Obesity and cardiovascular disease: The Framingham study

4 Obesity and Cardiovascular Disease: the Framingham Study TAVIA GORDON WILLIAM B. KANNEL

Despite a general presumption that obesity is unhealthy and a large body of research into the physiology of adiposity, scientific research has made little progress in unravelling its determinants and its health consequences remain controversial. Some investigators depreciate its medical hazards despite extensive actuarial and epidemiological evidence (Keys et al, 1972). All things considered, it must be admitted that obesity and its health consequences are still incompletely understood. The primary focus of this chapter will be on the medical association of obesity as determined from longitudinal observations in the Framingham cohort. METHODS USED IN THE FRAMINGHAM STUDY The Framingham Study has observed a group of 5209 men and women, aged 30 to 59 in 1950, by means of repeated biennial examinations (Gordon and Kannel, 1970). The examinations given included a standardised cardiovascular evaluation, a variety of blood analyses and a number of other tests and measurements. In addition, information on mortality and major cardiovascular morbidity was obtained from a variety of sources including death certificates and hospital records. On each examination the person was weighed on a clinical beam scale. The subject wore an examination gown. Shoes and street dress were removed but men wore their trousers. On the fourth and fifth biennial examinations there were extensive sets of anthropological measurements, including several skinfolds and girths, but this extensive anthropological characterisation was not repeated at other examinations. Hence, the standard measure of obesity used in the study was weight by height, expressing the weight as a percentage of a standard weight for height. The standard used in this chapter is derived from tables of desirable weight published by the Metropolitan Life Insurance Company. While there are various ways of translating measurements of height and weight into a measure of adiposity, they tend to be highly correlated and there is little reason to believe (as some do) that any are distinctly superior as Clinics in E n d o c r i n o l o g y a n d M e t a b o l i s m - -

Vol. 5, No. 2, July 1976.

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an index of the percentage of total body weight contained in adipose tissue. In any event, it is presumably not the quantity of fat tissue per se but the physiological consequences of gaining and maintaining excess adipose tissue which are of primary interest. Even a direct and precise measurement of body fat would be only an index of these physiological consequences. 'Obesity' is treated in this report as a graded characteristic rather than as a distinct condition. For convenience, and in deference to convention, we refer to 'obesity' and 'adiposity' but it should be understood throughout that no sharp demarcations are intended between obese and non-obese persons. Moreover, grossly overweight people, who might have direct medical problems from their massive body weight, are too few in this population to be examined separately. Details of specific measurements and disease criteria are published elsewhere (Shurtleff, 1974). DISTRIBUTION OF RELATIVE WEIGHT Figure 1 gives distributions of relative weight for selected age groups. It is obvious that the study group is, on average, well above 'desirable' weight and that only a small proportion of the cohort is below 'desirable' weight. Generally, young women are closer to their desirable weight than any other age--sex group, but at Exam. 5 only 16.9 per cent of women under age 45 had weights below the 'desirable' weight for height while twice that number had weights 20 per cent or more above 'desirable'. 30

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95 105 115 125 135 145 155 165 175

RELATIVE WEIGHT (Percent) Figure 1. Distribution of relative weight by age and sex. Framingham Study, Exam. 5.

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OBESITY AND CARDIOVASCULAR DISEASE

These findings are not unique to the F r a m i n g h a m cohort. Comparisons with data from a sample of the white population of the United States indicate that the F r a m i n g h a m cohort is very similar to the contemporaneous American population of the same age, both in height and weight (Roberts, 1966).

IMPACT ON HEALTH The relationship of relative weight to health, while well documented, is not well understood. There is a distinct excess incidence of cardiovascular disease and death in persons who are overweight, and this excess generally increases with the extent of overweight (Figure 2). To a considerable degree this is explained by the fact that as people gain weight their blood pressure and serum cholesterol levels tend to rise (Ashley and Kannel, 1974). As a consequence (in cross-sectional terms) persons who are obese have higher levels of blood pressure and serum cholesterol. This tendency is less in women than men. There is also a positive association between relative weight and glucose intolerance and uric acid levels. Hence, we may argue that an increase in weight leads to an increase in other factors which, in turn, lead to an increased cardiovascular risk. 30

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Figure 2. Two-year incidence of cardiovascular disease and death by relative weight. Framingham

Study: 18-yearfollow-up. NOTE: data shown are crude rates for the age group 45--74. Although this association of obesity with cardiovascular factors is weaker in women than men, obesity per se has at least as strong an association with the incidence of cardiovascular disease for women as for men. Furthermore, the strength of relationship of obesity to disease incidence appears to decrease with age. At age 65 to 74 the association is not statistically significant for any cardiovascular endpoint (Tables 1 to 5). In this respect relative weight behaves more like serum cholesterol (or LDL cholesterol) levels than blood pressure; for serum cholesterol as a risk factor is similarly age-dependent whereas blood pressure is not.

