- Email: [email protected]
Risk stratification of obesity as a coronary risk factor
Risk Stratification of Obesity as a Coronary Risk Factor William B. Kannel,
MD, MPH,
Peter W.F. Wilson, MD, Byung-Ho Nam, Ralph B. D’Agostino, PhD
PhD,
and
We examined the extent of coronary heart disease (CHD) risk factor clustering in overweight persons with a body mass index (BMI) of 25 to 29 and an obesity BMI of >30 and the influence of this on the hazard of myocardial infarction and coronary mortality. A total of 1,309 men and 739 women aged 30 to 74 years, initially free of cardiovascular disease, comprised the overweight subject group, and 375 men and 356 women comprised the obese subject group at risk. The sample was derived from the original Framingham Study cohort at the 11th biennial examination, and their offspring at initial examination. During 16 years of follow-up of overweight subjects, 188 men and 44 women had CHD events, indicating an age-adjusted rate that was not much different from the slim subjects. In the obese subject group, 72 men and 37 women developed CHD, corresponding to age-adjusted risk ratios 1.48 times that of lean men, and 2.09 times that of lean women. Risk factors were categorized as systolic blood pressure >140 mm Hg, total cholesterol >240 mg/dl,
high-density lipoprotein (HDL) cholesterol <35 mg/dl for men and <40 mg/dl for women, heart rate >80 beats/min, history of smoking, history of type 2 diabetes, and electrocardiographic left ventricular hypertrophy. Being overweight occurred in isolation of CHD risk factors in 22% of men and in 16.4% of women. Being obese occurred in isolation in only 12.8% of men and 9% of women. Clusters of >2 risk factors occurred in 56% of obese men and in 62.4% of obese women, a frequency substantially exceeding that in slim subjects. Compared with obese men without risk factors, those with >3 factors had a 2.07 age-adjusted relative risk of developing CHD, and obese women had a 10.9 relative risk (p <0.05). Being overweight and obese promotes clusters of CHD risk factors that greatly influence their impact. Global risk assessment can identify high-risk overweight candidates for CHD who most urgently need correction of associated risk factors, as well as sustained weight reduction. 䊚2002 by Excerpta Medica, Inc. (Am J Cardiol 2002;90:697–701)
verweight and obese persons are common in the United States, and their prevalence is increasing O at an alarming rate. Such persons experience excess
tion of cardiovascular risk factor status and development of cardiovascular disease. In 1971, another cohort of 5,124 men and women, who were offspring (and spouses) of the original cohort, were likewise enrolled.3,4 The population sample for this investigation is composed of the original Framingham Study cohort who attended their 11th biennial examination in 1971 to 1974 and their offspring at their 1971 to 1975 initial examination. Patients were stratified by body mass index (BMI) at their initial examination. Patients were designated as overweight at a BMI of 25 to 29.9 and were considered obese at a BMI of ⱖ30. A total of 375 men and 356 women (average age 47 to 52 years) met the criteria for obese subjects, and 1,309 men and 739 women (average age 48 to 53 years) met the criteria for overweight subjects. The selected participants were free of cardiovascular disease at baseline examination and were considered at risk for initial CHD events at their specified adiposity status (in relation to their burden of accompanying CHD risk factors). Each examination included a detailed cardiovascular assessment, blood pressure determination, and relevant laboratory tests. Morbidity and mortality were monitored using clinical examinations, hospital admission surveillance, and communications with personal physicians and the participant’s relatives. A panel of senior physician investigators adjudicated suspected CHD events using established criteria. Detailed descriptions of the sampling methods, examina-
1
dyslipidemia, higher blood pressures, more glucose intolerance, hyperinsulinemia, insulin resistance, and left ventricular hypertrophy.2 This study examines the prevalence of clusters of specified risk factors in overweight and obese populations and the relative risk of initial coronary heart disease (CHD) events (myocardial infarction or fatal coronary events) in relation to the amount of risk factor clustering. These populations were examined using multivariable risk analysis. The multivariable risk formula we derived enables risk stratification of adiposity to target those at high risk for CHD, for aggressive preventive measures to improve their global multivariable risk.
METHODS The Framingham Study was initiated in 1948, enrolling 5,209 men and women for biennial examinaFrom the Framingham Study, Boston University School of Medicine, Framingham, Massachusetts; and Department of Mathematics, Boston University, Boston, Massachusetts. Framingham Study research is supported by National Institutes of Health/National Heart, Lung, and Blood Institute, Bethesda, Maryland (Contract N01-HC-38038), and the Visiting Scientist Program, which is supported by Servier Ame´rique, Nevilly-Sur-Seine Cedex, France. Manuscript received January 15, 2002; revised manuscript received and accepted June 3, 2002. Address for reprints: William B. Kannel, MD, MPH, Framingham Heart Study, 5 Thurber Street, Framingham, Massachusetts 01702. E-mail: [email protected]. ©2002 by Excerpta Medica, Inc. All rights reserved. The American Journal of Cardiology Vol. 90 October 1, 2002
0002-9149/02/$–see front matter PII S0002-9149(02)02592-4
697
TABLE 1 Risk of Coronary Events* According to Body Mass Index (BMI) in Framingham Study Subjects (aged 30 to 74 years) BMI Men
No. of events No. at risk Age-adjusted rate† Risk ratio
Women
⬍25
25–29.9
30⫹
⬍25
25–29.9
30⫹
99 772 20.2% Referent
188 1,306 21.3% 1.08
72 375 28.3% 1.49‡
76 1,703 6.2% Referent
44 739 8.0% 1.08
37 356 14.5% 2.08‡
*Coronary events: Myocardial infarction and CHD death. † Age-adjusted rates are for 16 years. ‡ p ⬍0.005 for BMI ⱖ30.
