Metabolic Syndrome and Ischemic Heart Disease in Elderly Men and Women

Ulf Lindblad1, Robert D. Langer2, Deborah L. Wingard2, Ronald G. Thomas2 and Elizabeth L. Barrett-Connor2

1 Department of Community Medicine, Malmö University Hospital, Malmö, Sweden.
2 Department of Family and Preventive Medicine, Division of Epidemiology, University of California, San Diego, La Jolla, CA.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Associations between metabolic syndrome components and prevalent ischemic heart disease (IHD) were investigated in a cross-sectional, community-based study of elderly men (n = 1,015) and women (n = 1,259) in Rancho Bernardo, California, in 1984–1987. In both sexes, there were significant positive associations between IHD defined by resting electrocardiogram criteria and age, systolic blood pressure, fasting and postchallenge hyperglycemia, total cholesterol/high density lipoprotein cholesterol (HDL cholesterol) ratio, and triglycerides and an inverse significant association with HDL cholesterol. High collinearity and interactions between serum insulin and metabolic syndrome variables were accounted for by uncorrelated principal components identified by factor analysis. In both men and women, three uncorrelated principal components were identified, representing a central metabolic factor (body mass index, fasting and 2-hour serum insulin, high serum triglycerides, and low HDL cholesterol), a glucose factor, and a blood pressure factor. In a multivariate model with age and sex, all three factors were significantly associated with IHD by electrocardiogram criteria; central metabolic factor (odds ratio (OR) = 1.6, p = 0.001), glucose factor (OR = 1.4, p < 0.001), blood pressure factor (OR = 1.2, p = 0.005), age (10 years) (OR = 1.8, p < 0.001), and female sex (OR = 0.5, p < 0.02). Similar results were obtained in analyses using clinically manifest IHD as the outcome. These results support the thesis that the metabolic syndrome exerts effects through different risk factors by different mechanisms.

blood pressure; body constitution; electrocardiography; glucose; insulin; lipoproteins

Abbreviations: CI, confidence interval; ECG, electrocardiogram; HDL cholesterol, high density lipoprotein cholesterol; IHD, ischemic heart disease; IHD/clinical, clinical ischemic heart disease; IHD/ECG, ischemic heart disease by electrocardiogram; LDL cholesterol, low density lipoprotein cholesterol; OR, odds ratio.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The metabolic syndrome is said to consist of a cluster of heart disease risk factors, including low high density lipoprotein cholesterol (HDL cholesterol), high triglycerides, impaired carbohydrate metabolism, central obesity, and high blood pressure (1Go, 2Go). An important feature of this syndrome is insulin resistance, characterized in nondiabetics by increased levels of serum insulin, and it has been suggested that insulin itself is atherogenic (3Go). Epidemiologic studies have not consistently confirmed an association between hyperinsulinemia and cardiovascular mortality (4Go). No studies of the independent association between metabolic syndrome risk factors and nonfatal ischemic heart disease (IHD) by electrocardiogram (ECG) criteria have been reported.

The most commonly recognized risk factors in the syndrome are highly correlated with each other (5Go) and are presumed to reflect common metabolic pathways (6Go). The main objective of this study was to investigate the importance of individual IHD risk factors and of major components of the metabolic syndrome for IHD by ECG (IHD/ECG) criteria using factor (principal component) analysis. Resting ECG abnormalities suggestive of IHD have been shown to predict an increased risk of future coronary heart disease events in prospective population studies and in clinical trials (7GoGo–9Go) and are utilized to define subclinical IHD in epidemiologic studies of IHD (10GoGo–12Go).


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Between 1972 and 1974, a heart disease risk factor survey enrolled 82 percent of the adult residents of Rancho Bernardo, California (13Go). Between 1984 and 1987, 80 percent of the surviving members of the original cohort who were still local community-dwelling residents returned for another evaluation (14Go). This study is based on all 2,274 subjects aged 50–89 years (1,015 men and 1,259 women) who had complete ECG data (excluding 41 subjects) and had not taken insulin in the previous 2 weeks (excluding 16 subjects). Analyses were repeated with the 1,389 subjects who had no history of high blood pressure or antihypertensive medication. Analyses were also repeated based on clinical IHD (IHD/clinical), defined by angina pectoris (grades 1 and 2 by Rose criteria) (15Go), physician's diagnosis of previous heart attack, or a history of severe chest pain lasting for more than 30 minutes. At another visit, physician diagnoses had been validated in 85 percent of the cases by a panel of cardiologists who reviewed the records of a 30 percent sample of the cohort.