370

TAVIA GORDON AND WILLIAM B. KANNEL Table 1. Regression of 2-year incidence of cardiovascular disease on relative weight,

Framingham Study, 18-year follow-up Regression coefficient

Age

Men 45--54 55--64 65--74 Average all ages Bivariate Multivariate

0.0109 0.0072 0.0037 0.0072 0.008 0.004

Women 0.0175 0.0099 --0.0001 0.0098 0.0092 0.0028

T-value Men

Women

2.29 1.65 0.53 2.73 2.76 1.32

4.29 3.21 --0.02 4.51 4.14 1.14

Note: Logistic regression estimated by method of Walker and D u n c a n (1967).

Table 2. Regression of 2-year incidence of intermittent claudication on relative weight,

18-year follow-up, Framingham Cohort men and women 45--74 Regression coefficient

Age

Men 45--54 55--64 65--74 Average all ages Bivariate Multivariate

--0.0197 --0.0118 --0.0217 --0.0161 --0.0158 --0.0193

Women 0.0243 0.0011 --0.0039 0.0072 0.0047 --0.0016

T-value Men

Women

--1.51 --1.27 --1.54 --2.41 --2.38 --2.79

2.59 0.13 --0.40 1.35 0.84 --0.28

Note: Logistic regression estimated by method of Walker and Duncan (1967).

Table 3. Regression of 2-year incidence of congestive heart failure on relative weight,

Framingham Study, 18-year follow-up Age

45--54 55--64 65--74 Average all ages Bivariate Multivariate

Regression coefficient

T-value

Men

Women

Men

Women

0.0165 0.0061 0.0161 0.0122 0.0124 0.0057

0.0129 0.0235 0.0087 0.0182 0.0177 0.0111

1.50 0.61 1.31 1.93 1.95 0.85

1.17 4.93 1.24 4.89 4.64 2.72

Note: Logistic regression estimated by method of Walker and D u n c a n (1967).

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Table 4. Regression of 2-year incidence of brain infarction on relative weight, Framingham Study, 18-yearfollow-up Regression Coefficient

Age

Men 45--54 55--64 65--74

Average all ages Bivariate Multivariate

0.0056 0.0223 --0.0069 0.0100 0.0100 0.0031

T-value

Women

Men

0.0312 0.0171 0.0106 0.0196 0.0184 0.0089

0.32 1.73 --0.41 1.14 1.13 0.35

Women 3.87 2.41 1.26 4.36 3.94 1.76

Note: Logistic regression estimated by method of Walker and Duncan (1967).

Table 5. Regression of 2-year incidence of coronary heart disease on relative weight, Framingham Study, 18-yearfollow-up Regression coefficient

Age Men 45--54

55--64 65--74

Average all ages Bivariate Multivariate

0.0144 0.0109 0.0089 0.0119 0.0119 0.0101

Women 0.0178 0.0109 --0.0022 0.0101 0.0094 0.0024

T-value Men 2.73 2.31 1.10 3.68 3.70 2.98

Women 3.78 3.16 --0.40 4.09 3.72 0.84

Note: Logistic regression estimated by method of Walker and Duncan (1967).

Another anomaly is the fact that intermittent claudication (Table 2), which is also an atherosclerotic disease, is more likely to occur in lean people than in obese. Framingham data leave little doubt that 'obese' persons develop more cardiovascular disease than lean persons (Gordon and Kannel, 1973). Comparing obese (MRW >140) with lean persons (<90 MRW) the obese have a doubled incidence of brain infarction and congestive heart failure and a distinct, but more moderate, excess risk of coronary heart disease. Since the cardiovascular sequelae are the most dangerous of all the products of obesity, this warrants a more detailed examination. From regression analysis it is apparent that the effect of obesity in promoting cardiovascular disease is greater in women than men and that the effect diminishes with advancing age (Table 1). The multivariate regression includes, in addition to relative weight, systolic blood pressure, serum cholesterol, glucose intolerance, ECG--LVH and age. Comparing the bivariate coefficients (which adjust only for age) with the multivariate it is evident that much of the effect of obesity is mediated through the other risk factors.