TABLE 2 Distribution of Cardiovascular Risk Factors According to Body Mass Index (BMI) in Framingham Study Subjects (aged 30 to 74 years) BMI of Men
Continuous risk factors* BMI Systolic BP Total cholesterol HDL cholesterol Heart rate Categorical risk factors† Current smoker ECG-LVH Type 2 diabetes
BMI of Women
⬍25 (n ⫽ 772)
25–29.9 (n ⫽ 1,309)
ⱖ30 (n ⫽ 375)
⬍25 (n ⫽ 1,730)
25–29.9 (n ⫽ 739)
ⱖ30 (n ⫽ 356)
23.1 128.5 207.9 48.3 73.0
27.2 131.7 215.3 43.7 73.1
32.5‡ 139.9‡ 216.0§ 40.9‡ 74.9㛳
22.3 126.1 216.0 60.5 78.6
26.9‡ 129.7‡ 219.3 55.1‡ 78.9
33.9‡ 137.5‡ 220.6㛳 50.1‡ 81.8‡
47.2 1.6 3.0
37.5 1.2 3.9
36.3‡ 2.6 7.9‡
40.4 0.7 1.7
35.0㛳 0.7 2.4
30.6‡ 1.1 6.6‡
*Values are expressed as age-adjusted means. † Values are expressed as age-adjusted percentages. ‡p ⬍0.05; §p ⬍0.01; 㛳p ⬍0.001. BP ⫽ blood pressure; ECG-LVH ⫽ left ventricular hypertrophy by electrocardiography.
tion procedures, and the criteria for CHD end points have been reported elsewhere.4 The risk factors under consideration were age, total and high-density lipoprotein (HDL) cholesterol, BMI, type 2 diabetes, systolic blood pressure, heart rate, cigarette smoking, and electrocardiographic left ventricular hypertrophy. The BMI was calculated as weight in kilograms divided by height in square meters. Blood pressure was measured from the left arm with a mercury sphygmomanometer with the subject seated. A large cuff was used when required, and readings were recorded to the nearest even number. Fasting plasma was used for the determination of HDL cholesterol, which was measured after precipitation with heparin-manganese.5 Type 2 diabetes was designated if the fasting plasma glucose was ⱖ7.8 mmol/L during any 2 previous examinations, or if hypoglycemic drug therapy was reported. Fasting plasma glucose was measured with a hexokinase reagent kit. Fasting total cholesterol and triglycerides were measured by the Lipid Research Clinic protocol.5,6 Values designated as risk factors were: (1) BMIs as indicated above, (2) systolic blood pressure ⱖ140 mm Hg, (3) total cholesterol ⱖ240 mg/dl, (4) HDL cholesterol ⬍35 mg/dl for men and ⬍40 mg/dl for women, (4) heart rate ⬎80 beats/min and type 2 698 THE AMERICAN JOURNAL OF CARDIOLOGY姞
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diabetes, cigarette smoking, and electrocardiographic left ventricular hypertrophy. Cox regression models were used to examine the impact of the various risk factors individually and in combination, adjusting for age and other relevant factors. Gender-specific Cox regression models were developed to predict 16-year risk of CHD end points (myocardial infarction and coronary deaths) based on 20 years of follow-up. The loss to follow-up after 20 years was ⬍3%. Logistic regression was used for estimating the age and sample size-adjusted proportions of patients with CHD who had risk factors.
RESULTS Table 1 lists the number of events, number at risk, and age-adjusted 16-year average risks of CHD events from Cox regressions in those classified as overweight or obese, compared with those who had BMIs of ⬍25. During the overweight subject group’s follow-up period, there were 188 CHD end points in men and 44 in women (a 16-year age-adjusted rate of 21.3% for men and 8.0% for women). The group’s 1.08 age-adjusted risk ratio was not statistically significant when compared with ratios for slim men and women. However, in the obese subject group there were 72 events in men and 37 in women, signifying a substantial 1.49 risk OCTOBER 1, 2002
cally defined CHD risk factors accompany adiposity in each sex. Only 12.8% and 8.99% of obese men and BMI ⬍25 BMI 25–29.9 BMI 30⫹ women, respectively, were free of No. of the other cardiovascular risk factors. Risk Factors Men Women Men Women Men Women The 56% and 62.4% frequency of 0 23.7% 18.3% 22.0% 16.4% 12.8% 9.0% ⱖ2 risk factors in obese men and 1 36.3% 42.5% 36.8% 36.1% 31.2% 28.6% women, respectively, is significantly 2 26.2% 25.7% 24.1% 30.2% 30.9% 35.1% ⱖ3 13.8% 13.5% 17.1% 17.3% 25.1% 27.3% (p ⬍0.001) different from the frequency in nonobese (BMI ⬍25) subFrequency of ⱖ2 risk factors in the obese (BMI ⱖ30) differs significantly from nonobese (BMI ⬍25) (p jects. The extent of clustering in ⬍0.001), in both sexes. Risk factors considered were: age, systolic blood pressure, HDL cholesterol, total cholesterol, cigarette smoking, heart rate, diabetes, and left ventricular hypertrophy. For the overweight overweight subjects is less pro(BMI 25–29.9) the frequency of ⱖ2 risk factors is significantly different from BMI ⬍25 in women (p nounced but being overweight oc⬍0.05). curred in isolation in only 22% and 16.4% of men and women, respectively. Clusters of ⱖ2 risk factors occurred in overwieght women with TABLE 4 Risk of Myocardial Infarction and Coronary Heart Disease (CHD) Death a frequency significantly greater (p by Specified Cardiovascular Risk Factors (Cox regression model)* ⬍0.05) than was observed in the slim Relative Risk Confidence Intervals subjects. Table 4 lists the age and risk facRisk Factors Men Women Men Women tor-adjusted multivariable Cox reAge (1 yr) 