.6) 13.7 (16.8–101.0) 17.2 (78.0–196.0) 8.8 (37.0–104.0) 0.6 (3.5–8.8) 11.1 (63.7–158.0) 2.9 (1.0–22.0) 185.2 (0.0–2,488.5) 142 (24.4%) 80 (13.8%) 144 (24.8%) 139 (23.9%) 290 (49.9%) 172 (29.6%) 24 (4.1%) 418 (71.9%) 198 (34.1%) 105 (18.1%)
Values are mean ⫾ SD (ranges) or numbers of subjects (percentages). *There were 539 men who had LDL cholesterol values (values for 11 men were missing because triglycerides ⬎400 mg/dl [4.56 mmol/L]). † There were 579 women who had LDL cholesterol values (values for 2 women were missing because triglycerides ⬎400 mg/dl [4.56 mmol/L]). ‡ Hypertriglyceridemia defined as triglycerides ⱖ150 mg/dl (1.69 mmol/L). BP ⫽ blood pressure; HDL ⫽ high-density lipoprotein; LDL ⫽ low-density lipoprotein.
TABLE 2 Age- and Gender-adjusted Associations of the Metabolic Syndrome With the Presence and Quantity of Coronary Artery Calcium (CAC) Predictor Metabolic syndrome Abdominal obesity Hypertriglyceridemia Low HDL cholesterol High blood pressure Hyperglycemia No. of metabolic components 0 1 2 3 ⱖ4
Parameter Estimate ⫾ SE
Change in Probability of Having CAC
Percent Change in Quantity of CAC
p Value
⫾ ⫾ ⫾ ⫾ ⫾ ⫾
0.45 0.47 0.42 0.40 0.42 0.79
17.3% 13.8% 11.5% 9.4% 12.9% 14.8%
206.9% 79.5% 62.9% 49.6% 72.5% 85.5%
⬍0.001 ⬍0.001 ⬍0.001 0.001 ⬍0.001 0.009
Referent 0.92 ⫾ 0.58 1.85 ⫾ 0.60 2.93 ⫾ 0.68 4.00 ⫾ 0.77
6.7% 13.4% 21.2% 29.0%
32.1% 75.2% 243.0% 336.0%
0.111 0.002 ⬍0.001 ⬍0.001
2.40 1.93 1.61 1.33 1.80 2.04
Abbreviation as in Table 1.
wald’s equation.9 The 10-year risk for CHD was calculated with the gender-specific Framingham risk score.4 The metabolic syndrome was defined according to ATP III criteria4 as the presence of ⱖ3 of the following characteristics: abdominal obesity (waist circumference ⬎102 cm in men and ⬎88 cm in women), hypertriglyceridemia (triglyceride level ⱖ150 mg/dl), low level of high-density lipoprotein cholesterol (high-density lipoprotein cholesterol level ⬍40 mg/dl in men and ⬍50 mg/dl in women), high blood pressure (systolic blood pressure ⱖ130 mm Hg, diastolic
blood pressure ⱖ85 mm Hg, or use of antihypertensive medication), and hyperglycemia (glucose level ⱖ110 mg/dl). CAC was measured with an Imatron C-100 or C-150 electron beam computed tomographic scanner (Imatron Inc., South San Francisco, California). Forty contiguous, 3-mm thick, 2-dimensional transverse images were obtained from the level of the right branch of the pulmonary artery to the apex of the heart. Electron beam computed tomographic data were reviewed for technical quality by a radiologist and then scored by a radiologic technologist who used customBRIEF REPORTS
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FIGURE 1. Predicted probability of having CAC (A) and predicted mean CAC score (B) for hypothetical 60-year-old subjects who have the indicated number of metabolic abnormalities.
TABLE 3 Gender-adjusted Associations of the Metabolic Syndrome and 10-year Risk for Coronary Heart Disease With the Presence and Quantity of Coronary Artery Calcium (CAC) Predictor
Parameter Estimate ⫾ SE
Change in Probability of Having CAC
Percent Change in Quantity of CAC
p Value
Metabolic syndrome 10-Year risk for CHD
2.15 ⫾ 0.56 0.55 ⫾ 0.04
13.4% 3.4%
98.1% 18.1%
⬍0.001 ⬍0.001
ized computer software.10 CAC was defined as a hyperattenuating focus, ⱖ4 contiguous pixels, and computed tomographic numbers ⬎130 HU for each pixel. A score for each focus of CAC was calculated by multiplying the focus area (square millimeters) by a density measurement that was defined by the peak computed tomographic number in the focus.11 Total CAC score was calculated as the sum of scores for all foci in the epicardial arteries.11 A statistical significance level of 0.05 was used. Age- and gender-adjusted Tobit’s regression models were used to investigate associations of the metabolic syndrome, its individual components, and the number of the metabolic syndrome components with the presence and quantity of CAC. Tobit’s regression models are useful when the outcome variable is censored below a threshold value (in this study, below the threshold of detection).12,13 To decrease skewness, the natural log-transformation of the CAC score was taken among those with detectable CAC. Tobit’s regression model parameters were used to estimate a predicted probability of having detectable CAC and a predicted mean detected CAC quantity associated with 0, 1, 2, 3, and ⱖ4 metabolic syndrome components for hypothetical subjects 60 years of age. To evaluate the importance of the metabolic syndrome for predicting the presence and quantity of CAC after adjusting for conventional risk factors, Tobit’s regression model was fit with the metabolic syndrome, age, male gender, current smoking status, level of lowdensity lipoprotein cholesterol, and use of lipid-lowering medications as independent variables. We also evaluated the importance of the metabolic syndrome for predicting presence and quantity of CAC after adjusting for 10-year risk of CHD by fitting Tobit’s regression models that 1556 THE AMERICAN JOURNAL OF CARDIOLOGY姞