All participants provided informed consent according to the policies of the University of California, San Diego, Committee on Investigations Involving Human Subjects. A standard medical and behavioral interview queried smoking habits and a physician diagnosis of high blood pressure. Current use of antihypertensive medications was documented by using pills and prescriptions brought to the clinic for that purpose. Height and weight were measured with the participant wearing light clothing and no shoes; body mass index was calculated as weight (kg)/height (m)2. Blood pressure was measured according to the Hypertension Detection and Follow-up Program protocol by using a standard mercury sphygmomanometer after the subject had been seated for at least 5 minutes (16Go). The mean value of two measurements taken at least 1 minute apart was used in the analysis. Fifth-phase Korotkoff sound was used for diastolic blood pressure. A 75-g oral glucose tolerance test was administered in the morning after a 12-hour fast, with plasma glucose and serum insulin levels determined on venous blood obtained before and 2 hours after the glucose load. Plasma glucose levels were measured by glucose oxidase assay, and serum insulin levels were measured by a double-antibody radioimmunoassay in a diabetes research laboratory (17Go). Total plasma cholesterol and triglycerides were measured by enzymatic techniques using an ABA-200 biochromatic analyzer (Abbott Laboratories, Irving, Texas) in a Centers for Disease Control and Prevention-certified lipid laboratory. HDL cholesterol was measured according to the standardized procedures of the Lipid Research Clinics' protocol (18Go). Low density lipoprotein cholesterol (LDL cholesterol) was estimated by using the Friedwald formula (19Go). A 12-lead resting ECG was recorded before the oral glucose tolerance test and coded in the Minnesota Coding Laboratory according to Minnesota Code criteria (10Go).

The ratio of total serum cholesterol to HDL cholesterol was used as an estimate of the atherogenic profile of the serum lipids. Smoking was categorized as ever versus never, current smoking versus never or past smoking, and pack-years.

Ischemic electrocardiographic abnormalities were defined by using the Whitehall criteria as applied in the World Health Organization's Multinational Study of Diabetes and Vascular Disease (11Go, 20Go). Probable IHD/ECG included major Q or QS wave (Minnesota codes 1.1, 1.2) or complete left-bundle branch block (Minnesota code 7.1.1). Possible IHD/ECG included small Q or QS wave (Minnesota code 1.3), ST depression (Minnesota codes 4.1–4.3), or T wave items (Minnesota codes 5.1–5.3). ECGs that did not fulfill any of these criteria were categorized as normal.

High correlations between the measures typically included in the metabolic syndrome suggest the use of principal components to reduce collinearity (21Go). In addition, combining syndrome covariates into factors quantifies possible common pathways by which they can cause atherosclerosis. Factor analysis has been used in previous investigations of the clustering of metabolic risk factors (22GoGo–24Go). We used this method to define the associations between metabolic syndrome variables and IHD. Principal components with eigenvalues as large as 1.0 were retained, and varimax rotation was used to keep the correlation between the factors at zero (25Go). The loadings correspond to correlation coefficients derived to predict the variable from the factor. Only variables that shared at least 15 percent of the variance with the factor, corresponding to a factor loading of 0.40 or more, were used in the interpretation of the factors. To investigate the association between the factors and IHD/ECG or IHD/clinical, we used the factor coefficients relating to the individual risk factors to calculate each factor score for each subject. The factor scores were used as continuous index variables in a logistic regression model predicting IHD/ECG.

Additional analyses were concluded to address validity. Because antihypertensive medications can cause metabolic side effects resembling the pattern in the metabolic syndrome (26GoGo–28Go), analyses were repeated after excluding all known hypertensives. To test for internal consistency, we repeated the analyses, using history of IHD instead of resting ECG criteria (IHD/clinical).