1.04 1.05 1.02–1.05 1.03–1.07 gression estimates of the risk of Systolic blood pressure (ⱖ140 mm Hg) 1.31 1.80 1.04–1.64 1.26–2.57 CHD for the entire population samHDL cholesterol (⬍35 mg/dl) 1.49 1.67 1.17–1.90 1.09–2.56 Total cholesterol (ⱖ240 mg/dl) 1.59 1.86 1.28–1.99 1.34–2.60 ple. The sample was specified by inType 2 diabetes 1.94 1.85 1.39–2.70 1.14–3.03 crements in each risk factor. All reSmoker 1.93 2.78 1.56–2.39 1.99–3.87 gression estimates were statistically ECG-LVH 2.58 1.66 1.60–4.15 0.72–3.81 significant in men and women except Heart rate (⬎80 beats/min) 0.91 1.09 0.72–1.15 0.79–1.50 1.20 1.04 0.94–1.54 0.71–1.51 Overweight (BMI 25–29.9 kg/m2) for heart rate and being overweight. Obese (BMI ⱖ 30 kg/m2) 1.66 1.64 1.21–2.28 1.08–2.48 After adjusting for other risk factors including age, obesity per se contin*Reference group is BMI ⬍25 kg/m2. Abbreviation as in Table 2. ued to make a significant contribution to risk of developing coronary disease. This was not the case for the overweight subject group, which exTABLE 5 Proportion of Coronary Events by Number of Coexistent Risk Factors in hibited no independent effects. Framingham Study Subjects (aged 30 to 74 years)* Table 5 displays the proportion of Overweight Obese the CHD events that occur in obese No. of Associated and overweight subjects in relation Risk Factors Men Women Men Women to their burden of CHD risk factors. 0 11.5% 3.2%† 22.6% 1.7% We first calculated the projected 1 21.7%† 12.5%† 15.2% 13.6%† number of cases for each subgroup 2 29.2%† 34.7%† 22.5%† 32.1%† ⱖ3 37.6%† 49.5%† 39.7%† 52.7%† using the age-size adjusted rate and then calculated the proportion (pro*Values are adjusted for size of sample with a specified number of associated risk factors. † jected number of cases for each catp ⬍0.05 for difference from none. egory divided by the total projected number of cases), because the proportion of CHD events in these subratio for men and 2.08 ratio for women. These values jects is influenced by the size of each numerical risk were statistically significant (p ⬍0.005). Despite the factor category. Adjusting for age and sample size, the larger risk ratio for women, the age-adjusted incidence proportion of CHD events increased with the number of associated risk factors. Additionally, 40% to 50% of CHD for women is only half that of men. It is evident from Table 2 that the age-adjusted of the CHD events that evolved in obese or overmean level of most risk factors is unfavorable for weight subjects occurred in those with ⱖ3 additional overweight and obese subjects. The prevalence of type cardiovascular risk factors (Table 5). Age-adjusted CHD risk ratios in overweight sub2 diabetes and electrocardiographic left ventricular hypertrophy are substantially increased in obese sub- ects of either sex tended to increase with the amount jects, and significantly increased for subjects with type of risk factor clustering (Table 6). Men who had ⱖ3 2 diabetes. Only the level of cigarette smoking was associated risk factors had a fourfold increased risk significantly more favorable for CHD risk in over- and women had a relative risk of 8.6. A stepwise increase in relative risk was noted in obese women, weight and obese subjects. Table 3 lists the frequency with which categori- but in obese men only those with ⱖ3 accompanying TABLE 3 Frequency of Accompanying Risk Factors in Overweight and Obese Framingham Study Subjects (aged 30 to 74 years)
CORONARY ARTERY DISEASE/RISK STRATIFICATION OF ADIPOSITY
699
TABLE 6 Risk of Coronary Events by Number of Associated Risk Factors in Framingham Study Subjects (aged 30 to 74 years)* Age-adjusted Relative Risk Overweight
Age-adjusted 16-yr Incidence Obese
Overweight
Obese
No. of Risk Factors
Men
Women
Men
Women
Men
Women
Men
Women
0 1 2 ⱖ3
Referent 2.31 2.87‡ 3.95‡
Referent 2.80 5.70† 8.58†
Referent 0.66 0.94 2.07†
Referent 1.20 4.71 10.88†
6.2% 11.7% 15.8% 20.4%
0.8% 3.1% 8.6% 12.3%
15.6% 10.6% 15.7% 27.6%
0.6% 4.8% 11.2% 18.5%
*A rate of 1% was assigned as a referent value for women with no risk factors where no events occurred. † Not significantly different at p ⬍0.05. ‡ Not significantly different at p ⬍0.0005. See text for a list of risk factors.
risk factors had a significant (twofold) increased risk. In both sexes, age-adjusted 16-year incidence of CHD in obese and overweight subjects varied over a wide range, depending on their burden of accompanying risk factors (Table 6). Consistent with the previously mentioned factors, in overweight subjects of either sex, CHD incidence increased stepwise with the number of accompanying risk factors. This was also the case in obese women, but not in obese men, who required ⱖ3 additional risk factors to significantly escalate their CHD risk. A multivariable risk formulation is available to facilitate the estimation of CHD risk of obese or overweight subjects in relation to their burden of associated risk factors.7 This risk formulation equation includes other risk factors that often accompany obesity, enabling quantification of the probability that an obese subject will develop CHD.