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contained the metabolic syndrome, male gender, and 10-year risk of CHD. Because parameters from Tobit’s models are not directly interpretable, parameters estimated from each model were decomposed into (1) the change in the probability of having detectable CAC and (2) the percent change in CAC score among those who had detectable CAC. Because some subjects were members of the same sibship, their observations were independent across sibships but not within sibships. Therefore, all Tobit’s regression models incorporated the correlation among subjects in the same sibship into the estimated SE values and the variance– covariance matrix of the estimators. Ordinal logistic regression models that examined the relation between the metabolic syndrome and CAC after adjusting for male gender and (1) age and (2) 10-year risk for CHD were fit to decrease the chance that any associations found were due to the relatively large degree of skewness of the distribution of CAC scores. CAC score was categorized based on guidelines that corresponded to probability of significant coronary artery disease: 0 (very low probability of coronary artery disease), ⬎1 to ⱕ10 (very unlikely coronary artery disease), ⬎10 to ⱕ100 (likely mild to minimal coronary stenosis), ⬎100 to ⱕ400 (nonobstructive coronary artery disease likely), and ⬎400 (high likelihood of ⱖ1 “significant” coronary stenosis).14 The models allowed estimation of the odds of being in a higher CAC score category versus a lower CAC score category. Subjects’ characteristics are presented in Table 1. Approximately 75% of men and women had ⱖ1 component of the metabolic syndrome. The presence of DECEMBER 15, 2004
FIGURE 2. Prevalence of the metabolic syndrome increases significantly as the CAC category increases (p <0.001 for trend).
metabolic syndrome was the same in men and women (18.1%) and increased significantly with advancing age. Among men, prevalence of the metabolic syndrome increased from 2.4% among those 20 to 29 years of age to 34.3% among those 70 to 79 years of age; among women, prevalence of the metabolic syndrome increased from 3.7% among those 20 to 29 years of age to 51.2% among those 70 to 79 years of age (p ⬍0.001 for trend in men and women). Men who had the metabolic syndrome and those who did not had mean ⫾ SD CAC scores of 201 ⫾ 420 and 80 ⫾ 230, respectively, and median (range) CAC scores of 35 (0 to 3,037) and 0 (0 to 1,987), respectively. Women who had the metabolic syndrome and those who did not had mean ⫾ SD CAC scores of 98 ⫾ 262 and 29 ⫾ 161, respectively, and median (range) CAC scores of 1.04 (0 to 1,512) and 0 (0 to 2,489), respectively. The metabolic syndrome was associated with the presence and quantity of CAC after adjusting for age and male gender (p ⬍0.001; Table 2). Presence of the metabolic syndrome was associated with a 17.3% change in the probability of having CAC and an ⬃207% change in the quantity of CAC in those who had detectable CAC. Each component of the metabolic syndrome was significantly associated with the presence and quantity of CAC (Table 2). Having 2, 3, or ⱖ4 components was significantly associated with the presence and quantity of CAC compared with those who had 0 components after adjusting for age and male gender (Table 2). In men and women, after adjusting for age, the predicted probability of having CAC (Figure 1) and the predof having CACicted mean CAC score (if CAC was detected) increased as the number of metabolic syndrome components increased (Figure 1). The estimates presented in Figure 1 are for a hypothetical 60-year-old man and 60-year-old woman with the indicated number of metabolic abnormalities. The metabolic syndrome was significantly associated with the presence and quantity of CAC after adjusting for age, male gender, current smoking status, level of low-density lipoprotein cholesterol, and use of lipid-lowering medications (p ⬍0.001). All conventional risk factors except current smoking status were significant. In models that included male
gender, the metabolic syndrome, and 10-year risk for CHD, the metabolic syndrome and 10-year risk for CHD were statistically significantly associated with the presence and quantity of CAC (Table 3). Most subjects had no CAC (62%); 9.2% had CAC scores ⬎1 to ⱕ10, 16% had CAC scores ⬎10 to ⱕ100, 7.9% had CAC scores ⬎100 to ⱕ400, and 5.4% had CAC scores ⬎400. The distribution of the metabolic syndrome by CAC category is presented in Figure 2; prevalence of the metabolic syndrome increased significantly as the CAC category increased (p ⬍0.001 for trend). After adjusting for age and male gender, the metabolic syndrome was significantly and positively associated with CAC (p ⬍0.001). The metabolic syndrome remained significantly and positively associated with CAC after adjusting for the 10-year risk for CHD (p ⬍0.001). At any given level of 10-year risk for CHD, subjects who had the metabolic syndrome had 1.7 times (95% confidence interval 1.3 to 2.4) the odds of being in a higher CAC category versus a lower CAC category compared with those who did not have the metabolic syndrome. •••
This is the first study to report a significant association between the metabolic syndrome, according to the ATP III definition, and the presence and quantity of CAC in asymptomatic men and women who had been recruited from a community. The association was independent of a subject’s 10-year risk for CHD based on the Framingham risk score. The findings indicate that factors that contribute to atherosclerosis are not fully captured by conventional profiling of risk factors. Our findings suggest that 1 mechanism of increased CHD risk in subjects who have the metabolic syndrome may be an increase in coronary atherosclerotic plaque. 1. Wong ND, Sciammarella MG, Polk D, Gallagher A, Miranda-Peats L, Whit-