Statistical analyses were performed by using SPSS/PC (29Go). Because of the skewed distribution of fasting and postchallenge insulin and serum triglycerides, these variables were log-transformed for all calculations. All prevalence rates were age-standardized across four 10-year age groups, using all participants aged 50–89 years in this study as the standard. Differences in proportions between groups were tested by using Pearson's chi-square procedure. For correlations, Pearson's correlation coefficient was used. Adjusted differences in means were compared by using analysis of covariance. The independent association between possible and probable ischemic ECG and major IHD risk factors was analyzed by utilizing multiple logistic regression. One standard deviation was the unit used for calculation of odds ratios and confidence intervals for continuous variables except for age, for which a 10-year increment was used. All analyses were two-tailed, and p values less than 0.05 were considered statistically significant. The overall performance of the model was evaluated by its sensitivity and specificity in predicting the outcome variable (30GoGo–32Go).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
There were 1,015 men and 1,259 women with a median age of 70 years. As shown in table 1, the prevalence of IHD/ECG and IHD/clinical increased with age and showed a male preponderance. Seventy-eight percent of the women and 74 percent of the men had a normal ECG (p < 0.01); 19 percent of the men and 20 percent of the women had possible IHD/ECG (not significant); and 7 percent of the men and 2 percent of the women had probable IHD/ECG (p < 0.001). A history of IHD was reported by 37 percent of the men and 28 percent of the women who had ECG evidence of possible or probable IHD and by 13 percent of the men and 14 percent of the women who did not have evidence of ECG.


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TABLE 1. Distribution of ischemic heart disease defined by 12 leads resting electrocardiogram criteria and by history, by age and sex, Rancho Bernardo, California, 1984–1987

 
As shown in table 2, IHD/ECG was associated in both sexes with higher systolic pressure, fasting and postchallenge plasma glucose levels, plasma triglycerides, and total cholesterol/HDL cholesterol ratio, as well as lower HDL cholesterol levels. Fasting serum insulin levels were also significantly higher in women, but not in men, with IHD (p < 0.05). Diastolic pressure, postchallenge insulin, and total and LDL cholesterol were not associated with IHD/ECG in either sex. Similar patterns were observed for probable IHD/ECG.


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TABLE 2. Sex-specific distribution{dagger} of metabolic syndrome risk factors by electrocardiogram findings according to the Whitehall criteria, Rancho Bernardo, California, 1984–1987

 
As shown in figure 1, the strongest associations with IHD/ECG in both sexes were for age (10 years) (odds ratio (OR) = 1.8) and systolic pressure (OR = 1.5 in men and 1.3 in women, p < 0.001). Fasting glucose levels and, particularly, postchallenge plasma glucose levels were also significantly associated with IHD/ECG (OR = 1.3, p < 0.001 in both men and women). Serum triglycerides (OR = 1.2, p < 0.01 in men and 1.4, p < 0.001 in women) and the total cholesterol/HDL cholesterol ratio (OR = 1.2, p < 0.01 in men and OR = 1.4, p < 0.001 in women) were positively and significantly associated with IHD in both men and women. An inverse, but significant, association was seen with HDL cholesterol (OR = 0.75, p < 0.001 in men and 0.77, p < 0.001 in women).



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FIGURE 1. Sex-specific, age-adjusted odds ratios ({square}) and 95% confidence intervals per standard deviation associated with IHD for the full cohort. (*) without confidence intervals are corresponding odds ratios for the normotensive group; BMI, body mass index; DBP, diastolic pressure; HDL cholesterol, high density lipoprotein cholesterol; LDL cholesterol, low density lipoprotein cholesterol; SBP systolic pressure; TC, total cholesterol. Rancho Bernardo, California, 1984–1987.

 
Principal components factor analyses were performed separately for each sex, and factors with eigenvalues of at least 1.0 after orthogonal varimax rotation are shown in table 3. In men, a fourth factor (LDL cholesterol) loaded higher than 0.40 independent of HDL cholesterol and serum triglycerides. It was not included in the factors outcome analyses presented here because it contained only one variable, and LDL cholesterol is not considered to be part of the metabolic syndrome (22GoGo–24Go).


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TABLE 3. Factors and factor loadings from factor analysis of risk factors related to the metabolic syndrome in men and women, Rancho Bernardo, California, 1984–1987

 
The same three dominant factors were identified in both men and women. Factor 1 (the central metabolic factor) comprised body mass index, fasting and nonfasting serum insulin, and dyslipidemia (HDL cholesterol loading negative and serum triglycerides loading positive) in both sexes, and LDL cholesterol in women. Factor 2 (the glucose factor) included fasting and nonfasting plasma glucose, which were independent of the insulin measures contained in factor 1. Factor 3 (the blood pressure factor) contained systolic and diastolic pressures. No variable loaded in more than one factor. The total variance explained by the three factors was 56 percent in both sexes.