DISCUSSION National data indicate that obesity afflicts 20% of men and 25% of women ages 20 to 74 years who live in the United States.1 Its prevalence increases throughout most of adulthood but declines in advanced age. Beyond age 45 its prevalence in women exceeds that of men. Adiposity in the United States is not decreasing, despite the large number of Americans who report that they are dieting. The high average weight of Americans imposes a substantial penalty of excess CHD. The impact of weight change on the sum of cardiovascular risk factors, previously examined by the Framingham Study, showed that weight change is mirrored by changes in risk factor sum.8 A 5-lb reduction in weight lowered the sum of associated risk factors 43% in men and 40% in women. Obesity is an established major determinant of hypertension and non–insulin-dependent diabetes in the general population.9,10 In the Framingham Study, excess weight accounted for 40% to 70% of the observed occurrence of hypertension.9 Dyslipidemia is another well-documented atherogenic condition promoted by obesity, and weight loss consistently improves dyslipidemia, hypertension, insulin resistance, and blood glucose control.11 Adiposity is a biologically plausible promoter of 700 THE AMERICAN JOURNAL OF CARDIOLOGY姞
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CHD and its risk factors because visceral adiposity is a harbinger of an insulin resistant state associated with a relative deficiency of lipoprotein lipase, elevated triglycerides, reduced HDL cholesterol, small dense low-density lipoprotein, hypertension, glucose intolerance, and altered hemostasis.2 This obesity-induced insulin resistant state may afflict as much as 25% of the population. The risk stratification variables used herein do not include a number of ingredients of the insulin resistance syndrome such as triglycerides, small dense low-density lipoprotein, or fasting insulin, but they do contain risk factors proven to provide benefits when corrected. It is likely that obesity is associated with an increased hazard of CHD, considering the propensity of weight gain to promote most CHD risk factors 12,13 In the past there was an unjustified debate about the role of adiposity in CHD. Because its independent effect was considered small, some concluded that it was of little importance.14 –16 Evidence that change in weight is accompanied by corresponding change in multiple risk factors established adiposity as a true CHD hazard.17–19 In the Framingham Study, the degree of adiposity that optimizes the CHD risk profile is a BMI of 22.6 in men and 21.1 in women.20 Judging from its effect on risk factors, each 2% weight reduction in the obese should reduce CHD risk by 4%. Weight control is a logical first approach to the correction of dyslipidemia, hypertension, and glucose intolerance. Benefits of weight reduction on the major CHD risk factors should provide a powerful incentive to mitigate the unhealthy features of obesity, but we need better ways to achieve sustained weight control.1,21 Although CHD risk increases with adiposity, at any weight the CHD hazard varies widely depending on the amount of risk factor clustering. Using global risk stratification, one can more accurately quantify CHD risk. The multivariable CHD risk equation, based on these Framingham Study data, can be programmed into personal computers to facilitate office assessment of the CHD risk of overweight or obese subjects. Global risk assessment also helps focus attention on the potential of CHD risk reduction by not only weight loss, but by comprehensive risk factor correction. This is often important because of the difficulty many have in achieving sustained weight OCTOBER 1, 2002
reduction. Weight loss, by improving the CHD risk profile, should reduce vulnerability to CHD, but there are few long-term studies to testify to the potential benefit. Risk stratification of overweight and obese persons helps target those for which modification of CHD risk factors would prove to be most beneficial. The goal of treatment should be to reduce the global risk for development of CHD, a major hazard of obesity. 1. National Task Force on the Prevention and Treatment of Obesity. Overweight,
obesity and health risk. Arch Intern Med 2000;160:880 –890. 2. Reaven GM. Syndrome X. 6 years later. J Intern Med Suppl 1994;736:13–22. 3. Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP. An investigation of coronary heart disease in families: the Framingham Offspring Study. Am J Epidemiol 1979;110:281–290. 4. Kannel WB, Wolf PA, Garrison RJ. Section 34: some risk factors related to the annual incidence of cardiovascular disease and death using pooled repeated biennial measurements: Framingham Heart Study, 30-year follow-up. Springfield: National Technical Information Service. 1987:1– 459. 5. Lipid Research Clinics Program. Manual of Laboratory Operation. Bethesda, MD: National Institutes of Health, 1974. 6. McNamara JR, Schaefer EJ. Automated enzymatic standardized lipid analysis for plasma and lipoprotein fractions. Clin Chem Acta 1987;166:1–8. 7. Wilson PWF, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation 1998;97:1837–1847. 8. Wilson PWF, Kannel WB, Silbershatz H, D’Agostino RB. Clustering of
metabolic risk factors and coronary heart disease. Arch Intern Med 1999;159: 1104 –1109. 9. Garrison RJ, Kannel WB, Stokes J III, Castelli WP. Incidence and precursors of hypertension in young adults: the Framingham Study. Prev Med 1987;16:235– 251. 10. Wilson PWF, McGee DL, Kannel WB. Obesity, very low-density lipoproteins, and glucose intolerance over 14 years: the Framingham Study. Am J Epidemiol 1981;114:697–704. 11. Pi-Sunyer FX. A review of long-term studies of evaluating the efficiency of weight loss in ameliorating disorders associated with obesity. Clin Ther 1996; 18:1006 –1038. 12. Rimm EB, Stampfer MJ, Giovannucci E, Ascherio A, Spiegelman D, Colditz GA. Body size and fat distribution as predictors of coronary heart disease among middle-aged and older US men. Am J Epidemiol 1995;141:1117–1127. 13. Hubert H, Feinleib M, McNamara PM, Castelli WP. Obesity as an independent risk factor for cardiovascular disease: a 26-year follow-up of participants in the Framingham Heart Study. Circulation 1983;67:968 –977. 14. Keys A, Menotti A, Aravanis C. The Seven Countries Study: 2289 deaths in 15 years. Prev Med 1984;13:141–154. 15. Mann GV. The influence of body weight on health (second of two parts). N Engl J Med 1974;291:226 –232. 16. Barrett-Conner EL. Obesity atherosclerosis and coronary artery disease. Ann Intern Med 1985;103:1010 –1019. 17. Kissebah AH, Krakower GR. Regional obesity and morbidity. Physiol Rev 1994;74:761–811. 18. Denke MA, Sempos CT, Grundy SM. Excess body weight. An underrecognized contributor to dyslipidemia in white American women. Arch Intern Med 1994;154:401–410. 19. Despres JP, Moorjani S, Lupien PJ, Tremblay A, Nadeau A, Bouchard C. Regional distribution of body fat, plasma lipoproteins and cardiovascular disease. Arteriosclerosis 1990;10:497–511. 20. Garrison RJ, Kannel WB. A new approach for estimating healthy body weights. Int J Obes Metab Disord 1993;17:417–423. 21. Eckel RH, Krauss RM. American Heart Association call to action: obesity as a major risk factor for coronary heart disease. Circulation 1998;97:2099 –2100.