comb B, Hachamovitch R, Friedman JD, Hayes S, Berman DS. The metabolic syndrome, diabetes, and subclinical atherosclerosis assessed by coronary calcium. J Am Coll Cardiol 2003;41:1547–1553. 2. Hunt ME, O’Malley PG, Feuerstein I, Taylor AJ. The relationship between the ‘metabolic score’ and sub-clinical atherosclerosis detected with electron beam computed tomography. Coron Artery Dis 2003;14:317–322. 3. Arad Y, Newstein D, Cadet F, Roth M, Guerci AD. Association of multiple risk factors and insulin resistance with increased prevalence of asymptomatic coronary artery disease by an electron-beam computed tomographic study. Arterioscler Thromb Vasc Biol 2001;21:2051–2058. 4. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. 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;285:2486 –2497. 5. Maher JE, Raz JA, Bielak LF, Sheedy PF II, Schwartz RS, Peyser PA. Potential of quantity of coronary artery calcification to identify new risk factors for asymptomatic atherosclerosis. Am J Epidemiol 1996;144:943–953. 6. Bielak LF, Sheedy PF II, Peyser PA. Coronary artery calcification measured at electron-beam CT: agreement in dual scan runs and change over time. Radiology 2001;218:224 –229. 7. Turner ST, Weidman WH, Michels VV, Reed TJ, Ormson CL, Fuller T, Sing CF. Distribution of sodium-lithium countertransport and blood pressure in Caucasians five to eighty-nine years of age. Hypertension 1989;13:378 –391. 8. Kottke BA, Moll PP, Michels VV, Weidman WH. Levels of lipids, lipoproteins, and apolipoproteins in a defined population. Mayo Clin Proc 1991;66: 1198 –1208. 9. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499 –502.
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10. Reed JE, Rumberger JA, Davitt PJ, Kaufmann RB, Sheedy PF II. System for
quantitative analysis of coronary calcification via electron beam computed tomography. In: Hoffman EA, Acharya RS, eds. Medical Imaging, 1994: Physiology and Function From Multidimensional Images. Bellingham, WA: International Society for Optical Engineering, 1994:43–53. 11. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 1990;15:827– 832. 12. Breen R. Regression Models: Censored, Sample Selected, or Truncated Data.
Sage University Paper Series on Quantitative Applications in the Social Sciences, no. 07–111. Thousand Oaks, CA: Sage, 1996:27–30. 13. Jamjoum LS, Turner ST, Bielak LF, Sheedy PF II, Boerwinkle E, Raghunathan TE, Peyser PA. Relationship of blood pressure level and hypertension with coronary artery calcification. Med Sci Monit 2002;12:775– 781. 14. Rumberger JA, Brundage BH, Rader DJ, Kondos G. Electron beam computed tomographic coronary calcium scanning: a review and guidelines for use in asymptomatic persons. Mayo Clin Proc 1999;74:243–252.
Effectiveness of Therapeutic Lifestyle Changes in Patients With Hypertension, Hyperlipidemia, and/or Hyperglycemia Neil F. Gordon, MD, PhD, Richard D. Salmon, DDS, MBA, Barry A. Franklin, PhD, Laurence S. Sperling, MD, Linda Hall, PhD, Richard F. Leighton, MD, and William L. Haskell, PhD In this prospective study of 2,390 ethnically diverse men and women, we evaluated the clinical effectiveness of 12 weeks of participation in a communitybased lifestyle management program in helping patients who had hypertension, hyperlipidemia, and/or impaired fasting glucose or diabetes mellitus achieve goal risk factor levels without using pharmacotherapeutic agents. Although further research is warranted, the findings clearly show that many patients who have conventional risk factors for coronary heart disease can achieve goal levels without medications within 12 weeks of initiating therapeutic lifestyle changes and refute the notion that intensive lifestyle intervention is not worth the effort. 䊚2004 by Excerpta Medica Inc. (Am J Cardiol 2004;94:1558 –1561)
ecent studies have emphasized the need to intensify efforts aimed at the control of conventional R risk factors for coronary heart disease. National 1,2
clinical guidelines have promulgated therapeutic lifestyle changes as a standard of care in the management of conventional risk factors.3,4 However, because of the widespread availability of powerful medications, the value of therapeutic lifestyle changes per se in contemporary medical practice is often discounted by clinicians, health insurers, and patients. In this prospective study of 2,390 patients, we evaluated the clinical effectiveness of 12 weeks of therapeutic lifeFrom the Center for Heart Disease Prevention, St. Joseph’s/Candler Health System, Savannah, Georgia; the INTERVENT Coordinating Center, Savannah, Georgia; the Emory University School of Medicine, Atlanta, Georgia; the William Beaumont Hospital, Royal Oak, Michigan; the Forrest General Hospital, Hattiesburg, Mississippi; and the Stanford University School of Medicine, Palo Alto, California. Dr. Gordon’s address is: Center for Heart Disease Prevention, St. Joseph’s/Candler Health System, 5356 Reynolds Street, Suite 120, Savannah, Georgia 31405. E-mail: [email protected]. Manuscript received May 4, 2004; revised manuscript received and accepted August 4, 2004.