The factor scores for these three factors were used to analyze the independent associations between the factors and IHD/ECG. As shown in table 4, all three factors were directly and independently associated with IHD/ECG, as were age and male sex.


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TABLE 4. Association for age, sex, and three factor variables* with ischemic heart disease defined by electrocardiogram (Whitehall criteria), with men and women combined in the full cohort and in the reduced cohort with known hypertensives excluded, Rancho Bernardo, California, 1984–1987

 
To assess the performance of the model, sensitivity (proportion of all IHD/ECG correctly predicted) and specificity (proportion of all normal ECG correctly predicted) were calculated. Receiver operating characteristic curve analysis suggests the cutpoint of 0.22 on the predicted probability of an IHD/ECG as the point providing the highest, balanced combination of sensitivity and specificity, that is, a sensitivity of 65 percent and a specificity of 62 percent.

These analyses were repeated in 625 men and 764 women who did not have high blood pressure or use antihypertensive medication. The age-standardized proportion with normal ECG was 78.3 percent in men and 82.7 percent in women ({chi}2 p < 0.01). The proportion with possible IHD was the same in both sexes (15.6 percent); probable IHD was more frequent in men (6.1 percent) than in women (1.7 percent, p < 0.001). Cardiovascular risk factors aggregated in the same IHD categories as in the full cohort. Differences between the ECG categories were fully consistent with the results in the full cohort. In men, significant differences were found for age, systolic pressure, and postchallenge plasma glucose. In women, the ranges of risk factors were wider, and as in the full cohort, more factors differed significantly between normal ECG and IHD/ECG, including age, postchallenge plasma glucose, nonfasting insulin, serum triglycerides, and total cholesterol/HDL cholesterol ratio.

Sex-specific estimates of the odds ratios associated with IHD in the normotensive subgroup are shown in figure 1, overlaid in the graph for odds ratios in the total cohort. In a model limited to the reduced cohort, including the three factor variables, age, and sex (table 4), odds ratios consistently remained at the same level as in the full cohort; however, the 95 percent confidence interval included one for sex, the metabolic factor, and the blood pressure factor.

There were 198 men and 210 women with a clinical history of IHD. The partial correlation coefficient, controlled for age and sex, between IHD/ECG (possible and probable combined) and IHD/clinical was weak but significant (r = 0.19, p < 0.001). In both men and women, the pattern for metabolic syndrome variables was similar to that observed with IHD based on the ECG categories. In a multivariate logistic regression model, associations with the factors were largely consistent with those for IHD/ECG, allowing for the smaller sample size and intervention effects–age (10 years) (OR = 1.5, 95 percent confidence interval (CI): 1.3, 1.8, p < 0.001), sex (women compared with men) (OR = 0.49, 95 percent CI: 0.3, 0.9, p < 0.05), the metabolic syndrome (OR = 1.6, 95 percent CI: 1.2, 2.2, p < 0.01), glucose (OR = 1.2, 95 percent CI: 1.03, 1.4, p < 0.05), and blood pressure (OR = 0.9, 95 percent CI: 0.7, 1.01, not significant).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
In this cross-sectional study, there was a highly significant association between resting ECG evidence of IHD and all common components of the metabolic syndrome. These associations were consistent in both sexes in models using individual risk factors and in models using principal components from factor analysis representing a central metabolic factor, including body size, serum insulin and dyslipidemia, a glucose factor, which was independent of insulin represented in the metabolic factor, and a blood pressure factor, respectively. These associations persisted after exclusion of individuals with antihypertensive treatment or hypertension.

Factor analysis simplified the complex cluster of inter-related variables with high collinearity in the metabolic syndrome, reducing the number of factors involved and making them more interpretable, with no significant loss of predictive value. Each principal component represents a set of variables that are thought to act in combination on a common underlying pathologic process that predisposes to IHD.

Insulin resistance is proposed to be the underlying or driving mechanism for the metabolic syndrome (1Go). It was not measured directly in this study, but other studies suggest that fasting serum insulin, as used here, is a marker for insulin resistance in persons without diabetes (33Go). Serum insulin clustered with body size and dyslipidemia in the factor analysis. This is consistent with the thesis that serum insulin or insulin resistance shares a common pathway with them (6Go).