CORONARY ARTERY DISEASE/RISK STRATIFICATION OF ADIPOSITY
701
MD, MPH,
Peter W.F. Wilson, MD, Byung-Ho Nam, Ralph B. D’Agostino, PhD
PhD,
and
We examined the extent of coronary heart disease (CHD) risk factor clustering in overweight persons with a body mass index (BMI) of 25 to 29 and an obesity BMI of >30 and the influence of this on the hazard of myocardial infarction and coronary mortality. A total of 1,309 men and 739 women aged 30 to 74 years, initially free of cardiovascular disease, comprised the overweight subject group, and 375 men and 356 women comprised the obese subject group at risk. The sample was derived from the original Framingham Study cohort at the 11th biennial examination, and their offspring at initial examination. During 16 years of follow-up of overweight subjects, 188 men and 44 women had CHD events, indicating an age-adjusted rate that was not much different from the slim subjects. In the obese subject group, 72 men and 37 women developed CHD, corresponding to age-adjusted risk ratios 1.48 times that of lean men, and 2.09 times that of lean women. Risk factors were categorized as systolic blood pressure >140 mm Hg, total cholesterol >240 mg/dl,
high-density lipoprotein (HDL) cholesterol <35 mg/dl for men and <40 mg/dl for women, heart rate >80 beats/min, history of smoking, history of type 2 diabetes, and electrocardiographic left ventricular hypertrophy. Being overweight occurred in isolation of CHD risk factors in 22% of men and in 16.4% of women. Being obese occurred in isolation in only 12.8% of men and 9% of women. Clusters of >2 risk factors occurred in 56% of obese men and in 62.4% of obese women, a frequency substantially exceeding that in slim subjects. Compared with obese men without risk factors, those with >3 factors had a 2.07 age-adjusted relative risk of developing CHD, and obese women had a 10.9 relative risk (p <0.05). Being overweight and obese promotes clusters of CHD risk factors that greatly influence their impact. Global risk assessment can identify high-risk overweight candidates for CHD who most urgently need correction of associated risk factors, as well as sustained weight reduction. 䊚2002 by Excerpta Medica, Inc. (Am J Cardiol 2002;90:697–701)
verweight and obese persons are common in the United States, and their prevalence is increasing O at an alarming rate. Such persons experience excess
tion of cardiovascular risk factor status and development of cardiovascular disease. In 1971, another cohort of 5,124 men and women, who were offspring (and spouses) of the original cohort, were likewise enrolled.3,4 The population sample for this investigation is composed of the original Framingham Study cohort who attended their 11th biennial examination in 1971 to 1974 and their offspring at their 1971 to 1975 initial examination. Patients were stratified by body mass index (BMI) at their initial examination. Patients were designated as overweight at a BMI of 25 to 29.9 and were considered obese at a BMI of ⱖ30. A total of 375 men and 356 women (average age 47 to 52 years) met the criteria for obese subjects, and 1,309 men and 739 women (average age 48 to 53 years) met the criteria for overweight subjects. The selected participants were free of cardiovascular disease at baseline examination and were considered at risk for initial CHD events at their specified adiposity status (in relation to their burden of accompanying CHD risk factors). Each examination included a detailed cardiovascular assessment, blood pressure determination, and relevant laboratory tests. Morbidity and mortality were monitored using clinical examinations, hospital admission surveillance, and communications with personal physicians and the participant’s relatives. A panel of senior physician investigators adjudicated suspected CHD events using established criteria. Detailed descriptions of the sampling methods, examina-
1
dyslipidemia, higher blood pressures, more glucose intolerance, hyperinsulinemia, insulin resistance, and left ventricular hypertrophy.2 This study examines the prevalence of clusters of specified risk factors in overweight and obese populations and the relative risk of initial coronary heart disease (CHD) events (myocardial infarction or fatal coronary events) in relation to the amount of risk factor clustering. These populations were examined using multivariable risk analysis. The multivariable risk formula we derived enables risk stratification of adiposity to target those at high risk for CHD, for aggressive preventive measures to improve their global multivariable risk.