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style changes in helping patients who had hypertension, hyperlipidemia, and/or impaired fasting glucose or diabetes mellitus achieve goal risk factor levels without using pharmacotherapeutic agents. •••
A cohort of 2,390 consecutive adult patients who completed initial and 12-week follow-up assessments as part of their participation in a comprehensive, community-based lifestyle management program comprised the study population. Patients were self-referred or referred by a physician to participate in the program and met ⱖ1 of the following criteria: baseline (i.e., at program entry) systolic blood pressure (BP) ⱖ140 mm Hg and/or diastolic BP ⱖ90 mm Hg and not taking antihypertensive medications at baseline or follow-up, baseline fasting level ⱖ100 mg/dl for low-density lipoprotein cholesterol and not taking antilipemic medications at baseline or follow-up, or baseline fasting glucose level ⱖ110 mg/dl and not taking antidiabetic medications at baseline or follow-up. Written informed consent was obtained from each patient. Baseline clinical characteristics are listed in Table 1. The lifestyle management program was administered by non-physician health care providers who were guided by a computerized participant management system, as previously described.5,6 Briefly, the program included the following core components: (1) initial assessment, including completion of a comprehensive medical history questionnaire and measurement of height, weight, waist circumference, seated BP, fasting serum lipids and lipoproteins, and fasting glucose; (2) computer generation of risk factor goals based on national clinical guidelines3,7–11 and an action plan for achieving these goals through comprehensive lifestyle changes; (3) action plan implementation, including 1-on-1 behaviorally oriented counseling (face to face or, if the patient preferred, by telephone and the Internet) to help each patient acquire the skills, motivation, and support needed to implement and adhere to an individually prescribed 0002-9149/04/$–see front matter doi:10.1016/j.amjcard.2004.08.039
13. Danenberg HD, Lotan C, Hasin Y, Gotsman MS, Rozenman Y. Acute
Serrano P, Coen VL, Levendag PC, Serruys PW. Late coronary occlusion after intracoronary brachytherapy. Circulation 1999;100:789 –792. 10. Waksman R, Bhargava B, Mintz GS, Mehran R, Lansky AJ, Satler LF, Pichard AD, Kent KM, Leon MB. Late total occlusion after intracoronary brachytherapy for patients with in-stent restenosis. J Am Coll Cardiol 2000;36: 65– 68. 11. Rozenman Y, Gilon D, Welber S, Sapoznikov D, Wexler D, Lotan C, Mosseri M, Weiss AT, Hasin Y, Gotsman MS. Total coronary artery occlusion late after successful coronary angioplasty of moderately severe lesions: incidence and clinical manifestations. Cardiology 1994;85:222–228. 12. Farb A, Burke AP, Kolodgie FD, Virmani R. Pathological mechanisms of fatal late coronary stent thrombosis in humans. Circulation 2003;108:1701–1706.
myocardial infarction—a late complication of intracoronary stent placement. Clin Cardiol 2000;23:376 –378. 14. Heller LI, Shemwell KC, Hug K. Late stent thrombosis in the absence of prior intracoronary brachytherapy. Catheter Cardiovasc Interventions 2001;53:23–28. 15. Cha DH, Malik IA, Cheneau E, Ajani AE, Leborgne L, Wolfram R, Porrazzo M, Satler LF, Kent KM, Pichard AD, et al. Use of restenting should be minimized with intracoronary radiation therapy for in-stent restenosis. Catheter Cardiovasc Interventions 2003;59:1–5. 16. Waksman R, Lew R, Ajani AE, Pichard AD, Satler LF, Kent KM, Chan R, White RL, Suddath WO, Pinnow E, et al. Repeat intracoronary radiation for recurrent in-stent restenosis in patients who failed intracoronary radiation. Circulation 2003;108:654 – 656.
Association Between Metabolic Syndrome and Subclinical Coronary Atherosclerosis in Asymptomatic Adults Iftikhar J. Kullo, MD, Andrea E. Cassidy, MPH, Patricia A. Peyser, PhD, Stephen T. Turner, MD, Patrick F. Sheedy II, MD, and Lawrence F. Bielak, DDS, Metabolic syndrome was associated with the presence and quantity of coronary artery calcium, a marker of subclinical coronary atherosclerosis, in 1,129 asymptomatic adults, ages 20 to 79 years, from a community-based study. The association was independent of 10-year risk of coronary heart disease based on the Framingham risk score. 䊚2004 by Excerpta Medica Inc. (Am J Cardiol 2004;94:1554 –1558)
he complex inter-relations among components of the metabolic syndrome and 10-year risk for corT onary heart disease (CHD) based on the Framingham risk score and their relations to noninvasive measures of subclinical coronary atherosclerosis are not well established. Although several studies1–3 have demonstrated an association of the metabolic syndrome with coronary artery calcium (CAC), none of studies used the strict definition of the metabolic syndrome of the Adult Treatment Panel III (ATP III) of the National Cholesterol Education Panel,4 or the study cohorts were comprised of physician- or self-referred subjects. The goal of the present investigation was to determine whether the metabolic syndrome was independently associated with the presence and quantity of CAC in asymptomatic subjects from a community after conFrom the Division of Cardiovascular Disease, Division of Hypertension, Department of Internal Medicine; and Department of Diagnostic Radiology, Mayo Clinic and Foundation, Rochester, Minnesota; and Department of Epidemiology, University of Michigan, Ann Arbor, Michigan. This study was supported by grants R01 HL46292 and M01 RR00585 from the National Institutes of Health, Bethesda, Maryland; grant T32 HG00040 from the National Human Genome Research Institute; and a Mentored Patient-Oriented Research Award to Dr. Kullo (K23 RR17720-01) from the National Institutes of Health, National Center of Research Resources. Dr. Bielak’s address is: University of Michigan, Department of Epidemiology, 611 Church Street, Ann Arbor, Michigan 48104-3028. E-mail: [email protected]. Manuscript received May 11, 2004; revised manuscript received and accepted August 6, 2004.