The three principal components identified in this study are consistent with a report from the Framingham Offspring Study of younger men and women, which also identified a central factor including body size, dyslipidemia, and serum insulin (fasting and 2-hour insulin) and separate domains for impaired glucose tolerance and blood pressure (23Go). Similarly, a factor analysis in the Strong Heart Study, performed in nondiabetic and diabetic subjects separately (24Go), identified blood pressure as a specific separate factor. Hypertension acting as a separate factor from the central metabolic syndrome is consistent with a recent paper by Neel et al. (34Go).

This study did not exclude diabetic subjects, which might explain why glucose was not one of the central metabolic factor variables, since impaired beta-cell function is important in the development of non-insulin-dependent diabetes mellitus (23Go, 35Go, 36Go). These results, consistent with the Framingham Study, do not mean that serum insulin or insulin resistance are unrelated to glucose intolerance or hypertension, but suggest that risk factor clustering may originate from more than one physiologic process (23Go). The results in our study indicate that there could be multiple mechanisms by which the metabolic syndrome increases the risk of IHD.

Gender remained significantly associated with IHD/ECG when forced into a model that included age and the three components of the metabolic syndrome identified by factor analysis. Thus, gender and the metabolic syndrome had independent associations with prevalent IHD, which means that sex differences in IHD were not explained by the metabolic syndrome.

Lipids were significantly associated with IHD/ECG, largely based on the impact of high triglycerides and low HDL cholesterol levels. Total LDL cholesterol by itself was not related to IHD/ECG, but small, dense LDL cholesterol has been shown to be associated with the metabolic syndrome in other populations (37Go, 38Go). In the factor analysis, dyslipidemia loaded with the central metabolic factor in both men and women, but LDL cholesterol was recognized as part of this factor only in women. In men, LDL cholesterol loaded as a single variable in a fourth factor, which was discarded because it included only one variable and because total LDL cholesterol is not considered to be part of the metabolic syndrome (22GoGo–24Go). An alternative interpretation is that LDL cholesterol is so strong in men that it stands alone.

Elevated blood pressure was a significant independent risk factor for IHD/ECG in this cohort, and 30 percent of these subjects were treated with antihypertensive medications, some of which have metabolic side effects resembling the metabolic syndrome pattern (13GoGo–15Go). Epidemiologic studies of the relation between coronary heart disease and the metabolic syndrome could be confounded by the use of antihypertensives. Excluding all participants with known high blood pressure reduced the range of blood pressure and limited hypertensives to those newly identified at this study visit. Because these cardiovascular risk factors aggregate (39Go, 40Go), the exclusion of hypertensives also reduced the proportion of participants with diabetes, hypertriglyceridemia, and an elevated total cholesterol/HDL cholesterol ratio. Nevertheless, associations between the metabolic syndrome risk factors and ECG categories of IHD were still clearly demonstrated after the exclusion of known hypertensives, making it unlikely that the associations observed in the full cohort were caused by blood pressure treatment. We acknowledge, however, that other unreported medications could have caused nonspecific ECG changes.

Possible ischemic ECG based on ST and T wave changes occurred with equal frequency in both sexes, although it is well known that IHD is more prevalent in men, as indicated by the significantly higher rates of probable IHD in men. Possible ischemic ECG is likely to be less specific for IHD in women compared with men (41Go). Other studies of older populations have also reported a higher Q/QS wave prevalence in men and similar or higher ST-T wave prevalence in women (42Go, 43Go).

The Rancho Bernardo Study results are concordant with the Whitehall Study, which found significant associations between systolic pressure, blood glucose, and body mass index with the prevalence of ischemic ECG (20Go). Previous results from Rancho Bernardo and in the Pima Indians also confirmed an association of IHD/ECG with non-insulin-dependent diabetes mellitus (44Go, 45Go). Other studies have not consistently supported serum insulin as an independent risk factor for ischemic ECG (44Go, 46Go, 47Go). In these studies, associations with IHD/ECG were found in high-risk groups who had non-insulin-dependent diabetes mellitus or hypertension. In our study, the relation between risk factors that cluster in the metabolic syndrome and IHD was demonstrated in a community-dwelling cohort and confirmed in a subgroup at low risk.