METHODS The Framingham Study was initiated in 1948, enrolling 5,209 men and women for biennial examinaFrom the Framingham Study, Boston University School of Medicine, Framingham, Massachusetts; and Department of Mathematics, Boston University, Boston, Massachusetts. Framingham Study research is supported by National Institutes of Health/National Heart, Lung, and Blood Institute, Bethesda, Maryland (Contract N01-HC-38038), and the Visiting Scientist Program, which is supported by Servier Ame´rique, Nevilly-Sur-Seine Cedex, France. Manuscript received January 15, 2002; revised manuscript received and accepted June 3, 2002. Address for reprints: William B. Kannel, MD, MPH, Framingham Heart Study, 5 Thurber Street, Framingham, Massachusetts 01702. E-mail: [email protected]. ©2002 by Excerpta Medica, Inc. All rights reserved. The American Journal of Cardiology Vol. 90 October 1, 2002
0002-9149/02/$–see front matter PII S0002-9149(02)02592-4
697
TABLE 1 Risk of Coronary Events* According to Body Mass Index (BMI) in Framingham Study Subjects (aged 30 to 74 years) BMI Men
No. of events No. at risk Age-adjusted rate† Risk ratio
Women
⬍25
25–29.9
30⫹
⬍25
25–29.9
30⫹
99 772 20.2% Referent
188 1,306 21.3% 1.08
72 375 28.3% 1.49‡
76 1,703 6.2% Referent
44 739 8.0% 1.08
37 356 14.5% 2.08‡
*Coronary events: Myocardial infarction and CHD death. † Age-adjusted rates are for 16 years. ‡ p ⬍0.005 for BMI ⱖ30.
TABLE 2 Distribution of Cardiovascular Risk Factors According to Body Mass Index (BMI) in Framingham Study Subjects (aged 30 to 74 years) BMI of Men
Continuous risk factors* BMI Systolic BP Total cholesterol HDL cholesterol Heart rate Categorical risk factors† Current smoker ECG-LVH Type 2 diabetes
BMI of Women
⬍25 (n ⫽ 772)
25–29.9 (n ⫽ 1,309)
ⱖ30 (n ⫽ 375)
⬍25 (n ⫽ 1,730)
25–29.9 (n ⫽ 739)
ⱖ30 (n ⫽ 356)
23.1 128.5 207.9 48.3 73.0
27.2 131.7 215.3 43.7 73.1
32.5‡ 139.9‡ 216.0§ 40.9‡ 74.9㛳
22.3 126.1 216.0 60.5 78.6
26.9‡ 129.7‡ 219.3 55.1‡ 78.9
33.9‡ 137.5‡ 220.6㛳 50.1‡ 81.8‡
47.2 1.6 3.0
37.5 1.2 3.9
36.3‡ 2.6 7.9‡
40.4 0.7 1.7
35.0㛳 0.7 2.4
30.6‡ 1.1 6.6‡
*Values are expressed as age-adjusted means. † Values are expressed as age-adjusted percentages. ‡p ⬍0.05; §p ⬍0.01; 㛳p ⬍0.001. BP ⫽ blood pressure; ECG-LVH ⫽ left ventricular hypertrophy by electrocardiography.
tion procedures, and the criteria for CHD end points have been reported elsewhere.4 The risk factors under consideration were age, total and high-density lipoprotein (HDL) cholesterol, BMI, type 2 diabetes, systolic blood pressure, heart rate, cigarette smoking, and electrocardiographic left ventricular hypertrophy. The BMI was calculated as weight in kilograms divided by height in square meters. Blood pressure was measured from the left arm with a mercury sphygmomanometer with the subject seated. A large cuff was used when required, and readings were recorded to the nearest even number. Fasting plasma was used for the determination of HDL cholesterol, which was measured after precipitation with heparin-manganese.5 Type 2 diabetes was designated if the fasting plasma glucose was ⱖ7.8 mmol/L during any 2 previous examinations, or if hypoglycemic drug therapy was reported. Fasting plasma glucose was measured with a hexokinase reagent kit. Fasting total cholesterol and triglycerides were measured by the Lipid Research Clinic protocol.5,6 Values designated as risk factors were: (1) BMIs as indicated above, (2) systolic blood pressure ⱖ140 mm Hg, (3) total cholesterol ⱖ240 mg/dl, (4) HDL cholesterol ⬍35 mg/dl for men and ⬍40 mg/dl for women, (4) heart rate ⬎80 beats/min and type 2 698 THE AMERICAN JOURNAL OF CARDIOLOGY姞
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diabetes, cigarette smoking, and electrocardiographic left ventricular hypertrophy. Cox regression models were used to examine the impact of the various risk factors individually and in combination, adjusting for age and other relevant factors. Gender-specific Cox regression models were developed to predict 16-year risk of CHD end points (myocardial infarction and coronary deaths) based on 20 years of follow-up. The loss to follow-up after 20 years was ⬍3%. Logistic regression was used for estimating the age and sample size-adjusted proportions of patients with CHD who had risk factors.