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MPH
sidering (1) conventional CHD risk factors and (2) the estimated 10-year risk for a CHD event. •••
The Epidemiology of Coronary Artery Calcification Study is an ongoing community-based study of the etiology of CAC in Rochester, Minnesota.5,6 Subjects were recruited from the community-based Rochester Family Heart Study, were not self or physician referred, and did not have previous bypass surgery, angioplasty, or other coronary surgery.7,8 Between December 1990 and May 1998, 1,240 subjects were examined for CAC with electron beam computed tomography. We excluded 8 subjects who were ⱖ80 years of age, 23 who had a history of stroke or myocardial infarction, 5 who were nonwhite, 19 who had diabetes mellitus, 37 who had missing data (including 17 who had missing fasting glucose values), and 19 who had outliers for risk factor data. The final study group consisted of 1,129 asymptomatic white subjects (548 men and 581 women). Subjects belonged to 843 sibships (668 singletons, 105 sibships of size 2, 45 sibships of size 3, 3 sibships of size 4, 2 sibships of size 5, and 3 sibships of size 6). Study protocols were approved by the institutional review boards of the Mayo Clinic and the University of Michigan, and subjects gave written informed consent. During an interview, subjects reported current medication use, history of smoking, physician-diagnosed hypertension, myocardial infarction, stroke, or diabetes. Systolic and diastolic blood pressures at rest were measured in the right arm with a random-zero sphygmomanometer (Hawksley and Sons, London, United Kingdom). Three measurements ⱖ2 minutes apart were taken, and the average of the second and third measurements was used. Waist circumference was measured between the lowest rib and the iliac crest. Blood samples were obtained after an overnight fast. Standard enzymatic methods were used to measure plasma glucose, total cholesterol, high-density lipoprotein cholesterol, and triglycerides. Low-density lipoprotein cholesterol was calculated with Friede0002-9149/04/$–see front matter doi:10.1016/j.amjcard.2004.08.038
TABLE 1 Subjects’ Characteristics Men (n ⫽ 548)*
Variable Age (yrs) Waist circumference (cm) Total cholesterol (mmol/L) Total cholesterol (mg/dl) Triglycerides (mmol/L) Triglycerides (mg/dl) LDL cholesterol (mmol/L) LDL cholesterol (mg/dl) HDL cholesterol (mmol/l) HDL cholesterol (mg/dl) Systolic BP (mm Hg) Diastolic BP (mm Hg) Fasting glucose (mmol/L) Fasting glucose (mg/dl) 10-year risk for CHD (%) CAC score Presence of CAC Current smoker Abdominal obesity Hypertriglyceridemia‡ Low HDL cholesterol High blood pressure Hyperglycemia ⱖ1 Component of the metabolic syndrome ⱖ2 Components of the metabolic syndrome Metabolic syndrome
47.2 92.4 4.9 190.4 1.5 135.2 3.2 124.1 1.0 39.4 119.1 78.0 5.0 89.9 7.6 101.5
⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾
14.6 (20.0–78.8) 10.6 (68.0–135.0) 1.0 (2.6–8.5) 37.5 (99.0–327.0) 0.9 (0.4–8.6) 79.5 (37.0–759.0) 0.9 (0.7–6.1) 33.2 (26.4–236.8) 0.3 (0.5–2.0) 9.5 (18.0–75.8) 15.5 (84.0–184.0) 9.8 (43.0–120.0) 0.6 (2.5–8.0) 9.9 (44.3–144.8) 7.1 (1.0–30.0) 277.5 (0.0–3,036.7) 289 (52.7%) 85 (15.5%) 96 (17.5%) 160 (29.2%) 316 (57.7%) 188 (34.3%) 20 (3.7%) 416 (75.9%) 224 (40.9%) 99 (18.1%)
Women (n ⫽ 581)† 48.5 80.5 5.0 191.7 1.4 120.9 3.0 116.3 1.3 51.1 116.8 73.9 4.9 87.4 2.3 41.5
⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾ ⫾
14.3 (20.2–79.2) 13.6 (55.1–147.6) 1.0 (2.4–8.6) 39.7 (94.0–331.0) 0.7 (0.2–5.4) 63.5 (21.0–477.0) 0.9 (0.5–6.9) 33.7 (18.5–266.9) 0.4 (0.4–2.6) 13.7 (16.8–101.0) 17.2 (78.0–196.0) 8.8 (37.0–104.0) 0.6 (3.5–8.8) 11.1 (63.7–158.0) 2.9 (1.0–22.0) 185.2 (0.0–2,488.5) 142 (24.4%) 80 (13.8%) 144 (24.8%) 139 (23.9%) 290 (49.9%) 172 (29.6%) 24 (4.1%) 418 (71.9%) 198 (34.1%) 105 (18.1%)
Values are mean ⫾ SD (ranges) or numbers of subjects (percentages). *There were 539 men who had LDL cholesterol values (values for 11 men were missing because triglycerides ⬎400 mg/dl [4.56 mmol/L]). † There were 579 women who had LDL cholesterol values (values for 2 women were missing because triglycerides ⬎400 mg/dl [4.56 mmol/L]). ‡ Hypertriglyceridemia defined as triglycerides ⱖ150 mg/dl (1.69 mmol/L). BP ⫽ blood pressure; HDL ⫽ high-density lipoprotein; LDL ⫽ low-density lipoprotein.