A previous report from the Rancho Bernardo Study (48Go) found no positive association between fasting or postchallenge serum insulin level in men or women and subsequent IHD or cardiovascular disease mortality rates. In that report, unlike in our study, all persons who had diabetes or IHD (by Q waves or by history) at baseline were excluded. Thus, the earlier prospective study differed from the current cross-sectional study, which did not exclude persons by IHD or diabetes criteria. Outcome variables were also different: incident mortality in the previous paper and prevalent (nonfatal) coronary heart disease by ECG in the current report. The studies are consistent, considering that the prevalence of insulin resistance increases with age (49Go) and that surviving subjects, by getting older, will also be exposed to the risk of IHD that accompanies increased age, including an increased rate of nonfatal IHD. Others have shown that serum insulin is positively associated with prevalent nonfatal coronary heart disease (50Go). Alternatively, serum insulin could be a stronger risk factor in younger versus older adults.

The role of hyperinsulinemia or insulin resistance remains controversial (4Go): some (51GoGo–53Go), but not all (44Go, 48Go, 54GoGo–56Go), epidemiologic studies suggest that serum insulin promotes atherosclerosis (3Go). An association is supported by the Insulin Resistance and Arteriosclerosis Study (IRAS) (57Go), which recently reported an inverse association between insulin sensitivity (based on the frequently sampled intravenous glucose tolerance test) and carotid artery arteriosclerosis measured in 1,397 subjects. This association was partially, but not completely, explained by other cardiovascular risk factors, compatible with an independent role for insulin resistance. The Insulin Resistance and Arteriosclerosis Study has been criticized for not including serum triglycerides in the analyses (58Go). In the Atherosclerosis Risk in Communities Study (59Go), there was also a synergistic effect of glucose and serum insulin, as well as of triglycerides and serum insulin, on arterial stiffness. It is also plausible that insulin resistance and atherosclerosis share an underlying etiology (6Go).

In our study, about 30 percent of the participants were missing serum insulin values because the laboratory was not standardized at the beginning of the study. Subjects without insulin values were a little older, but the distribution of other metabolic syndrome variables did not differ from the rest of the cohort, and their exclusion is unlikely to bias the associations reported in this paper.

There could also be methodological explanations for the inconsistent results relating hyperinsulinemia and cardiovascular disease. Insulin is more difficult to measure and may have more diurnal variation than other coronary heart disease risk factors. The proportions of specific insulin to proinsulin may also be important (60GoGo–62Go), although intact and proinsulin values measured at a separate visit in a subset of this cohort did not vary differentially in their association with metabolic syndrome risk factors (J-Y. Oh et al., unpublished data).

We focused on ECG criteria for prevalent IHD without regard to known (clinical) IHD because of the possibility that persons with known disease might have lost weight, changed behaviors, and modified the syndrome. The majority of persons with IHD/ECG had no history of known IHD, and the effects of treatments may explain why the associations between the factor components and IHD/clinical were weaker than IHD/ECG criteria. Although the correlation between IHD/ECG and IHD/clinical was rather low, the associations between these categories of IHD and the cardiovascular risk factors and the factors identified by the factor analysis were consistent.

In summary, principal component analysis shows an association between metabolic syndrome variables and prevalent IHD in older adult men and women. Serum insulin, body size, and dyslipidemia appear to represent a composite central metabolic factor, whereas glucose and blood pressure may each reflect other physiologic processes. The frequency of unrecognized IHD in older adults with the metabolic syndrome supports the potential for prevention efforts in persons with the metabolic syndrome or its components (63Go).


    ACKNOWLEDGMENTS
 
Supported by grant DK 31801 from The National Institute of Diabetes, Digestive and Kidney Diseases.

Dr. Lindblad is a recipient of a fellowship from Skaraborg Institute, Skövde, Sweden, the NEPI Foundation (The Swedish Network for Pharmacoepidemiology), Malmö and Stockholm, Sweden, the Swedish Society of Medicine, and the Swedish Medical Research Council.


    NOTES
 
Reprint requests to Dr. Elizabeth Barrett-Connor, Department of Family and Preventive Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093–0607 (e-mail: ebarrettconnor{at}ucsd.edu).


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 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
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Received for publication March 30, 1998. Accepted for publication March 20, 2000.