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TAVIA GORDONAND WILLIAMB. KANNEL

In looking at the specific cardiovascular disease, the impact in women is greatest for congestive heart failure (Table 3) and brain infarction (Table 4), while for men it is roughly equivalent for all types of cardiovascular disease (except for a strong negative association with intermittent claudication) (Table 2). Significant n e t contributions of overweight are found in men only for coronary heart disease (Table 4) and in women only for congestive failure (Table 3). From a public health viewpoint, however, an obese person remains at greater cardiovascular risk even where a significant net contribution cannot be demonstrated, precisely because he is more likely to have an elevated blood pressure, elevated serum cholesterol and glucose intolerance. Compared to other risk factors, relative weight ranks quite low in men but somewhat higher in women as judged from the size of ~he standardised univariate regression coefficients for the various risk factors for cardiovascular disease (Table 6). Nevertheless, because it reversibly promotes atherogenic traits like hypertension, diabetes and hyperlipidaemia, reduction of overweight is probably the most important hygienic measure (aside from avoidance of cigarettes) available for the control of cardiovascular disease. The negative coefficients for the regression of death on relative weight are somewhat puzzling but they reflect a consistent finding in the Framingham Study, namely, an excess mortality both at low and high relative weights. This is not unique to the Framingham Study cohort (Dyer et al, 1975). It is partly accounted for by the fact that seriously ill persons, who have lost weight because of their illness, are at greater risk of death. However, despite considerable exploration of the data we do not yet have a full explanation of this finding. Table 6. Average univariate standardised logistic regression coefficients for death and cardiovascular disease incidence, Framingham Study, 18-year follow-up

Cardiovascular disease

Death

Independent variable Men Relative weight 0.125 Serum cholesterol 0.230 Systolic blood pressure 0.419 Diastolic blood pressure 0.342 Vital capacity --0.173 Diabetes 0.169 LVH-ECG 0.223 Cigarettes/day 0.223

Women

Men

Women

0.216 0.270 0.470 0.378 --0.332 0.202 0.252 0.038

--0.189 --0.099 0.294 0.195 --0.384 0.116 0.361 0.226

--0.060 --0.017 0.254 0.172 --0.411 0.218 0.294 0.130

Note: Logisticregressions were calculated for each 10-yearage group in the range 45--74 and

weighted by the inverse of their variances to compute average coefficients. Estimated by method of Walker and Duncan (1967).

E S T I M A T I O N OF R I S K

A logistic function prepared for analytical purposes is a different matter than one prepared for estimating risk. Logically, before being medically concerned with a person's weight, it would seem sensible to estimate his risk of

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developing cardiovascular disease or of dying. Tables for assessing the risk of a person originally free from cardiovascular disease developing the various cardiovascular diseases are in print (McGee, 1973). These, however, do not include relative weight as a risk factor. It may be helpful to supplement this information with a set of more complicated functions which include relative weight a m o n g the variables. These may be used to estimate the risk of persons 30 to 64 years old developing cardiovascular disease within 10 years, or of dying in that period. The functions are restricted to persons initially free from cardiovascular disease (Table 7). Table 7. Logistic regression coefficients for the lO-year incidence of cardiovascular disease and death given certain characteristics in persons free of cardiovascular disease at Exam 2, Framingham Study

Characteristics

Cardiovascular disease Men

Relative weight (per cent) 0.0094358b Age (years) 0.4230619e Diastolic blood pressure (mrn Hg) 0.0204239c Serum cholesterol (mg/ml) 0.0205275b Cigarettes/day 0.0599176b Vital capacity ( d l ) --0.0013572 Pulse rate 0.0065277 Diabetesa 1.2064293c LVH-ECGa 1.3089251c Age --0.0028447 b Age X cholesterol --0.0002344 Age X cigarettes/day --0.0005473 Constant --21.1296685 apresent (definite)

=

1,

Death

Women

Men

Women

0.0075781b 0.1260685c

--0.0082315 0.1612311

0.0153156 b

0.0264676

0.0159573

0.0145005 0.0025045 0.0497954 0.0723086 --0.0032197 b --0.0052825 --0.0004253 0.0140600 1.5525138 c 1.0304984 1.1578399 b 0.9611221 0.000175Sb --0.0006176 --0.0002030 --0.0000071 --0.0005620 --0.0007502 --12.1306775 --10.5036815

0.0104825 0.0689721 --0.0020435 --0.0048993 1.4785188 1.3074035 0.0013050 --0.0001837 --0.0008564 --6.7035243

--0.0007280 --0.0116870

not present = 0

bp<0.05 ep
The various second order terms (age 2, age X cholesterol, age X cigarettes/day) are included to improve graduation and have no obvious analytical meaning; moreover, they confuse the analytical picture for age, serum cholesterol and cigarette smoking. However, multiple logistic regression equations tabulated here are useful for their intended purpose, i.e. estimating risk. The positive coefficient for cardiovascular disease is significant at a five per cent level (on a one-sided test) so that even in the context of this large array of risk factors, relative weight makes a statistically significant contribution to the assessment of risk, t h o u g h less than weightdependent factors like blood pressure, serum cholesterol and diabetes. As in the previous analysis (Table 6), the coefficient for the regression of death on relative weight is negative, even after excluding from the population at risk people suffering from definite, clinically manifest, cardiovascular disease.