TABLE 2 Age- and Gender-adjusted Associations of the Metabolic Syndrome With the Presence and Quantity of Coronary Artery Calcium (CAC) Predictor Metabolic syndrome Abdominal obesity Hypertriglyceridemia Low HDL cholesterol High blood pressure Hyperglycemia No. of metabolic components 0 1 2 3 ⱖ4
Parameter Estimate ⫾ SE
Change in Probability of Having CAC
Percent Change in Quantity of CAC
p Value
⫾ ⫾ ⫾ ⫾ ⫾ ⫾
0.45 0.47 0.42 0.40 0.42 0.79
17.3% 13.8% 11.5% 9.4% 12.9% 14.8%
206.9% 79.5% 62.9% 49.6% 72.5% 85.5%
⬍0.001 ⬍0.001 ⬍0.001 0.001 ⬍0.001 0.009
Referent 0.92 ⫾ 0.58 1.85 ⫾ 0.60 2.93 ⫾ 0.68 4.00 ⫾ 0.77
6.7% 13.4% 21.2% 29.0%
32.1% 75.2% 243.0% 336.0%
0.111 0.002 ⬍0.001 ⬍0.001
2.40 1.93 1.61 1.33 1.80 2.04
Abbreviation as in Table 1.
wald’s equation.9 The 10-year risk for CHD was calculated with the gender-specific Framingham risk score.4 The metabolic syndrome was defined according to ATP III criteria4 as the presence of ⱖ3 of the following characteristics: abdominal obesity (waist circumference ⬎102 cm in men and ⬎88 cm in women), hypertriglyceridemia (triglyceride level ⱖ150 mg/dl), low level of high-density lipoprotein cholesterol (high-density lipoprotein cholesterol level ⬍40 mg/dl in men and ⬍50 mg/dl in women), high blood pressure (systolic blood pressure ⱖ130 mm Hg, diastolic
blood pressure ⱖ85 mm Hg, or use of antihypertensive medication), and hyperglycemia (glucose level ⱖ110 mg/dl). CAC was measured with an Imatron C-100 or C-150 electron beam computed tomographic scanner (Imatron Inc., South San Francisco, California). Forty contiguous, 3-mm thick, 2-dimensional transverse images were obtained from the level of the right branch of the pulmonary artery to the apex of the heart. Electron beam computed tomographic data were reviewed for technical quality by a radiologist and then scored by a radiologic technologist who used customBRIEF REPORTS
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FIGURE 1. Predicted probability of having CAC (A) and predicted mean CAC score (B) for hypothetical 60-year-old subjects who have the indicated number of metabolic abnormalities.
TABLE 3 Gender-adjusted Associations of the Metabolic Syndrome and 10-year Risk for Coronary Heart Disease With the Presence and Quantity of Coronary Artery Calcium (CAC) Predictor
Parameter Estimate ⫾ SE
Change in Probability of Having CAC
Percent Change in Quantity of CAC
p Value
Metabolic syndrome 10-Year risk for CHD
2.15 ⫾ 0.56 0.55 ⫾ 0.04
13.4% 3.4%
98.1% 18.1%
⬍0.001 ⬍0.001
ized computer software.10 CAC was defined as a hyperattenuating focus, ⱖ4 contiguous pixels, and computed tomographic numbers ⬎130 HU for each pixel. A score for each focus of CAC was calculated by multiplying the focus area (square millimeters) by a density measurement that was defined by the peak computed tomographic number in the focus.11 Total CAC score was calculated as the sum of scores for all foci in the epicardial arteries.11 A statistical significance level of 0.05 was used. Age- and gender-adjusted Tobit’s regression models were used to investigate associations of the metabolic syndrome, its individual components, and the number of the metabolic syndrome components with the presence and quantity of CAC. Tobit’s regression models are useful when the outcome variable is censored below a threshold value (in this study, below the threshold of detection).12,13 To decrease skewness, the natural log-transformation of the CAC score was taken among those with detectable CAC. Tobit’s regression model parameters were used to estimate a predicted probability of having detectable CAC and a predicted mean detected CAC quantity associated with 0, 1, 2, 3, and ⱖ4 metabolic syndrome components for hypothetical subjects 60 years of age. To evaluate the importance of the metabolic syndrome for predicting the presence and quantity of CAC after adjusting for conventional risk factors, Tobit’s regression model was fit with the metabolic syndrome, age, male gender, current smoking status, level of lowdensity lipoprotein cholesterol, and use of lipid-lowering medications as independent variables. We also evaluated the importance of the metabolic syndrome for predicting presence and quantity of CAC after adjusting for 10-year risk of CHD by fitting Tobit’s regression models that 1556 THE AMERICAN JOURNAL OF CARDIOLOGY姞
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contained the metabolic syndrome, male gender, and 10-year risk of CHD. Because parameters from Tobit’s models are not directly interpretable, parameters estimated from each model were decomposed into (1) the change in the probability of having detectable CAC and (2) the percent change in CAC score among those who had detectable CAC. Because some subjects were members of the same sibship, their observations were independent across sibships but not within sibships. Therefore, all Tobit’s regression models incorporated the correlation among subjects in the same sibship into the estimated SE values and the variance– covariance matrix of the estimators. Ordinal logistic regression models that examined the relation between the metabolic syndrome and CAC after adjusting for male gender and (1) age and (2) 10-year risk for CHD were fit to decrease the chance that any associations found were due to the relatively large degree of skewness of the distribution of CAC scores. CAC score was categorized based on guidelines that corresponded to probability of significant coronary artery disease: 0 (very low probability of coronary artery disease), ⬎1 to ⱕ10 (very unlikely coronary artery disease), ⬎10 to ⱕ100 (likely mild to minimal coronary stenosis), ⬎100 to ⱕ400 (nonobstructive coronary artery disease likely), and ⬎400 (high likelihood of ⱖ1 “significant” coronary stenosis).14 The models allowed estimation of the odds of being in a higher CAC score category versus a lower CAC score category. Subjects’ characteristics are presented in Table 1. Approximately 75% of men and women had ⱖ1 component of the metabolic syndrome. The presence of DECEMBER 15, 2004
FIGURE 2. Prevalence of the metabolic syndrome increases significantly as the CAC category increases (p <0.001 for trend).