RESULTS Table 1 lists the number of events, number at risk, and age-adjusted 16-year average risks of CHD events from Cox regressions in those classified as overweight or obese, compared with those who had BMIs of ⬍25. During the overweight subject group’s follow-up period, there were 188 CHD end points in men and 44 in women (a 16-year age-adjusted rate of 21.3% for men and 8.0% for women). The group’s 1.08 age-adjusted risk ratio was not statistically significant when compared with ratios for slim men and women. However, in the obese subject group there were 72 events in men and 37 in women, signifying a substantial 1.49 risk OCTOBER 1, 2002
cally defined CHD risk factors accompany adiposity in each sex. Only 12.8% and 8.99% of obese men and BMI ⬍25 BMI 25–29.9 BMI 30⫹ women, respectively, were free of No. of the other cardiovascular risk factors. Risk Factors Men Women Men Women Men Women The 56% and 62.4% frequency of 0 23.7% 18.3% 22.0% 16.4% 12.8% 9.0% ⱖ2 risk factors in obese men and 1 36.3% 42.5% 36.8% 36.1% 31.2% 28.6% women, respectively, is significantly 2 26.2% 25.7% 24.1% 30.2% 30.9% 35.1% ⱖ3 13.8% 13.5% 17.1% 17.3% 25.1% 27.3% (p ⬍0.001) different from the frequency in nonobese (BMI ⬍25) subFrequency of ⱖ2 risk factors in the obese (BMI ⱖ30) differs significantly from nonobese (BMI ⬍25) (p jects. The extent of clustering in ⬍0.001), in both sexes. Risk factors considered were: age, systolic blood pressure, HDL cholesterol, total cholesterol, cigarette smoking, heart rate, diabetes, and left ventricular hypertrophy. For the overweight overweight subjects is less pro(BMI 25–29.9) the frequency of ⱖ2 risk factors is significantly different from BMI ⬍25 in women (p nounced but being overweight oc⬍0.05). curred in isolation in only 22% and 16.4% of men and women, respectively. Clusters of ⱖ2 risk factors occurred in overwieght women with TABLE 4 Risk of Myocardial Infarction and Coronary Heart Disease (CHD) Death a frequency significantly greater (p by Specified Cardiovascular Risk Factors (Cox regression model)* ⬍0.05) than was observed in the slim Relative Risk Confidence Intervals subjects. Table 4 lists the age and risk facRisk Factors Men Women Men Women tor-adjusted multivariable Cox reAge (1 yr) 1.04 1.05 1.02–1.05 1.03–1.07 gression estimates of the risk of Systolic blood pressure (ⱖ140 mm Hg) 1.31 1.80 1.04–1.64 1.26–2.57 CHD for the entire population samHDL cholesterol (⬍35 mg/dl) 1.49 1.67 1.17–1.90 1.09–2.56 Total cholesterol (ⱖ240 mg/dl) 1.59 1.86 1.28–1.99 1.34–2.60 ple. The sample was specified by inType 2 diabetes 1.94 1.85 1.39–2.70 1.14–3.03 crements in each risk factor. All reSmoker 1.93 2.78 1.56–2.39 1.99–3.87 gression estimates were statistically ECG-LVH 2.58 1.66 1.60–4.15 0.72–3.81 significant in men and women except Heart rate (⬎80 beats/min) 0.91 1.09 0.72–1.15 0.79–1.50 1.20 1.04 0.94–1.54 0.71–1.51 Overweight (BMI 25–29.9 kg/m2) for heart rate and being overweight. Obese (BMI ⱖ 30 kg/m2) 1.66 1.64 1.21–2.28 1.08–2.48 After adjusting for other risk factors including age, obesity per se contin*Reference group is BMI ⬍25 kg/m2. Abbreviation as in Table 2. ued to make a significant contribution to risk of developing coronary disease. This was not the case for the overweight subject group, which exTABLE 5 Proportion of Coronary Events by Number of Coexistent Risk Factors in hibited no independent effects. Framingham Study Subjects (aged 30 to 74 years)* Table 5 displays the proportion of Overweight Obese the CHD events that occur in obese No. of Associated and overweight subjects in relation Risk Factors Men Women Men Women to their burden of CHD risk factors. 0 11.5% 3.2%† 22.6% 1.7% We first calculated the projected 1 21.7%† 12.5%† 15.2% 13.6%† number of cases for each subgroup 2 29.2%† 34.7%† 22.5%† 32.1%† ⱖ3 37.6%† 49.5%† 39.7%† 52.7%† using the age-size adjusted rate and then calculated the proportion (pro*Values are adjusted for size of sample with a specified number of associated risk factors. † jected number of cases for each catp ⬍0.05 for difference from none. egory divided by the total projected number of cases), because the proportion of CHD events in these subratio for men and 2.08 ratio for women. These values jects is influenced by the size of each numerical risk were statistically significant (p ⬍0.005). Despite the factor category. Adjusting for age and sample size, the larger risk ratio for women, the age-adjusted incidence proportion of CHD events increased with the number of associated risk factors. Additionally, 40% to 50% of CHD for women is only half that of men. It is evident from Table 2 that the age-adjusted of the CHD events that evolved in obese or overmean level of most risk factors is unfavorable for weight subjects occurred in those with ⱖ3 additional overweight and obese subjects. The prevalence of type cardiovascular risk factors (Table 5). Age-adjusted CHD risk ratios in overweight sub2 diabetes and electrocardiographic left ventricular hypertrophy are substantially increased in obese sub- ects of either sex tended to increase with the amount jects, and significantly increased for subjects with type of risk factor clustering (Table 6). Men who had ⱖ3 2 diabetes. Only the level of cigarette smoking was associated risk factors had a fourfold increased risk significantly more favorable for CHD risk in over- and women had a relative risk of 8.6. A stepwise increase in relative risk was noted in obese women, weight and obese subjects. Table 3 lists the frequency with which categori- but in obese men only those with ⱖ3 accompanying TABLE 3 Frequency of Accompanying Risk Factors in Overweight and Obese Framingham Study Subjects (aged 30 to 74 years)
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TABLE 6 Risk of Coronary Events by Number of Associated Risk Factors in Framingham Study Subjects (aged 30 to 74 years)* Age-adjusted Relative Risk Overweight
Age-adjusted 16-yr Incidence Obese
Overweight
Obese
No. of Risk Factors
Men
Women
Men
Women
Men
Women
Men
Women
0 1 2 ⱖ3
Referent 2.31 2.87‡ 3.95‡
Referent 2.80 5.70† 8.58†
Referent 0.66 0.94 2.07†
Referent 1.20 4.71 10.88†
6.2% 11.7% 15.8% 20.4%
0.8% 3.1% 8.6% 12.3%
15.6% 10.6% 15.7% 27.6%
0.6% 4.8% 11.2% 18.5%
*A rate of 1% was assigned as a referent value for women with no risk factors where no events occurred. † Not significantly different at p ⬍0.05. ‡ Not significantly different at p ⬍0.0005. See text for a list of risk factors.