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TAVIA GORDON AND WILLIAM B. KANNEL

MECHANISMS It is not known exactly how storage of calories in the adipose tissue raises lipids, elevates blood pressure, impairs glucose tolerance and promotes hyperuricaemia. The answer to this question should greatly enhance our understanding of the biology of obesity. Obesity, like so many other chronic conditions, is more often controllable than curable and it is more likely to respond to management if corrected early in its course. Also, like most chronic diseases obesity is prone to exacerbations and recurrences. The earlier in life obesity is established and the more pronounced and longstanding it is, the more resistant it is to treatment (Brook, 1974). From the existing evidence of the efficacy of treatment of longstanding obesity it must be classed as one of the less tractable diseases. For this reason it is better prevented than cured. It would be most helpful if the medical profession developed a sense of urgency about obesity so that when it first appears, like a lump in the breast or a high blood sugar, something is done about it promptly. Only in this way can we hope to avoid the refractory obese state. Once obesity is sustained for a long period the evidence available suggests that it is a self-perpetuating condition, as if homeostatic mechanisms have set the 'thermostat' to maintain the heavier weight. Whether this is a consequence of permanent hyperplasia of insulin-insensitive fat cells, blunted ability to regulate intake to need, psychosocial factors or other factors is unclear (Mann, 1974). Whatever the reason, it would appear imprudent to allow obesity to develop fully and persist any length of time. Cardiovascular disease still accounts for half the annual toll of mortality in affluent countries and chances of developing some major cardiovascular disease before age 60 are, for men, one in three. There is every indication that this continuing epidemic has evolved from our way of life and the remedy would appear to entail an alteration of our ecology to one more favourable to cardiovascular health. Control of excessive calory intake and increasing opportunities for exercise are required, as well as a reduction in the tendency to use food as a form of entertainment. For those who doubt that obesity poses a threat to cardiovascular health, only a clear demonstration that correction of longstanding obesity does in fact prolong life will suffice. In view of our poor performance in achieving sustained control of such obesity this evidence will be a long time in coming. Can we afford iconoclasm while awaiting proof of efficacy? Not really, since weight control is logically the first approach in correcting or avoiding hypertension, diabetes and hyperlipidaemia. There is no sound basis for predicting the benefit of a rigorous controlled clinical trial which at the present time seems manifestly impossible. It can be estimated from Framingham data that if everyone were at optimal weight we would have 25 per cent less CHD and 35 per cent less congestive failure and brain infarctions. This potential benefit would seem worth considerable effort to attain.

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REFERENCES

Ashley, F. W. Jr & Kannel, W. B. (1974) Relation of weight change to changes in atherogenic traits. The Framingham Study. Journal of Chronic Disease, 27, 103-114. Brook, C. G. D. (1974) Critical periods in childhood obesity. In Obesity (Ed.) Burland, W. L., Samuel, P. D. & Yudkin, J. Edinburgh: Churchill Livingstone. Dyer, A. R., Stamler, J., Berkson, D. M. & Lindberg, H. A. (1975) Relationship of relative weight and body mass index to 14-year mortality in the Chicago Peoples Gas Company Study. Journal of Chron& Diseases, 28, 109-123. Gordon, T. & Kannel, W. B. (1970) The Framingham Study 20 years later. In The Community as an Epidemiolog&al Laboratory: A Casebook of Community Studies (Ed.) Kessler, I. I. & Levin, M. L. Baltimore: Johns Hopkins Press. Gordon, T. & Kannel, W. B. (1973) The effects of overweight on cardiovascular diseases. Geriatrics, 28~ 80-88. Keys, A., Aravanis, C., Blackburn, H., Van Buckem, F. S. P., Busina, R., Djordevic, B. S., Findanza, F. F., Karvonen, M. J., Menotti, A., Puddu, V. & Taylor, H. L. (1972) Coronary heart disease: Overweight and obesity as risk factors. Annals of Internal Medicine, 77, 15-27. Mann, G. V. (1974) The influence of obesity on health (2). New England Journal of Medicine, 291, 226-232. McGee, D. (1973) The probability of developing certain cardiovascular diseases in eight years at specified values of some characteristics. In The Framingham Study (Ed.) Kannel, W. B. & Gordon, T. Washington, D. C.: U.S. Government Printing Office, DHEW Publication (NIH) 74-618. Roberts, J. (1966) Weight by height and age of adults. In Public Health Service Publication, No. 1000, Series 11, No. 14. Shurtleff, D. (1974) Some characteristics related to the incidence of cardiovascular disease and death: The Framingham Study, 18-year follow-up. In The Frarningham Study (Ed.) Kannel, W. B. & Gordon, T. Washington, D.C.: U.S. Government Printing Office, DHEW Publication (NIH) 74-599. Walker, S. H. & Duncan, D. B. (1967) Estimation of the probability of an event as a function of several independent variables. Biometrika, 54, 167-179.