metabolic syndrome was the same in men and women (18.1%) and increased significantly with advancing age. Among men, prevalence of the metabolic syndrome increased from 2.4% among those 20 to 29 years of age to 34.3% among those 70 to 79 years of age; among women, prevalence of the metabolic syndrome increased from 3.7% among those 20 to 29 years of age to 51.2% among those 70 to 79 years of age (p ⬍0.001 for trend in men and women). Men who had the metabolic syndrome and those who did not had mean ⫾ SD CAC scores of 201 ⫾ 420 and 80 ⫾ 230, respectively, and median (range) CAC scores of 35 (0 to 3,037) and 0 (0 to 1,987), respectively. Women who had the metabolic syndrome and those who did not had mean ⫾ SD CAC scores of 98 ⫾ 262 and 29 ⫾ 161, respectively, and median (range) CAC scores of 1.04 (0 to 1,512) and 0 (0 to 2,489), respectively. The metabolic syndrome was associated with the presence and quantity of CAC after adjusting for age and male gender (p ⬍0.001; Table 2). Presence of the metabolic syndrome was associated with a 17.3% change in the probability of having CAC and an ⬃207% change in the quantity of CAC in those who had detectable CAC. Each component of the metabolic syndrome was significantly associated with the presence and quantity of CAC (Table 2). Having 2, 3, or ⱖ4 components was significantly associated with the presence and quantity of CAC compared with those who had 0 components after adjusting for age and male gender (Table 2). In men and women, after adjusting for age, the predicted probability of having CAC (Figure 1) and the predof having CACicted mean CAC score (if CAC was detected) increased as the number of metabolic syndrome components increased (Figure 1). The estimates presented in Figure 1 are for a hypothetical 60-year-old man and 60-year-old woman with the indicated number of metabolic abnormalities. The metabolic syndrome was significantly associated with the presence and quantity of CAC after adjusting for age, male gender, current smoking status, level of low-density lipoprotein cholesterol, and use of lipid-lowering medications (p ⬍0.001). All conventional risk factors except current smoking status were significant. In models that included male
gender, the metabolic syndrome, and 10-year risk for CHD, the metabolic syndrome and 10-year risk for CHD were statistically significantly associated with the presence and quantity of CAC (Table 3). Most subjects had no CAC (62%); 9.2% had CAC scores ⬎1 to ⱕ10, 16% had CAC scores ⬎10 to ⱕ100, 7.9% had CAC scores ⬎100 to ⱕ400, and 5.4% had CAC scores ⬎400. The distribution of the metabolic syndrome by CAC category is presented in Figure 2; prevalence of the metabolic syndrome increased significantly as the CAC category increased (p ⬍0.001 for trend). After adjusting for age and male gender, the metabolic syndrome was significantly and positively associated with CAC (p ⬍0.001). The metabolic syndrome remained significantly and positively associated with CAC after adjusting for the 10-year risk for CHD (p ⬍0.001). At any given level of 10-year risk for CHD, subjects who had the metabolic syndrome had 1.7 times (95% confidence interval 1.3 to 2.4) the odds of being in a higher CAC category versus a lower CAC category compared with those who did not have the metabolic syndrome. •••
This is the first study to report a significant association between the metabolic syndrome, according to the ATP III definition, and the presence and quantity of CAC in asymptomatic men and women who had been recruited from a community. The association was independent of a subject’s 10-year risk for CHD based on the Framingham risk score. The findings indicate that factors that contribute to atherosclerosis are not fully captured by conventional profiling of risk factors. Our findings suggest that 1 mechanism of increased CHD risk in subjects who have the metabolic syndrome may be an increase in coronary atherosclerotic plaque. 1. Wong ND, Sciammarella MG, Polk D, Gallagher A, Miranda-Peats L, Whit-
comb B, Hachamovitch R, Friedman JD, Hayes S, Berman DS. The metabolic syndrome, diabetes, and subclinical atherosclerosis assessed by coronary calcium. J Am Coll Cardiol 2003;41:1547–1553. 2. Hunt ME, O’Malley PG, Feuerstein I, Taylor AJ. The relationship between the ‘metabolic score’ and sub-clinical atherosclerosis detected with electron beam computed tomography. Coron Artery Dis 2003;14:317–322. 3. Arad Y, Newstein D, Cadet F, Roth M, Guerci AD. Association of multiple risk factors and insulin resistance with increased prevalence of asymptomatic coronary artery disease by an electron-beam computed tomographic study. Arterioscler Thromb Vasc Biol 2001;21:2051–2058. 4. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. 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;285:2486 –2497. 5. Maher JE, Raz JA, Bielak LF, Sheedy PF II, Schwartz RS, Peyser PA. Potential of quantity of coronary artery calcification to identify new risk factors for asymptomatic atherosclerosis. Am J Epidemiol 1996;144:943–953. 6. Bielak LF, Sheedy PF II, Peyser PA. Coronary artery calcification measured at electron-beam CT: agreement in dual scan runs and change over time. Radiology 2001;218:224 –229. 7. Turner ST, Weidman WH, Michels VV, Reed TJ, Ormson CL, Fuller T, Sing CF. Distribution of sodium-lithium countertransport and blood pressure in Caucasians five to eighty-nine years of age. Hypertension 1989;13:378 –391. 8. Kottke BA, Moll PP, Michels VV, Weidman WH. Levels of lipids, lipoproteins, and apolipoproteins in a defined population. Mayo Clin Proc 1991;66: 1198 –1208. 9. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499 –502.