risk factors had a significant (twofold) increased risk. In both sexes, age-adjusted 16-year incidence of CHD in obese and overweight subjects varied over a wide range, depending on their burden of accompanying risk factors (Table 6). Consistent with the previously mentioned factors, in overweight subjects of either sex, CHD incidence increased stepwise with the number of accompanying risk factors. This was also the case in obese women, but not in obese men, who required ⱖ3 additional risk factors to significantly escalate their CHD risk. A multivariable risk formulation is available to facilitate the estimation of CHD risk of obese or overweight subjects in relation to their burden of associated risk factors.7 This risk formulation equation includes other risk factors that often accompany obesity, enabling quantification of the probability that an obese subject will develop CHD.
DISCUSSION National data indicate that obesity afflicts 20% of men and 25% of women ages 20 to 74 years who live in the United States.1 Its prevalence increases throughout most of adulthood but declines in advanced age. Beyond age 45 its prevalence in women exceeds that of men. Adiposity in the United States is not decreasing, despite the large number of Americans who report that they are dieting. The high average weight of Americans imposes a substantial penalty of excess CHD. The impact of weight change on the sum of cardiovascular risk factors, previously examined by the Framingham Study, showed that weight change is mirrored by changes in risk factor sum.8 A 5-lb reduction in weight lowered the sum of associated risk factors 43% in men and 40% in women. Obesity is an established major determinant of hypertension and non–insulin-dependent diabetes in the general population.9,10 In the Framingham Study, excess weight accounted for 40% to 70% of the observed occurrence of hypertension.9 Dyslipidemia is another well-documented atherogenic condition promoted by obesity, and weight loss consistently improves dyslipidemia, hypertension, insulin resistance, and blood glucose control.11 Adiposity is a biologically plausible promoter of 700 THE AMERICAN JOURNAL OF CARDIOLOGY姞
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CHD and its risk factors because visceral adiposity is a harbinger of an insulin resistant state associated with a relative deficiency of lipoprotein lipase, elevated triglycerides, reduced HDL cholesterol, small dense low-density lipoprotein, hypertension, glucose intolerance, and altered hemostasis.2 This obesity-induced insulin resistant state may afflict as much as 25% of the population. The risk stratification variables used herein do not include a number of ingredients of the insulin resistance syndrome such as triglycerides, small dense low-density lipoprotein, or fasting insulin, but they do contain risk factors proven to provide benefits when corrected. It is likely that obesity is associated with an increased hazard of CHD, considering the propensity of weight gain to promote most CHD risk factors 12,13 In the past there was an unjustified debate about the role of adiposity in CHD. Because its independent effect was considered small, some concluded that it was of little importance.14 –16 Evidence that change in weight is accompanied by corresponding change in multiple risk factors established adiposity as a true CHD hazard.17–19 In the Framingham Study, the degree of adiposity that optimizes the CHD risk profile is a BMI of 22.6 in men and 21.1 in women.20 Judging from its effect on risk factors, each 2% weight reduction in the obese should reduce CHD risk by 4%. Weight control is a logical first approach to the correction of dyslipidemia, hypertension, and glucose intolerance. Benefits of weight reduction on the major CHD risk factors should provide a powerful incentive to mitigate the unhealthy features of obesity, but we need better ways to achieve sustained weight control.1,21 Although CHD risk increases with adiposity, at any weight the CHD hazard varies widely depending on the amount of risk factor clustering. Using global risk stratification, one can more accurately quantify CHD risk. The multivariable CHD risk equation, based on these Framingham Study data, can be programmed into personal computers to facilitate office assessment of the CHD risk of overweight or obese subjects. Global risk assessment also helps focus attention on the potential of CHD risk reduction by not only weight loss, but by comprehensive risk factor correction. This is often important because of the difficulty many have in achieving sustained weight OCTOBER 1, 2002
reduction. Weight loss, by improving the CHD risk profile, should reduce vulnerability to CHD, but there are few long-term studies to testify to the potential benefit. Risk stratification of overweight and obese persons helps target those for which modification of CHD risk factors would prove to be most beneficial. The goal of treatment should be to reduce the global risk for development of CHD, a major hazard of obesity. 1. National Task Force on the Prevention and Treatment of Obesity. Overweight,
obesity and health risk. Arch Intern Med 2000;160:880 –890. 2. Reaven GM. Syndrome X. 6 years later. J Intern Med Suppl 1994;736:13–22. 3. Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP. An investigation of coronary heart disease in families: the Framingham Offspring Study. Am J Epidemiol 1979;110:281–290. 4. Kannel WB, Wolf PA, Garrison RJ. Section 34: some risk factors related to the annual incidence of cardiovascular disease and death using pooled repeated biennial measurements: Framingham Heart Study, 30-year follow-up. Springfield: National Technical Information Service. 1987:1– 459. 5. Lipid Research Clinics Program. Manual of Laboratory Operation. Bethesda, MD: National Institutes of Health, 1974. 6. McNamara JR, Schaefer EJ. Automated enzymatic standardized lipid analysis for plasma and lipoprotein fractions. Clin Chem Acta 1987;166:1–8. 7. Wilson PWF, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation 1998;97:1837–1847. 8. Wilson PWF, Kannel WB, Silbershatz H, D’Agostino RB. Clustering of
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