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10. Reed JE, Rumberger JA, Davitt PJ, Kaufmann RB, Sheedy PF II. System for
quantitative analysis of coronary calcification via electron beam computed tomography. In: Hoffman EA, Acharya RS, eds. Medical Imaging, 1994: Physiology and Function From Multidimensional Images. Bellingham, WA: International Society for Optical Engineering, 1994:43–53. 11. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 1990;15:827– 832. 12. Breen R. Regression Models: Censored, Sample Selected, or Truncated Data.
Sage University Paper Series on Quantitative Applications in the Social Sciences, no. 07–111. Thousand Oaks, CA: Sage, 1996:27–30. 13. Jamjoum LS, Turner ST, Bielak LF, Sheedy PF II, Boerwinkle E, Raghunathan TE, Peyser PA. Relationship of blood pressure level and hypertension with coronary artery calcification. Med Sci Monit 2002;12:775– 781. 14. Rumberger JA, Brundage BH, Rader DJ, Kondos G. Electron beam computed tomographic coronary calcium scanning: a review and guidelines for use in asymptomatic persons. Mayo Clin Proc 1999;74:243–252.
Effectiveness of Therapeutic Lifestyle Changes in Patients With Hypertension, Hyperlipidemia, and/or Hyperglycemia Neil F. Gordon, MD, PhD, Richard D. Salmon, DDS, MBA, Barry A. Franklin, PhD, Laurence S. Sperling, MD, Linda Hall, PhD, Richard F. Leighton, MD, and William L. Haskell, PhD In this prospective study of 2,390 ethnically diverse men and women, we evaluated the clinical effectiveness of 12 weeks of participation in a communitybased lifestyle management program in helping patients who had hypertension, hyperlipidemia, and/or impaired fasting glucose or diabetes mellitus achieve goal risk factor levels without using pharmacotherapeutic agents. Although further research is warranted, the findings clearly show that many patients who have conventional risk factors for coronary heart disease can achieve goal levels without medications within 12 weeks of initiating therapeutic lifestyle changes and refute the notion that intensive lifestyle intervention is not worth the effort. 䊚2004 by Excerpta Medica Inc. (Am J Cardiol 2004;94:1558 –1561)
ecent studies have emphasized the need to intensify efforts aimed at the control of conventional R risk factors for coronary heart disease. National 1,2
clinical guidelines have promulgated therapeutic lifestyle changes as a standard of care in the management of conventional risk factors.3,4 However, because of the widespread availability of powerful medications, the value of therapeutic lifestyle changes per se in contemporary medical practice is often discounted by clinicians, health insurers, and patients. In this prospective study of 2,390 patients, we evaluated the clinical effectiveness of 12 weeks of therapeutic lifeFrom the Center for Heart Disease Prevention, St. Joseph’s/Candler Health System, Savannah, Georgia; the INTERVENT Coordinating Center, Savannah, Georgia; the Emory University School of Medicine, Atlanta, Georgia; the William Beaumont Hospital, Royal Oak, Michigan; the Forrest General Hospital, Hattiesburg, Mississippi; and the Stanford University School of Medicine, Palo Alto, California. Dr. Gordon’s address is: Center for Heart Disease Prevention, St. Joseph’s/Candler Health System, 5356 Reynolds Street, Suite 120, Savannah, Georgia 31405. E-mail: [email protected]. Manuscript received May 4, 2004; revised manuscript received and accepted August 4, 2004.
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©2004 by Excerpta Medica Inc. All rights reserved. The American Journal of Cardiology Vol. 94 December 15, 2004
style changes in helping patients who had hypertension, hyperlipidemia, and/or impaired fasting glucose or diabetes mellitus achieve goal risk factor levels without using pharmacotherapeutic agents. •••
A cohort of 2,390 consecutive adult patients who completed initial and 12-week follow-up assessments as part of their participation in a comprehensive, community-based lifestyle management program comprised the study population. Patients were self-referred or referred by a physician to participate in the program and met ⱖ1 of the following criteria: baseline (i.e., at program entry) systolic blood pressure (BP) ⱖ140 mm Hg and/or diastolic BP ⱖ90 mm Hg and not taking antihypertensive medications at baseline or follow-up, baseline fasting level ⱖ100 mg/dl for low-density lipoprotein cholesterol and not taking antilipemic medications at baseline or follow-up, or baseline fasting glucose level ⱖ110 mg/dl and not taking antidiabetic medications at baseline or follow-up. Written informed consent was obtained from each patient. Baseline clinical characteristics are listed in Table 1. The lifestyle management program was administered by non-physician health care providers who were guided by a computerized participant management system, as previously described.5,6 Briefly, the program included the following core components: (1) initial assessment, including completion of a comprehensive medical history questionnaire and measurement of height, weight, waist circumference, seated BP, fasting serum lipids and lipoproteins, and fasting glucose; (2) computer generation of risk factor goals based on national clinical guidelines3,7–11 and an action plan for achieving these goals through comprehensive lifestyle changes; (3) action plan implementation, including 1-on-1 behaviorally oriented counseling (face to face or, if the patient preferred, by telephone and the Internet) to help each patient acquire the skills, motivation, and support needed to implement and adhere to an individually prescribed 0002-9149/04/$–see front matter doi:10.1016/j.amjcard.2004.08.039